Browse Topic: Collision intervention systems

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Challenges and advantages in implementing ADAS systems in buses: a broad overview (Desafios e vantagens na implementação de sistemas ADAS em ônibus: uma visão abrangente)2026-36-03447/30/2026
The implementation of ADAS in buses represents both a significant opportunity and a complex challenge for the future of urban mobility. While ADAS technologies such as lane departure warning, adaptive cruise control, blind spot detection, and autonomous emergency braking have been widely adopted in passenger cars and trucks, their integration into buses has been slower due to unique operational and safety concerns. This paper provides a broad overview of the advantages and obstacles associated with ADAS deployment in public transport vehicles, with particular emphasis on passenger safety, regulatory frameworks, and operational efficiency. Key barriers include the vulnerability of standing passengers during sudden braking events, the unpredictability of pedestrians and cyclists in dense urban environments, and the economic constraints faced by bus operators. At the same time, regulatory initiatives such as Transport for London’s Bus Safety Standard, the European Union’s General Safety Regulation, and Brazil’s MOVER program are driving the gradual adoption of these systems. The benefits of ADAS in buses extend beyond accident reduction, encompassing improved driver ergonomics, reduced fatigue, lower maintenance costs, and enhanced passenger comfort. Case studies from Europe, Brazil, and Asia highlight both the safety potential and the reluctance of drivers to fully embrace these technologies, often due to knowledge gaps and perceived inconvenience. The analysis underscores that successful implementation requires not only technological adaptation but also comprehensive driver training, infrastructure readiness, and public policy support. Ultimately, ADAS in buses should be understood as a transitional step toward autonomous mobility, offering immediate safety gains while reshaping the paradigm of urban transport.
Marcon, Ederson, Michelon, Gabriel, do Nascimento, Vagner
Experimental and Computational Study on Combustion and Performance Characteristics of an Ammonia–Diesel Dual-Fuel Engine under Low Load Conditions2026-01-50627/22/2026
Ammonia is receiving heightened attention as a carbon-neutral and hydrogen energy carrier alternative fuel for compression ignition engines. However, replacing diesel with ammonia poses significant challenges due to its low reactivity and slow-burning nature, particularly at low-load conditions. This study investigated the effect of ammonia energy share (AES) on the combustion characteristics and performance of an ammonia–diesel dual-fuel (ADDF) compression ignition engine operating under low loads and at a constant speed of 1800 RPM. The experiments were conducted at three different loads: 6 Nm, 13.5 Nm, and 18 Nm, corresponding to 11%, 25%, and 33% of full load, respectively. At each load, the AES was incrementally increased, ranging from zero to its maximum limit, while maintaining the COV of IMEP below 3% to ensure stable combustion. Furthermore, CFD simulations were performed using a CONVERGE CFD model of the engine to analyze the in-cylinder thermal and chemical behavior, and the model was validated against the experimental data. The experimental results showed that the AES reached 40%, 58%, and 61% for engine loads of 6 Nm, 13.5 Nm, and 18 Nm, respectively. Increasing AES reduced the mean in-cylinder temperature and peak cylinder pressure, and shifted the peak pressure location toward the expansion stroke. Combustion phasing was delayed, and combustion duration increased with higher ammonia substitution. CFD analysis revealed weaker high-temperature and OH reaction zones, along with reduced OH and H radical activity, and increased persistence of NH2 and HO2 evolution at higher AES, indicating slower oxidation of the ammonia-containing mixture. The results highlight the challenges associated with high-ammonia operation at low loads and provide deeper insight into the combustion processes governing ADDF engine performance.
Sardar, Gobinda, Kishore, Kislay, Pradeep, P., Mittal, Mayank
Effect of Aftermarket Suspension Modifications on ADAS Functionality of Five Light Vehicles12-09-04-00317/15/2026
Advanced Driver Assistance Systems (ADAS) are increasingly prevalent in light vehicles, both in the United States and worldwide. Moreover, ADAS are steadily being incorporated into regulatory requirements globally. Like ADAS, the automotive aftermarket is also increasing in size and significance. As both ADAS and the aftermarket industry are growing, the effect of aftermarket modifications on ADAS functionality should be examined. However, there is very little information available in the public domain about the effect of aftermarket modifications on original equipment ADAS. This work is centered on a considerable research project that was conducted to address the knowledge gap at the intersection of ADAS and the aftermarket. The project investigates five light vehicles that are important to the aftermarket, including four pickup trucks and one sport-utility vehicle. It focuses solely on the effect of popular aftermarket suspension modifications, and it does not evaluate aftermarket ADAS equipment. Typical suspension modifications were applied to the test vehicles in five modification categories, including stock, lower kits, level kits, 3–4 in. lift kits, and 6 in. lift kits. Six ADAS test procedures were performed for the test vehicles, comprised of blind spot detection, crash imminent braking, lane departure warning, pedestrian automatic emergency braking, rear cross traffic alert, and traffic jam assist. The physical tests were developed based on National Highway Traffic Safety Administration (NHTSA) New Car Assessment Program (NCAP) written experimental procedures. Statistical hypothesis testing was performed for the purpose of determining if average measured dynamic responses varied in the modified vehicles compared to stock. The results show that vehicles modified with typical aftermarket modifications will likely retain their ADAS functionality, given the limitations of the small sample size of five vehicles. Vehicles with 6 in. lift kits are expected to exhibit greater variability in their dynamic responses compared to stock. Plans for future work and unanswered research questions are outlined, with the goal of advancing aftermarket ADAS integration and ensuring the safety and performance of modified vehicles.
Bastiaan, Jennifer M., Morales, Luis, Muller, Mike
Reverse Automatic Emergency Braking (AEB) Testing SummaryJ3339_202607 (Current)7/14/2026
This SAE Information Report provides a broad summary of existing Reverse Automatic Emergency Braking test protocols to help assess whether additional test protocols are needed. Eventually, the task force may develop additional protocols to support testing of Reverse Automatic Emergency Braking systems.
Active Safety and Driver Support Systems Standards Committee
748 Airborne Weather Radar with Advanced Antenna TechnologyARINC748 (Current)6/15/2026
This ARINC Standard was prepared to take advantage of technical advances in airborne weather radar and its associated components. Emphasis is placed upon windshear and weather detection/analysis capability and performance, reliability, installation ease, and reduced cost of ownership.
Airlines Electronic Engineering Committee
Characterization of Pedestrian Automatic Emergency Braking Acceleration in Modern Light Vehicles: Potential Implications for Occupant Safety09-14-01-00075/4/2026
The objective of this study was to characterize and compare pedestrian automatic emergency braking (PAEB) pulses in modern light vehicles to understand the loading environment that vehicle occupants are being exposed to during PAEB maneuvers. PAEB tests (n = 8008) conducted using 2018–2023 vehicle model years were analyzed. Pulse, vehicle, and impact characteristics (e.g., jerk, peak acceleration, pedestrian scenario, etc.) were derived from each PAEB test. Two k-means clustering analyses were used to group PAEB pulses with and without target collisions based on their similarity between characteristics. One-way ANOVA and Kruskal–Wallis tests were performed on the PAEB pulse characteristics to examine differences between clusters (p < 0.05). Two non-collision clusters (NC1 and NC2) were identified for PAEB pulses without collisions: NC1 had a statistically significant lower jerk (0.8 ± 0.4 g/s) and peak acceleration (1.0 ± 0.1 g) compared to NC2 (1.6 ± 0.8 g/s and 0.9 ± 0.1 g, respectively, p < 0.001). NC1 was mostly represented by stationary adult (88.6%), 60 km/h (99.5%), and 40 km/h (62.2%) tests. NC2 was mostly represented by crossing scenarios (child: 92.3%; adult: 70.5%) and 20 km/h (96.2%) tests. Three collision clusters (C1, C2, and C3) were identified for PAEB pulses with collisions. C3 showed a greater jerk (1.5 ± 0.8 g/s) compared to C1 (0.9 ± 0.6 g/s) and C2 (1.1 ± 0.9 g/s, p < 0.001). These results suggest that with successful avoidance, deceleration begins earlier with higher speeds and a stationary pedestrian, resulting in potentially milder loading conditions for vehicle occupants (i.e., lower jerk in NC1 vs NC2). With unsuccessful avoidance, in daytime pedestrian crossing scenarios, lower impact speeds were observed, resulting in potentially non-optimal loading conditions (i.e., higher jerk and peak acceleration in C3) for vehicle occupants. At night with low beams, C2 may result in advantageous loading conditions for vehicle occupants (i.e., lower jerk and peak acceleration), but it may lead to the worst outcome for pedestrians (i.e., greatest impact speed).
Witmer, Maitland, Kidd, David, Graci, Valentina
Understanding and Modeling Effectiveness of Predictive Risk Notifications for Early Assistance for Safe Driving: A Public Road Testing Study09-14-01-00265/4/2026
While an enlarged lead time from risk notifications to collisions is widely acknowledged to facilitate safe driving, it remains challenging to effectively notify drivers of invisible risks and non-apparent risks coming from uncertain behaviors on the part of road users. The current study examined whether verbal notifications are able to assist early awareness of predictive risks. We also attempted to identify human and environmental factors that could possibly improve the effectiveness of predictive risk information. Twenty-eight licensed drivers participated in a public road test conducted in two different urban areas on 3 days. They drove predefined courses on which potential risk locations were identified prior to the test, using a sport utility vehicle equipped with an automatic verbal notification system triggered based on the distance to the potential risk locations. After passing through the locations each time, the participants were instructed to verbally evaluate the shift in awareness provided by the notification and the usefulness of the assistance. After the driving test was completed, we acquired a subjective evaluation on annoyance acceptability and a self-report of participants’ road usage frequency at notified locations in daily life, as well as questionnaires on their driving style and workload sensitivity. We found that the effectiveness of verbal notifications increased by conveying uncertainty risks at visible locations and by using interrogative sentences or expressions of risk target perspective, although it decreased as a function of age. Our model showed strong performance in predicting positive ratings for the notifications, but this was not the case for negative ratings. We identified individual characteristics and the risk factor of uncertainty as important features in our model. In conclusion, the findings provide an important reference for understanding the early notification of predictive risk and constructing a numerical model for the implementation of assistance systems in vehicles and nomadic devices.
Maruyama, Masaki, Koyama, Keiichiro, Ezaki, Toru, Sakamoto, Junichi, Sawada, Yuta, Matsuoka, Takahiro
Characterization of Fatal Cyclist Collisions Involving Nine Vehicle Types Traveling at Low and High Speeds in Japan09-14-01-00055/4/2026
To reduce traffic fatalities through vehicle safety measures, particular attention must be given to cyclist-related fatalities. Clarifying the characteristics of hazardous events leading to cyclist fatalities, not only by vehicle speed range but also by vehicle type, is essential and should be based on analyses of real-world accident data. Accordingly, this study aimed to characterize fatal cyclist accidents involving vehicles traveling at low and high speeds in Japan. We used macro accident data from the Japanese Institute for Traffic Accident Research and Data Analysis covering the period from 2013 to 2022. Based on nine vehicle types, we investigated the effects of road type, vehicle behavior, and accident type on cyclist fatalities. Additionally, we identified the five most frequent accident scenarios separately for each low- and high-speed category. At signalized intersections, the proportions of cyclist fatalities involving vehicles traveling at low speeds were higher than those involving vehicles traveling at high speeds across all vehicle types. In contrast, on straight roads, the proportions at low speeds were lower than those at high speeds for all vehicle types. In the low-speed range, cyclist fatalities within the top five scenarios accounted for 65% of all fatalities, with the most frequent scenario occurring at signalized intersections during left-turn maneuvers, where heavy-duty trucks accounted for 86% of the fatalities. In the high-speed range, cyclist fatalities within the top five scenarios accounted for 71% of all fatalities. The most frequent high-speed scenario involved crossing collisions at unsignalized intersections when vehicles traveled straight, with light passenger cars and sedans accounting for 29% and 24% of the fatalities, respectively. These findings provide valuable insights for the development of targeted traffic safety regulations and vehicle technologies aimed at reducing vehicle–cyclist collisions across different speed ranges.
Matsui, Yasuhiro, Oikawa, Shoko
High Order Control Lyapunov Function - Control Barrier Function - Quadratic Programming Based Autonomous Driving Controller for Bicyclist Safety2026-01-00344/7/2026
Ensuring the safety of Vulnerable Road Users (VRUs) is a critical challenge in the development of advanced autonomous driving systems in smart cities. Among vulnerable road users, bicyclists present unique characteristics that make their safety both critical and also manageable. Vehicles often travel at significantly higher relative speeds when interacting with bicyclists as compared to their interactions with pedestrians which makes collision avoidance system design for bicyclist safety more challenging. Yet, bicyclist movements are generally more predictable and governed by clear traffic rules as compared to the sudden and sometimes erratic pedestrian motion, offering opportunities for model-based control strategies. To address bicyclist safety in complex traffic environments, this study proposes and develops a High-Order Control Lyapunov Function–High-Order Control Barrier Function–Quadratic Programming (HOCLF-HOCBF-QP) control framework. Through this framework, CLFs constraints guarantee system stability so that the vehicle can track its reference trajectory, whereas CBFs constraints ensure system safety by letting vehicle avoiding potential collisions region with surrounding obstacles. Then by solving a QP problem, an optimal control command that simultaneously satisfies stability and safety requirements can be calculated. Three key bicyclist crash scenarios recorded in the Fatality Analysis Reporting System (FARS) are recreated and used to comprehensively evaluate the proposed autonomous driving bicyclist safety control strategy in a simulation study. Simulation results demonstrate that the HOCLF-HOCBF-QP controller can help the vehicle perform robust, and collision-free maneuvers, highlighting its potential for improving bicyclist safety in complex traffic environments.
Chen, Haochong, Cao, Xincheng, Guvenc, Levent, Aksun Guvenc, Bilin
A Cloud-Vehicle Integrated Closed-Loop Testing Framework for Intelligent Chassis2026-01-00514/7/2026
Vehicle system testing serves as a critical phase in obtaining road certification for prototype vehicles. While direct road testing with physical vehicles yields the most authentic data, this approach entails significant costs, challenges in reproducing extreme scenarios, and inherent safety risks. In contrast, virtual vehicle-based testing technologies represent advanced simulation methodologies for enhancing development efficiency and quality, effectively mitigating risks associated with complex real-world operating conditions and hazardous physical testing. However, virtual vehicle models often rely on idealized parameters, limiting their ability to reflect real-world dynamics and resulting in lower credibility of test outcomes. Furthermore, as evidenced in current mainstream virtual testing software, environmental simulations predominantly remain confined to the visual domain, with limited direct interaction between dynamic environmental changes and virtual vehicle responses. To address these limitations, this study proposes a novel testing framework leveraging vehicle-cloud integration technology, which combines the authenticity of physical testing with the flexibility of virtual simulation. The proposed system is validated through an AEB (Automatic Emergency Braking) function activation test. Experimental results demonstrate real-time data interoperability between physical and virtual vehicles, achieving a 89% accuracy rate in synchronizing virtual scenario velocities with real-world speeds. This approach enables safe and efficient preliminary testing, providing robust data support for subsequent physical validation and significantly lowers the overall testing cycle.
Liao, Yinsheng, Cheng, Qing Hua, Qu, Wenying, Wang, Zhenfeng, Wu, Yan, He, Chengkun, Zhang, Junzhi, Lu, Yukun
Study of Automatic Emergency Braking Effects on Human and Surrogate Passengers2026-01-05564/7/2026
The influence of modern Automatic Emergency Braking (AEB) on the head and neck behavior of the occupants in a vehicle continues to be an active area of research. Occupant kinematics and kinetics were evaluated using a vehicle equipped with a pedestrian AEB system. The vehicle was tested in several different scenarios with speeds between 15 and 45 mph. Two instrumented 50th-percentile male Hybrid-III Anthropomorphic Test Devices (ATD) were positioned in certain seats of the vehicle, while minimally instrumented human volunteers occupied the remaining seats. Displacement transducers and video analysis were utilized to capture the kinematics of each occupant. The findings of this study indicate that in AEB-only events with belted-occupants, the test vehicle did not result in any occupant motion that would have placed the occupants out-of-position (OOP) had an impact occurred immediately following the AEB event. This means that when evaluating real-world AEB events, it may not be necessary to analyze and model properly seated and restrained occupant kinematics prior to an impact event when only AEB occurs. Consistent with the published literature, the kinetic results continue to show that the belted occupant exposure is significantly below any accepted injury criteria and is comparable to routine activities of daily living. Tests were also completed in two seating configurations with unbelted ATDs to evaluate the difference in vehicle braking (if any) and the excursion differences when unbelted. The study found greater excursion for unbelted ATDs compared to that of belted volunteers and provides a sample of unbelted ATD kinematics via AEB activation.
Bartholomew, Meredith, Dahiya, Akshay, Russell, Caleb, Morr, Douglas, Castro, Elaine, Nguyen, An
Collision Avoidance Testing of the Waymo Automated Driving System2026-01-05194/7/2026
This paper describes Waymo's Collision Avoidance Testing (CAT) methodology: a scenario-based testing method that evaluates the safety of the Waymo Driver Automated Driving Systems' (ADS) intended functionality in conflict situations initiated by other road users that require urgent evasive maneuvers. Because SAE Level 4 ADS are responsible for the dynamic driving task (DDT), when engaged, without immediate human intervention, evaluating a Level 4 ADS using scenario-based testing is difficult due to the potentially infinite number of operational scenarios in which hazardous situations may unfold. To that end, in this paper we first describe the safety test objectives for the CAT methodology, including the collision and serious injury metrics and the reference behavior model representing a non-impaired eyes on conflict human driver used to form an acceptance criterion. Afterward, we introduce the process for identifying potentially hazardous situations from a combination of human data, ADS testing data, and expert knowledge about the product design and associated Operational Design Domain (ODD). The test allocation and execution strategy is presented next, which exclusively utilize simulations constructed from sensor data collected on a test track, real-world driving, or from simulated sensor data. The paper concludes with the presentation of results from applying CAT to the fully autonomous ride-hailing service that Waymo operates in San Francisco, California and Phoenix, Arizona. The iterative nature of scenario identification, combined with over ten years of experience of on-road testing, results in a scenario database that converges to a representative set of responder role scenarios for a given ODD. Using Waymo's virtual test platform, which is calibrated to data collected as part of many years of ADS development, the CAT methodology provides a robust and scalable safety evaluation.
Kusano, Kristofer, Beatty, Kurt, Schnelle, Scott, Favaro, Francesca, Crary, Cam, Victor, Trent
The Balance of Illumination and Glare Prevention of Upward Directed Lighting2026-01-05164/7/2026
This study examines the ongoing challenge of balancing sufficient forward illumination for vehicle operation with the need to limit glare experienced by other road users. This analysis specifically focuses on the portion of a headlight's beam pattern intensity distribution located above the horizontal plane, which is particularly relevant for lighting overhead signs and the upper portions of vulnerable road users but is also a potential contributor to glare. In particular, the study investigates how the adoption of LED headlamp technology has influenced upward-directed lighting relative to historical halogen beam intensity distributions. Two different comparative analyses were performed within this study. The first analysis was the calculation of intensity on targets positioned at multiple locations relative to the headlamps considering vehicle conditions. The second analysis was performed as at selected discrete points referenced directly to the headlamp and independent of vehicle height. The results of the study show that the changes in upward directed lighting due to transition to LED technology were inconsequential relative to historical variability of the halogen headlamp systems. Analysis of this data reveals trends in light distributions and can provide information for considerations of future headlamp strategies balancing the needs of drivers to illuminate potential vulnerable road users and the glare experienced by other road users.
Allen, Jodi Mary Jean
Evaluation of PAEB Performance of a GM Vehicle Using EDR and Ground Truth Data2026-01-00544/7/2026
In order to determine the on-board EDR data recording characteristics of a GM vehicle, a 2023 GMC Sierra Denali was tested in several Pedestrian Automatic Emergency Braking (P-AEB) scenarios. Using a variety of test tools, including the STRIDE robotic platform and its onboard data systems, a GPS/IMU installed in the vehicle, and several camera units, the vehicle was put into collision imminent scenarios in which the crash avoidance systems were actuated. The flags in the EDR data, the order in which EDR events were written, and the correlation between the EDR and data recorded by the aforementioned external acquisition systems were examined for each test case. Testing was done in both forward and reverse scenarios and at low speeds only. These results provide a picture of the current state of the additional data available in current EDRs installed on GM vehicles equipped with P-AEB capability, as well as an insight into the accuracy and meaning of that data which should prove beneficial to the accident reconstruction community, among others.
Bartholomew, Meredith, Arnett, Michael, Guenther, Dennis
Predictive AEB Activation for Secondary Collision Risk Reduction2026-01-05184/7/2026
Although the evaluation criteria of New Car Assessment Programs (NCAP) continue to evolve, they still predominantly focus on one-to-one collision scenarios. However, accident analyses based on traffic databases from the National Highway Traffic Safety Administration (NHTSA) in the United States and the Institute for Traffic Accident Research and Data Analysis (ITARDA) in Japan indicate that in real-world traffic environments, particularly at intersections with multi-lane arterial roads, complex situations involving multiple vehicles are likely to arise. Further examination of these crash configurations suggests that AEB activation, depending on the resulting stopping position, may entail a potential secondary collision risk under certain intersection conditions. To mitigate secondary collision risks, this study introduces a Secondary Collision Mitigation Logic (SCM Logic), which estimates Time-To-Intercept (TTI) for multiple crossing vehicles to predict when each vehicle will reach the potential collision area. In addition to TTI, the system evaluates whether the ego vehicle’s predicted post-braking position is likely to overlap with the trajectory of a secondary target. This combined assessment enables the system to proactively identify scenarios where a potential risk of secondary side collisions may occur after AEB activation, allowing for earlier intervention than conventional TTC-based methods. The proposed SCM Logic was evaluated in closed-loop virtual simulations with CarMaker. In addition, open-loop vehicle tests with dummy targets were conducted to validate trigger timing, and the avoidance outcomes were assessed through estimated stopping-distance analyses based on measured and assumed parameters. Across representative scenarios, the results indicate a reduction tendency in predicted secondary collision occurrences relative to a baseline AEB. These findings suggest that incorporating multi-vehicle intersection scenarios into future NCAP evaluations would enable a more accurate and realistic assessment of AEB effectiveness in real-world traffic environments. The proposed approach contributes to the advancement of vehicle safety technologies and supports the development of more comprehensive and practical safety standards across the automotive industry.
Kobayashi, Fumiya, Fukuda, Kentaro, Tani, Hiroaki
Accuracy Requirements for the Road Friction Coefficient Estimation of a Friction-Adaptive Automatic Emergency Braking System as a Software Solution for Integrated Chassis Control Systems10-10-02-00163/10/2026
As part of this work, the accuracy requirements for the road friction coefficient estimation of a friction-adaptive automatic emergency braking (AEB) system are determined using a complex, nonlinear vehicle model. The AEB system varies its trigger distance depending on an estimated value of the road friction coefficient. The accuracy requirements are determined at a driving speed of 40 km/h depending on the severity classification of ISO 26262 in the statistically relevant Euro NCAP test scenario with a stationary target vehicle. MATLAB/Simulink is used as simulation software. The permissible estimation error (difference between estimated value and road friction coefficient) is determined by the severity classification S1 (light and moderate injuries). The results show that the positive permissible estimation error (road friction coefficient is overestimated) must not exceed about 30% of the road friction coefficient to comply with the severity classification S1 of ISO 26262.
Ahrenhold, Tim, Wielitzka, Mark, Binnewies, Tomas, Henze, Roman
Human-Like Automatic Braking Algorithm Based on Kinematic Cue: Yield Behavior Analysis and Fuzzy Controller Design10-10-03-00192/25/2026
Pedestrians are among the most vulnerable participants in traffic, particularly when crossing the road. Extensive research has been conducted globally on the yielding behavior analysis of vehicle–pedestrian interaction and the design of automatic vehicle braking systems to mitigate pedestrian casualties. However, few studies have comprehensively addressed lateral risks using implicit kinematic cues in pedestrian–vehicle interactions. Moreover, the design of collision avoidance systems has rarely taken into account driving behavior, along with the pedestrian’s kinematics and crossing behavior. This article presents a human-like automatic braking fuzzy control strategy for pedestrian–vehicle collision avoidance, combining the advantages of professional driver emergency braking behavior and kinematic interaction cues. First, a high-fidelity driving simulator is used to investigate the yielding behavior of pedestrian–vehicle interaction when pedestrians cross the road. Second, the intrusion position (XP), as a new lateral risk index, is designed to overcome the limitation of lateral distance in complex pedestrian–vehicle interaction scenarios. Various metrics are considered to analyze driver emergency braking behavior using statistical methods from both lateral and longitudinal aspects. Subsequently, based on driver braking behavior, the human-like automatic braking fuzzy control strategy is proposed. Finally, simulation examples verify the reliability of the analysis results and the proposed controller’s effectiveness. Compared with a conventional automatic braking system, the timing of interventions of the proposed system is on average 2.9 s earlier, and the braking deceleration is reduced by 3.59 m/s2.
Zhang, Wenyan, Huang, Xiaorong, Sun, Shulei, Fu, Kairong, Xiong, Qing, Huang, Haibo
Dynamic Stability Enhancement during Emergency Obstacle Avoidance under Inappropriate Driver Operation10-10-02-00152/2/2026
In response to the decline in vehicle stability and the resulting safety risks caused by inappropriate driver operations during high-speed emergency obstacle avoidance, a human–machine cooperative control strategy based on driver operation recognition is proposed. The strategy establishes a vehicle controllability boundary by integrating real-time driver inputs with tire adhesion limits, enabling dynamic evaluation of the influence of operations on system controllability and identification of potential inappropriate operations. On this basis, a control authority allocation mechanism is developed, capable of adaptively adjusting to vehicle states and driver operations. By combining road boundary constraints with vehicle stability envelope constraints, the strategy dynamically regulates the steering angle, ensuring vehicle stability while retaining the driver’s effective intentions as much as possible. Unlike conventional path-tracking or single-envelope control approaches, the proposed method achieves early identification and proactive mitigation of instability risks induced by inappropriate driver operations, thereby reducing associated safety hazards. To validate the effectiveness of the strategy, two representative scenarios, double lane change and curve avoidance, were designed. Simulation and driver-in-the-loop experiments demonstrate superior performance in terms of vehicle stability, human–machine cooperation, and safety, achieving a higher level of coordinated control and performance balance. The findings provide new insights into the design of human–machine cooperative control strategies under extreme conditions, contributing to enhanced fault tolerance of intelligent driving systems against inappropriate driver operations and improved driving safety.
Liu, Yangyi, Zhou, Bing, Wu, Xiaojian, Jiang, Xiaokun, Cui, Qingjia
Mileage Accumulation Target Identification for Autonomous Emergency Braking System Validation for Medium & Heavy Trucks Considering Real-World Accidents in India2026-26-00361/16/2026
Robust validation of Advanced Driver Assistance Systems (ADAS) considering real-world conditions is a vital for ensuring safety. Mileage accumulation is a one of the validation method for ensuring ADAS system robustness. By subjecting systems to diverse real-world driving environments and edge-case scenarios, engineers can evaluate performance, reliability, and safety under realistic conditions. In accordance with ISO 21448 (SOTIF), known hazardous scenarios are explicitly tested during robustness validation in combination of virtual and physical testing at component, sub system and vehicle level, while unknown hazards may emerge through extended mileage by running vehicles on roads, allowing them to be identified and classified. However, defining a mileage target that ensures comprehensive safety remains a significant engineering challenge. This paper proposes a data-driven approach to define mileage accumulation targets for validating Autonomous Emergency Braking Systems (AEBS), using detailed analysis of real-world accident data in India along with ISO 21448 (SOTIF) validation framework. National-level accident data from MoRTH and the RASSI database, along with statistics for medium and heavy commercial vehicles, are utilized to derive the base incident rate for frontal collisions that AEBS is intended to mitigate. The framework integrates critical factors such as hazardous behavior probability, controllability, and severity to calculate a target incident rate, which then informs the required test mileage needed to statistically validate AEBS performance at a specified confidence level. The study outlines the derivation of mileage requirements by considering both accident and fatality reduction as primary safety metrics. This approach provides engineering guidance for defining test mileage requirements with respective to the defined acceptance criteria that ensure AEBS system robust validation considering the real world scenarios in India.
Koralla, Sivaprasad, Ravjani, Amin, Tatikonda, Vijay, Gadekar, Ganesh
Market Research on Actual User Experience and Efficacy of ADAS Features in Indian Driving Conditions2026-26-00351/16/2026
Advanced Driver Assistance Systems (ADAS) have become increasingly prevalent in modern vehicles, promising improved safety and reducing accidents. However, their implementation comes with several challenges and limitations. The efficacy of these systems in diverse and challenging road conditions of India, remains as a concern. For deeper understanding of the ADAS feature related concerns in Indian market due to the factors such as unique road conditions, traffic situations, driving patterns, an extensive study was done throughout Indian terrain. The functionality and performance of different ADAS features were evaluated in the real-world scenarios. The objective data of the observations and occurrence conditions were captured with help of data loggers & camera setups inside the vehicle. This research paper represents a comprehensive study on the challenges faced by user while using ADAS enabled cars in Indian road conditions. We captured the performance data of various ADAS features, including lane departure warning (LDW), lane keep assist (LKA), adaptive cruise control (ACC), automatic emergency braking (AEB), Forward Collision Warning (FCW) and blind spot monitoring (BSM) in real-world driving scenarios and assessed the functionality and limitations of various ADAS features. Study shows that ADAS can significantly enhance road safety, however in certain cases effectiveness is compromised by factors such as poor road infrastructure, inadequate lane markings, unpredictable driver behavior etc. The result of the study highlights the challenges and give insights to develop the ADAS for Indian market scenarios and gives opportunity to auto OEMs for making test cases as per Indian road & driving conditions.
Kumbhar, Prasad Uttam, Pyasi, Praveen
Crowdsourcing Indian Traffic Scenarios for ADAS Development and Testing2026-26-00461/16/2026
In the Indian context, introduction of ADAS can play a positive role in improving road safety by assisting the driver and preventing unsafe driver behaviour. Technologies like Automated Emergency Braking (AEB), Lane Keep System, Adaptive Cruise Control, Driver Drowsiness Detection, Driver Alcohol detection etc., if deployed safely and used in a safe manner can help prevent many of the current road deaths in India. Safe deployment and safe use of such ADAS technologies require the systems to operate without failure within their operational design domains (ODD) and not surprise the drivers with sudden or unpredictable failures, to help develop their trust in the technology. As a result, identifying test scenarios remain a key step in the development of Advanced Driver Assistance Systems (ADAS). This remains a challenge due to the large test space especially for the Indian context due to the unpredictable traffic behaviour and occasional road infrastructure. In this paper, we introduce a novel open-access crowd-sourcing public platform, Safety Pool™ Studio, to enable crowdsourcing of traffic scenarios in the Indian context. Safety Pool™ Studio platform enables any member of the public or the road traffic ecosystem (e.g. traffic police, local authorities, academia etc.) to create a traffic scenario using a graphical interface, like a LEGO making exercise. This would enable the users to share their real-life experiences of traffic scenarios in a simple, accessible and inclusive manner and contribute to a global pool of traffic scenarios in the Indian context. Safety Pool™ Studio provides multi-language support for India’s regional languages like Hindi, Bengali, Tamil, Marathi, Punjabi, Kannada, Telugu, Gujrati among others. Safety Pool™ Studio has been developed in a way the graphical scenarios can automatically be converted into programmatic description of scenarios for traditional simulation-based testing of ADAS.
Serry, Hamid, Dodoiu, Tudor, Alakkad, Fadi, Zhang, Xizhe, Khastgir, Siddartha, Jennings, Paul
Advancing Safe and Sustainable Mobility: A Review of Emerging Trends and Challenges in ADAS2026-26-00421/16/2026
India’s severe road safety challenges, marked by high accident rates and fatalities, necessitate innovative solutions like Advanced Driver Assistance Systems (ADAS) to align with SIAT 2026’s theme, “Innovative Pathways for Safe and Sustainable Mobility.” This paper synthesizes recent studies to explore ADAS’s role in enhancing safety and sustainability in India’s unique traffic environment. Technologies such as automatic emergency braking, lane departure warnings, and driver monitoring systems show promise in reducing crashes caused by human error, a leading factor in road incidents. However, India’s complex road conditions—unmarked lanes, dense urban traffic, and prevalent two-wheelers—pose significant challenges to ADAS effectiveness. There developed is a strong public support recently for ADAS, with many Indian road users recognizing its safety benefits and advocating for its integration into vehicles especially passenger vehicles. Despite growing adoption by automakers like Tata and Mahindra, barriers such as high costs and inadequate infrastructure limit widespread use. This paper proposes an original ADAS framework tailored for India, incorporating AI-driven sensors to navigate erratic traffic and cost-effective designs to improve accessibility, particularly for two-wheeler and passenger vehicle users. By addressing these challenges, ADAS can significantly reduce accidents and support India’s Vision Zero aspirations for zero road fatalities. The review also emphasizes sustainable mobility, exploring energy-efficient ADAS technologies to complement India’s push for greener transportation. This synthesis offers a scalable model for integrating ADAS into India’s mobility ecosystem, providing insights for emerging markets and contributing to global safety standards. Through infrastructure enhancements and standardized protocols, this work charts a pathway for safer, sustainable roads in India.
Neelakanthu, Karra, Sreenivasulu, T, Kumar, Om, Haregaonkar, Rushikesh Sambhaji, Kumar, Rajiv
Methodical Approach to Preparedness of India Specific Automotive Database Matrix with Example of AEB Scenarios2026-26-06511/16/2026
The purpose of this report is to identify systematic approach of formation of India specific automotive database matrix. At first the paper reviews the practices used to prepare automotive dataset catalogue with established pattern to showcase automotive dataset from which appropriate data clusters can be picked up judiciously in order to train ADAS algorithms. The work applies this framework which helps to establish strategy to build a grid in which Indian automotive dataset can be contoured and selection of serviceable data bunches can be picked. This would make sure prompt selection of database aiming model training with valid input. This serves the purpose of implementation and evaluation of varied ADAS levels in India which insist upon good quality of distinguished dataset pertaining to Indian scenarios. The paper describes the approach with the example of AEB scenarios and present appropriate matrix readiness comprising of relevant data objects excluding unnecessary junk data targeting aftermath. The methodology can be base for amalgam of various Indian specific scenarios layered as per traffic objects and functions which can be picked up based on prerequisites of the test criteria and model training.
Behere, Sayali Rajendra, Karle, Manish, Karle, Ujjwala
Integrated Evaluation of Pre-Crash Braking and Crash Injury Outcomes Using Human Body Models and ATDs2026-26-00191/16/2026
Traditionally, occupant safety research has centered on passive safety systems such as seatbelts, airbags, and energy-absorbing vehicle structures, all designed under the assumption of a nominal occupant posture at the moment of impact. However, with increasing deployment of active safety technologies such as Forward Collision Warning (FCW) and Autonomous Emergency Braking (AEB), vehicle occupants are exposed to pre-crash decelerations that alter their seated position before the crash. Although AEB mitigates the crash severity, the induced occupant movement leads to out-of-position behavior (OOP), compromising the available survival space phase and effectiveness of passive restraint systems during the crash. Despite these evolving real-world conditions, global regulatory bodies and NCAP programs continue to evaluate pre-crash and crash phases independently, with limited integration. Moreover, traditional Anthropomorphic Test Devices (ATDs) such as Hybrid III dummies, although highly repeatable, lack the bio-fidelity necessary to capture human-like kinematics during pre-crash braking events involving low g. ATDs do not simulate the spinal articulation, posture adjustments and active muscle contraction that occur during emergency maneuvers or pre-crash scenarios. To overcome these limitations, researchers have increasingly turned to Human Body Models (HBMs) such as Total Human Model for Safety (THUMS) and Global Human Body Model Consortium (GHBMC). These models enable high-fidelity finite element (FE) simulations with anatomical realism, allowing for the inclusion of active musculature and posture changes. This study aims to quantify the occupant forward excursion under pre-crash phase (due to AEB) and explore the possibility of an integrated simulation framework that evaluates occupant safety across both pre-crash and crash events. For this, the approach was to carry out full vehicle braking tests (1g braking pulse) with adult male (AM50) volunteers at different speeds to measure forward head excursion during pre-crash. These scenarios were replicated in LS-Dyna using THUMS HBM, showing strong agreement with experimental data. The resulting excursed postures were then used in crash simulations with ATDs to evaluate the effect on injury outcomes. Overall, the findings demonstrate effect of forward excursion on occupant injuries and the effectiveness of HBMs in capturing occupant kinematics, during pre-crash events.
Pendurthi, Chaitanya Sagar, THANIGAIVEL RAJA, T, Kondala, Hareesh, Sudarshan, B.Sudarshan, Nehe, Vaibhav, Rao, Guruprakash
Leveraging Road Accident Database to Enhance ADAS Features and Testing Protocols in Context of Indian Driving Conditions2026-26-00141/16/2026
ADAS i.e. Advanced Driver Assistance Systems are pivotal towards amplifying road safety by reducing human error and assisting drivers in critical situations. Most major ADAS technologies are developed and validated using data and test scenarios that are predominantly based on the driving conditions and road environments of developed countries. However, in a country like India, where driving behavior, traffic dynamics, road infrastructure, and accident characteristics differ significantly, the ADAS technologies and test scenarios validated by different forums create a critical gap in deploying such systems on vehicles to work on Indian roads. The major aim of this study was to determine and generate India-specific ADAS test scenarios from the Road Accident Sampling System India (RASSI) database, available MoRTH reports, and data from previously executed ADAS test cases. Through this research, we propose a methodology to identify, extract, and analyze accident scenarios pertaining to the Indian driving environment and their usefulness in developing ADAS technologies to achieve the best results when deployed on vehicles in India. The RASSI database provides exposure to various data factors related to accidents from accident reconstructions, such as velocities at different timestamps, positions of vehicles with respect to time, and pre-crash maneuvers. In addition, the data from MoRTH reports regarding different categories of vehicle collisions will be analyzed extensively for scenario identification and generation for the evaluation of different ADAS functionalities, like Forward Collision Warning, Lane departure warning (LDW), Automatic emergency braking (AEB), and Blind spot detection System. Furthermore, the data generated from the available ADAS Test validations were examined to verify the different parameters related to specific ADAS features. For the purpose of authentication of the pinpointed scenarios, they will be simulated in the simulation software named IPG Carmaker for affirmation of the effectiveness of ADAS functionality if present in the India specific identified accident test scenarios. With the purpose of minimizing the localization gap in ADAS testament, this study provides a data driven, standardized approach towards generation of test scenarios adapted to Indian driving environment.
Adhikari, Mayur, Bhagat, Ajinkya, Verma, Harshal, Kale, Jyoti Ganesh, Karle, Ujjwala, Sharma, Chinmaya
Modeling and Validating Foreseeable Misuse in Safety of the Intended Functionality: A Case Study of Automated Emergency Braking12-09-03-001712/31/2025
This study presents a structured evaluation framework for reasonably foreseeable misuse in automated driving systems (ADS), grounded in the ISO 21448 Safety of the Intended Functionality (SOTIF) lifecycle. Although SOTIF emphasizes risks that arise from system limitations and user behavior, the standard lacks concrete guidance for validating misuse scenarios in practice. To address this gap, we propose an end-to-end methodology that integrates four components: (1) hazard modeling via system–theoretic process analysis (STPA), (2) probabilistic risk quantification through numerical simulation, (3) verification using high-fidelity simulation, and (4) empirical validation via driver-in-the-loop system (DILS) experiments. Each component is aligned with specific SOTIF clauses to ensure lifecycle compliance. We apply this framework to a case of driver overreliance on automated emergency braking (AEB) at high speeds—a condition where system intervention is intentionally suppressed. Initial numerical analysis suggested that the scenario narrowly satisfies the acceptance criteria. Applying the proposed framework to this scenario reveals that significant safety risks can persist even when the system functions according to its design intent. Our findings demonstrate that foreseeable misuse can be formally modeled, simulated, and empirically validated within the SOTIF framework. The proposed approach enables system developers to quantify behavioral risk and assess human-centered edge cases with greater rigor. This work contributes to operationalizing SOTIF for behavioral safety assurance and lays the foundation for future research on risk mitigation through adaptive HMI and context-aware alerts.
Kang, Do Wook, Kim, Woojin, Jang, Eun Hye, Chang, Mi, Yoon, Daesub, Jang, Youn-Seon
Development of an Adaptive Algorithm for the Automatic Emergency Braking System10-10-01-000812/13/2025
Automatic emergency braking (AEB) systems are crucial for road safety but often face performance challenges in complex road and climatic conditions. This study aims to enhance AEB effectiveness by developing a novel adaptive algorithm that dynamically adjusts braking parameters. The core of the contribution is a refined mathematical model that incorporates vehicle-specific correction coefficients and a real-time prediction of the road–tire friction coefficient. Furthermore, the algorithm features a unique driver-style adaptation module to optimize warning times. The developed system was functionally tested on a vehicle prototype in scenarios including dry, wet, and snow-covered surfaces. Results demonstrate that the adaptive algorithm significantly improves collision avoidance performance compared to a non-adaptive baseline, particularly on low-friction surfaces, without introducing excessive false interventions. The study concludes that the proposed adaptive approach is a vital step toward all-weather capable AEB systems.
Petin, Viktor, Keller, Andrey, Shadrin, Sergey, Makarova, Daria, Antonyan, Akop, Furletov, Yury
TOC99-07-06-0TOC12/2/2025
TOC
Tobolski, Sue
Automatic Brake Failure Detection with Electromagnetic Braking System2025-28-037310/30/2025
Brake failures in the vehicles can cause hazardous accidents so having a better monitoring and emergency braking system is very important. So, this project consists of an autonomous brake failure detector integrated with Automatic Braking using Electromagnetic coil braking which detects the braking failure at the time and applied the combinations of the brakes, to overcome this kind of accidents. So, here the system comprises of IR sensor circuit, control unit and electromagnetic braking system. How it works: The IR sensor monitors the brake wire, and if the wire is broken, the control unit activates the electromagnetic brakes, stopping the vehicle in a safe manner. This system enhances vehicle safety by ensuring immediate braking action without driver intervention. Key advantages include real-time brake monitoring, reduced mechanical wear, quick response time, and an automatic failsafe mechanism. The system’s minimal reliance on hydraulic components also makes it suitable for harsh or variable conditions. The proposed system can be widely implemented in automobiles, especially those using drum brakes, as well as railway systems to prevent accidents due to brake failure. Future advancements in predictive maintenance, machine learning, and AI integration could further improve the reliability, adaptability, and overall efficiency of this advanced braking system.
Raja, Selvakumar, John, Godwin, Siddarth, J P, Senthilkumar, Akash, Mathew, Abhay, R. S., Nakandhrakumar, Nandagopal, Sasikumar, Arumugam, Sivasankar
Design and Development of a Data-Driven Animal Collision Avoidance System2025-01-50396/10/2025
A collision avoidance system is an advanced driver assistance system (ADAS) designed to prevent vehicle collisions. The existing system is designed primarily to detect and prevent collisions with humans, vehicles, or other objects on the road, but not specifically designed to address collisions involving animals. When it comes to animals, the collision avoidance rate is low, which is due to low animal detection accuracy, high false positives/negatives and unsuitable methods of mitigating collisions, hence, an enhancement of the system is required. Humans are warned off the road during the approach of a vehicle through the horn sound. In ADAS systems, the vehicle stops as the human behavior is quite predictable on sight or approach of a speeding vehicle, but this is ineffective on animals. Not all animals can hear the honk due to their different hearing ranges, and the unpredictability of their behaviors makes it impossible to predict their next move to avoid an accident; this leads ultimately to a collision even when equipped with the most advanced collision avoidance systems. There needs to be a more preventive approach to keep the animals that are likely to collide, off the road. It can be done with enhancement of the collision avoidance system. The animal collision avoidance system (ACAS) uses ADAS sensor suite and GPS inputs to detect and predict the behavior of an approaching animal. Further, the ACAS calculates the likelihood of collision and reacts accordingly to warn off the animal either through a threat warning in its hearing range or by adapting the vehicle to not collide with the animal.
Arckja, W.
Detect and Avoid function for UAVs using ACAS Xu for Non-Cooperative TargetsF-0081-2025-02745/20/2025
Advanced Air Mobility (AAM) is an innovative concept that aims to revolutionize air transportation through electric and unmanned aircraft, enabling applications such as urban air taxis and medical transport. However, one of the key challenges to its widespread adoption is ensuring safety, particularly in collision avoidance. This study focuses on the development of a perception and guidance system for avoiding collisions with non-cooperative targets, which do not share their position or trajectory. To achieve this, a Frequency-Modulated Continuous Wave (FMCW) radar and an InfraRed(IR) camera are used. Compared to traditional pulsed or panel radars, FMCW radars offer higher resolution, better detection of small and slow-moving objects, and improved performance in cluttered environments. The IR camera enhances situational awareness by providing visual confirmation and additional tracking capability, making this sensor fusion approach particularly suitable for AAM applications. Our collision avoidance system follows ACAS Xu standards, which provide autonomous conflict detection and resolution for unmanned aerial vehicles. The maneuver selection process is based on precomputed lookup tables generated through a Markov Decision Process (MDP), optimizing responses based on risk and energy consumption. The entire system is tested in a simulation environment using Ansys AVxcelerate, a physics-based simulator capable of generating realistic sensor data. This approach allows for comprehensive testing of detection, tracking, and maneuver execution in a highly realistic scenario, ensuring the effectiveness of the proposed solution before real-world deployment.
Brivio, Riccardo, Crippa, Anna, Baiguera, Matteo, Portanti, Samuele, Bertolo, Mattia
Automatic Emergency Braking (AEB) System Performance TestingJ3087_202504 (Current)4/14/2025
This document describes an SAE Recommended Practice for Automatic Emergency Braking (AEB) system performance testing which: Establishes uniform vehicle level test procedures Identifies target equipment, test scenarios, and measurement methods Identifies and explains the performance data of interest Does not exclude any particular system or sensor technology Identifies the known limitations of the information contained within (assumptions and “gaps”) Is intended to be a guide toward standard practice and is subject to change on pace with the technology Focuses on “Vehicle Front to Rear, In Lane Scenarios” expanded to include additional offset impacts This document describes the equipment, facilities, methods, and procedures needed to evaluate the ability of Automatic Emergency Braking (AEB) systems to detect and respond to another vehicle, in its forward path, as it is approached from the rear. This document does not specify test conditions (e.g., speeds, decelerations, clearance gaps, etc.). Those values will be defined by the tester according to the intended purpose of a given test sequence. Informative examples are provided for reference in Appendix B. The procedure includes three test scenarios: Stopped lead vehicle (Test 1): The vehicle being approached is stopped in the lane of the test vehicle. Slower lead vehicle (Test 2): The vehicle being approached is moving at a constant speed that is slower than the test vehicle. Decelerating lead vehicle (Test 3): The vehicle being approached is initially moving at the same speed as the test vehicle, but then slows.
Active Safety and Driver Support Systems Standards Committee
Research on the Boundary of Pedestrian Leg Impactor Test in Low-Speed Passive and Active Conditions2025-01-87354/1/2025
With the widespread application of the Automatic Emergency Braking System (AEB) in vehicles, its impact on pedestrian safety has received increasing attention. However, after the intervention of AEB, the kinematic characteristics of pedestrian leg collisions and their corresponding biological injury responses also change. At the same time, in order to accurately evaluate the pedestrian protection performance of vehicles, the current assessment regulations generally use advanced pedestrian protection leg impactors (aPLI) and rigid leg impactors (TRL) to simulate the movement and injury conditions of pedestrian legs. Based on this, in order to explore the collision boundary conditions and changes in injury between vehicles and APLI and TRL leg impactors under the action of AEB, this paper first analyzes the current passive and active assessment conditions. Secondly, the simulation software LS-DYNA is used to build a finite element model of APLI and TRL impactor-vehicle collisions to analyze the changes in collision boundary conditions between leg impactors and vehicles. Finally, based on the simulation model, the changes in injury of leg impactors with and without AEB are further analyzed. The research results show that after the intervention of AEB, the impact positions of aPLI and TRL on the front of the vehicle will change, and the change of sedan is more significant than that of SUV. At the same time, under the action of AEB, the damage of aPLI and TRL will change significantly, and the front edge position of the vehicle is more sensitive. This study provides important theoretical support for the subsequent integrated safety assessment of pedestrian protection, provides design references for future pedestrian protection regulation assessments, and has important guiding significance for the optimization of vehicle front-end structures.
Ye, Bin, Hong, Cheng, Wan, Xinming, Liu, Yu, Cheng, James, Long, Yongchen, Hao, Haizhou
Numerical Investigation of Fuel Injection Strategies for Ammonia-Diesel Dual-Fuel Engine2025-01-83684/1/2025
This study numerically investigates ammonia-diesel dual fuel combustion in a heavy-duty engine. Detailed and reduced reaction mechanisms are validated against experimental data to develop injection timing maps aimed at maximizing indicated thermal efficiency (ITE) while mitigating environmental impacts using stochastic reactor model (SRM). The equivalence ratio, ammonia energy share (AES), injection timing, and engine load are varied to optimize combustion efficiency and minimize emissions. The results demonstrate that advancing injection timing reduces ITE due to heightened in-cylinder temperatures, resulting in increased heat losses through walls and exhaust gases. Maximum chemical efficiency is observed at an equivalence ratio near 0.9 but decreases thereafter, influenced by ammonia’s narrow flammability range. Emission analysis highlights significant reductions in Global Warming Potential (GWP) and Eutrophication Potential (EP) with higher AES, driven by decreased CO2 and nitrogen oxides (NOx) emissions. Acidification Potential (ACP) initially rises with higher AES due to increased NOx production but diminishes as Pressure Rise Rate (PRR) and Ringing Intensity (RI) increase with higher AES and advancing injection timing. Conversely, Ozone Forming Potential (OFP) diminishes with higher AES due to reduced volatile organic compounds emissions.
Karenawar, Shivraj Anand, Yadav, Neeraj Kumar, Maurya, Rakesh Kumar
Collision Avoidance System at Urban Intersections Using V2X Communication2025-01-80304/1/2025
Driving safely through urban intersections is quite challenging for self-driving vehicles due to complicated road geometries and the highly dynamic maneuvers of oncoming traffic, which can cause a high risk of collisions. Traditional onboard sensors like cameras, radar, and lidar give limited visibility in this environment. To overcome these limitations, this paper explores implementing a collision avoidance system at urban intersections utilizing vehicle-to-everything (V2X) communication. The system leverages V2X map data to identify warning zones and uses vehicle-to-vehicle (V2V) communication to estimate the maneuver types and paths of approaching vehicles. The system assesses collision risk by calculating the intersection points of predicted paths for the ego vehicle and oncoming traffic. Depending on the level of collision risk, the system generates a collision warning signal to the driver or activates emergency braking when necessary to prevent accidents. We implement the system using Simulink and the RoadRunner scenario simulation tool. To evaluate system performance in a virtual simulation environment, we create a complex urban scene with intersections and traffic signals using RoadRunner. The high-definition (HD) map from RoadRunner is converted into V2X map messages compliant with the T/CSAE 53-2020 standard. RoadRunner’s Signal Tool configures junction signalization and traffic phases. RoadRunner Scenario uses this traffic signal phase information to simulate traffic signals, which are then converted into V2X SPaT (Signal Phase and Timing) messages.
Park, Seo-Wook, Suresh, Raynier, Ailuri, Anusha
Analysis of OEM Collision Avoidance Data Outputs during VRU Testing2025-01-80534/1/2025
Using OEM tools to analyze data available from on-vehicle collision avoidance systems can shed light on the data scope that is available to analyze failures in these systems. In this work, an Advanced Driver Assistance System (ADAS)-equipped vehicle was tested to determine the performance in several collision imminent scenarios. Vehicle Event Data Recorder (EDR) data was pulled and compared to data collected from independent instrumentation to determine the vehicle system accuracy in detecting targets, investigate timings, and understand the scope of data available to an agency investigating a failure. Images and data files are presented as an example of scope of output. Tests included several variable overlap tests, along with several tests specifically chosen due to compare performance across the operating design domain.
Bartholomew, Meredith, Heydinger, Gary
Development of a Computer-Less Robotic Platform for ADAS Testing2025-01-80644/1/2025
Testing collision avoidance systems on vehicles has become increasingly complex. Robotic platforms called Pedestrian Target Carriers (PTC) typically require Global Positioning System (GPS), network communications, tuning, and ever-increasing scope to the user interface to function. As an alternative to these complicated systems, but as an improvement to a pulley system pedestrian target carrier, a simplistic robotic platform was developed. An open-loop user interface was designed and developed, and a series of tests were performed to evaluate the effectiveness of the robot in performing basic, repeatable straight-line tests with a vehicle in the loop. Based on testing outcomes, the development of further control algorithms, user requirements, and the prototype improvements are analyzed for future work.
Bartholomew, Meredith, Muthaiah, Ponaravind, Heydinger, Gary, Zagorski, Scott
Compensation Algorithm Development in Platform for Pedestrian ADAS Testing2025-01-80664/1/2025
Test procedures such as EuroNCAP, NHTSA’s FMVSS 127, and UNECE 152 all require specific pedestrian to vehicle overlaps. These overlap variations allow the vehicle differing amounts of time to respond to the pedestrian’s presence. In this work, a compensation algorithm was developed to be used with the STRIDE robot for Pedestrian Automatic Emergency Braking tests. The compensation algorithm uses information about the robot and vehicle speeds and positions determine whether the robot needs to move faster or slower in order to properly overlap the vehicle. In addition to presenting the algorithm, tests were performed which demonstrate the function of the compensation algorithm. These tests include repeatability, overlap testing, vehicle speed variation, and abort logic tests. For these tests of the robot involving vehicle data, a method of replaying vehicle data via UDP was used to provide the same vehicle stimulus to the robot during every trial without a robotic driver in the vehicle.
Bartholomew, Meredith, Nguyen, An, Helber, Nicholas, Heydinger, Gary
Do Aftermarket and Original Equipment Forward Collision Warning Systems Respond the Same to Vehicles and Pedestrians?2025-01-86774/1/2025
About 32% of registered vehicles in the U.S are equipped with automatic emergency braking or forward collision warning (FCW) systems [1]. Retrofitting vehicles with aftermarket devices can accelerate the adoption of FCW, but it is unclear if aftermarket systems perform similarly to original equipment manufacturer (OEM) systems. The performance of four low-cost, user-installable aftermarket windshield-mounted FCW systems was evaluated in various Insurance Institute for Highway Safety (IIHS) rear-end and pedestrian crash avoidance tests and compared with previously tested OEM systems. The presence and timing of FCWs were measured when vehicles approached a stationary passenger car at 20, 40, 50, 60, and 70 km/h, motorcycle and dry van trailer at 50, 60, and 70 km/h, adult pedestrian at 40 and 60 km/h, and child pedestrian crossing the road at 20 and 40 km/h. Equivalence testing was used to determine if FCW performance was similar for aftermarket and OEM systems. OEM systems provided a warning in 95% of trials, while aftermarket systems warned in 67%. Performance was similar with the passenger car, but aftermarket systems warned in significantly fewer trials with the motorcycle, dry van trailer, and child pedestrian. On average, OEM systems warned 1.1 to 2.5 seconds before impact with different targets, while the aftermarket systems warned 0.3 to 3.5 seconds before impact. The findings indicate that existing aftermarket FCW systems can address the most common rear-end crash type involving other passenger cars but not rear-end crashes involving motorcycles or heavy trucks or crashes with pedestrians, all of which are more likely to be fatal. By expanding existing testing programs to aftermarket devices, regulatory agencies and consumer information organizations can inform consumers about the technologies, accelerate adoption, and encourage aftermarket device manufacturers to improve the performance of their systems so that the devices can provide the safety benefits observed with OEM systems.
Kidd, David, Floyd, Philip, Aylor, David
Daytime and Nighttime Performance Evaluations of the Automatic Emergency Braking and Forward Collision Warning Systems on a 2020 and 2022 Kia Telluride2025-01-86994/1/2025
Testing was conducted in daytime and nighttime conditions to evaluate the performance of the Automatic Emergency Braking and Forward Collision Warning systems present on both a 2020 and 2022 Kia Telluride. The 2022 Kia Telluride was tested during the day at speeds between 35 and 70 miles per hour, while the 2020 Kia Telluride was tested both during the day and at night at speeds between 35 and 60 miles per hour (mph). The daytime testing of both the 2020 and 2022 Kia Telluride utilized a foam stationary vehicle target. The nighttime testing of the 2020 Kia Telluride utilized a live 2006 Chevrolet Tahoe as the target with the brake lights on. Testing measured the Time to Collision (TTC) values of the visual/audible component of the Forward Collision Warning (FCW) that was presented to the driver. Further, testing also quantified the timing and magnitude of the two-phase response of the Automatic Emergency Braking (AEB) system. The results of both sets of testing add higher speed FCW and AEB testing scenarios to the database of publicly available tests for the Kia Telluride.
Harrington, Shawn, Patrick-Moline, Peyton, Nagarajan, Sundar Raman
An Evaluation of the Performance of the Automatic Emergency Braking and Forward Collision Warning System in a 2020 Jeep Grand Cherokee during Daytime and Nighttime Conditions2025-01-86984/1/2025
Testing was conducted to evaluate the performance of the 2020 Jeep Grand Cherokee’s Forward Collision Warning (FCW) and Automatic Emergency Braking (AEB) collision mitigation systems at speeds between 35 and 70 miles per hour (mph). Two different 2020 Jeep Grand Cherokee’s were utilized under varying testing conditions in order to evaluate the performance of their collision mitigation systems. A total of 40 tests were conducted: 29 tests were conducted during daytime and 11 tests were conducted at nighttime. Testing measured the Time to Collision (TTC) values of the visual/audible component of the Forward Collision Warning that was presented to the driver. In addition, the testing quantified the TTC response of the Automatic Emergency Braking (AEB) system including the timing and magnitude of the automatic braking response. The results of the testing add higher speed FCW and AEB testing scenarios to the database of publicly available tests for the 2020 Jeep Grand Cherokee.
Harrington, Shawn, Lieber, Victoria, Nagarajan, Sundar Raman
Active and Passive Security Generalization Algorithm and Typical Case Analysis2025-01-87444/1/2025
In order to effectively predict the vehicle safety performance and reduce the cost of enterprise safety tests, a generalized simulation model for active and passive vehicle safety was proposed. The frontal driver-side collision model under the intervention of the Autonomous Emergency Braking (AEB) was created by using the MADYMO software. The collision acceleration obtained from the sled test was taken as the original input of the model to conduct simulation for the working conditions under different sitting postures of the human body. The injury values of various parts of the Hybrid III 50th dummy were read. Based on the correlation between the two, an active and passive simulation model was established through the Back Propagation (BP) neural network. The input of the model was the inclination angle centered on the dummy's waist, and the output was the acceleration of the dummy's head. The results showed that the comprehensive prediction accuracy rate exceeded 80%. Therefore, the design of the model algorithm can effectively predict the degree of injury suffered by the driver in the event of a collision, which is conducive to the rapid evaluation of vehicle safety performance.
Ge, Wang, fengyao, LV
A Study on Affections of Active Neck Muscle Force on Neck Injury Responses in Frontal Impact with Automatic Emergency Braking Conditions2025-01-87424/1/2025
Neck injury is one of the most common injuries in traffic accidents, and its severity is closely related to the posture of the occupant at the time of impact. In the current era of smart vehicle, the triggered AEB and the occupant's active muscle force will cause the head and neck to be out of position which has significant affections on the occurrence and severity of neck injury responses. Therefore, it is very important to study the influences of active muscle force on neck injury responses in in frontal impact with Automatic Emergency Braking conditions. Based on the geometric characteristics of human neck muscles in the Zygote Body database, the reasonable neck muscle physical parameters were obtained firstly. Then a neck finite element model (FEM) with active muscles was developed and verified its biofidelity under various impact conditions, such as frontal, side and rear-end impacts. Finally, using the neck FEM with or without active muscle force, a comparative study was conducted on the kinematics and injury responses of the neck in the frontal impact with AEB condition. The research findings indicate that the activation of cervical active muscle forces effectively reduces the displacement of the head's center of gravity prior to the collision and significantly decreases the relative angular displacements between cervical vertebrae during the collision. These dynamic response changes mitigate the injury severity of cervical vertebrae, ligaments, and intervertebral discs, thereby enhancing the biomechanical tolerance of the cervical structure to mechanical loads.
Junpeng, Xu, Gan, Qiuyu, Jiang, Binhui, Zhu, Feng
Study on the Impact of Vehicle Pitch During Braking on Pedestrian Leg Injuries2025-01-87414/1/2025
With the increasing prevalence of Automatic Emergency Braking Systems (AEB) in vehicles, their performance in actual collision accidents has garnered increasing attention. In the context of AEB systems, the pitch angle of a vehicle can significantly alter the nature of collisions with pedestrians. Typically, during such collisions, the pedestrian's legs are the first to come into contact with the vehicle's front structure, leading to a noticeable change in the point of impact. Thus, to investigate the differences in leg injuries to pedestrians under various pitch angles of vehicles when AEB is activated, this study employs the Total Human Model for Safety (THUMS) pedestrian finite element model, sensors were established at the leg location based on the Advanced Pedestrian Legform Impactor (APLI), and a corresponding vehicle finite element model was used for simulation, analyzing the dynamic responses of the pedestrian finite element model at different pitch angles for sedan and Sport Utility Vehicle (SUV), and comparing injury indicators for the thigh, lower leg, and knee joint. The results indicate that the vehicle's pitch angle reduces the elongation of the medial collateral ligament (MCL) in the pedestrian's knee and increases the maximum bending moment of the thigh. For sedan with pitch angles, the maximum bending moment of the pedestrian's lower leg decreases at a vehicle speed of 40 km/h and increases at speeds of 30 km/h and 20 km/h. The impact of SUV on the maximum bending moment of the lower leg is opposite to that of sedan. This study holds guiding significance for optimizing vehicle design, enhancing the effectiveness of AEB systems, and establishing stricter pedestrian protection standards.
Hong, Cheng, Ye, Bin, Zhan, Zhenfei, Liu, Yu, Wan, Xinming, Hao, Haizhou
High-Speed FCW & AEB Testing of Tesla Model 3's Across Software Updates2025-01-86954/1/2025
A total of 148 tests were conducted to evaluate the Forward Collision Warning (FCW) and Automatic Emergency Braking (AEB) systems in five different Tesla Model 3 vehicles between model years 2018 and 2020. The testing occurred across four calendar years from 2020 to 2024. These tests involved testing against stationary vehicle targets, including a foam Stationary Vehicle Target (SVT), a Deformable Stationary Vehicle Target (DSVT), a live vehicle with brake lights, and a SoftCar360 designed for high-speed impact tests. The evaluations were conducted at speeds of 35, 50, 60, 65, 70, 75, and 80 miles per hour (mph) during both daytime and nighttime conditions. The analysis encompassed comparisons of Time to Collision (TTC) at FCW, TTC at AEB, and emergency braking deceleration magnitudes across the different software versions. Testing of the Traffic Aware Cruise Control (TACC) system was also conducted against a stationary target in the Tesla’s lane at a speed of 80 mph. The findings demonstrate consistent and repeatable FCW alerts across all tests and software versions, although differences in performance between software versions were found. Peak AEB decelerations greater than 1g were observed in some tests where AEB engaged.
Harrington, Shawn, Nagarajan, Sundar Raman
Advanced Driver Assistance Systems (ADAS): Assessing the Efficacy of Non-Impact Testing for Evaluating the Performance of Frontal Collision Mitigation Technology2025-01-80564/1/2025
As Automatic Emergency Braking (AEB) systems become standard equipment in more light duty vehicles, the ability to evaluate these systems efficiently is becoming critical to regulatory agencies and manufacturers. A key driver of the practicality of evaluating these systems’ performance is the potential collision between the subject vehicle and test target. AEB performance can depend on vehicle-to-vehicle closing speeds, crash scenarios, and nuanced differences between various situational and environmental factors. Consequently, high speed impacts that may occur while evaluating the performance of an AEB system, as a result of partial or incomplete mitigation by an AEB activation, can cause significant damage to both the test vehicle and equipment, which may be impractical. For tests in which impact with the test target is not acceptable, or as a means of increasing test count, an alternative test termination methodology may be used. One such method constitutes the application of a late steering maneuver by the driver to avoid the target prior to a potential collision. In this study, a test series was performed with and without late steering input to determine if this alternative AEB evaluation methodology can be used to accurately predict the degree to which an AEB system performs. The results were compared to non-swerve tests to assess whether non-impact testing can be used to determine the extent to which AEB system response would have mitigated a collision. The findings indicate that there are significant limitations to the accuracy of predictions made with this approach.
Kuykendal, Michelle, Easter, Casey, Koszegi, Giacomo, Alexander, Ross, Paradiso, Marc, Scally, Sean
Research on Automatic Emergency Braking Pedestrian System Considering Road Adhesion Coefficient10-09-03-00223/8/2025
To further optimize the automatic emergency braking for pedestrian (AEB-P) control algorithm, this study proposes an AEB-P hierarchical control strategy considering road adhesion coefficient. First, the extended Kalman filter is used to estimate the road adhesion coefficient, and the recursive least square method is used to predict the pedestrian trajectory. Then, a safety distance model considering the influence factor of road adhesion coefficient is proposed to adapt to different road conditions. Finally, the desired deceleration is converted into the desired pressure and desired current to the requirements of the electric power-assisted braking system. The strategy is verified through the hardware-in-the-loop (HIL) platform; the simulation results show that the control algorithm proposed in this article can effectively avoid collision in typical scenarios, the safe distance of parking is between 0.61 m and 2.34 m, and the stop speed is in the range of 1.85 km/h–27.64 km/h.
Wang, Zijun, Wang, Liang, Ma, Liang, Sun, Yong, Li, Chenghao, Yang, Xinglong
TOC99-07-01-0TOC2/17/2025
TOC
Tobolski, Sue
FPGA Implementation of HLS Crypto Accelerators for Embedded Security in Autonomous Vehicles2025-28-02052/7/2025
The growing ubiquity of autonomous vehicles (AVs) has introduced a new attack surface for malicious actors: the embedded systems that govern a vehicle's critical operations. Security breaches in these systems could have catastrophic consequences, potentially leading to loss of control, manipulation of sensor data, or even physical harm. To mitigate these risks, robust cybersecurity measures are paramount. This research delves into a specific threat – side-channel attacks – where attackers exploit data leakage through unintentional physical emanations, like power consumption or electromagnetic waves, to steal cryptographic keys or sensitive information. While various software and hardware countermeasures have been proposed, this study focuses on the implementation of masking techniques within the realm of embedded security. Masking techniques aim to obfuscate sensitive data during cryptographic operations, making it significantly harder for attackers to exploit side-channel vulnerabilities. This research explores the suitability of a Boolean masking approach within a high-level synthesis environment. This system-level approach offers several advantages over traditional design methodologies. It facilitates faster design processes by enabling early identification and rectification of errors. Additionally, it streamlines hardware-software co-design, allowing for a more integrated and efficient security architecture within the autonomous vehicle's embedded systems. Furthermore, the system-level approach enables the application of advanced validation strategies, ensuring the effectiveness of the implemented masking techniques. To evaluate the efficacy of the Boolean masking approach, the research investigates its application to three prominent block cipher algorithms – PRESENT, AES, and Serpent – all of which are based on substitution-permutation networks (SPNs). By implementing these masked algorithms in C and simulating their performance within an embedded system context, the study assesses factors like resource utilization and overall processing speed. This comparative analysis aims to identify the most effective masking implementation for protecting cryptographic operations in autonomous vehicles. Ultimately, the findings of this research can inform the development of robust security frameworks that safeguard autonomous vehicles against side-channel attacks and other cyber threats, paving the way for a safer and more secure future of transportation.
Deepan Kumar, Sadhasivam, R, Vishnu Ramesh Kumar, M, Boopathi, Manojkumar, R, R, Gobinath, M, Vignesh
Software Architecture for Autonomous Vehicles using MATLAB Simulink2025-28-01902/7/2025
Autonomous vehicles utilise sensors, control systems and machine learning to independently navigate and operate through their surroundings, offering improved road safety, traffic management and enhanced mobility. This paper details the development, software architecture and simulation of control algorithms for key functionalities in a model that approaches Level 2 autonomy, utilising MATLAB Simulink and IPG CarMaker. The focus is on four critical areas: Autonomous Emergency Braking (AEB), Adaptive Cruise Control (ACC), Lane Detection (LD) and Traffic Object Detection. Also, the integration of low-level PID controllers for precise steering, braking and throttle actuation, ensures smooth and responsive vehicle behaviour. The hardware architecture is built around the Nvidia Jetson Nano and multiple Arduino Nano microcontrollers, each responsible for controlling specific actuators within the drive-by-wire system, which includes the steering, brake and throttle actuators. Communication between these components is facilitated through the CAN protocol, which ensures accurate and reliable data transfer essential for real-time decision-making. AEB achieves precise emergency braking and enhances driver comfort through the use of PID controllers, while ACC leverages radar data to maintain a safe distance from the vehicle ahead. LD employs the Hough Transform algorithm for accurate road edge detection. Furthermore, a trained neural network within the system identifies and responds to traffic signals, signage, pedestrians and vehicles. The camera interfaces directly with the Jetson Nano, while radar data is shared with the IMU through a dedicated CAN bus. This integrated approach represents a significant advancement in autonomous vehicle control, thus contributing to enhanced safety, comfort and reliability for both drivers and passengers. This software architecture is designed based on aBaja 2024 competition and according to its rules, regulations, requirements and specifications, the controllers and simulations were designed.
Ann Josy, Tessa, Sadique, Anwar, Thomas, Merlin, Manaf T M, Ashik, Vr, Sreeraj
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