Browse Topic: Collision intervention systems

Items (469)
Verifying training datasets in vision-based vehicle safety applications is crucial to understanding the potential limitations of detection capabilities that may result in a higher safety risk. Vision-based pedestrian safety applications with crash avoidance technologies rely on prompt detection to avoid a crash. This research aims to develop a verification process for vulnerable road user safety applications with vision-based detection functionalities. It consists of reviewing the application’s safety requirements, identifying the target objects of detection in the operational design domain and pre-crash scenarios, and evaluating the safety risks qualitatively by examining the training dataset based on the results of pre-crash scenarios classification. As a demonstration, the process is implemented using open-source pedestrian tracking software, and the pre-crash scenarios are classified based on the trajectories of pedestrians in an example training dataset used in a pedestrian
Hsu, Chung-Jen
To address the issues of unreasonable collision avoidance path planning algorithms and inadequate safety in high-speed scenarios, a trajectory prediction-based collision avoidance path planning algorithm has been proposed. First, a trajectory prediction model is constructed using the long–short-term memory (LSTM) network, and the trajectory prediction model is trained and tested with the HighD dataset. Second, the future trajectory of the obstacle car is predicted, the future trajectory information of the two cars is combined to generate the lane-changing decision, and the three-times B-spline curves are used to generate the collision avoidance path clusters. The optimal collision avoidance paths are generated based on the multi-objective optimization function. Finally, build a MATLAB/CarSim simulation platform to verify the reasonableness and safety of the planned paths by taking the three scenarios of the continuous overtaking, preceding car pulling out, and the neighboring car
Liu, Xiao LongZhang, LeiLi, Peng KunXie, RuWang, QingLi, Ran Ran
Cooperation lies at the core of multiagent systems (MAS) and multiagent reinforcement learning (MARL), where agents must navigate between individual interests and collective benefits. Advanced driver assistance systems (ADAS), like collision avoidance systems and adaptive cruise control, exemplify agents striving to optimize personal and collective outcomes in multiagent environments. The study focuses on strategies aimed at fostering cooperation with the aid of game-theoretic scenarios, particularly the iterated prisoner’s dilemma, where agents aim to optimize personal and group outcomes. Existing cooperative strategies, such as tit-for-tat and win-stay lose-shift, while effective in certain contexts, often struggle with scalability and adaptability in dynamic, large-scale environments. The research investigates these limitations and proposes modifications to align individual gains with collective rewards, addressing real-world dilemmas in distributed systems. By analyzing existing
Nidamanuri, JaswanthSathi, VaigaraiShaik, Sabahat
The off-highway industry witnesses a vast growth in integrating new technologies such as advance driver assistance systems (ADAS/ADS) and connectivity to the vehicles. This is primarily due to the need for providing a safe operational domain for the operators and other people. Having a full perception of the vehicle’s surrounding can be challenging due to the unstructured nature of the field of operation. This research proposes a novel collective perception system that utilizes a C-V2X Roadside Unit (RSU)-based object detection system as well as an onboard perception system. The vehicle uses the input from both systems to maneuver the operational field safely. This article also explored implementing a software-defined vehicle (SDV) architecture on an off-highway vehicle aiming to consolidate the ADAS system hardware and enable over-the-air (OTA) software update capability. Test results showed that FEV’s collective perception system was able to provide the necessary nearby and non-line
Feiguel, MatthieuObando, DavidAlzubi, HamzehAlRousan, QusayTasky, Thomas
Automatic emergency braking (AEB) systems play a crucial role in enhancing vehicular safety. Current research predominantly focuses on the longitudinal dynamics of vehicles, utilizing various control algorithms to improve braking effectiveness. However, there has been limited exploration into utilizing wheel deflection as a method to further enhance emergency braking performance. This study aims to contribute by proposing an advanced enhancement of the AEB system through coordinated wheel deflection strategies. In an emergency situation, when the speed of AEB-equipped vehicle drops to the set threshold due to wheel braking, the innovative control system will activate. The vehicle’s coaxial wheels will then execute a counter-deflection maneuver to maximize friction between the tires and the road surface. As a result, this approach reduces braking distance, thereby enhancing vehicle safety. The effectiveness of the proposed control algorithm is validated through combined simulation using
Lai, FeiXiao, HaoHuang, Chaoqun
India is a diverse country in terms of road conditions, road maintenance, traffic conditions, traffic density, quality of traffic which implies presence of agricultural tractors, bullock carts, autos, motor bikes, oncoming traffic in same lane, vulnerable road users (VRU) walking in the same lanes as vehicles, VRU’s crossing roads without using zebra crossings etc. as additional traffic quality deterrents in comparison to developed countries. The braking capacity of such vivid road users may not be at par with global standards due to their maintenance, loading beyond specifications, driver behavior which includes the tendency to maintain a close gap between the preceding vehicle etc. which may lead to incidents specifically of rear collisions due to the front vehicle going through an emergency braking event. The following paper provides a comprehensive study of the special considerations or intricacies in implementation of Autonomous Emergency Braking (AEBS) feature into Indian traffic
Kartheek, NedunuriKhare, RashmitaSathyamurthy, SainathanManickam, PraveenkumarKuchipudi, Venkata Sai Pavan
This article proposes a new model for a cooperative and distributed decision-making mechanism for an ad hoc network of automated vehicles (AVs). The goal of the model is to ensure safety and reduce energy consumption. The use of centralized computation resource is not suitable for scalable cooperative applications, so the proposed solution takes advantage of the onboard computing resources of the vehicle in an intelligent transportation system (ITS). This leads to the introduction of a distributed decision-making mechanism for connected AVs. The proposed mechanism utilizes a novel implementation of the resource-aware and distributed–vector evaluated genetic algorithm (RAD-VEGA) in the vehicular ad hoc network of connected AVs as a solver to collaborative decision-making problems. In the first step, a collaborative decision-making problem is formulated for connected AVs as a multi-objective optimization problem (MOOP), with a focus on energy consumption and collision risk reduction as
Ghahremaninejad, RezaBilgen, Semih
In contrast to passenger cars, whose regulation allowed only a simple trailer combination, the autonomous technologies implementation of Electronic Stability Control (ESC) and Advanced Emergency Braking System (AEBS) for commercial vehicles demands more application and calibration efforts. At this case, the focus is on dynamic control of towing vehicles when applying the service brakes of trailer, in special when complex combination as bi-train and road-train, allowed in North and South America. However, the major risk is present occurrence when an ESC or AEBS equipped towing vehicles is connected to a double or triple trailer combination with a conventional braking system, it means: a system that is not equipped with Anti-lock Braking System (ABS). For instance, if during autonomous control, trailers wheels lock, a jackknifing phenomenon can easily occur. Therefore, in case longer and heavier vehicles (LHV) or megatrucks as called in Europe, the strategy for safety assistance systems
Guarenghi, Vinicius MendesPizzi, Rafael FortunaDepetris, AlessandroPinto, Gustavo Laranjeira NunesCollobialli, Germano
New tests for a Truck Safe rating scheme aim to emulate real-world collisions and encourage OEMs to fit collision avoidance technologies and improve driver vision. Euro NCAP has revealed the elements it is considering as part of an upcoming Truck Safe rating, and how it intends to test and benchmark truck performance. The announcement was made to an audience of international road safety experts at the NCAP24 World Congress in Munich, Germany, in April. The action is intended to mitigate heavy trucks' impact on road safety. The organization cited data showing that trucks are involved in almost 15% of all EU road fatalities but represent only 3% of vehicles on Europe's roads. Euro NCAP says the future rating scheme is designed to go further and faster than current EU truck safety regulations. The organization's goal is to drive innovation and hasten the adoption of advanced driver-assistance systems (ADAS) such as automatic emergency braking (AEB) and lane support systems (LSS), while
Gehm, Ryan
The traditional approach to applying safety limits in electromechanical systems across various industries, including automated vehicles, robotics, and aerospace, involves hard-coding control and safety limits into production firmware, which remains fixed throughout the product life cycle. However, with the evolving needs of automated systems such as automated vehicles and robots, this approach falls short in addressing all use cases and scenarios to ensure safe operation. Particularly for data-driven machine learning applications that continuously evolve, there is a need for a more flexible and adaptable safety limits application strategy based on different operational design domains (ODDs) and scenarios. The ITSC conference paper [1] introduced the dynamic control limits application (DCLA) strategy, supporting the flexible application of diverse limits profiles based on dynamic scenario parameters across different layers of the Autonomy software stack. This article extends the DCLA
Garikapati, DivyaLiu, YitingHuo, Zhaoyuan
AEB systems are critical in preventing collisions, yet their effectiveness hinges on accurately estimating the distance between the vehicle and other road users, as well as understanding road conditions. Errors in distance estimation can result in premature or delayed braking and varying road conditions alter road-tire friction coefficients, affecting braking distances. The integration of advanced sensors like LiDARs has significantly enhanced distance estimation. Cameras and deep neural networks are also employed to estimate the road conditions. However, AEB systems face notable challenges in urban environments, influenced by complex scenarios and adverse weather conditions such as rain and fog. Therefore, investigating the error tolerance of these estimations is essential for the performance of AEB systems. To this end, we develop a digital twin of our test vehicle in the IPG CarMaker simulation environment, which includes realistic driving dynamics and sensor models. Our simulated
Wang, YifanIatropoulos, JannesThal, SilviaHenze, Roman
While various Advanced Driver Assistance System (ADAS) features have become more prevalent in passenger vehicles, their ability to potentially avoid or mitigate vehicle crashes has limitations. Due to current technological limitations, forward collision mitigation technologies such as Forward Collision Warning (FCW) and Automated Emergency Braking (AEB) lack the ability to consistently perform in many unique and challenging scenarios. These limitations are often outlined in driver manuals for ADAS equipped vehicles. One such scenario is the case of a stationary lead vehicle at the side of the road. This is generally considered to be a challenging scenario for FCW and AEB to address because it can often be difficult for the system to discern this threat accurately and consistently from non-threatening roadway infrastructure without unnecessary or nuisance system activations. This is made more difficult when the stationary lead vehicle is only partially in the driving lane and not
Scally, SeanParadiso, MarcKoszegi, GiacomoEaster, CaseyKuykendal, MichelleAlexander, Ross
Pedestrian Automatic Emergency Braking (P-AEB) is a technology designed to avoid or reduce the severity of vehicle to pedestrian collisions. This technology is currently assessed and evaluated via EuroNCAP and similar procedures in which a pedestrian test target is crossing the road, walking alongside the road, or stationary in the forward vehicle travel path. While these assessment methods serve the purpose of providing cross-comparison of technology performance in a standardized set of scenarios, there are many scenarios which could occur which are not considered or studied. By identifying and performing non-EuroNCAP, non-standardized scenarios using similar methodology, the robustness of P-AEB systems can be analyzed. These scenarios help identify areas of further development and consideration for future testing programs. Three scenarios were considered as a part of this work: straight line approach, curved path approach, and parking lot testing. Exemplar tests were performed for
Bartholomew, MeredithHelber, NicholasHeydinger, GaryZagorski, Scott
Robustness testing of Advanced Driver Assistance Systems (ADAS) features is a crucial step in ensuring the safety and reliability of these systems. ADAS features include technologies like adaptive cruise control, lateral and longitudinal controls, automatic emergency braking, and more. These systems rely on various sensors, cameras, radar, lidar, and software algorithms to function effectively. Robustness testing aims to identify potential vulnerabilities and weaknesses in these systems under different conditions, ensuring they can handle unexpected scenarios and maintain their performance. Mileage accumulation is one of the validation methods for achieving robustness. It involves subjecting the systems to a wide variety of real-world driving conditions and driving scenarios to ensure the reliability, safety, and effectiveness of the ADAS features. Following ISO 21448 (Safety of the intended functionality-SOTIF), known hazardous scenarios can be tested and validated through robustness
Almasri, HossamFan, Hsing-HuaMudunuri, Venkateswara Raju
Automatic emergency braking and forward collision warning (FCW) reduce the incidence of police-reported rear-end crashes by 27% to 50%, but these systems may not be effective for preventing rear-end crashes with nonpassenger vehicles. IIHS and Transport Canada evaluated FCW performance with 12 nonpassenger and 7 passenger vehicle or surrogate vehicle targets in five 2021-2022 model year vehicles. The presence and timing of an FCW was measured as a test vehicle traveling 50, 60, or 70 km/h approached a stationary target ahead in the lane center. Equivalence testing was used to evaluate whether the proportion of trials with an FCW (within ± 0.20) and the average time-to-collision of the warning (within ± 0.23 sec) for each target was meaningfully different from a global vehicle car target (GVT). A similar approach was used to determine if FCW performance was reproducible between 3 targets tested by both IIHS and Transport Canada and was equivalent between surrogate car and motorcycle
Kidd, DavidAnctil, BenoitCharlebois, Dominique
The Advanced Driver Assistance System (ADAS) is a comprehensive feature set designed to aid a driver in avoiding or reducing the severity of collisions while operating the vehicle within specified conditions. In General Motors (GM) vehicles, the primary controller for the ADAS is the Active Safety Control Module (ASCM). In the 2013 model year, GM introduced an ASCM utilizing the GM internal nomenclature of External Object Calculation Module (EOCM) in some of their vehicles produced for the North American market. Similar to the Sensing and Diagnostic Module (SDM) utilized in the restraints system, the EOCM3 LC contains an Event Data Recorder (EDR) function to capture and record information surrounding certain ADAS or Supplemental Inflatable Restraint (SIR) events. The ASCM EDR contains information from external object sensors, various chassis and powertrain control modules, and internally calculated data. This event data includes date and time, GPS location, driver inputs and vehicle
Bare, CleveSkiera, JasonSmyth, BrianBeetham, TommyFloyd, DonaldKoo, WinstonNewell, Devin
The Bendix Wingman Fusion – a radar and camera collision mitigation system (CMS) available on commercial vehicles – was evaluated in two separate test series to determine its performance in simulated rear collision scenarios. In the first series of tests, evaluations were conducted in daytime, nighttime, and rainy conditions between 15 to 58 miles per hour (mph) to evaluate the performance of the audible and visual forward collision warning (FCW) system in a first-generation Bendix Wingman Fusion CMS while approaching a stationary live vehicle target (SLVT) in a 2017 Kenworth T680. A second test series was conducted with a 2017 Kenworth T680 traveling at 50 mph in daytime conditions approaching a decelerating vehicle to evaluate the Bendix Wingman Fusion CMS on the truck. Both test series sought to determine the maximum distance the system would warn prior to the test driver swerving around the SLVT or moving vehicle target. The first test series utilized a 2014 Ford F150 as the SLVT
Harrington, ShawnMartin, NicholasLeiss, Peter
A total of 93 tests were conducted in daytime conditions to evaluate the effect on the Time to Collision (TTC), emergency braking, and avoidance rates of the Forward Collision Warning (FCW) and Automatic Emergency Braking (AEB) provided by a 2022 Tesla Model 3 against a 4ActivePA adult static pedestrian target. Variables that were evaluated included the vehicle speed on approach, pedestrian offsets, pedestrian clothing, and user-selected FCW settings. As a part of the Tesla’s Collision Avoidance AssistTM, these user-selected FCW settings change the timing of the issuance of the visual and/or audible warning provided. This testing evaluated the Tesla at speeds of 25 and 35 miles per hour (mph) versus a stationary pedestrian target in early, medium, and late FCW settings. Testing was also conducted with a 50% pedestrian offset and 75% offset conditions relative to the right side of the Tesla. The pedestrian target was clothed with and without a reflective safety vest to account for
Harrington, ShawnNagarajan, Sundar RamanLau, James
In the dense fabric of urban areas, electric scooters have rapidly become a preferred mode of transportation. As they cater to modern mobility demands, they present significant safety challenges, especially when interacting with pedestrians. In general, e-scooters are suggested to be ridden in bike lanes/sidewalks or share the road with cars at the maximum speed of about 15-20 mph, which is more flexible and much faster than pedestrians and bicyclists. Accurate prediction of pedestrian movement, coupled with assistant motion control of scooters, is essential in minimizing collision risks and seamlessly integrating scooters in areas dense with pedestrians. Addressing these safety concerns, our research introduces a novel e-Scooter collision avoidance system (eCAS) with a method for predicting pedestrian trajectories, employing an advanced Long short-term memory (LSTM) network integrated with a state refinement module. This method predicts future trajectories by considering not just past
Yan, XukeShen, Dan
Intelligent vehicle-to-everything connectivity is an important development trend in the automotive industry. Among various active safety systems, Autonomous Emergency Braking (AEB) has garnered widespread attention due to its outstanding performance in reducing traffic accidents. AEB effectively avoids or mitigates vehicle collisions through automatic braking, making it a crucial technology in autonomous driving. However, the majority of current AEB safety models exhibit limitations in braking modes and fail to fully consider the overall vehicle stability during braking. To address these issues, this paper proposes an improved AEB control system based on a risk factor (AERF). The upper-level controller introduces the risk factor (RF) and proposes a multi-stage warning/braking control strategy based on preceding vehicle dynamic characteristics, while also calculating the desired acceleration. Furthermore, a lower-level PID-based controller is designed to track the desired acceleration
Guo, ShaozhongGuo, JunZhang, YunqingWu, Jinglai
Starting in 2021 Ducati introduced a radar based adaptive cruise control (ACC) developed by Bosch. It utilizes a single radar unit on the front of the motorcycle to detect the presence of vehicles ahead, as well as the separation distance. The system is not an automatic emergency braking (AEB) system but does have similar features. The Ducati ACC system does have limitations, some of which are explored in the subject research. Initial testing was conducted to document the engine braking in each gear. Following initial testing, several tests were performed at high closing speeds of over 100 kph. It was determined that at a closing speed of approximately 100 kph the ACC system would not react to a moving vehicle ahead. Additionally, the system will not react to a stopped vehicle or a “swerve-around” stopped vehicle that suddenly appears. Another series of tests were performed while actively following a vehicle at various speeds, with the front vehicle suddenly slowing to a stop and
Fatzinger, Edward C.Gonzaga, William
An automatic collision avoidance control method integrating optimal four-wheel steering (4WS) and direct yaw-moment control (DYC) for autonomous vehicles on curved road is proposed in this study. Optimal four-wheel steering is used to track a predetermined trajectory, and DYC is adopted for vehicle stability. Two single lane change collision avoidance scenarios, i.e., a stationary obstacle in front and a moving obstacle at a lower speed in the same lane, are constructed to verify the proposed control method. The main contributions of this article include (1) a quintic polynomial lane change trajectory for collision avoidance on curved road is proposed and (2) four different kinds of control method for autonomous collision avoidance, namely 2WS, 2WS+DYC, 4WS, and 4WS+DYC, are compared. In the design of DYC controller, two different feedback control methods are adopted for comparison, i.e., sideslip angle feedback and yaw rate feedback. The simulation results demonstrate significant
Lai, Fei
From the past few years, there is a pressing need for implementation of automatic in-vehicle safety systems to avoid vehicle crashes and fatalities. Development of autonomous emergency braking systems (AEBS) to detect and avoid collisions in such critical moments is of paramount importance. In this paper, AEBS is developed for a four-wheeler system that aims to detect vehicles and controls the ego vehicle based on the expected stooping distance (ESD). This control system aims to react based on the real-time relative distance & speed of the ego vehicle to actuate appropriate braking force. Control systems developed in Altair Activate are co-simulated with CARLA, a virtual reality simulator for autonomous driving research. Various scenarios including low and high-speed car to car motion, urban high and low traffic density environments are simulated to study the robustness of the control system. Further, studies are conducted to evaluate the effectiveness of the systems by varying the
K V, ManojKamikkiya, PUrs, Hriday V.
Autonomous Emergency Braking (AEB) systems play a critical role in ensuring vehicle safety by detecting potential rear-end collisions and automatically applying brakes to mitigate or prevent accidents. This paper focuses on establishing a framework for the Verification & Validation (V&V) of Advanced Driver Assistance Systems (ADAS) by testing & verifying the functionality of a RADAR-based AEB ECU. A comprehensive V&V approach was adopted, incorporating both virtual and physical testing. For virtual testing, closed-loop Hardware-in-Loop (HIL) simulation technique was employed. The AEB ECU was interfaced with the real-time hardware via CAN. Data for the relevant target such as the target position, velocity etc. was calculated using an ideal RADAR sensor model running on the real-time hardware. The methodology involved conducting a series of test scenarios, including various driving speeds, obstacle types, and braking distances. Automation was leveraged to perform automated testing and
Bhagat, AjinkyaKale, Jyoti GaneshPachhapurkar, NinadKarle, ManishR, ManishKarle, Ujjwala
Road traffic fatalities in India have been increasing, reaching around 150,000 fatalities a year. To reduce fatalities, some prospective studies suggested using active safety technologies such as Forward Collision Warning (FCW), and Autonomous Emergency Braking (AEB). However, the effectiveness of FCW and AEB on Indian roads using retrospective studies is not known. Vehicle data such as radar, and controller area network signals could be used for the evaluation of the systems (FCW and AEB). However, these data are not readily accessible. This exploratory study aims to explore the opportunities and limitations of using simple dashboard cameras for a Field Operational Test. One European car with state-of-the-art FCW and AEB systems was rented. Fifteen drivers shared the vehicle, driving almost 10,000 km over 29 days. The vehicle was mounted with a set of dashboard cameras. The navigator noted the “system activated” events and “no activation” events in the logbook during the drive. Post
Shaikh, JunaidLubbe, Nils
Vehicle-to-Everything (V2X) communications has the potential to increase the safety and autonomy of automated vehicles in addition to improving reliability, efficiency, infotainment, traffic, road safety, energy consumption, and costs. V2X is enabled by 5G technologies which promise faster connections, lower latency, higher reliability, more capacity and wider coverage. However, research is lacking in determining exactly how V2X can improve the safety, security, and autonomy of automated vehicles and more specifically what are the main V2X requirements. This paper provides a novel framework and structure to introduce V2X as a perception sensor sub-system into ADAS and ADS and to allocate top level target safety requirements to this new modality. To illustrate the novel structure, an example is provided using AD use cases in the context of the five SAE driving automation levels Level 1 through Level 5. The design follows methodologies from standards and regulations such as ISO 26262
Pimentel, Juan
This paper proposes an intelligent car testing and evaluation method based on digital twins, which is crucial for ensuring the proper functioning of autonomous driving systems. This method utilizes digital twin testing technology to effectively map and integrate real vehicles in real-world testing scenarios with virtual test environments. By enriching the testing and validation environment for smart cars, this approach improves testing efficiency and reduces costs. This study connects real test vehicles with simulation software testing toolchains to build a digital twin autonomous driving testing platform. This platform facilitates the validation, testing, and evaluation of functional algorithms, and case study is conducted through testing and validation of an emergency collision avoidance system. By rapidly applying digital twin testing and evaluation techniques for intelligent cars, this approach accelerates the development and deployment of autonomous vehicles.
Jianyu, DuanWang, YingDing, JuanDeng, Weiwen
Provizio promises its 5D Perception stack can safely compete with expensive lidar sensors at a fraction of the cost. “Safety first” is more than a catchphrase. For sensing company Provizio, it's the only way the transportation industry should introduce autonomous vehicles. In Provizio's view, using AV building blocks - technology such as automatic emergency braking and lane-keep assist - can be valuable in ADAS systems, but they should not be used to drive vehicles until the perception problem has been solved. “It's not that we're skeptical about autonomous driving, it's just that we strongly believe that the industry has taken this wrong path,” Dane Mitrev, machine learning engineer at Provizio, told SAE Media at September 2023's AutoSens Brussels conference. “The industry has looked at things the other way around. They tried to solve autonomy first, without looking at accident prevention and simpler ADAS systems. We are building a perception technology which will first eliminate road
Blanco, Sebastian
In this article, we present a spatiotemporal trajectory planning algorithm for emergency obstacle avoidance. Utilizing obstacle and driving environment data from the sensing module, we construct a 3D spatiotemporal grid map. This informs our improved hybrid A* algorithm, which identifies collision-safe, dynamically feasible trajectories. The traditional hybrid A* algorithm is enhanced in three significant ways to make the search practical and feasible: (1) optimizing search efficiency with motion primitives based on child node acceleration, (2) integrating collision risk into the heuristic function to reduce ineffective node exploration, and (3) introducing a One-Shot search based on the Optimal Boundary Value Problem (OBVP) to improve goal state searches. Finally, the algorithm is tested in two scenarios: (1) a vehicle cut-in from an adjacent lane and (2) a pedestrian crossing. Simulation results indicate that our proposed emergency obstacle avoidance trajectory planning method can
Chen, GuoyingYao, JunGao, ZhenhaiGao, ZhengZhao, XuanmingXu, NanHua, Min
In autonomous driving vehicles with an automation level greater than three, the autonomous system is responsible for safe driving, instead of the human driver. Hence, the driving safety of autonomous driving vehicles must be ensured before they are used on the road. Because it is not realistic to evaluate all test conditions in real traffic, computer simulation methods can be used. Since driving safety performance can be evaluated by simulating different driving scenarios and calculating the criticality metrics that represent dangerous collision risks, it is necessary to study and define the criticality metrics for the type of driving scenarios. This study focused on the risk of collisions in the confluence area because it was known that the accident rate in the confluence area is much higher than on the main roadway. There have been several experimental studies on safe driving behaviors in the confluence area; however, there has been little study logically exploring the merging
Imaseki, TakashiSugasawa, FukashiKawakami, ErikoMouri, Hiroshi
The progressive development toward highly automated driving poses major challenges for the release and validation process in the automotive industry, because the immense number of test kilometers that have to be covered with the vehicle cannot be tackled to any extent with established test methods, which are highly focused on the real vehicle. For this reason, new methodologies are required. Simulation-based testing and, in particular, virtual driving tests will play an important role in this context. A basic prerequisite for achieving a significant reduction in the test effort with the real vehicle through these simulations are realistic test scenarios. For this reason, this article presents a novel approach for generating relevant traffic situations based on a traffic flow simulation in SUMO and a vehicle dynamics simulation in CarMaker. The procedure is shown schematically for an emergency braking function. A driving function under test faces the major challenges when the other road
Riegl, PeterGaull, AndreasBeitelschmidt, Michael
This SAE Information Report develops a concept of operations (ConOps) to evaluate a cooperative driving automation (CDA) Feature for occluded pedestrian collision avoidance using perception status sharing. It provides a test procedure to evaluate this CDA Feature, which is suitable for proof-of-concept testing in both virtual and test track settings.
Cooperative Driving Automation(CDA) Committee
ABSTRACT Unmanned ground vehicles (UGVs) that autonomously maneuver over off-road terrain are susceptible to a loss of stability through untripped rollovers. Without human supervision and intervention, untripped rollovers can damage the UGV and render it unusable. We create a runtime monitor that can provide protection against rollovers that is independent of the type of high-level autonomy strategy (path planning, navigation, etc.) used to command the platform. In particular, we present an implementation of a predictive system monitor for untripped rollover protection in a skid-steer robotic platform. The system monitor sits between the UGV’s autonomy stack and the platform, and it ensures that the platform is not at risk of rollover by intercepting mobility commands sent by the autonomy stack, predicting platform stability, and adjusting the mobility commands to avoid potential rollovers. We demonstrate our implementation through experiments with skid-steer UGVs in Gazebo simulation
Dietrich, ElizabethPohland, SaraGenin, DanielSchmidt, AuroraVallabha, GautamComposto, AnthonyRandolph, Marcus
Previous volunteer studies focused on low-speed frontal events have demonstrated that muscle activation (specifically pre-impact bracing) can significantly affect occupant response. However, these tests do not always include a sufficient number of small female volunteers to compare their unique responses to the typically studied midsize male population. The purposes of this study were to quantify the occupant kinetics and muscle responses of relaxed and braced small female and midsize male volunteers during low-speed frontal sled tests and to compare between muscle states and demographic groups. Small female and midsize male volunteers experienced multiple low-speed frontal sled tests consisting of two pulse severities (1 g and 2.5 g) and two muscle states (relaxed and braced) per pulse severity. The muscle activity of 30 muscles (15 bilaterally) and reaction forces at the volunteer-test buck interfaces and seat belt were measured before and during each sled test. Compared to the
Chan, HanaAlbert, Devon L.Gayzik, F. ScottKemper, Andrew R.
The key issues of automatic emergency braking (AEB) control algorithm are when and how to brake. This article proposes an AEB control algorithm that integrates risk perception (RP) and emergency braking characteristics of professional drivers for rear-end collision avoidance. Using the formulated RP by time to collision (TTC) and time headway (THW), the brake trigger time can be determined. Based on the professional driver fitting (PDF) characteristic, the brake pattern can be developed. Through MATLAB/Simulink simulation platform, the European New Car Assessment Programme (Euro-NCAP) test scenarios are used to verify the proposed control algorithm. The simulation results show that compared with the TTC control algorithm, PDF control algorithm, and the integrated PDF and TTC control algorithm, the proposed integrated PDF and RP control algorithm has the best performance, which can not only ensure safety and brake comfort, but also improve the road resource utilization rate.
Lai, FeiHuang, ChaoqunJiang, Chengyue
Recently, there has been a slight increase in interest in the use of responder-to-vehicle (R2V) technology for emergency vehicles, such as ambulances, fire trucks, and police cars. R2V technology allows for the exchange of information between different types of responder vehicles, including connected and automated vehicles (CAVs). It can be used in collision avoidance or emergency situations involving CAV responder vehicles. The benefits of R2V are not limited to fully autonomous vehicles (e.g., SAE Level 4), but can also be used in Level 2 CAV scenarios. However, despite the potential benefits of R2V, discussions on this topic are still limited. Responder-to-Vehicle Technologies for Connected and Autonomous Vehicles aims to provide an overview of R2V technology and its applications for CAV systems, particularly in the context of collision avoidance features. The responder vehicles in question can be autonomous or non-autonomous. It is hoped that it will provide valuable information
Abdul Hamid, Umar Zakir
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