Browse Topic: Vehicle drivers

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Driver’s Pedal Control for Detecting Pedal Misapplication2025-01-8675To be published on 04/01/2025
Drivers sometimes operate the accelerator pedal instead of the brake pedal due to driver error, potentially resulting in serious accidents. Acceleration Control for Pedal Error (ACPE) has been developed, a system that detects such errors and controls vehicle acceleration to prevent these incidents. The United Nations is already considering regulations for this technology. If ACPE can detect errors based on the operations of the accelerator pedal at various driving speeds, the system will be even more effective in terms of safety. The purpose of this study is to investigate the operation characteristics of the accelerator pedal and brake pedal, focusing on the pedal operation characteristics of pedal stroke speed and pedal force speed used as thresholds for the operation of ACPE. We believe that if there is a significant difference in the operations of the accelerator pedal and brake pedals while driving, it can be used as a threshold for judging misstep. In this study, we utilized a
Natsume, Hayato, Shen, Shuncong, Hirose, Toshiya
Technical Paper
Recommendation of Adaptive Safe Speed Limit for different driver Profiles using Deep Learning2025-01-8106To be published on 04/01/2025
Personalization and driver profiling have emerged as popular topics within the Advanced Driver Assistance Systems domain. Several features, like seat position adjustment and route selection deliver a customized experience for everyone. The systems often profile the driver and their preferences using Machine Learning algorithms to anticipate the needs of the driver. Within this field, personalization of speed limits is not explored to the fullest. Currently, speed limits are the same for all drivers, irrespective of their driving style. Even when the speed limits are designed to address adverse weather conditions, they do not consider the driver’s capabilities. Thus, we propose a novel idea to recommend a safe speed limit based on the driving style and the surrounding environmental conditions. The architecture consists of Long Short-Term Memory based neural networks that capture the driver’s traits based on risks of the environment. The system identifies if a driver is uncomfortable in
Perumal, Rathapriya, Chouhan, Madhvendra, Rangarajan, Rishi
Technical Paper
Integrated Multimodal System for Real-Time Driver Fatigue Detection and Cognitive Load Assessment2025-01-8076To be published on 04/01/2025
Paying attention to safety while traveling in a vehicle was essential. One of the greatest barriers to travel safety is driver fatigue. In order to tackle this issue, we designed an all-inclusive hardware and software environment for analyzing driver interaction with highly automated vehicles, providing a special emphasis on detection of driver’s cognitive load and providing appropriate alerts in advance. There are three essential types of measurements included in this system. First, the facial features of the driver are measured through the use of Driver Behavior Measurements (DBM) which are made from RGB and IR cameras that capture the eye aspect ratio (EAR), mouth aspect ratio (MAR), pupil circularity (PUC), and mouth to eye aspect ratio (MOE), Most of these measurements have been shown to work under normal as well as more extreme conditions including low light conditions or use of sunglasses by the drivers. Secondly, Vehicle Dynamics Measurements (VDM) is performed by an Inertial
Jirjees, Abdullah, Rahman, Taufiq, Farhani PhD, Ghazal, Singh, Daniel, Charlebois, Dominique
Technical Paper
Objective and subjective evaluation of the interaction of automated vehicles and human drivers in take-over scenarios2025-01-8048To be published on 04/01/2025
The research activity aims at defining specific Operational Design Domains (ODDs) representative of Italian traffic environments. The paper focuses on the human-machine interaction in Automated Driving (AD), with a focus on take-over scenarios. The study, part of the European/Italian project “Interaction of Humans with Level 4 AVs in an Italian Environment - HL4IT”, describes suitable methods to investigate the effect of the Take-Over Request (TOR) on the human driver’s psycho-physiological response. The DriSMI dynamic driving simulator at Politecnico di Milano has been used to analyse three different take-over situations. Participants are required to regain control of the vehicle, after a take-over request, and to navigate through a urban, suburban and highway scenario. The psycho-physiological characterization of the drivers, through psychological questionnaires and physiological measures, allows for analyzing human factors in automated vehicles interactions and for contributing to
Gobbi, Massimiliano, Boscaro, Linda, De Guglielmo, Veronica, Fossati, Andrea, Galbiati, Andrea, Mastinu, Leda, ponti, Marco, Mastinu, Gianpiero, Previati, Giorgio, Sabbioni, Edoardo, Signorini, Maria Gabriella, Somma, Antonella, Subitoni, Luca, Uccello, Lorenzo
Technical Paper
Modeling and Evaluation of FSAE Vehicle Cockpit Ergonomics2025-01-8610To be published on 04/01/2025
This paper seeks to define an analytical approach to ergonomic design, utilizing RAMSIS software to create a driver model that considers the discomfort, fatigue, and force availability to evaluate cockpit designs that are produced from defined constraint inputs. The multifunctional model is applicable to various settings of vehicle design and is tuned toward proving performance in operation tasks, as well as setting the groundwork for a multi-variable optimization to determine the preferred driver controls positions for effort and fatigue pareto surfaces. Initial research done in the RAMSIS ergonomic software develops a collection of fatigue and joint discomfort data related to individual joint angles. Anthropometric data is compiled to show the proportional limb lengths from an individual’s sex and height percentile. The optimization function works by selecting a range of driver percentiles and creating random vehicle control positions within the bounds established. From this, each
Mayor, J.Rhett, Bezaitis, Megan, Oromi, Negar, Winters, Emily, Repp, Alex
Technical Paper
Comparative Kinematic Performance Testing to SAE J3230 on a Dynamometer and Test Track2025-01-8792To be published on 04/01/2025
SAE J3230 provides Kinematic Performance Metrics for Powered Standing Scooters. These performance metrics include many tests which require specific conditions including flat pavement with a near zero slope, drivers of specific height and weights, and data acquisition equipment. In order to determine the efficacy of replicating SAE J3230 tests in a laboratory setting, a device called the Micromobility Device Thermo-Electric Dynamometer was used alongside outdoor tests to provide a comparison of scooter performance in these two testing applications. Based on the testing outcomes, it can be determined whether SAE J3230 and similar standards for other micromobility devices can be replicated in a lab-based setting, saving time, operator hazard, and providing more thorough data outputs
Bartholomew, Meredith, Andreatta, Dale, Zagorski, Scott, Heydinger, Gary
Technical Paper
Design of A Differential Braking Controller Based on Road Reaction Force Estimation to respond to Steering System Failure in Autonomous Driving Situations2025-01-8797To be published on 04/01/2025
As the electrification of chassis systems accelerates, the demand for fail-safety strategies is increasing. In the past, the steering system was mechanically connected, so the driver could respond directly to some extent. However, the Steer-By-Wire system is composed of the column and rack bar as electrical signals, so the importance of response strategies for steering system failure is gradually increasing. When a steering system failure occurs, a differential braking control using the difference in braking force between the left and right wheels was studied. Recently, some studies have been conducted to model the wheel reaction force generated during a differential braking. Those studies linearly modeled the reaction force generated at the kingpin axis. Since actual tires and road surfaces are nonlinear and cause large model errors, model-based control methods have limited performance. Also, in previous studies assumed that the driver normally operates the steering wheel in a failure
Kim, Sukwon, Kim, Young Gwang, Kim, SungDo, Moon, Sung Jin
Technical Paper
Research on road-sense simulation algorithm and analysis of its effect on different steering wheels2025-01-8753To be published on 04/01/2025
With the continuous development of automotive intelligence, cars increasingly want chassis to be more intelligent, electronically controlled, integrated and lightweight. Therefore, the steer-by-wire system, controlled by the line, with high precision and fast response, can provide better flexibility, stability and comfort for the car and can well meet the above requirements, has been widely concerned. As the steer-by-wire system eliminates the mechanical structure, the road sense cannot be directly transmitted to the steering wheel. The road sense obtained according to the vehicle state or combined with the driving environment planning needs to be applied to the steering wheel through the road sense motor to complete the simulation of the road sense so that the driver can feel the feedback similar to driving the traditional steering vehicle. In this way, the driving experience of the driver can be increased. It can also enhance driving safety, so it is very important to study the road
Li, Shang, Zheng, Hongyu, Kaku, Chuyo
Technical Paper
Correlation of Subjective Assessments and Objective Metrics for On-Center Feeling2025-01-8287To be published on 04/01/2025
Steering feeling plays a critical role in the driving experience and is one of the most significant topics during a new vehicle development process. To reach a consensus for the customers’ satisfaction in both the subjective and objective characteristics in a particular market segment, there have been several studies to investigate the correlations between subjective and objective evaluations of on-center steering feeling. However, it is still not clear how to determine the steering characteristic based on the correlations. In this paper, a series of new correlation between subjective and objective evaluations are built, which focus on steering effort, on-center feel, torque ripple, torque dead band etc. Firstly, we extract a set of objectives metrics from on-center handling test based on ISO 13674-1 2023, which are followed by professional test drivers or tuning experts. Secondly, we list numerical on-center handling tests of vehicles to test and verify the representativeness and
Jin, Ankang, Luo, Kaijie, Yang, Jianyuan, Zheng, Yue
Technical Paper
A Novel Hybrid Approach for Segmenting Driver Based on their Driving Style2025-01-8205To be published on 04/01/2025
Drivers present a diverse landscape with their distinct personalities, preferences, and driving habits influenced by many factors. While drivers exhibit a wide range of behaviors, identifiable patterns in driving styles enable the classification of drivers into discrete segments. Discrete segmentation provides a practical and effective way to categorize and address the differences in driving style. The segmentation approach offers many benefits, including simplification, measurement, proven methodology, customization, and safety. Numerous studies have investigated driving style classification using real-world vehicle data. These studies employed various methods to identify and categorize distinct driving patterns, including naturalist differences in driving and field operational tests. This paper presents a novel hybrid approach for segmenting driver behavior based on their driving patterns. We leverage vehicle acceleration data to create granular driver segments by combining event
Chavan, Shakti Pradeep, Chinnam, Ratna Babu
Technical Paper
A Comparative Analysis of Acceleration and Deceleration Profiles for Aggressive Driving Styles and Fuel Economy Test Cycles2025-01-8605To be published on 04/01/2025
Efficient and sustainable transportation in urban environments depends on understanding driving behaviors, and their implications. This study explores into the distinction between aggressive and non-aggressive driving patterns, leveraging an on-road driving dataset provided by an automotive company. By contrasting this data with established Fuel Economy cycles from United States Environmental Protection Agency (EPA) and employing curve-fitting techniques, the research not only reveals driving patterns but also predicts potential behaviors in unfamiliar scenarios. Results show significantly different acceleration profile patterns between different driving behaviors which has serious impact in fuel economy and environmental wellness. The findings highlights the environmental impact of driving behaviors, paving the way for environmentally responsible policy recommendations and sustainable driving practices
Padmanaban, Gandhimathi, Feng, Fred, Dai, Edward, Saini, Ankit, Hu, Guopeng, Zhao, Yanan
Technical Paper
Driving Under the Influence: A Review of Fitness to Drive, Drug-Induced Impairments, and Simulation Testing2025-01-8666To be published on 04/01/2025
This literature review examines the concept of fitness to drive and how it can be affected by drugs consumption. The Systematic Literature Review (SLR) methodology is used to analyse the Literature, exploiting Scopus, Consensus and Elicit databases. Firstly, the paper presents research across mechanical engineering and related fields to establish a comprehensive and multidisciplinary understanding of how fitness to drive is evaluated. This includes a definition of the term and the identification of the protocols used for its assessment. Secondly, the emphasis is on the impact of drug use on driving performance, excluding alcohol and cannabis. Driving simulators represent a valid possibility for analysing such effects in a safe, controlled and replicable environment. They are presented considering their most relevant characteristics and the measurements collected for the driver's state analysis. Key findings reveal a lack of a comprehensive taxonomy for fitness to drive, resulting in
Uccello, Lorenzo, Mastinu, Gianpiero, Elli, Chiara, Novella, Alessio, Nobili, Alessandro, Pasina, Luca
Technical Paper
OPTIMAL INVESTIGATION ABOUT CAB OF BSC RACING CAR BASED ON ERGONOMICS2025-01-8669To be published on 04/01/2025
In the Baja competition, the racing cars need to run under a variety of complex off-road conditions such as pebble road, shell pit, the road with many broken stones, hump, water puddle and so on，in the endurance race，the driver even has to drive continuously for four hours. In the process of this high-intensity and high-concentration race, the irrational designs of cab in ergonomics will easily cause the driver's visual and handling fatigue, so that the driver's attention is not concentrated，and cause the security accidents. Moreover, the lower back pain, sciatic nerve discomfort, lumbar spine diseases and other occupational diseases are basically caused by uncomfortable driving posture and unreasonable manipulation interface, and these have a lot to do with unreasonable ergonomic designs. In order to solve the unreasonable designs of the cab in ergonomics and improve the safety and comfort of the driver, first of all, establish the overall model of BSC racing car in Catia to obtain a
Liu, Yuzhou, Liu, Silang
Technical Paper
A Proactive System to Anticipate and Store the Damage Information on a Parked Car using Machine Learning Algorithm2025-01-8211To be published on 04/01/2025
Vehicle ADAS Systems majorly comprises of two functions: Driving and Parking. The most common form of damage to the vehicle which goes unnoticed with unidentified cause are parking damages. A vehicle once parked at a certain location may get damaged without knowledge of the user. In this work developed a solution that not only pre-warns the driver but also prepares the vehicle beforehand if it suspects a damage may occur. This eliminates the latency between damage and information capture, detects small damages such as scratches, classifies the type of damage and also informs the user beforehand. This is solution is different from our competitors as the existing solutions informs the user about the scratches/damages, but these solutions are expensive, have high response time, and the damage information is captured after the damage has occurred. The solution consists of the following check blocks: Precondition, Sensor Control and Action Module. The Precondition Module observes the
Debnath, Sarnab, PATIL, Prasad, Belur Subramanya, Sheshagiri, Govinda, Shiva Prasad
Technical Paper
Optimal usage of engine torque to engage a disconnect device in situations where battery power is not available2025-01-8578To be published on 04/01/2025
This paper introduces a novel approach to optimize battery power usage and optimal engine torque for wheel end disconnect device engagement under power constrained scenarios for range extended hybrid vehicles. Range extended hybrid architecture provides benefits of BEV architecture and relief the range anxiety that BEV drivers often have. The wheel end disconnect device helps improve the efficiency of the battery power usage when it is disconnected and provides better drivability and performance to fulfill driver demand when it is connected. Under power constraint scenario, the disconnect device engagement could take too long or eventually fail to engage and result in degradation for drivability and vehicle level performance. This novel approach is utilizing engine to either generate more power to spin up the disconnect motor faster under discharge limited case or generate less power to allow the disconnect motor to spin down under charge limited case. The effectiveness of this
Sha, Hangxing, Madireddy, Krishna Chaitanya, Banuso, Abdulquadri, Khanal, Shishir, Rock, Joe, Patel, Nadirsh
Technical Paper
End to End Large Model Predictive Control of Automated Driving Vehicles2025-01-8113To be published on 04/01/2025
In the drive burden alleviation of automated turning, false look ahead of speed and curvature cooperation will cause issues of multiple functional boundary operations. In the author’s previous research from SAEWCX2020, the risk feeling model on multiple lanes was proposed. However, the issues of corner operations were not considered. In real world situations of corner cases with multiple functional boundary operations, it is new and important to utilize more accurate dynamic vehicle model based on end to end large model to deal with issues of wheelbase differential dynamics, slip angle dynamics, and yaw rate dynamics. Human drivers sequentially update their predictive view point along the target lane and predict the intent of other traffic participants, and interact with them to decide the target speed. The above challenges on turning scenarios is tackled with the advance methods of predictive lattice trajectory generation using functional safety modes. In this study, the proposed
Yu, Kaijiang
Technical Paper
Driver Distraction Recognition Based on the Information Bottleneck Theory and Graph Convolutional Networks2025-01-8112To be published on 04/01/2025
Driver distraction remains a leading cause of traffic accidents, making its recognition critical for enhancing road safety. In this paper, we propose a novel method that combines the Information Bottleneck (IB) theory with Graph Convolutional Networks (GCNs) to address the challenge of driver distraction recognition. Our approach introduces a 2D pose estimation-based action recognition network that effectively enhances the retention of relevant information within neural networks, compensating for the limited data typically available in real-world driving scenarios. The network is further refined by integrating the CTR-GCN (Channel-wise Topology Refinement Graph Convolutional Network), which models the dynamic spatial-temporal relationships of human skeletal data. This enables precise detection of distraction behaviors, such as using a mobile phone, drinking water, or adjusting in-vehicle controls, even under constrained input conditions. The IB theory is applied to optimize the trade
Zhang, Ji, Bai, Yakun
Technical Paper
Real-world emissions in a high-altitude city: A comparison between LPG and gasoline- fueled cars2025-01-8494To be published on 04/01/2025
To study the real driving emissions characteristics of light-duty vehicles fueled with liquefied petroleum gas (LPG) and gasoline in the high-altitude city, experimental investigations were performed on two LPG taxis and three gasoline passenger cars in Lhasa using a portable emission measurement system (PEMS). The results reveal that the emission factors of CO2, CO, NOx, and HC of LPG taxis are (159.19±11.81), (18.38±9.73), (1.53±0.46), and (1.27±0.99) g/km, and those of gasoline cars are (223.51±23.1), (1.51±0.68), (0.27±0.16), and (0.06±0.04) g/km, respectively. The emissions show strong relationships with driving modes, which are considerably affected by driving behaviors. Furthermore, as vehicle speeds increase, the emission factors of both LPG taxis and gasoline cars decrease. The emission rates of both types of vehicles are low and change slightly at vehicle specific power (VSP) of 0 kW/t or below; after that, these rates slowly increase initially, and then increase rapidly with
Lyu, Meng, Xu PhD, Yan, Huang, Meihong, Wang, Yunjing
Technical Paper
Research on Composite Braking Strategy of Pure Electric Commercial Vehicle on Downhill Low-adhesion Road considering Rainfall Intensity2025-01-8813To be published on 04/01/2025
As a distributed wire control brake system, the electro-mechanical brake (EMB) may face challenges due to the need to integrate the actuator in the limited space beside the wheel. During extended downhill braking, especially on wet roads with reduced adhesion, the EMB must operate at high intensity. The significant heat generated by friction can lead to thermal deformation of components, such as the lead screw, compromising braking stability.This paper focuses on pure electric light trucks and proposes a parallel composite braking method. This approach uses an eddy current retarder or motor to provide basic braking torque, while the EMB supplies the dynamic portion of the braking torque, thereby alleviating the braking pressure on the EMB. First, a driver model, tire model, motor model and braking models are developed based on the vehicle's longitudinal dynamics. In addition, the impact of various factors, such as rainfall intensity, road slope, ramp length, road type, and vehicle
Liu, Wang, Zhang, Yu, Xiao, Hongbiao, Shen, Leiming
Technical Paper
Predicting Head Injury Criterion in Real-World Frontal Impacts2025-01-8709To be published on 04/01/2025
Research on modeling head injury metrics and head acceleration waveforms from real-world collisions has been limited compared to vehicle crash pulses. Prior studies have used simple pulse functions to model vehicle crash pulses and have employed more complex approximations for head injury metrics. This study aimed to develop a method to predict 15 ms Head Injury Criterion (HIC15) in frontal passenger vehicle impacts using simple pulse functions, where only occupant peak head acceleration and head impact duration are known. Vehicle crash tests from the New Car Assessment Program (NCAP) were selected for frontal impacts that include driver occupants, then separated for training and testing. The resultant head acceleration-time curves of the driver Hybrid III 50th percentile male anthropomorphic test devices were collected. Rectangular, triangular, quadratic, half-sine, and half-haversine pulse functions were modeled using peak head acceleration and the duration of significant head
Westrom, Clyde, Tanczos, Rachel, Adanty, Kevin, Shimada, Sean
Technical Paper
Active and passive security generalization algorithm and typical case analysis2025-01-8744To be published on 04/01/2025
In order to be able to effectively predict the safety performance of vehicles and reduce the cost of enterprise safety tests, a generalized model for automotive active and passive safety simulation is proposed. The frontal driver's side collision model under AEB intervention is created by MADYMO software, and the collision acceleration obtained from the bench test is used as the model input to simulate the human body in different seating postures, and the damage values of each part of the Hybrid III 50th dummy are read, and the active-passive simulation model is established by BP neural network according to the correlation relationship between the two, and the model input is the inclination angle centered at the waist of the dummy, and the output is the damage values of each part of the dummy. The input of the model is the tilt angle centered on the waist of the dummy, and the output is the damage value of each part of the dummy. The results surface: the prediction accuracy is more
Ge, Wang
Technical Paper
Research on Dangerous Driving Behavior Recognition Algorithm Based on LSTM2025-01-8204To be published on 04/01/2025
To address the issue of high accident rates in road traffic due to dangerous driving behaviors, this paper proposes a recognition algorithm for dangerous driving behaviors based on Long Short-Term Memory (LSTM) networks. Compared with traditional methods, this algorithm innovatively integrates high-frequency trajectory data, historical accident data, weather data, and features of the road network to accurately extract key temporal features that influence driving behavior. By modeling the behavioral data of high-accident-prone road sections, a comprehensive risk factor is consistent with historical accident-related driving conditions, and assess risks of current driving state. The study indicates that the model, in the conditions of movement track, weather, road network and conditions with other features, can accurately predict the consistent driving states in current and historical with accidents, to achieve an accuracy rate of 85% and F1 score of 0.82. It means the model can
Huang, Yinuo
Technical Paper
Real-Time Application of Torque Converter Modeling for Enhanced System Response in a Hybrid Powertrain2025-01-8529To be published on 04/01/2025
This paper explores the application of a modeled torque converter in the real-time control of a hybrid electric powertrain. The study aims to determine the optimal gear selection and engine speed target required to meet driver demands. It also delves into the concept of torque converter input inertia compensation, particularly during open, open-to-close, and close-to-open states. The primary objective is to achieve the intended driver torque while minimizing torque sag and bumps during these transitions. This approach ensures improved powertrain response and maintains system integrity within the operational limits of the battery, motors, and engine
Madireddy, Krishna Chaitanya, Banuso, Abdulquadri, Sha, Hangxing, Patel, Nadirsh, Karogal, Indrasen, Khanal, Shishir
Technical Paper
Data Collection for Real-World Driving Studies: Challenges and Lessons from a Project on assessing EV Viability in Rural Michigan2025-01-8525To be published on 04/01/2025
Real-world driving data is an invaluable asset for several types of transportation research ranging from emissions estimation to vehicle control systems development. Traditional methods of real-world driving data collection utilize advanced and expensive GPS-based data logging equipment. Such equipment may possess unnecessarily excessive capabilities depending on the type of study, increasing study complexity and expenditure. This paper proposes the implementation of the Google Maps Application as a surrogate measurement device for real-world driving data logging, reducing study complexity and cost. Driving data can be collected from drivers who use Google Maps on their smartphones, making the process of implementation minimally invasive. The merits and disadvantages of this type of data logging will be analyzed through the case study of the ‘Rural Driving Study – Analysis of the Viability of Electric Vehicles in Rural Michigan’ research project that is currently being undertaken at
Manoj, Ashwin, Yin, Sally, Ahmed, Omar, Vaishnav, Parth, Stefanopoulou, Anna, Tomkins, Sabina
Technical Paper
Identifying Negative Driver States that Share Commonalities for Interventions2025-01-8676To be published on 04/01/2025
Advancements in sensor technologies have led to increased interest in detecting and diagnosing "driver states"-collections of internal driver factors generally associated with negative driving performance, such as alcohol intoxication, cognitive load, stress, and fatigue. This is accomplished using imperfect behavioral and physiological indicators that are associated with those states. An example is the use of elevated heart rate variability, detected by a steering wheel sensor, as an indicator of frustration. Advances in sensor technologies, coupled with improvements in machine learning, have led to an increase in this research. However, a limitation is that it often excludes naturalistic driving environments, which may have conditions that affect detection. For example, reductions in visual scanning are often associated with cognitive load (e.g., Angell et al., 2015); however, these reductions can also be related to novice driver inexperience (e.g., Stahl et al., 2019) and alcohol
Seaman, Sean, Zhong, Peihan, Angell, Linda, Domeyer, Joshua, Lenneman, John
Technical Paper
Predictive steering angle generation algorithm for high-efficiency vehicle's path optimization2025-01-8791To be published on 04/01/2025
Predictive performance simulation of a high-efficiency lightweight vehicle is performed through development of a multi-physics MATLAB Simulink model including advanced vehicle’s dynamics. The vehicle is put into a three-dimensional representation of the racetrack, including its limits, slope, banking, and adhesion coefficient along the model space, elaborated from the track GPS data points. The vehicle’s reference trajectory is not priorly provided to the model at the simulation start as, during run-time, a predictive Steering Angle Generation (SAG) algorithm based on NMPC (Nonlinear Model Predictive Control) computes the optimal steering angle input needed to drive the vehicle on the track within its limits. Computation is based on fast predictive simulations of a simplified version of vehicle’s dynamics modelling of the prototype. Each single simulation exploits a different possible steering angle to be applied by the virtual driver, starting from the initial conditions given by the
De Carlo, Matteo, Manzone, Simone, de Carvalho Pinheiro, Henrique, Carello, Massimiliana
Technical Paper
An Adaptive Risk-Based Access Control with Trusted Execution Environment for Vehicles2025-01-8089To be published on 04/01/2025
The rapid development of intelligent and connected vehicles is transforming them into data-rich information carriers, which generate and store vast amounts of sensitive information. However, the frequent sharing of resources within these vehicles poses substantial risks to user privacy and data security. Should sensitive resources be accessed maliciously, the consequences could be severe, leading to significant threats to the safety, property, and reputation of both drivers and passengers. To address these risks, this paper proposes an adaptive risk-based access control with Trusted Execution Environment (TEE) specifically designed for vehicles, aimed at managing and restricting access permissions based on risk assessments. Firstly, this paper designs an adaptive risk model in accordance with ISO 21434, taking into account factors such as the security levels of subjects and objects, context, and the risk history of subjects to separately quantify threats and impacts. By adjusting the
Luo, Feng, Li, Zhihao, Wang, Jiajia, Luo, Cheng
Technical Paper
Operational Evaluation of a Pre-Production L2 System HMI2025-01-8050To be published on 04/01/2025
The study analyzed data from naturalistic, on-road drives of a pre-production Level 2 (L2) partial automation system using a sample of 27 drivers ranging from 21 to 75 years of age. This system provides continuous automatic lateral and longitudinal control but requires the driver to remain attentive and intervene when necessary. The L2 system was equipped with a Driving Monitoring System (DMS) that issued escalating alerts to remind the driver to pay attention or take over when needed. During the 14-month study period, drivers completed 354,768 miles of travel with the L2 system engaged, totaling 5,913 trips. The results of the study showed that drivers were highly responsive to attention reminders and takeover alerts, with high compliance rates and quick response times. Importantly, there was no evidence of habituation to these alerts over time. These findings support the effectiveness of the system's DMS and alert HMI (Human-Machine Interface) strategy in promoting the proper use of
Llaneras, Robert, Glaser, Yi, Landry, Steven, Kiefer, Raymond, Green, Charles
Technical Paper
Optimization of Electric Vehicle Battery Charging Strategy Based on Reinforcement Learning2025-01-8116To be published on 04/01/2025
The battery capacity of electric vehicles (EVs) is a critical factor influencing their overall performance. Selecting an appropriate charging strategy based on the EV driver’s travel behaviors can significantly mitigate battery capacity degradation and prolong its lifespan. This study integrated a physics-based battery degradation model with an EV powertrain system energy consumption model to enhance the prediction accuracy for the battery status under real-world driving conditions. In addition, it employed the Q-learning algorithm to provide suggestions on the driver’s charging behaviors, including charging start time, charging duration, and charger types. To create a reasonable reward function in the Q-learning algorithm, this study addressed the issue of car rental costs when the battery capacity is insufficient to support daily mileage. With the algorithm, this study modeled the 3-year use of an EV by an average driver sampled from the New England area in the U.S. The simulation
Wang, Jiayi, Jing, Hao, Ou, Shiqi(Shawn), Lin, Zhenhong
Technical Paper
The Effect of Directional Tactile Guidance on Takeover Performance in Level 3 Automated Driving2025-01-8049To be published on 04/01/2025
Automated driving is an important development direction of the current automotive industry. Level 3 automated driving allows the driver to perform non-driving related tasks (NDRTs) during automated driving, however, once the operating conditions exceed the designed operating domain, the driver is still required to take over. Therefore, it is important to rationally design takeover requests (TORs) in Level 3 conditional automated driving. This paper investigates the effect of directional tactile guidance on driver takeover performance in emergency obstacle avoidance scenarios during the transfer of control from automated driving mode to manual driving.18 participants drove a Level 3 conditional automated driving vehicle in a driving simulator on a two-way four-lane urban road, performed a takeover, and avoided obstacles while performing non-driving related tasks. The driver's takeover performance during the takeover process was measured and subjective driver evaluation data was
Liang, Xinying, Liang, Yunhan, Ma, Xiaoyuan, Wang, Luyao, Chen, Guoying, Hu, Hongyu
Technical Paper
A Path Tracking Control Method Considering Vehicle Stability and Road Curvature2025-01-8038To be published on 04/01/2025
The current research on path tracking control focuses on the improvement of tracking accuracy, while ignoring the comfort of the passengers inside the vehicle. Improving comfort can be achieved by improving the algorithm in two aspects: imitating human driving behavior and considering vehicle driving stability. Therefore, this paper proposes a path tracking control method considering vehicle stability indicators and road curvature changes, with the following main content: first, vehicle dynamics modeling is performed, and its dynamics characteristics are analyzed to extract key indicators related to the enhancement of ride comfort in the driving process. This includes combining the human comfort evaluation index of whole-body vibration and the vehicle maneuverability index, and calculating the interval of the relevant vehicle dynamics indexes for the case where the passenger comfort is the highest in the vehicle driving process. Second, the path tracking controller is designed by
lu, jun, Zeng, Dequan, Hu, Yiming, Wang, Xiaoliang, liu, dengcheng, Jiang, Zhiqiang
Technical Paper
Integrated Driver Health Monitoring System With Real-time Alerts Using In-Cabin Sensors and Vehicle Telematics2025-28-0195To be published on 02/07/2025
Automotive industries focus on driver safety leading to raising improvements and advancements in Advanced Driver Assistance Systems (ADAS) to avoid collisions and provide safety and comfort to the drivers. This paper proposes a novel approach toward Driver health and fatigue monitoring systems that uses cabin cameras and biometric sensors communicating continuously with vehicle telematics systems to enhance real-time monitoring and predictive intervention. The data from the camera and biometric sensors is sent to the machine learning algorithm (LSboost) which processes the data and if anything is wrong concerning the driver's behavior then immediately it communicates with vehicle telematics and sends information to the emergency services. This approach enhances driver safety and reduces accidents caused due to health-related driver impairment. This system comprises several sensors and fusion algorithms are applied between different sensors like cabin camera and biometric sensors, all
Bhargav, Matavalam
Technical Paper
Physical and Cognitive Driver Reactions Characterization in Response to Active Safety Systems: A Preliminary Study2024-36-013612/20/2024
Advanced Driver Assistance Systems (ADAS) are technologies that automate, facilitate, and improve the vehicle’s systems. Indeed, these systems directly interfere with braking, acceleration, and drivability of driving operations. Thus, the use of ADAS directly reflects the psychology behind driving a vehicle, which can have an automation level that varies from fully manual (Level 0) to fully autonomous (Level 5). Even though ADAS technologies provide safer driving, it is still a challenge to understand the complexity of human factors that influence and interact with these new technologies. Also, there has been limited exploration of the correlation between the physical and cognitive driver reactions and the characteristics of Brazilian roads and traffic. Therefore, the present work sought to establish a preliminary investigation into a method for evaluating the driving response profile under the influence of ADAS technologies, such as Lane Centering and Forward Collision Warning, on
Castro, Gabriel M., Silva, Rita C., Miosso, Cristiano J., Oliveira, Alessandro B. S.
Technical Paper
Impact of Replacing a 6-Speed Gearbox with a 5-Speed Gearbox on Vehicle Performance2024-36-012512/20/2024
This study investigates the effects of replacing a 6-speed gearbox with a 5-speed gearbox in a sports vehicle, while keeping all other parameters constant. Through computational simulations, data is collected for comparative performance analysis. The study aims to understand the potential implications of this change on acceleration, fuel efficiency, engine response, as well as aspects such as driver comfort. The results may provide valuable insights for the automotive industry, guiding future transmission design and engineering decisions
Marinho, Gabriel Jannuzzi, de Campos, Josué Queiroz, Lopes, Elias Dias Rossi, Rodrigues, Gustavo Simão
Technical Paper
Trajectory Planning and Tracking Control for Single Lane Changing with Different Driving Styles of Intelligent Vehicles Based on Seventh-Degree Polynomial12-08-03-002812/14/2024
Single lane changing is one of the typical scenarios in vehicle driving. Planning an appropriate lane change trajectory is crucial in autonomous and semi-autonomous vehicle research. Existing polynomial trajectory planning mostly uses cubic or quintic polynomials, neglecting the lateral jerk constraints during lane changes. This study uses seventh-degree polynomials for lane change trajectory planning by considering the vehicle lateral jerk constraints. Simulation results show that the utilization of the seventh-degree method results in a 41% reduction in jerk compared to the fifth-degree polynomial. Furthermore, this study also proposes lane change trajectory schemes that can cater to different driving styles (e.g., safety, efficiency, comfort, and balanced performance). Depending on the driving style, the planned lane change trajectory ensures that the vehicle achieves optimal performance in one or more aspects during the lane change process. For example, with the trajectory that
Lai, Fei, Huang, Chaoqun
Journal Article
Human-like Behavior Strategy for Autonomous Vehicles Considering Driving Styles2024-01-704612/13/2024
Autonomous driving technology plays a crucial role in enhancing driving safety and efficiency, with the decision-making module being at its core. To achieve more human-like decision-making and accommodate drivers with diverse styles, we propose a method based on deep reinforcement learning. A driving simulator is utilized to collect driver data, which is then classified into three driving styles—aggressive, moderate, and conservative—using the K-means algorithm. A driving style recognition model is developed using the labeled data. We then design distinct reward functions for the Deep Q-Network (DQN), Proximal Policy Optimization (PPO), and Soft Actor-Critic (SAC) algorithms based on the driving data of the three styles. Through comparative analysis, the SAC algorithm is selected for its superior performance in balancing comfort and driving efficiency. The decision-making models for different styles are trained and evaluated in the SUMO simulation environment. The results indicate that
Shen, Chuanliang, Zhang, Longxu, Shi, Bowen, Ma, Xiaoyuan, Li, Yi, Hu, Hongyu
Technical Paper
Interaction-Aware Deep Reinforcement Learning Approach Based on Hybrid Parameterized Action Space for Autonomous Driving2024-01-703512/13/2024
Learning-based motion planning methods such as reinforcement learning (RL) have shown great potential of improving the performance of autonomous driving. However, comprehensively ensuring safety and efficiency remain a challenge for motion planning technology. Most current RL methods output discrete behavioral action or continuous control action, which lack an intuitive representation of the future motion and then face the problems with unstable or reckless driving behavior. To address these issues, this work proposes an interaction-aware reinforcement learning approach based on hybrid parameterized action space for autonomous driving in lane change scenario. The proposed method can output high-level feasible trajectory and low-level actuator control command to control the vehicle’s motion together. Meanwhile, the reward functions for the local traffic environment are designed to evaluate the effect of the interaction between ego vehicle and surrounding vehicles. The contributions of
Li, Zhuoren, Jin, Guizhe, Yu, Ran, Leng, Bo, Xiong, Lu
Technical Paper
A Driving Behavior Decision Method Based on Gradient Boosting Tree Algorithm2024-01-703012/13/2024
In order to reduce the incidence of traffic accidents and improve passengers’ driving experience, intelligent driving technology has attracted more and more attention. The core content of intelligent driving technology includes environment perception, behavior decision-making and control follow-up. Simulating driver’s behavior decision-making based on multi-source heterogeneous environment information is the key to liberate drivers and become the focus and difficulty of intelligent driving technology. Aiming at this key problem, this paper presents a design method of driving behavior decision maker based on machine learning after fuzzy classification of historical data. Firstly, 1000 sets of driving environment-decision results database are generated randomly according to driving rules and driving state. A fuzzy classification rule is established to classify driving environment information such as speed and relative distance. Then, a driving behavior decision maker is designed based on
Li, Hongluo, Xia, Hongyang, Huang, Yongxian, Xu, You, Xu, Wei
Technical Paper
Driving Behavior Modeling Based on Inverse Reinforcement Learning2024-01-702912/13/2024
With the advancement of intelligent driving technology, today’s smart vehicles must not only make accurate and safe driving decisions but also exhibit high human-likeness to ensure better acceptance from people. Developing vehicle behavior models with increased human-likeness has become a significant industry focus. However, existing vehicle behavior models often struggle to balance human-likeness and interpretability. While some researchers use inverse reinforcement learning (IRL) to model vehicle behavior, ensuring both human-likeness and a degree of interpretability, challenges such as reward function design difficulties and low human-likeness in background vehicle modeling persist. This study addresses these issues by focusing on highway scenarios without on-ramps, specifically following and lane-changing behaviors, using the CitySim dataset. IRL is employed to create a vehicle behavior model with improved human-likeness, utilizing a linear reward function to capture driver
Xu, Xiaobin, Han, Wei, Leng, Bo, Xiong, Lu
Technical Paper
Design and Implementation of a Detailed Digital Fuel Indicator System for Accurate Fuel Monitoring2024-01-520012/10/2024
This research introduces a Detailed Digital Fuel Indicator (DDFI) system to enhance fuel monitoring accuracy in automobiles using advanced infrared (IR) sensor technology for precise fuel level detection. The innovative system includes a secondary tank, meticulously calibrated to the volumetric ratio of the primary tank, to ensure consistent and accurate readings. The DDFI system provides real-time data on fuel levels with an impressive accuracy of ±5%, a notable improvement over the traditional methods. Key components of the system include an IR sensor, a programmable integrated circuit (IC), and a secondary tank fabricated from galvanized iron (GI) sheet metal, ensuring durability and reliability in various environmental conditions. The system is designed to be user-friendly, offering an intuitive interface for drivers to monitor fuel levels effortlessly. Additionally, the DDFI system integrates seamlessly with existing vehicle systems, allowing for easy installation and minimal
Mallieswaran, K., Nithya, R., Rajendran, Shuruti, Arulaalan, M.
Technical Paper
Truck Driver Shin-Knee Position for Clutch and AcceleratorJ1521_202412 (Current)12/06/2024
This SAE Recommended Practice describes two-dimensional, 95th percentile truck driver, side view, seated shin-knee contours for both the accelerator operating leg and the clutch operating leg for horizontally adjustable seats (see Figure 1). There is one contour for the clutch shin-knee and one contour for the accelerator shin-knee. There are three locating equations for each curve to accommodate male-to-female ratios of 50:50, 75:25, and 90:10 to 95:5
Truck and Bus Human Factors Committee
Recommended Practice
Truck Driver Stomach PositionJ1522_202412 (Current)12/06/2024
This SAE Recommended Practice describes two-dimensional 95th percentile truck driver side view, seated stomach contours for horizontally adjustable seats (see Figure 1). There is one contour and three locating lines to accommodate male-to-female ratios of 50:50, 75:25, and 90:10 to 95:5
Truck and Bus Human Factors Committee
Recommended Practice
Driver Selected Seat Position for Class B Vehicles - Seat Track Length and SgRPJ1517_202412 (Current)12/06/2024
This Recommended Practice provides a procedure to locate driver seat tracks, establish seat track length, and define the SgRP in Class B vehicles (heavy trucks and buses). Three sets of equations that describe where drivers position horizontally adjustable seats are available for use in Class B vehicles depending on the percentages of males to females in the expected driver population (50:50, 75:25, and 90:10 to 95:5). The equations can also be used as a checking tool to estimate the level of accommodation provided by a given length of horizontally adjustable seat track. These procedures are applicable for both the SAE J826 HPM and the SAE J4002 HPM-II
Truck and Bus Human Factors Committee
Recommended Practice
Describing and Evaluating the Truck Driver's Viewing EnvironmentJ1750_202412 (Current)12/06/2024
This SAE Recommended Practice establishes three alternate methods for describing and evaluating the truck driver's viewing environment: the Target Evaluation, the Polar Plot and the Horizontal Planar Projection. The Target Evaluation describes the field of view volume around a vehicle, allowing for ray projections, or other geometrically accurate simulations, that demonstrate areas visible or non-visible to the driver. The Target Evaluation method may also be conducted manually, with appropriate physical layouts, in lieu of CAD methods. The Polar Plot presents the entire available field of view in an angular format, onto which items of interest may be plotted, whereas the Horizontal Planar Projection presents the field of view at a given elevation chosen for evaluation. These methods are based on the Three Dimensional Reference System described in SAE J182a. This document relates to the driver's exterior visibility environment and was developed for the heavy truck industry (Class B
Truck and Bus Human Factors Committee
Recommended Practice
Development of an Assessment Methodology for Synchronizer Ring (CuZn Alloy) Wear Durability2024-28-018512/05/2024
Gear shifting effort or force especially in manual transmission has been one of the key factors for subjective assessment in passenger vehicle segment. An optimum effort to shift into the gears creates a big difference in overall assessment of the vehicle. The gear shifting effort travels through the transmission shifting system that helps driver to shift between the different available gears as per the torque and speed demand. The shifting system is further divided into two sub-systems. 1. Peripheral system [Gear Shift Lever with knob and shift Cable Assembly] and Shift system inside the transmission [Shift Tower Assembly, Shift Forks, Hub and sleeve Assembly with keys, Gear Cones and Synchronizer Rings etc.] [1]. Both the systems have their own role in overall gear shifting effort. There has been work already done on evaluation of the transmission shifting system as whole for gear shifting effort with typical test bench layouts. Also, work has been on assessment of life of the
Singh, Paramjeet, Yadav, Sanjay Kumar
Technical Paper
Validation Methodology of Different Driver Monitoring Systems Using a Modular Motion Drive Simulator2024-28-026312/05/2024
In India, Driver Drowsiness and Attention Warning (DDAW) system-based technologies are rising due to anticipation on mandatory regulation for DDAW. However, readiness of the system to introduce to Indian market requires validations to meet standard (Automotive Industry Standard 184) for the system are complex and sometimes subjective in nature. Furthermore, the evaluation procedure to map the system accuracy with the Karolinska sleepiness scale (KSS) requirement involves manual interpretation which can lead to false reading. In certain scenarios, KSS validation may entail to fatal risks also. Currently, there is no effective mechanism so far available to compare the performance of different DDAW systems which are coming up in Indian market. This lack of comparative investigation channel can be a concerning factor for the automotive manufactures as well as for the end-customers. In this paper, a robust validation setup using motion drive simulator with 3 degree of freedom (DOF) is
Raj, Prem raj Anand, Selvam, Dinesh Kumar, Thanikachalam, Ganesh, Sivakumar, Vishnu
Technical Paper
Trailer Disengage Confirmation Alarm System for Electric Subsystems2024-28-021312/05/2024
The truck industry's primary focus is on global transportation, necessitating the efficient movement of goods and materials. There are many types of trucks designed for different purposes, and one of the most significant ones is the tractor trailer which offers great flexibility and can carry heavy loads. The tractor-trailer assembly unit consists of a complex integration of mechanical, electrical, and pneumatic connections, each serving a critical role in the overall functionality and performance of the vehicle. The disconnection of electrical interconnections between the truck trailer and tractor is crucial to prevent damage to the connectors within the wiring harness, which can lead to hazardous situations on the road. The tractor unit serves as the power source, while the trailer is responsible for carrying cargo, with the wiring harness being a crucial yet vulnerable component. When the trailer disengages from the fifth wheel coupling, it is vital to ensure that the electrical
Singh, Amandeep, Kumar, Pradeep, Suresh, Karthikrajan, Kotian, Pradeep, T, Thirunavukkarasu, Chitreddy, Bharath, R, Sunilkumar
Technical Paper
Enhancing Testing and Simulation with Virtualized Base Software2024-28-024812/05/2024
The fusion of virtualized base software with simulation technologies has transformed the methods used for development and system testing. This paper examines the architecture, implementation, and advantages of employing virtualization to improve simulation environments. Virtualized base software enables the creation of isolated, scalable, and replicable settings, essential for executing complex simulations that replicate real-world situations. Utilizing virtualization enhances simulations by making them more efficient, flexible, and cost-effective. The study covers the essential elements of virtualized simulation platforms, such as containerization, network abstraction and virtual drivers. It also analyzes how these components collaborate to create a strong framework for simulating diverse applications, ranging from software testing to hardware emulation. This approach offers several benefits, including better resource utilization, quicker deployment times, and the flexibility to
Shenoy, Ganesh, Malchow, Florian
Technical Paper
Customized Vehicle Feature Control through Driver Recognition Technology2024-28-021912/05/2024
This paper presents a novel approach for customizing vehicle features through driver recognition technology. The system combines Cultural Adaptive Face Recognition (CAFR) using FaceNet and Contrastive Language-Image Pretraining (CLIP) models, along with OpenCV, to recognize drivers and customize vehicle feature control. To identify a driver, the system compares their features against a pre-existing database using FaceNet, which generates efficient face embeddings. The driver image and contextual information collected is processed by OpenAI’s CLIP to generate CLIP embeddings which leverages multimodal learning. FaceNet and CLIP embeddings’ fusion is done and are stored in the Qdrant search database for efficient retrieval and similarity searches. Once the driver is recognized, the system adjusts vehicle features such as temperature settings, music selections, and seat adjustments according to the driver's preferences. Additionally, the system implements optical character recognition
Marimuthu, Ranjithkumar
Technical Paper
Design and Development of Steering based Adaptive Headlight System2024-28-027212/05/2024
Driving at night presents a myriad of challenges, with one of the most significant being visibility, especially on curved roads. Despite the fact that only a quarter of driving occurs at night, research indicates that over half of driving accidents happen during this period. This alarming statistic underscores the urgent need for improved illumination solutions, particularly on curved roads, to enhance driver visibility and consequently, safety. Conventional headlamp systems, while effective in many scenarios, often fall short in adequately illuminating curved roads, thereby exacerbating the risk of accidents during nighttime driving. In response to this critical issue, considerable efforts have been directed towards the development of alternative technologies, chief among them being Adaptive Front Lighting Systems (AFS). The primary objective of this endeavor is to design and construct a prototype AFS that can seamlessly integrate into existing fixed headlamp systems. Throughout the
T, Karthi, G, Manikandan, P C, Murugan, S, Sakthivel, N, Vinu, P, Dineshkumar
Technical Paper
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