FSAE is a competition designed to maximize car performance, in which the steering system is a key subsystem, and the steering system performance directly affects the cornering performance of the car. The driver relies on the steering system for effective handling, which is also crucial for cornering and achieving faster lap times. Therefore, while improving the performance of the steering system, it is crucial to match the vehicle design to the driver's habits. Traditionally, steering systems typically use an Ackermann rate between 0% and 100% to offset the slip angle caused by tire deformation, thus achieving the purpose of reducing tire wear. Calculations have shown that a 40-60% Ackermann rate provides a similar compensation effect with little difference in tire wear. The traditional steering design method also does not consider the driver's driving habits and feedback, which is not conducive to the improvement of the overall performance of the car. In FSAE's figure-of-eight loops

Wu, Hailin, Li, Mingyuan

Modeling and Evaluation of FSAE Vehicle Cockpit Ergonomics

2025-01-8610

04/01/2025

This paper seeks to define an analytical approach to ergonomic cockpit design for SAE formula style vehicles. The proposed approach uses a data driven driver model based on RAMSIS ergonomic FEA that considers the discomfort, fatigue, and force availability to evaluate cockpit designs that are generated considering defined constraint inputs, such as driver gender and size. 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 minimum effort and fatigue. In this initial research, RAMSIS ergonomic software is used to generate fatigue and joint discomfort data related to individual joint angles. Anthropometric data is used to calculate the proportional limb lengths from an individual’s gender and height percentile. The optimization function works by selecting a range of driver

Mayor, J.Rhett, Bezaitis, Megan, Oromi, Negar, Winters, Emily, Repp, Alex

Driver Distraction Recognition Based on the Information Bottleneck Theory and Graph Convolutional Networks

2025-01-8112

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

Comparative Kinematic Performance Testing to SAE J3230 on a Dynamometer and Test Track

2025-01-8792

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

Design Methodology and Evaluation Techniques for Pelvic Pusher Energy Absorption Pad

2025-01-8615

04/01/2025

Pelvic pusher energy absorption pad in a vehicle saves the occupant from pelvic injuries in the event of a crash, especially side or pole crash. This pelvic pusher pad plays a crucial role in absorbing the impact energy from the body side and minimizing the impact to the occupant. Positioning of pelvic pusher pad with respect to occupant manikin position and torso angle, stiffening criteria for the energy absorption pad, maximum force and energy absorption target setting methodology and evaluation methods through CAE and part level physical validations are all discussed in detail. Pelvic pusher pad are of various types such as EPP moulded, blow moulded or injection moulded and the criteria differ for each type. For EPP moulded type, based on the EPP grade, S-S Graph gets converted to F-S Graph and validated accordingly. F-S Graph for a test vehicle is generated through sled test where the sled is made to impact the pelvis of ES2 Dummy at a constant velocity and the F-S Graph is

S M, Rahul, d, Anantha, Kakani, Phani Kumar, Malliboina, Mahendra

Recommendation of Adaptive Safe Speed Limits for Different Driver Profiles Using Deep Learning

2025-01-8106

04/01/2025

Personalization is a growing topic in the automotive space, where Artificial Intelligence can be used to deliver a customized experience in features like seat positioning and climate control. Considering that the leading cause of accidents is driving at an inappropriate speed, personalizing the speed limit for a driver can greatly improve vehicle safety. Current speed limits apply to all drivers, irrespective of skill, including special speed limits when there are adverse weather conditions. As these speed limits do not consider an individual’s skill and capabilities, the limit could still be inappropriate for a given driver in that specific driving context. Therefore, we propose a system that can profile the driver’s style to recommend a personalized speed limit, based on both the environmental context and their skill in that environment. The system uses a neural network to classify the driver’s behavior in specific environments by monitoring the vehicle data and the environmental

Perumal, Rathapriya, Chouhan, Madhvendra, Rangarajan, Rishi

Analysis of Occupants' Responses in Frontal Sled Tests under a Reclined Rigid Seat Environment

2025-01-8734

04/01/2025

With the increasing adoption of Zero-Gravity Seats in intelligent cockpits, there is a growing concern over the safety of occupants in reclined postures during collisions. The newly released anthropomorphic test device (ATD), THOR-AV, has modified the neck, spine, and pelvis structures to better match reclined postures. This study aims to investigate the changes in kinematic response and injury metrics for occupants in reclined postures, through high-speed frontal sled tests utilizing the THOR-AV. The tests were conducted using an adjustable rigid seat with a zero-gravity characteristic and an integrated three-point seat belt. Six tests were performed across four seat configurations: Standard, Semi-Reclined, Reclined, and Zero-gravity postures. The input acceleration pulse for these tests was derived from the equivalent double trapezoidal waveform of the Mobile Progressive Deformable Barrier (MPDB) test. Data from sensors and high-speed video were collected for analysis. The results

Wang, Qiang, Liu, Yu, Fei, Jing, Yang, Xiaoting, Wang, Peifeng, Bai, Zhonghao

Integrated Multimodal System for Real-Time Driver Fatigue Detection and Cognitive Load Assessment

2025-01-8076

04/01/2025

As human drivers' roles diminish with higher levels of driving automation (SAE L2-L4), understanding driver engagement and fatigue is crucial for improving safety. We developed an integrated hardware and software system to analyze driver interaction with automated vehicles, with a particular focus on cognitive load and fatigue assessment. The system includes three submodules; namely the Driver Behavior Measurement (DBM), Vehicle Dynamics Measurement (VDM), and the Driver Physiological Measurement (DPM). The DBM module uses electro-optical (EO) and infrared (IR) camera to track a number of facial features such as eye aspect ratio (EAR), mouth aspect ratio (MAR), pupil circularity (PUC), and mouth to eye aspect ratio (MOE). Although determining these metrics from images of the driver’s face in conditions such as low light or with sunglasses is challenging, the paper showed that fusion of EO and IR image analysis produces robust performance. The VDM module utilizes an Inertial Measurement

Jirjees, Abdullah, Rahman, Taufiq, Farhani, Ghazal, Singh, Daniel, Charlebois, Dominique

A Proactive System to Anticipate and Store the Damage Information on a Parked Car Using Machine Learning Algorithm

2025-01-8211

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 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 vehicle

Debnath, Sarnab, Patil, Prasad, Belur Subramanya, Sheshagiri, Govinda, Shiva Prasad

Literature Review and Framework for Identifying Seat Belt Misuse and Misrouting in Frontal Collisions

2025-01-8721

04/01/2025

The effect of seat belt misuse and/or misrouting is important to consider because it can influence occupant kinematics, reduce restraint effectiveness, and increase injury risk. As new seatbelt technologies are introduced, it is important to understand the prevalence of seatbelt misuse. This type of information is scarce due to limitations in available field data coding, such as in NASS-CDS and FARS. One explanation may be partially due to assessment complexity in identifying misuse and/or misrouting. An objective of this study was to first identify types of lap-shoulder belt misuse/misrouting and associated injury patterns from a literature review. Nine belt misuse/misrouting scenarios were identified including shoulder belt only, lap belt only, or shoulder belt under the arm, for example, while belt misrouting included lap belt on the abdomen, shoulder belt above the breasts, or shoulder belt on the neck. Next, the literature review identified various methods used to assess misuse

Gu, Emily, Parenteau, Chantal

The Influence of out-of-Position Displacement during Emergency Braking on Occupant Whiplash Injury in Subsequent Rear-End Collisions

2025-01-8720

04/01/2025

In the pre-crash emergency braking scenario, the occupant inside the vehicle will move forward due to inertia, deviating from the standard upright seating position for which conventional restraint systems are designed. Previous studies have mainly focused on the influence of out-of-position (OOP) displacement on occupant injuries in frontal collisions, and provided solutions such as active pretensioning seatbelts (APS). But little attention has been paid to the influence of OOP on whiplash injury during a subsequent rear-end collision. To investigate the forward OOP impact on whiplash injuries and the effectiveness of APS in this accident scenario, a vehicle interior model with an active human body model (AHBM) was setup in the MADYMO simulation platform. Different braking strengths (0.8g and 1.1g), APS triggering times (from 0.2s before to 0.2s after the braking initiation) and pretensioning forces (from 100N to 600N) were input to the simulation matrix. The occupant’s forward OOP

Fei, Jing, Qiu, Hang, Wang, Peifeng, Liu, Yu, Cheng, James Chih, Zhou, Qing, Tan, Puyuan

An Adaptive Risk-Based Access Control with Trusted Execution Environment for Vehicles

2025-01-8089

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/SAE 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

Luo, Feng, Li, Zhihao, Wang, Jiajia, Luo, Cheng

Research on Composite Braking Strategy of Pure Electric Commercial Vehicle on Downhill Low-Adhesion Road Considering Rainfall Intensity

2025-01-8813

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 tandem composite braking method. This approach uses an eddy current retarder (ECR) 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 and vehicle speed, on

Liu, Wang, Zhang, Yu, Xiao, Hongbiao, Shen, Leiming

A Deep Learning Framework for Time Series Prediction of Passenger Motion Sickness Based on Vehicle Dynamics Data

2025-01-8104

04/01/2025

Technology development for enhancing passenger experience has gained attention in the field of autonomous vehicle (AV) development. A new possibility for occupants of AVs is performing productive tasks as they are relieved from the task of driving. However, passengers who execute non-driving-related tasks are more prone to experiencing motion sickness (MS). To understand the factors that cause MS, a tool that can predict the occurrence and intensity of MS can be advantageous. However, there is currently a lack of computational tools that predict passenger's MS state. Furthermore, the lack of real-time physiological data from vehicle occupants limits the types of sensory data that can be used for estimation under realistic implementations. To address this, a computational model was developed to predict the MS score for passengers in real time solely based on the vehicle's dynamic state. The model leverages self-reported MS scores and vehicle dynamics time series data from a previous

Kolachalama, Srikanth, Sousa Schulman, Daniel, Kerr, Bradley, Yin, Siyuan, Wachsman, Michael Ben, Pienkny, Jedidiah Ethan Shapiro, Jalgaonkar, Nishant M., Awtar, Shorya

A Co-Simulation Methodology for Predicting Occupant Thermal Comfort for Cabin Cooldown and Warmup Scenarios

2025-01-8188

04/01/2025

Achieving and maintaining thermal comfort for vehicle cabin cool down and warm up is a challenging task. Keeping the passenger comfortable in all driving scenarios needs a properly sized system. Predicting thermal comfort in a virtual environment consisting of thermal system and vehicle cabin gives us the opportunity to size the system components to maintain thermal comfort. These studies could then be extended to develop comfort-based control strategies that help us achieve a system optimized for performance. The present study focuses on developing a co-simulation methodology for predicting thermal comfort in a vehicle for hot and cold ambient conditions. Key to proper system sizing would be to capture the cabin thermal loads accurately. Traditionally, either a 1D or 3D cabin model is used for assessment of thermal comfort. Both these cabin models have their own applications and limitations. A 1D-3D cabin model along with the developed co-simulation methodology in this work addresses

Balasubramanian, Sudharsan, Natarajan, Shankar

Identifying Negative Driver States that Share Commonalities for Interventions

2025-01-8676

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 [1]; however, these reductions can also be related to novice driver inexperience [2] and alcohol intoxication [3]. Through our analysis of the

Seaman, Sean, Zhong, Peihan, Angell, Linda, Domeyer, Joshua, Lenneman, John

A Preliminary Study of Occupant Kinematics and Injuries in a Frontal Crash with Occupant Face-to-Face Scenario

2025-01-8736

04/01/2025

This paper investigates a novel seating arrangement where occupants face each other, focusing on occupant safety during a 56 km/h frontal impact, a standard test condition for assessing crashworthiness. A preliminary study was carried out, examining three distinct cases: a forward-facing 50th percentile occupant in third row seat, a rear-facing 50th percentile occupant in second row seat, and the interaction between these two occupant orientations. The study utilized both elastic flexible and rigid seat designs to analyze the impact on occupant kinematics and injury outcomes. The results demonstrate that the seating position has a significant influence on occupant injuries. Rear-facing occupants are primarily at risk due to seat design, whereas forward-facing occupants face a higher risk of injury from the increased space between occupants, lacking a reactive surface to mitigate impact forces. Notably, direct interaction between occupants did not result in severe injuries. However

Liu, Chong, Li, Kun, Liu, Yutao, Lv, Xiaojiang, Wang, Yonghui, Zhou, Dayong, Yang, Heping

Design of A Differential Braking Controller Based on Road Reaction Force Estimation to Respond to Steering System Failure in Autonomous Driving Situations

2025-01-8797

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 (SbW) 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. 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 situation. However, if limited to a situation such as autonomous driving

Kim, Sukwon, Kim, Young Gwang, Kim, SungDo, Moon, Sung Jin

Optimal Usage of Engine Torque for a Disconnect Device in Situations Where Battery Power is Constrained

2025-01-8578

04/01/2025

This paper introduces a novel approach to optimize battery power usage and optimal engine torque for Axle 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 Axle 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 [1]. 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 the 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 approach

Sha, Hangxing, Madireddy, Krishna Chaitanya, Banuso, Abdulquadri, Khanal, Shishir, Rock, Joe, Patel, Nadirsh

Operational Evaluation of a Pre-Production L2 System HMI

2025-01-8050

04/01/2025

The study analyzed data from on-road drives with a pre-production Level 2 (L2) partial automation system using a sample of 27 drivers ranging from 21 to 75 years of age. The 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 the system

Llaneras, Robert, Glaser, Yi, Green, Charles, August, Maureen, Landry, Steven

Objective and Subjective Evaluation of the Interaction of Automated Vehicles and Human Drivers in Take-Over Scenarios

2025-01-8048

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 psychophysiological 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 psychophysiological 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

Optimal Investigation About Cab of BSC Racing Car Based on Ergonomics

2025-01-8669

04/01/2025

In the Baja race, off-road vehicles need to run under a variety of real and complex off-road conditions such as pebble road, shell pit, stone bad road, hump, water puddle, etc. In the process of this high-intensity and high-concentration race, the unoptimized design of the cab in ergonomics will easily cause the driver's visual and handling fatigue, so that the driver's attention is not concentrated. Cause the occurrence of security accidents. Moreover, lower back pain, sciatic nerve discomfort, lumbar spine diseases and other occupational diseases are basically caused by uncomfortable driving posture and unreasonable control matching, and these have a lot to do with unreasonable ergonomic design. In order to solve these problems, firstly establish the human body model of the driver, and then build the BSC racing car model by using 3D modeling software Catia. Then use the ergonomics simulation software Jack to analyze the visibility, accessibility and comfort. Based on the simulation

Liu, Yuzhou, Liu, Silang

Research on Road-Sense Simulation Algorithm and Analysis of Its Effect on Different Steering Wheels

2025-01-8753

04/01/2025

With the continuous development of automotive intelligence, there is an increasing demand for vehicle chassis systems to become more intelligent, electronically controlled, integrated, and lightweight. In this context, the steer-by-wire system, which is electronically controlled, offers high precision and fast response. It provides greater flexibility, stability, and comfort for the vehicle, thus meeting the above requirements and has garnered widespread attention. Unlike traditional systems, the steer-by-wire system eliminates mechanical components, meaning the road feel cannot be directly transmitted to the steering wheel. To address this, the road feel, which is derived from the vehicle's state or integrated with environmental driving data, must be simulated and transmitted to the steering wheel through a road feel motor. This motor generates feedback that mimics the road feel, similar to that experienced in a conventional steering system. This simulation enhances the driver's

Li, Shang, Kaku, Chuyo, Zheng, Hongyu, Zhang, Yuzhou

Driving under the Influence: A Review of Fitness to Drive, Drug-Induced Impairments, and Simulation Testing

2025-01-8666

04/01/2025

This literature review examines the concept of Fitness to Drive (FTD) and its impairment due to drug consumption. Using a Systematic Literature Review (SLR) methodology, the paper analyzes literature from mechanical engineering and related fields to develop a multidisciplinary understanding of FTD. Firstly, the literature is analysed to provide a definition of FTD and collect methods to assess it. Secondly, the impact of drug use on driving performance is emphasized. Finally, driving simulators are presented as a valid possibility for analysing such effects in a safe, controlled and replicable environment. Key findings reveal a lack of a comprehensive taxonomy for FTD, with various assessment protocols in use. Only static simulators are employed for drug evaluation, limiting realism and result reliability. Standard Deviation of Lane Position (SDLP) emerges as a gold-standard measure for assessing driver performance. Future research should focus on developing standard definitions for

Uccello, Lorenzo, Nobili, Alessandro, Pasina, Luca, Novella, Alessio, Elli, Chiara, Mastinu, Gianpiero

Effects of Aging on PVC-Based Instrument Panel Skin for Passenger Airbag Deployment Analysis

2025-01-8321

04/01/2025

Plasticized polyvinyl chloride (PVC) has many applications in automotive industry including electrical harnesses, door handles, seat and head rest covers, and instrument panel (IP) and other interior trim. In IP applications, the PVC skin plays a critical role in passenger airbag deployment (PAB) by tearing along the scored edge of the PAB door and allowing the door to open and the airbag to inflate to protect the occupant. As part of the IP, the PVC skin may be exposed to elevated temperatures and ultraviolet (UV) radiation during the years of the vehicle life cycle which can affect the PVC material properties over time and potentially influence the kinematics of the airbag deployment. Chemical and thermal aging of plasticized PVC materials have been studied in the past, yet no information is found on how the aging affects mechanical properties at high rates of loading typical for airbag deployment events. This paper compares mechanical properties of the virgin PVC-based IP skin

G, Karthigan, Savic, Vesna, Ravichandran, Gowrishankar

A Novel Hybrid Approach for Segmenting Drivers Based on Their Driving Style

2025-01-8205

04/01/2025

Drivers present diverse landscapes with their distinct personalities, preferences, and driving habits influenced by many factors. Though drivers' behavior is highly variable, they can exhibit clear patterns that make sorting them into one category or another possible. Discrete segmentation provides an 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 and trip-based methodologies

Chavan, Shakti Pradeep, Chinnam, Ratna Babu

A Comparative Analysis of Acceleration and Deceleration Profiles for Aggressive Driving Styles and Fuel Economy Test Cycles

2025-01-8605

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

A Path Tracking Control Method Considering Vehicle Stability and Road Curvature

2025-01-8038

04/01/2025

The current research landscape in path tracking control predominantly focuses on enhancing tracking accuracy, often overlooking the critical aspect of passenger comfort. To address this gap, we propose a novel path tracking control method that integrates vehicle stability indicators and road curvature variations to elevate passenger comfort. The core contributions are threefold: firstly, we conduct comprehensive vehicle dynamics modeling and analysis to identify key parameters that significantly impact ride comfort. By integrating human comfort metrics with vehicle maneuverability indices, we determine the optimal range of dynamics parameters for maximizing passenger comfort during driving. Secondly, inspired by human driving behavior, we design a path tracking controller that incorporates an anti-saturation algorithm to stabilize tracking errors and a curvature optimization algorithm to mimic human driving patterns, thereby enhancing comfort. Lastly, comparative simulations with two

Lu, Jun, Zeng, Dequan, Hu, Yiming, Wang, Xiaoliang, Liu, Dengcheng, Jiang, Zhiqiang

Active and Passive Security Generalization Algorithm and Typical Case Analysis

2025-01-8744

04/01/2025

In order to effectively predict the vehicle safety performance and reduce the cost of enterprise safety tests, a generalized simulation model for active and passive vehicle safety was proposed. The frontal driver-side collision model under the intervention of the Autonomous Emergency Braking (AEB) was created by using the MADYMO software. The collision acceleration obtained from the sled test was taken as the original input of the model to conduct simulation for the working conditions under different sitting postures of the human body. The injury values of various parts of the Hybrid III 50th dummy were read. Based on the correlation between the two, an active and passive simulation model was established through the Back Propagation (BP) neural network. The input of the model was the inclination angle centered on the dummy's waist, and the output was the acceleration of the dummy's head. The results showed that the comprehensive prediction accuracy rate exceeded 80%. Therefore, the

Ge, Wang, fengyao, LV

Study of Indian Population’s Eye Point to Adapt Indian Vehicle Design to Indian Anthropometry for Accident Risk Mitigation

2025-01-8665

04/01/2025

India has one of the highest accident rates in the world. Quite a few accidents have been attributed to poor driver visibility. Driver visibility is an important factor that can help mitigate the risk of accidents. The optimal visibility of in-vehicle controls is also essential for improving driver experience. Optimized driver visibility improves driving comfort and gives confidence to the driver, ensuring the safety of drivers and subsequently that of pedestrians. Driver visibility is an important consideration for vehicle occupant packaging and SAE has defined various standards and regulations for the same. These guidelines are defined considering American anthropometry, helping OEMs create global vehicles with uniform checkpoints. However, due to anthropometric differences, a need was felt to capture and analyze Indian-specific eyellipse and eye points. To measure the eye point of the user in a controlled environment, the interiors of a passenger vehicle were simulated using a

P H, Salman, Kalra, Prerita, Rawat, Ashish, Sharma, Deepak, Singh, Ashwinder

Predicting Head Injury Criterion in Real-World Frontal Impacts

2025-01-8709

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 rectangular, triangular, polynomial, half-sine, and haversine 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 these 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 included driver occupants. Head acceleration and shoulder belt load channels of Hybrid III 50th percentile male anthropomorphic test devices were collected and separated for training a set of ratios and testing their performance. Rectangular, triangular, quadratic, half-sine, and haversine pulse functions

Westrom, Clyde, Tanczos, Rachel, Adanty, Kevin, Shimada, Sean

Research on Dangerous Driving Behavior Recognition Algorithm Based on LSTM

2025-01-8204

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, Zhang, Miaomiao, Xue, Ming, Jin, Xin

The Effect of Directional Tactile Guidance on Takeover Performance in Level 3 Automated Driving

2025-01-8049

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

Real World Emissions in a High-Altitude City: A Comparison between LPG Taxis and Gasoline Cars

2025-01-8494

04/01/2025

To study the real driving emission characteristics of light-duty vehicles fueled with liquefied petroleum gas (LPG) and gasoline in a 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 mode, which is considerably affected by driving behavior. Furthermore, as vehicle speed increases, 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 a vehicle specific power (VSP) of 0 kW/t or below; After that, the rates slowly increase initially and then increase rapidly with increasing VSP. These

Lyu, Meng, Xu, Yan, Huang, Meihong, Wang, Yunjing

Lessons and Challenges from Crowd-Sourced Data in Rural Michigan to Assess EV Suitability based on Analyzing Personal Driving

2025-01-8525

04/01/2025

Abstract Real-world driving data is an invaluable asset for several types of transportation research, including emissions estimation, vehicle control development, and public infrastructure planning. Traditional methods of real-world driving data collection use expensive GPS-based data logging equipment which provide advanced capabilities but may increase complexity, cost, and setup time. This paper focuses on using the Google Maps application available for smartphones due to the potential to scale-up real-world driving data logging. Samples of the potential data processing and information that can be gathered by such a logging methodology is presented. Specifically, two months of Google Maps driving data logged by a rural Michigan resident on their smartphone may provide insights on their driving range, duration, and geographic area of coverage (AOC) to guide them on future vehicle purchase decisions. Aggregating such statistics from crowd-sourcing real-world driving data via Google

Manoj, Ashwin, Yin, Sally, Ahmed, Omar, Vaishnav, Parth, Stefanopoulou, Anna, Tomkins, Sabina

Real-Time Application of Torque Converter Modeling for Enhanced System Response in a Hybrid Powertrain

2025-01-8529

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

Optimizing Battery Charging Strategies through Q-Learning and Electric Vehicle Powertrain System Modeling

2025-01-8116

04/01/2025

Battery health status and driving rangeof electric vehicles (EVs) are critical factors in determining their market penetration. Choosing an optimal charging strategy—specifying how, when, and for how long to charge based on the driver’s travel behavior—can significantly mitigate battery degradation and extend battery life. This study introduces an EV powertrain system energy model designed to enhance the prediction accuracy of battery status under real-world driving conditions. By integrating with the Q-learning approach, this studyprovides tailored recommendations on charging behaviors, including charger type, start time, and charging duration. This study innovatively considers the rental costs caused by the battery capacity not being able to meet the daily driving range. Simulating a typical three-year usage scenario for an average driver in New England, the results indicate that thecharging strategy proposed by this study reduces battery degradation rates by 1.53‰, 3.57‰, and 7.68

Wang, Jiayi, Jing, Hao, Ou, Shiqi (Shawn), Lin, Zhenhong

Predictive Steering Angle Generation Algorithm for High Efficiency Vehicle’s Path Optimization

2025-01-8791

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 dynamics. The vehicle is put into a three-dimensional representation of the racetrack, including its dimensions, 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 Nonlinear Model Predictive Control (NMPC) 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 dynamics modelling of the vehicle. Each single simulation exploits a different possible steering angle to be applied by the virtual driver, starting from the initial conditions given by the actual

De Carlo, Matteo, Manzone, Simone, de Carvalho Pinheiro, Henrique, Carello, Massimiliana

Improved Model and Physical Prototype of an Online Corrective Look-Ahead Road Profiling System (CLARPS) for Active Suspension Applications

2025-01-8790

04/01/2025

Online road profiling capability is required for automotive active suspension systems to be realized in a consumer and commercial landscape. One challenge that impedes the realization of these systems is the need for the online road profiler to maintain an optimal spatial resolution of the oncoming road profile. Shifting of the road profiling sensor measurement frame of reference due to body motion experienced by the vehicle can negatively impact profiling accuracy. Prior work proposed a corrective look-ahead road profiling system (CLARPS) and demonstrated the CLARPS architecture and initial MATLAB/Simulink simulation environment. First, this work further develops the robust simulation environment. The simulation allows the look-ahead viewing angles to be optimized for the best road profile spatial resolution and facilitates a study on the impact of road profiler sensor location on the accuracy of the generated road profile. Second, this work introduces a lab-scale physical CLARPS

Morison, Dane, Mynderse, James

Research on Pedal Operation Characteristics for Detecting Pedal Misapplication

2025-01-8675

04/01/2025

Drivers sometimes operate the accelerator pedal instead of the brake pedal due to driver error, which can potentially result in serious accidents. To address this, the Acceleration Control for Pedal Error (ACPE) system has been developed. This system detects such errors and controls vehicle acceleration to prevent these incidents. The United Nations is already considering regulations for this technology. This ACPE system is designed to operate at low speeds, from vehicle standstill to creep driving. However, if the system can detect errors based on the driver's operation of the accelerator pedal at various driving speeds, the system will be even more effective in terms of safety. The activation threshold of ACPE is designed to detect operational errors, and it is necessary to prevent the system from being activated during operational operations other than operational errors, i.e., false activation. This study focuses on the pedal operation characteristics of pedal stroke speed and

Natsume, Hayato, Shen, Shuncong, Hirose, Toshiya

Correlation of Subjective Assessments and Objective Metrics for on-Center Feeling

2025-01-8287

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 correlations between subjective and objective evaluations are built, which focus on steering stiffness, on-center feel, torque symmetry, torque ripple etc. Firstly, a set of objective metrics which are followed by professional test drivers or tuning experts have been extracted from 12 vehicles’ on-center handling test based on ISO 13674-1 2023, these vehicles covering different motorcycle type, various brands and diverse tuning styles

Jin, Ankang, Luo, Kaijie, Yang, Jianyuan, Zheng, Yue

Modeling Vehicle Behavior in Highway On-Ramps: A Game Theory and Deep Reinforcement Learning Method

12-08-04-0037

03/28/2025

With the improvement of autonomous driving technology, the testing methods for traditional vehicles can no longer meet autonomous driving needs. The simulation methods based on virtual scenario have become a current research hotpot. However, the background vehicles are often pre-set in most existing scenarios, making it difficult to interact with the tested autonomous vehicles and generate dynamic test scenarios that meet the characteristics of different drivers. Therefore, this study proposes a method combining game theory and deep reinforcement learning, and uses a data-driven approach to realistically simulate personalized driving behavior in highway on-ramps. The experimental results show that the proposed method can realistically simulate the speed change and lane-change actions during vehicle interaction. This study can provide a dynamic interaction test scenario with different driver style for autonomous vehicle virtual test in highway on-ramps and a more realistic environment

Qiu, Fanke, Wang, Kan, Li, Wenli

Longitudinal Analysis of Forward Blind Zone Changes in Popular Vehicle Models (1997–2023)

09-13-01-0005

03/26/2025

Background. In 2022, vulnerable road user (VRU) deaths in the United States increased to their highest level in more than 40 years. At the same time, increasing vehicle size and taller front ends may contribute to larger forward blind zones, but little is known about the role that visual occlusion may play in this trend. Goal. Researchers measured the blind zones of six top-selling light-duty vehicle models (one pickup truck, three SUVs, and two passenger cars) across multiple redesign cycles (1997–2023) to determine whether the blind zones were getting larger. Method. To quantify the blind zones, the markerless method developed by the Insurance Institute for Highway Safety was used to calculate the occluded and visible areas at ground level in the forward 180° arc around the driver at ranges of 10 m and 20 m. Results. In the 10-m forward radius nearest the vehicle, outward visibility declined in all six vehicle models measured across time. The SUV models showed up to a 58% reduction

Epstein, Alexander K., Brodeur, Alyssa, Drake, Juwon, Englin, Eric, Fisher, Donald L., Zoepf, Stephen, Mueller, Becky C., Bragg, Haden

Improving Safety of Autonomous Vehicles: A Verifiable Method for Graceful Degradation of Decision and Control Responsibilities

12-08-02-0021

03/24/2025

Developing safe and reliable autonomous vehicles is crucial for addressing contemporary mobility challenges. While the goal of autonomous vehicle development is full autonomy, up to SAE Level 4 and beyond, human intervention remains necessary in critical or unfamiliar driving scenarios. This article introduces a method for gracefully degrading system functionality and seamlessly transferring decision-making and control between the autonomous system and a remote safety operator when needed. This transfer is enabled by an onboard dependability cage, which continuously monitors the vehicle’s performance during its operation. The cage communicates with a remote command control center, allowing for remote supervision and intervention by a safety driver. We assess this methodology in both lab and test field settings in a case study of last-mile parcel delivery logistics and discuss the insights and results obtained from these evaluations.

Aniculaesei, Adina, Aslam, Iqra, Zhang, Meng, Buragohain, Abhishek, Vorwald, Andreas, Rausch, Andreas

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