Browse Topic: Chassis

Items (14,642)

Experimental Validation of a Multi-Row Tapered Roller Bearing Analytical Model for Relating Preload to Frequency Response Characteristics

2026-01-0008To be published on 04/07/2026

Roller bearings are used in many rotating power transmission systems in the automotive industry. During the assembly process of the power transmission system, some types of roller bearings (e.g., tapered roller bearings) require a compressive preload force. Those bearings' rolling resistance and lifespan strongly depend on the preload set during the installation process. Therefore, accurate setting of the preload can improve bearing efficiency, increase bearing lifespan and reduce maintenance costs over the life of the vehicle. A new method for bearing preload measurement has shown potential for both high accuracy and fast cycle time using the frequency response characteristics of the power transmission system. An open problem is experimental validation of the multi-row tapered roller bearing analytical model. After validation, the analytical model can be used to predict the assembled system damped natural frequency for a desired bearing preload. This work presents the experimental

Gruzwalski, David, Mynderse, James

LiDAR-Driven A* Path Planning with Dynamic Obstacle Avoidance for Autonomous Navigation in ROS

2026-01-0030To be published on 04/07/2026

Autonomous mobile robots are becoming a key part of everyday operations in industries like manufacturing, logistics, healthcare, and even home assistance. A core requirement for these robots is the ability to navigate efficiently and reliably within their operating environments. To do this automation, the robot needs to understand its surroundings, figure out where it is on a map, and find a safe path from where it is to where it needs to go without bumping into anything. This paper presents an effective grid-based path planning solution for autonomous indoor navigation with a mobile robot. Achieving reliable and collision-free navigation in changing environments is a major challenge for mobile robotics. This is especially true when obstacles can appear unexpectedly, requiring quick re-planning. To tackle this issue, an improved A* algorithm was implemented to work closely with LiDAR for environmental awareness. The improved algorithm was added to the robot’s navigation system, and

Devaraj, Sriram Sanjeev, Park, Jungme

Autonomous Racing Control Using Reinforcement Learning with Racing Line Guidance

2026-01-0031To be published on 04/07/2026

In recent years, with the emergence of autonomous racing competitions such as Roborace, autonomous racing cars have become a prominent research focus and have undergone rapid development. This paper establishes a reinforcement learning-based decision-making and control framework for autonomous racing cars, achieving cooperative optimization between high-speed racing and safety control under extreme operating conditions. By integrating a Control Barrier Function constrained reward function for dynamic stability and a racing line-guided path optimization, the proposed framework achieves a synergistic balance between minimum lap time and operational safety. Dynamic stability domain constraints based on a two-degree-of-freedom single-mass rigid-body model and racing line optimization based on track geometric modeling are established. The phase plane stability boundary is constructed using the yaw rate method and double-line method, upon which Control Barrier Function constraints are

peng, tao, Zhang, Weiqi, Li, Zengwen, sudong, jiang

Leveraging Machine Learning for Occupant Body Size Estimation via B-Pillar Seatbelt Systems

2026-01-0559To be published on 04/07/2026

Occupant body size in vehicles varies significantly, encompassing differences in height, weight, and overall body composition. Adaptive restraint systems, featuring adjustable parameters such as belt load limiters, steering column load limiters and stroke, seat pan stiffness, and airbag pressure, can offer more equitable protection tailored to individual body sizes. In this study, a test rig modeled after the Volvo XC90 was used to collect data from 47 seated participants. Key seatbelt-related parameters, including D-ring angle, belt payout length, lap belt length, and buckle tension, were measured. These measurements were used to train machine learning models to predict occupant characteristics: height, weight, sitting height. The results demonstrate that low-cost sensors embedded in the seatbelt system can provide sufficiently accurate occupant body size estimations to inform adaptive restraint systems. The prediction errors across both training and test datasets were as follows

Wang, Da, Ahmed, Jawwad, Rowe, Mike, Brase, Dan

Bias and uncertainty in the time, position, and speed data of consumer-grade GPS devices

2026-01-0544To be published on 04/07/2026

The goal of this study is to quantify the accuracy and uncertainty of position and speed measurements acquired by a wide range of consumer-grade GPS-enabled devices while road cycling. We acquired position and speed data simultaneously from 13 consumer devices (e.g., phones, watches, bicycle computers) at their maximum sampling rate (typically 1 Hz) during 10 hours (thirty 20 minute sessions) and 150 km of road cycling in a suburban environment. The position data from these devices were compared to real-time kinematic (RTK) data acquired using a differential GPS system and the speed data from these devices were compared to speed data acquired with high-resolution wheel rotation sensors (23,040 pulses per revolution) synchronized with the RTK data. Based on these comparisons, we generated probability distributions for the errors in the position and speed measured by each of the consumer devices. This study provides foundational data needed to quantify the accuracy and uncertainty across

Booth, Gabrielle R., Mitchell, Alan L., Siegmund, Gunter P.

The Effect of Tread Depth on Antilock-Brake System (ABS)-Equipped Decelerations for Dry and Wet Asphalt and Concrete Road Surfaces

2026-01-0549To be published on 04/07/2026

The effect of tire tread depth on the performance of anti-lock brake systems (ABS) in newer vehicles is not well studied. A single ABS-equipped SUV was used to perform a series of 216 ABS-engaged braking tests on dry and wet asphalt and concrete surfaces using uniform sets of tires with tread depths varying from 0.8 mm (1/32”) to 7.1 mm (9/32”). Vehicle speed and deceleration as a function of time were calculated from 5th-wheel data sampled at 200 Hz. Tests were initially conducted on a dry surface, with tire sets changed between tests. A water truck then distributed water onto the road to create a wet condition and additional tests of each tire set were conducted. Deceleration levels did not change significantly from 7.1 mm (9/32”) down to 2.4 mm (3/32”) of remaining tread on both surfaces in both conditions. Compared to the deceleration levels at these larger tread depths, dry deceleration levels increased for tread depths of about 0.8 mm (1/32”) and 1.8 mm (2/32”) on both asphalt

Miller, Ian, King, David, Siegmund, Gunter P.

Vehicle Deceleration Levels during Wet-to-Dry Transitions on an Asphalt Surface with a High Proportion of Aggregate

2026-01-0542To be published on 04/07/2026

The goal of this study is to quantify how the braking performance of newer anti-lock braking systems (ABS) changes as the level of road wetness varies on an asphalt road surface with a high proportion of aggregate present in the asphalt matrix. To achieve this goal, we conducted 375 straight-line braking tests using a late-model sedan and SUV on a public road in Mississauga, ON. Each vehicle was equipped with a 5th wheel (resolution 0.1 mm) sampled at 200 Hz, from which vehicle speed and deceleration were calculated. The road surface was wetted four times and allowed to dry each time under ambient conditions over a period of about one hour. As the road transitioned from wet to dry, a continuous series of ABS-braking tests were performed from an initial speed of 60 km/h. Both the maximum and average decelerations for each braking event were compared between six “wetness” categories assigned to the road surface condition present for each test. We found that the vehicles were able to

Ahrens, Matthew, Arnold, Nikolas, Miller, Ian, Siegmund, Gunter P.

OFEODM: An Onboard Fast and Efficient Object Detection and Distance Prediction Model

2026-01-0017To be published on 04/07/2026

Object detection and distance prediction have advanced significantly in recent years. The YOLO series has released its 11th version, along with numerous variants that have been applied across various fields. Meanwhile, the Detection Transformer (DETR) has repeatedly set new state-of-the-art (SOTA) records in the field of object detection. Depth Anything also released its second version last year, further pushing the boundaries of distance detection. Although these models achieve impressive performance, they often require substantial computational resources. However, for algorithms intended for real-world applications and deployment on onboard devices, computational resources are limited and valuable. Inference time per frame is a critical factor in ensuring an algorithm's reliability and feasibility. Designing a model that operates in real time without sacrificing accuracy remains an extremely challenging problem, and extensive research is ongoing in this area. To address this

Li, Taozhe, Wang, Hanchen, Hajnorouzali, Yasaman, Xu, Bin

Navigation Integrated End-to-end Path Planning Development and Vehicle Testing

2026-01-0032To be published on 04/07/2026

In order to achieve fully autonomous driving, point to point autonomous navigation is the most important task. Most existing end-to-end models output a short-horizon path which makes the decision process hard to interpret and unreliable at intersections and complex driving scenarios. In this research, we build a navigation-integrated end-to-end path planner on top of an openpilot open source model. We created a navigation branch that encodes route polyline geometry, distance-to-next-maneuver, and high-level instructions and combines with path plan branch using residual blocks and feed-forward layers. By adding minimal parameters, new model keeps the original openpilot tasks unchanged and have the path output based on the navigation information. The model is trained on diverse urban scenes and lighting conditions, and it shows improved route adherence in vehicle testing. The proposed model is validated in a comma 3x device installed on a 2025 Nissan Leaf test vehicle. The road test

Wang, Hanchen, Li, Taozhe, Hajnorouzali, Yasaman, Burch, Collin, li, Victoria, Tan, Lin, Arjmanzdadeh, Ziba, Xu, Bin

Reliability-Based Vibration Design of Vehicle Systems with Tuned Mass Dampers (TMD)

2026-01-0139To be published on 04/07/2026

Tuned Mass Dampers (TMDs) are widely used in the automotive industry to mitigate Noise, Vibration, and Harshness (NVH) issues across various vehicle systems. These passive devices are particularly effective in reducing structural and tactile vibrations in components subjected to resonant excitation. However, real-world applications often face challenges due to manufacturing variability and system-level build differences, which can cause deviations in both the TMD’s tuned frequency (up to ±15%) and the excitation characteristics of the host structure. These uncertainties—in both the TMD properties and the vehicle subsystem dynamics—can be modeled using statistical distributions. This paper presents a generalized methodology for vibration analysis and design under uncertainty, combining reliability engineering with dynamic vibration modeling. The approach formulates a unified mathematical framework that incorporates probabilistic and stochastic modeling to assess TMD performance under a

Abbas, Ahmad, Haider, Syed, d'souza, Suneel

Attention and Intrinsic Curiosity-Enhanced Deep Reinforcement Learning for Path Planning in Dynamic Environments

2026-01-0044To be published on 04/07/2026

Efficient and reliable path planning remains a core challenge for autonomous vehicles operating in dynamic and crowded environments. Although Deep Reinforcement Learning (DRL) has shown considerable potential in autonomous decision-making, it still faces challenges such as insufficient feature extraction, sparse rewards, and low obstacle avoidance efficiency in complex scenarios. To address these issues, this paper proposes an end-to-end path planning framework, PPO-ICM-Attn. Built upon the Proximal Policy Optimization (PPO) algorithm, the framework incorporates a dual-channel attention convolutional neural network module (Attention-CNN) to enhance spatial and semantic understanding of dynamic obstacles, and introduces an Intrinsic Curiosity Module (ICM) to promote active exploration in sparse reward settings. Furthermore, a reactive avoidance reward function based on velocity obstacle theory is designed and embedded to achieve real-time proactive collision avoidance in highly dynamic

Shen, Shiquan, Liu, Jiahao, Chen, Zheng, Li, Zongdian, Zhao, Yuting, Wu, Minggong, Zhao, Jie, Qin, Zongquan, Wang, Yanfeng

Analyzing Fastened Joints in Hydraulic Dampers using Simulation and Experimental Methods

2026-01-0585To be published on 04/07/2026

The main purpose of this study is to develop and validate an accurate calculation model for an unorthodox hydraulic damper piston joint, enabling reliable torque specification and clamp behavior without full prototype iteration. The joint features a bolted interface with a laminated shim stack of many thin disks with varying outer diameters. Analysis of such unorthodox joints are uncommon in literature, making the effects of load distribution truncation in the member stack due to varying outer diameters and surface contact effects between thin members during compression and torquing difficult to quantify. The model discussed in this paper is based on frustum load distribution combined with annular-plate bending and elastic-foundation effects to capture the effects of washer cupping. Concrete outputs of the calculator include member load distribution, bolt and member stiffnesses, torque-to-preload relationships, including friction factors and a variable effective-bearing-diameter, and

Dresen, Gabriel S., Vollmar, Race, Roy Chowdhury, Sourav

Research on Attitude Control and Stability of Water-Wading Vehicles

2026-01-0627To be published on 04/07/2026

With the intensification of global climate change, the frequency of extreme rainfall has increased, and the number of urban waterlogging and water-crossing sections in the wild has significantly risen. The scenarios where vehicles encounter complex water-crossing road conditions are also on the rise, which poses unprecedented challenges to the passability and safety of modern vehicles. This article conducts a study on the problem of attitude instability that occurs when vehicles are driving in water. Traditional vehicles have insufficient passability when wading through water. Their passive suspension systems cannot adaptively adjust when wading through water, resulting in insufficient vehicle stability and a high risk of serious accidents such as "water skidding" or even overturning. The safety of driving through water cannot be guaranteed. In this regard, this paper first establishes a dynamic model of a wading vehicle body considering the effect of buoyancy. On this basis, it

Li, LiuYuanHeng, Tan, Gangfeng, Dong, Chenchen, Fayzullayevich, Jamshid, Han, YiFei

Data-driven Study on Chassis Suspension Performance Degradation

2026-01-0582To be published on 04/07/2026

The performance of chassis suspension mechanisms critically affects vehicle handling, ride comfort, and safety. Under severe operating conditions, health monitoring of chassis suspension mechanisms can detect potential problems in time, thereby reducing safety risks and optimizing maintenance costs. With the rapid development of sensing and data analytics technologies, data-driven approaches are increasingly used in health monitoring. This study aims to achieve real-time monitoring of chassis suspension performance degradation using a deep neural network (DNN). First, a semi-vehicle suspension model is constructed to simulate the vehicle's degraded state under bumpy road conditions, generating a dataset of key suspension parameters. Subsequently, a DNN model comprising three hidden layers is developed to assess suspension performance degradation. To optimize model performance, the effects of different numbers of neurons and hidden layers on model accuracy are explored. Experimental

Liao, Yinsheng, Lei, Yisong, Su, Ailin, Wang, Zhenfeng

Revisiting Rear Seat Safety: Field Evaluations of Relative Injury Risk Across Seating Positions and the Integration of Advanced Rear Seat Belt Systems.

2026-01-0561To be published on 04/07/2026

Despite advances in automotive crash avoidance, occupant restraint systems remain crucial in protecting the motoring public. Following decades of improvement in occupant protection, including the development of features such as frontal airbags, collapsable steering columns, and seat belt pretensioners and load limiters for the front seat, the safety of rear seat occupants has recently undergone scrutiny. Studies evaluating rear seat occupant injury risk via field crash data have reported findings of reduced relative safety in the rear seating positions and alluded to rear seat advanced restraints, such as pretensioners and load limiters, as a potential solution. While the pursuit of certain novel technologies has historically improved automotive occupant outcomes, evaluation of these new systems in both controlled laboratory environments and field crashes is necessary to understand potential positive and negative effects of widespread introduction. This study expanded upon prior field

Rapp van Roden, Elizabeth Ann, Miller, Bruce, Pearson, Joseph, Williamson, James, Brown, Thomas

Advanced Tire Looseness Identification through Algorithmic Gear Error Analysis and Probabilistic Assessment

2026-01-0590To be published on 04/07/2026

At present, tire failures directly affect road safety, and the number of incidents caused by them is gradually increasing. Examining tire looseness on time is vital for vehicle safety. Tire-related incidents not only put people in peril but also have a detrimental effect on the economy. Therefore, the goal of this research is to develop a new and effective method for identifying tire looseness. A novel gear error reduction approach, distinct from traditional methods, combines advanced computing and probabilistic analysis. This paper involves three key components: extracting looseness eigenvalues, calculating ring gear errors, and computing the tire loosen probabilities. Gear errors derived from the Kalman filter and adjusted for speed, eigenvalues were calculated, and a tire loosening probability analysis was performed. Real-car trials across speeds and roads confirm its accuracy and reliability. This technology can improve automotive safety and maintenance, reducing accidents, claims

Zhao, Gaoming, Zhang, Zhijie, Liu, Jianjian, Ma, Guangtao, Wang, Zhenfeng, Zhao, Binggen

Target Cascading Kinematics and Compliance Tables to Suspension Design

2026-01-0584To be published on 04/07/2026

During the initial design phase, automotive Original Equipment Manufacturers (OEMs) require the adaptability to examine various suspension system architectures while maintaining focus on the specific performance objectives. Those requirements are expressed by Kinematics and Compliance (K&C) look-up tables and represent the footprint of what the suspension should look like in real-world applications. However, translating those requirements into the full geometric hardpoint layout is not straightforward. This process often relies on trial-and-error approaches, making it time consuming and requiring significant expertise. This challenge, known as "target cascading," remains a major hurdle for many engineers. The main objective of this paper is to cascade the suspension requirements from K&C look-up tables to hardpoint locations by adopting an automatic workflow and ensuring respect for constructive and feasibility constraints. Design space exploration was conducted using a robust

Brigida, Piero, Di Carlo, Paolo, Di Gioia, Niccolò, Geluk, Theo, Tong, Son, Alirand, Marc, Gorgoretti, Davide, Occhineri, Marco, Tassini, Nicola, Berzi, Lorenzo

Two-Channel Pressure Control Using an Electric Cylinder and a Solenoid Valve for Electronically Controlled Brake Systems

2026-01-0638To be published on 04/07/2026

With the rapid proliferation of electrified vehicles (xEVs), maximizing regenerative energy recovery has become a crucial challenge in realizing zero-emission mobility. In front-wheel-drive (FWD) vehicles, regenerative braking acts only on the front axle, resulting in a braking-force distribution biased toward the front. When uniform hydraulic pressure is applied to both axles, excessive braking force on the front wheels may cause premature wheel lock and hinder the intended regenerative braking effect. To address this issue, it is essential to implement an independent pressure control strategy (two-channel pressure control) that appropriately reduces front pressure according to regenerative force while independently maintaining adequate rear pressure. This study proposes a new two-channel pressure control architecture utilizing a simple and reasonable actuator set consisting of one electric cylinder and one solenoid valve. The electric cylinder generates hydraulic pressure by

Kaneko, Shosuke, Deno, Yoshitomo, Kobayashi, Tatsushi, Kawamura, Hikaru

Modelling and Analysis of Rolling Truck Tire over Dry and Snow-Covered Surfaces Using Advanced Computational Techniques

2026-01-0591To be published on 04/07/2026

This paper presents a novel approach to modelling and analyzing a 315/80R22.5-sized truck tire under snow-covered road conditions. The tire is modelled using Finite Element Method (FEM) in ESI Virtual Performance Solutions (VPS) software. The tire model consists of various parts representing the tread, under tread, carcass, sidewalls and beads in addition to the rim. The tire model is then verified in both static and dynamic domains against experimental data. The experimental results were conducted over a dry surface at a high-speed test track in Hällered, Sweden, at a constant travelling speed of 80 km/h, and a constant vertical load of 27 kN with sensors depicting both temperature and inflation pressure changes throughout a 40-minute run. A tire thermal model is developed, and the simulation results are correlated with the measured temperature of the tested tires. In addition, the rolling resistance variation with speed, temperature and inflation pressure is predicted and analyzed

Opatha, Dillon, Oijer, Fredrik, El-Sayegh, Zeinab, El-Gindy, Moustafa

Research on Fault-Tolerant Control Strategy for Drive System Failure of Corner Module-by-Wire Chassis Vehicles

2026-01-0620To be published on 04/07/2026

As an emerging research focus, corner module-by-wire chassis vehicles address the pain points of traditional chassis in flexibility, cost, and development efficiency, and have become one of the key infrastructures in the autonomous driving era. However, their large number of actuators significantly increases the risk of failures. This paper analyzes the characteristics of such vehicles and studies the fault-tolerant control for their drive system failures. Firstly, a full-vehicle dynamic model was established, with mathematical modeling conducted for the vehicle body, motor, tire, and corner module system models. Secondly, a hierarchical yaw stability control strategy was designed for the non-faulty actuator scenario: the decision-making and control layer adopted both Sliding Mode Control (SMC) and fuzzy PID control, selecting the method with better performance to output the additional yaw moment; the control allocation layer used a quadratic programming algorithm based on tire load

Zheng, Hongyu, Zhang, Tianhao, Zhang, Yuzhou

Embedded Real-Time Control of a Distributed Trailer Propulsion System with Regenerative Braking for Net Neutral Load Towing

2026-01-0065To be published on 04/07/2026

Towing significantly degrades vehicle efficiency, reducing battery-electric vehicle (BEV) range by up to 50% and increasing internal-combustion engine (ICE) fuel consumption by ~30%. To address this challenge, this paper presents a real-time embedded control architecture for a distributed trailer propulsion system that actively regulates drawbar force to achieve net neutral load towing while enabling regenerative braking. Unlike prior e-trailer concepts, this platform demonstrates a cost-effective, fully networked, model-based control implementation using commercial off-the-shelf components. The control system integrates dual Raspberry Pi controllers running ROS 2: one samples a hitch-mounted load cell at 100 Hz and the other processes OBD-II/CAN messages. Controllers designed in MATLAB/Simulink are deployed to a 5 kWh LiFePO₄ pack and a 5 kW traction motor, utilising embedded Linux for real-time scheduling and onboard data logging. Two operating modes are implemented: (i) PI

Joshi, Gaurav, Adelman, Ian, Liu, Jun, Donnaway, Ruthie

Development of A Tire Blowout Experimental Platform for Dynamics and Control Validation

2026-01-0202To be published on 04/07/2026

Tires are critical to vehicle dynamics, transmitting traction, braking, and cornering forces to the road. A tire blowout, the sudden and rapid loss of inflation pressure due to puncture or structural failure, can cause severe instability, rollover, or collisions. Understanding vehicle response during blowout events is essential for developing robust safety systems and control strategies. Earlier developed simulation models are used to study and understand vehicle behavior during blowouts, but there is a lack of on-road testing platforms to validate these models experimentally. A custom-built blowout device integrated with a data acquisition system has been developed to address this gap. It consists of multiple solenoid valves mounted on the wheel surface and powered by a 12V supply. All valves are triggered at the same time using an RF remote, producing rapid and synchronized deflation. An Arduino-based actuation system is being developed for individual valve actuation and custom

KANTHALA, Maha Vishnu Vardhan Reddy, Krishnakumar, Ashwin, Lin, Wen-Chiao, Chen, Yan

Research on Parameter Matching and Control Strategy of Electric Semi trailer Power System

2026-01-0449To be published on 04/07/2026

Reducing carbon emissions is an important issue for environmental protection, while also saving fossil fuels for all mankind and preventing global warming. Therefore, reducing carbon emissions is of great significance. The carbon emissions in the transportation sector account for an important proportion of global carbon emissions, and the carbon emissions of heavy-duty commercial vehicles also account for an important proportion of the carbon emissions in the transportation sector. Therefore, the electrification of heavy-duty commercial vehicles is one of the important ways to save energy and reduce emissions for heavy-duty vehicles. Especially the research topic of this article: semi-trailer trains. Similar to passenger cars, semi-trailer trains also have two electrification ideas: hybrid and electric drive. Considering the high energy demand of heavy-duty commercial vehicles, the high cost of large capacity batteries, the current low level of development of electric heavy-duty

Zheng, Hongyu, Zhu, Kaixuan, Zhang, Yuzhou

Quantifying the Impact of Towing on BEV Energy Use: Instrumented On Road Testing and Chassis Dynamometer Reproduction

2026-01-0431To be published on 04/07/2026

Electrification is rapidly entering all vehicle classes, including light- and heavy-duty trucks designed for heavy towing capabilities. Still, the quantitative impact of towing on battery-electric vehicle (BEV) energy use and range remains under-characterized. We conducted controlled towing tests with a Ford F-150 Lightning using two trailers of different sizes and varying payloads to isolate aerodynamic and mass effects across the vehicle’s rated towing capacity. The vehicle was instrumented at the CAN bus level to capture motor power, torque, speed, and other related internal signals. On-road testing consisted of repeated back-and-forth passes on level, straight road segments at set speeds focusing on highway operation, where aerodynamic drag is stronger and real-world towing use cases occur. From these data, we extracted road load equations and dynamometer coefficients for each trailer combination, then reproduced equivalent conditions on a four-wheel drive chassis dynamometer

Timermans Ladero, Inigo

Impact of User-Adjustable Vehicle-Dynamics Tuning on Vehicle Durability

2026-01-0194To be published on 04/07/2026

Software-defined vehicles offer customers a greater degree of customization on vehicle operation. One such feature is a user-adjustable tuning of vehicle ride and handling, where customers can vary the ride height, the active damper stiffness (affecting ride comfort), front-rear torque balance (affecting ride handling), and other vehicle dynamics features. While promising a great customer experience, such a feature can expose the vehicle to a wider range of structural loads than before, particularly when such tuning is extended to cover spirited “sport” mode driving, offroad driving, etc. In this paper we present a novel methodology combining Road Load Data Acquisition (RLDA) data and real-world telemetry data to estimate the impact of user-adjustable vehicle-dynamics tuning on structural durability.  In doing so, the method combines the physics of damage accumulation (from RLDA data) with user behavior (from telemetry data) to present an accurate assessment of the impact on durability

Demiri, Albion, White, Dylan, Ramakrishnan, Sankaran, Borton, Zackery, Khapane, Prashant

Trajectory Prediction Model for Autonomous Vehicles in Highway Scenarios Based on Spatiotemporal Interaction Feature Extraction

2026-01-0027To be published on 04/07/2026

Accurately predicting the future trajectories of surrounding vehicles is one of the core tasks in autonomous driving, and its precision is directly related to the safety and reliability of decision-making, path planning, and control execution. However, challenges such as the complexity of traffic participants’ behaviors, the variability of interactions, and the highly dynamic nature of traffic environments make it difficult for existing methods to effectively model spatiotemporal dependencies and achieve accurate long-term prediction in dynamic scenarios, thus limiting their applicability in real-world settings. In this paper, we propose a Transformer-based trajectory prediction model with a spatiotemporal attention mechanism to extract and effectively model vehicle motion and spatial interactions. Specifically, the temporal attention module captures the motion patterns of the target vehicle across the time dimension, while the spatial attention module constructs vehicle interactions

Zhang, Lijun, Hu, Xingyu, Meng, Dejian, Zhu, Zhehui

Impact of Instantaneous Center of Rotation Variability on Path Planning and Performance of Park Assist Systems

2026-01-0053To be published on 04/07/2026

Parking assist systems are among the most widely adopted driver-assistance features in modern vehicles. A key component of these systems is the path planning module, which ensures accurate vehicle alignment within a parking slot while satisfying various constraints such as maintaining slot centering, avoiding collisions in confined spaces, minimizing maneuver count, and achieving the shortest feasible path. Multiple path generation techniques—such as geometric, polynomial-based, and search-based methods—have been developed to enable safe and efficient parking maneuvers. However, most of these approaches rely on the simplifying assumption that the vehicle’s instantaneous center of rotation (ICR) is fixed, typically located on the non-steering axle. In practice, the ICR is not constant and can vary significantly across vehicles due to several physical and kinematic factors, including steering geometry, tire slip characteristics, suspension configuration, and weight distribution

Awathe, Arpit, Patanwala, Abizer, Jain, Arihant, Varunjikar, Tejas

Design development and optimization of hybrid cross car beam for performance

2026-01-0513To be published on 04/07/2026

The cross-car beam (CCB) within the instrument panel (IP) is a multifunctional structural element that supports safety, vibration control and modular integration in automotive design. The reduction of mass without compromising structural integrity plays a vital role in this endeavor. This study presents the design and optimization of design intent model of magnesium beam to meet the performance requirements Vs study model of hybrid cross car beam using magnesium steering column bracket, steel and plastic material to achieve reduced mass and enhanced stiffness while meeting performance targets. Advanced Computer Aided Engineering (CAE) techniques were employed, including topology optimization, lattice optimization, bracket sensitivity studies as well as shape & gauge optimization. Performed benchmarking against industry models such as Tesla Model Y observed hybrid material with structural simplification. The final hybrid beam design demonstrated overall cost reduction, while satisfying

Didgur, Gulzarahmed, McAdams, Ian, Viswaraj, Obuliraj

A Helical Compression Spring Fracture under Impact Velocity in Pump Operation by Theoretical Study and FEA

2026-01-0271To be published on 04/07/2026

Helical compression springs have been used widely in various industries from automotive, aerospace and heavy-duty industries to electronics and medical devices. In the automotive industry, they appear in many places such as suspension, valvetrain, etc., especially in the discharge check valve of Gasoline Direct Injection (GDI) pump, which is the subject of study due to a recent fracture in lab testing. A theoretical study is conducted first to establish equation governing spring dynamic motion under impact velocity, which can be in high magnitude with surging shock wave along spring axis. A new spring shock wave equation is developed for spring axial motion coupled with coil torsional effect. This newly derived shock wave equation has a broad term than the classic spring formula found in engineering book. In the paper, it proves that the classic spring shock wave equation is only a special case for the new general wave equation discovered. Also, a formula on spring shock wave

Pang, Michael L., GUNTURU, SRINU, Norkin, Eugene

Study of Approaches for Enhanced Traction Control Response for Hybrid Powertrain Architectures

2026-01-0415To be published on 04/07/2026

Traction Control functionality requires fast and accurate response by powertrain system for wheel slip control. Close loop control effort of wheel slip shall be greatly reduced with more accurate feedforward torque. This paper explores the method of achieving requested traction control torque with better accuracy for torque converter-based hybrid electric powertrain architectures using improved dynamic modeling of torque converter. This method uses input inertia compensation involving feedforward and closed loop control modeling of torque converter and includes conversion of traction control intervention request through appropriate domains. Commanded torques by hybrid controller at wheel with and without these approaches are compared in Model in the loop simulation environment to identify optimum approach.

Karogal, Indrasen, Ober, Mitchell, Banuso, Abdulquadri, Sharma, Ashay

Methodology for generating off-road tracks for powertrain simulation of off-road passenger vehicles

2026-01-0275To be published on 04/07/2026

For off-road driving, particularly on steep grades and over barriers, the engine torque is a key design criterion of off-road vehicles. In conventional powertrains with combustion engines, mechanical all-wheel-drive systems combined with differential locks are used to distribute the torque demand between the front and the rear axle based on wheel-specific traction. With the growing market share of electric powertrains, off-road applications are becoming increasingly relevant for electric passenger cars. In comparison to conventional powertrains, electric all-wheel-drive configurations do not have a mechanical torque transfer between the two axles. If one axle experiences low traction, the second axle can rely on its own torque capability only. Transfer of unused torque of the slipping axle to the other one is not possible. The challenge, therefore, is to specify the right torque requirements for each axle for off-road driving while avoiding an over-dimensioning and high powertrain

Martin, Michael, Winkelheide, Jonas, Hartmann, Lukas, Sturm, Axel, Henze, Roman

Research on Vehicle and Longitudinal Tire Model Parameters Identification Based on Electro-Mechanical Brake System

2026-01-0634To be published on 04/07/2026

The Electro-Mechanical Brake (EMB) system is a novel type of brake by wire systems with independently controllable characteristics. This system aids in the decoupling analysis of the vehicle and actuator dynamics, thereby improving the accuracy of parameter identification. Therefore, this paper proposes an innovative parameter identification method for vehicle parameters and longitudinal tire model parameters, based on the characteristics of the EMB system and onboard sensors. First, based on the wind resistance and rolling resistance coefficients obtained from the vehicle coasting conditions, a decoupled constant clamping force sequence braking condition for the front and rear axles is designed by integrating the characteristics of the EMB actuator and vehicle dynamics. This approach enables the identification of vehicle and nonlinear longitudinal tire model parameters, significantly improving the accuracy of parameter identification. Next, considering the nonlinear characteristics of

Huang, Jiayi, Cheng, Yulin, Zhuo, Guirong, Le, Qiao, Wei, Wei, Shu, Qiang

A Cooperative AFS/DYC Control for FWDIEV Based on Dissipative Energy Method

2026-01-0619To be published on 04/07/2026

To enhance the lateral stability of four-wheel-drive intelligent electric vehicles (FWDIEV) under extreme operating conditions, this paper proposes a cooperative control strategy integrating active front steering (AFS) and direct yaw moment control (DYC) based on dissipative energy method. A nonlinear three-degree-of-freedom vehicle model is established to analyze the evolution of the vehicle state phase trajectory. A quantitative lateral stability index is constructed using dissipative energy to accurately evaluate the vehicle's lateral dynamics. Utilizing dissipative energy and its gradient information, a time-varying stability boundary is defined under dynamic constraints, and adaptive weighting coordination between the AFS and DYC systems is designed to achieve coordinated control of front steering angle and additional yaw moment. A feedforward–model predictive control (FF-MPC) framework is developed, in which a feedforward module generates compensation based on driver intent to

Zhao, Kun, Zhao, Zhiguo, Wang, Yutao, Xia, Xue, Chen, Xi, Hu, Yingjia

Hybrid Prediction Model of Wheel-Traction Force on Soft Soil Based on High-Precision Contact Angle

2026-01-0594To be published on 04/07/2026

Traction force plays a critical role in the design of off-road vehicles and the evaluation of terrain trafficability. The accuracy of the traditional Bekker-Wong semi-empirical formula for predicting wheel traction force depends on the precision of parameters such as the entry contact angle, departure contact angle, and maximum stress angle. However, the calculation of these angles is often influenced by multiple empirical factors, which significantly reduces the accuracy of traction force prediction.To improve prediction accuracy, this study proposes a hybrid traction force prediction method that integrates Abaqus simulation with a semi-empirical model. First, a wheel-soil interaction simulation model was established in Abaqus using the FEM-SPH coupling method. Then, computer vision-based image feature extraction techniques were applied to process the simulation result contours, obtaining accurate values for the entry contact angle, departure contact angle, and maximum stress angle

Cao, Ruibin, Wang, Kaidi, Shen, Yanhua, Liu, Zuyang

An Adaptive Brake Force Allocation Strategy for Rear-Wheel Driven EVs

2026-01-0636To be published on 04/07/2026

Due to changed requirements compared to conventional propulsion concepts, electromobility demands new and innovative strategies for energy-efficient vehicle motion control. For example, the challenge in purely rear-wheel drive (RWD) electric vehicles (EVs) is to achieve a maximum of regenerative braking power in order to increase energy recovery and to ensure, that this does not impair the braking stability. Within this conflict between energy efficiency and braking dynamics, it is necessary to design an intelligent strategy to optimise recuperation. This paper presents such a strategy, which improves an existing approach formerly presented by the authors, but specifically optimises it to overcome weaknesses. The previous approach had two major limitations: First, the efficiency map of the in-wheel machines (IWMs) was not considered. Second, there was no possibility of switching flexibly between different brake force distributions to guarantee both, maximized recovery potential and

Mitsching, Thomas, Heydrich, Marius, Ivanov, Valentin

A Research on Driving Performance of Vehicle Body Control using vehicle height adjustment system

2026-01-0626To be published on 04/07/2026

Recently, premium cars include a device in the suspension that can adjust the ride height. The main function of this system is to help the vehicle pass through uneven roads by keeping the vehicle body high so that the lower part of the vehicle does not contact the road surface. In particular, the device of the air spring type improves riding comfort by adjusting the vehicle's wheel rate. The proposed system was designed to adjust the ride height by adjusting the position of the spring lower seat up and down. By modeling the machinery topology of the proposed system in detail using a dynamics tool, we would like to investigate the feasibility of implementing driving performance by controlling not only the height adjustment function but also the vehicle body Posture of the vehicle during driving.

Park, Jaeyong, Sang Hoon, Lee, Jong Min, Kim, Choi, Jang Han

Design, Fabrication, and Assessment of a User-Friendly Suspension System for a 2025 BAJA Vehicle

2026-01-0588To be published on 04/07/2026

A suspension system was designed, fabricated, and tested following a systems design approach by the Desert Hare Off-road Team from South Dakota State University (SDSU). Compared to previous suspensions, the new suspension system is more reparable and contains a minimal number of custom parts, while still maintaining sufficient strength to withstand dynamic loads experienced when operating the vehicle. Modifications were also made to fit the newly designed vehicle body frame. As an integral part of the team’s 2025 Baja vehicle, the redesigned suspension system contributed to the vehicle’s improved performance during the 2025 SAE (Society of Automotive Engineers) Baja Competition. This paper presents a detailed account of the design, development, and fabrication process of the suspension system. The final design was tested and evaluated via both computer simulations and physical tests, whose efficiency and reliability were finally demonstrated by the team’s improved ranking in the 2025

Liu, Yucheng, Anderson, Matthew, Larson, Cody, Rodgers, Joshua, Seberger, Aaron, Letcher, Todd

Backlash Evasion Strategy for Enhancing Vehicle Cornering Performance

2026-01-0640To be published on 04/07/2026

This study presents a torque distribution control strategy for EVs with e4WD powertrain to overcome the trade-off between ensuring vehicle acceleration and deceleration responsiveness and mitigating backlash shock in the driving system. The deterioration of the drivability which occurs from the intrinsic hardware characteristics of the drivetrain is prevented by designing a response-priority drive mode in which neither front or rear motor torque is allowed to change its sign. Instead, in such drive mode, the front motor torque is only allowed to perform regenerative braking while the rear motor torque is only allowed to produce positive acceleration torque. In order to avoid sacrificing the maximum acceleration by applying such strategy, the mode transition function is implemented as well. In addition, in order to prevent backlash impact due to drivetrain compliance, variable offset torque based on drivetrain compliance model is evaluated in real time and applied to each motor command

Oh, JIWON, Lee, Ho Wook

A Study of Federal Motor Vehicle Safety Standard 126 and 136 Test Procedures on a Class 5 Vehicle

2026-01-0616To be published on 04/07/2026

Federal Motor Vehicle Safety Standards (FMVSS) 126 and 136 are standards imposed on four of the eight recognized road vehicle classes in The United States. These standards make it mandatory for Electronic Stability Control modules (ESC) to be mounted to Class 1,2,7, and 8 vehicles. These modules strategically activate the vehicle brakes via the Antilock Brake System (ABS) to limit the recorded yaw rate and lateral displacement of a vehicle during an extreme cornering maneuver such as a sudden swerve to avoid an obstacle on the road. The two aforementioned FMVSS mandates also specify three different driving maneuvers that are conducted to profile and analyze ESC module performance. There is now an interest in creating a new FMVSS that makes ESC modules mandatory for Class 5 vehicles. The purpose of this paper is to analyze how one specific Class 5 vehicle’s ESC module performed when subjected to the two test procedures that correspond to FMVSS 126 and 136. As will be seen, the vehicle’s

Cazares, Richard Isaac, Guenther, Dennis, Heydinger, Gary

Development of a model-based data-driven control algorithm for a Drive-By-Wire System for a Level 4 Automated Vehicle

2026-01-0043To be published on 04/07/2026

Precision control in Level 4 Automated Vehicles is essential for enhancing operational efficiency, accuracy, and safety, including improvements in time and fuel consumption. This research, conducted as part of ARPA-E’s NEXTCAR program, focuses on developing a robust control algorithm for a 2021 Honda Clarity Plug-In Hybrid Electric Vehicle (PHEV) to enable drive-by-wire functionality. A model-based control algorithm was created for a 2021 Honda Clarity Plug-In Hybrid Electric Vehicle (PHEV) to enable drive-by-wire functionality for longitudinal and lateral motion controls. This vehicle was equipped with a set of sensors and an onboard processing unit to enable Level 4 automation. An algorithm was designed to command steering torque to the electronic power steering module, ensuring the vehicle could attain the desired steering angle position at varying speeds. The system leveraged feedforward and feedback mechanisms to command steering torque to the electronic power steering module

Adsule, Kartik, Bhagdikar, Piyush, Drallmeier, Joseph, Alden, Joshua, Gankov, Stanislav

Modular 3-D Lumped Parameter Thermal Network for Thermal Estimation of Permanent Magnet Synchronous Motors in Electro-Mechanical Braking Systems

2026-01-0136To be published on 04/07/2026

With the development of electric intelligent vehicles, drive-by-wire systems are gradually popularized, the thermal reliability of electro-mechanical brake (EMB) motors, as the key actuators of drive-by-wire systems, is closely related to vehicle safety. However, the blocked-rotation operating condition of EMB motors typically involves applying unequal DC currents to the three-phase windings to achieve braking. This results in uneven winding heating, and conventional thermal models may fail to accurately represent the heat transfer dynamics arising from such tangential thermal imbalance, creating risks of motor local overheating. This paper is focused on thermal performance analysis of EMB motors under blocked-run conditions. First, a single-tooth lumped-parameter thermal network module (tooth module) incorporating external interfaces was developed. This module was adapted using experimental and simulation data, with its internal thermal parameters identified via a particle swarm

duan, yanlong, Xiong, Lu, Wang, Xinjian, Zhuo, Guirong, Zeng, Jie

RRT*_Heuristic_Adaptiv_maxR: A practical path planning method based on novel adaptive framework for autonomous mobile agent

2026-01-0038To be published on 04/07/2026

Aim at addressing the problem of random sampling and low efficiency of rapidly-exploring random tree (RRT) path planning algorithm, a practical path planning method is proposed for autonomous mobile agents, named RRT*_Heuristic_Adaptiv_maxR. This method is based on a new adaptive framework, balancing the search efficiency and convergence accuracy of path planning by dynamically adjusting the maximum radius parameters in the search process. Combining the heuristic search strategy, guiding the sampling direction, accelerating convergence to the target area, the obstacle detection mechanism is used to optimize the path in real time to avoid collisions. Experimental results show that the proposed method, RRT*_Heuristic_Adaptiv_maxR, has higher planning success rate and path quality in complex environments compared with various RRT algorithms, and it is verified the effectiveness of the adaptive framework and the maximum radius dynamic adjustment strategy in mobile agent path planning.

Dong, Xiaomei, Zeng, Dequan, Petitti, Antonio, You, Jingyi, xiong, min, GAO, Letian, Jiang, Xiaomeng, Yu, Yinquan, CARBONE, GIUSEPPE, Hu, Yiming, Nawaz, Aamir, Linh, Nguyen Vu

Multi-steering Mode and Path Following Control of Vehicle with Dual Modular Chassis

2026-01-0625To be published on 04/07/2026

The cooperative formation of four-wheel-steering and four-wheel-drive (4WS-4WD) modular chassis offers a flexible and scalable solution for oversized cargo transportation. To enable coordinated control between the dual chassis modules, a distributed model predictive control (DMPC) framework is introduced. This framework facilitates inter-module communication between the front and rear chassis controllers, thereby achieving consistent and cooperative behavior. Each chassis module is equipped with an independent model predictive control (MPC) path tracking controller, which is designed based on a single-module dynamic model. The MPC cost function jointly optimizes path tracking accuracy and roll stability. In terms of path planning, a hierarchical framework is proposed: the upper layer generates a global path, while the lower layer derives local reference trajectories for the front and rear modules based on their respective poses. Moreover, multiple steering modes are analyzed under

Liu, Zuyang, Shen, Yanhua, Wang, Kaidi, Lv, Xin

A Control Method for Dual Motor Redundant Steer System based on Zeroing Neural Networks

2026-01-0581To be published on 04/07/2026

In the process of driving a vehicle, the steering system directly determines the vehicle's travel path and direction, serving as the physical basis for precise control in autonomous driving. Whether it is lane keeping, turning, or obstacle avoidance, high responsiveness of the steering control is required to execute the commands of the decision-making system. This study focuses on the dual-motor steer-by-wire (SBW) system, addressing the tracking issues arising from factors such as dual-motor coupling. A control strategy for coordinated dual motor drive in an autonomous driving steering system based on dual-motor redundancy is proposed. A dynamic model of the steer-by-wire system is constructed, and the software algorithm employing a zeroing neural network for the dual-motor redundant steering is used to solve the synchronization issues of the dual-motor system, based on the concept of cross-coupled control. Finally, simulation analysis was performed on the MATLAB simulation platform

Yang, Lingang, xiong, min, Zeng, Dequan, Petitti, Antonio, Nawaz, Aamir, Linh, Nguyen Vu, Hu, Yiming, Yu, Yinquan, CARBONE, GIUSEPPE, GAO, LETIAN, Jiang, Xiaomeng

A Study of Tire Grip Performance Evolution Under Dry, Wet and Snow Roads with Tire Wear

2026-01-0589To be published on 04/07/2026

This study focuses on investigating how tire grip performance on dry, wet, and snowy road surfaces varies with the different level of tire wear. The new, 50% worn and the end-of-life tires are prepared following the worn tire preparation standards. Additionally, worn tires obtained by real driving conditions in the market are used. Tire grip performances on dry, wet and snowy roads are characterized respectively by using an indoor flat belt machine, an outdoor trailer, and a specially designed snow spin truck. The results demonstrate a grip performance evolution according to the tire wear. The different impact of worn tire preparation whether real driving or artificial is identified especially on snowy road surface. Furthermore, this study investigates the effects of tire reduced tread depth and tread surface roughness of worn tires on each type of road surface. The objective of this study is to enhance the understanding of tire behavior throughout its lifecycle to enable more

Kim, Changsu, Saito, Yoshinori

Research on electro-hydraulic compound braking coordinated control strategy based on sliding mode control

2026-01-0631To be published on 04/07/2026

Hydraulic braking torque and motor braking torque are the main sources of braking torque of new energy vehicles. Hydraulic braking converts vehicle kinetic energy into heat dissipation, and motor braking converts vehicle kinetic energy into electric energy to achieve energy recovery. In the process of vehicle braking, when the wheels tend to lock, it is easy to cause vehicle instability, which seriously threatens the safety of driving.Therefore, how to coordinated the braking torque of the two braking systems to ensure the vehicle braking safety and energy recovery efficiency is still an urgent problem to be solved. In this paper, the electric vehicle equipped with electro-hydraulic compound braking system is taken as the research object, and the electro-hydraulic compound braking coordinated control strategy considering the general braking state and emergency braking state is proposed. Firstly, a 3-DOF vehicle longitudinal dynamic model is established according to the vehicle dynamic

Zhao, Gaoming, Zhao, Bingquan, Zhao, Binggen, He, Chengkun, Zhang, Xiaoyang

Study on performance parameters of retarder in mountain condition of hybrid electric vehicle

2026-01-0617To be published on 04/07/2026

In mountain driving scenarios, the continuous braking demands of vehicles pose significant challenges to the performance and reliability of braking systems. Traditional fuel-powered vehicles primarily rely on friction brakes for deceleration, which face issues such as high thermal fade risks and severe brake wear. While pure electric vehicles can utilize motor energy recovery to provide braking force and recover energy, their braking capacity is limited by the maximum regenerative torque of the motor. Moreover, when the battery State of Charge (SOC) is high, the energy recovery function may be restricted or disabled to protect the battery, leading to a sharp reduction or complete loss of braking torque—a safety hazard. Range-extended hybrid vehicles combine the advantages of both engine and electric drive systems. During long downhill operations, their motors can also serve as priority decelerators for efficient energy recovery. However, similar to pure electric vehicles, their motor

duan, xianqi, Tan, Gangfeng, Li, LiuYuanHeng, Tian, Tian, Yang, Yong

Backward Fuzzy Driving Control for 6×4 Off-Road Vehicles

2026-01-0148To be published on 04/07/2026

Offroad autonomous vehicle systems must be able to operate across unstructured and variable terrain while avoiding obstacles. This presents significant challenges in vehicle and control system design, especially for less conventional platforms such as 6x4 vehicles. While forward driving autonomy has developed and matured in recent years, effective reverse navigation remains an under-explored area of vehicle co-design. Reversing 6x4 vehicles have limited rear steering authority, an extended wheelbase, and asymmetric traction, which introduce complex dynamics into any control system that is used. To address this need, a robust and experimentally validated fuzzy logic control architecture for 6x4 reverse navigation was developed during the course of this project. This architecture incorporates both near-field and long-range path data with adaptive outputs controlling steering and velocity based on a rule base that covers the whole vehicle state space. This method has low computational

Dekhterman, Sam, Patterson, Albert, Sreenivas PhD, Ramavarapu, Norris, William, Soylemezoglu PhD, Ahmet, Nottage PhD, Dustin

Multiple-Parameter Joint Estimation for Unmanned Mining Trucks Based on Real-Time Cornering Stiffness Identification

2026-01-0618To be published on 04/07/2026

High-precision estimation of key vehicle–road state parameters is essential for accurate and safe vehicle control, as well as for reliable trajectory tracking and path planning. However, the strong nonlinearity of tire forces makes real-time estimation of tire cornering stiffness challenging, and the uncertainty of this parameter significantly limits the performance of conventional estimation methods. To overcome this issue, this study proposes a novel joint estimation framework that integrates the Square-Root Cubature Kalman Filter (SCKF) with Moving Horizon Estimation (MHE). In the proposed approach, the SCKF provides high-accuracy estimation of the vehicle sideslip angle, while the MHE enables real-time identification and updating of tire cornering stiffness using vehicle state information over a short horizon. This establishes a closed-loop joint estimation mechanism between sideslip angle and cornering stiffness. Furthermore, the real-time updated cornering stiffness is

Xia, Xue, Shen, Peihong, Jiao, Leqi, Li, Tao, Chen, Huiyong, Zhao, Kun, Jiao, Leqi, Zhao, Zhiguo

Vehicle Test Platform with Experimentally Correlated Tire Model for Torque Vectoring Control

2026-01-0622To be published on 04/07/2026

This paper presents a testing platform for torque vectoring controls utilizing a 10 degree of freedom (DOF) vehicle simulation and a ⅕ scale radio control test vehicle. These vehicle simulations or “Digital Twins” have been widely adopted throughout the automotive industry for their lower operating costs and ease of implementation. Virtual models are not perfect representations of reality, however, and physical testing is still necessary to validate systems for use in the real world. This is especially true when testing safety-critical features such as Advanced Driver Assist Systems (ADAS). As a result, a simulation environment working in conjunction with a test vehicle represents an optimal hybrid approach. In this work, a 1/5 scale radio controlled vehicle with torque vectoring capability is designed and assembled. A high fidelity vehicle model is then constructed in the Matlab/Simulink environment to model test vehicle behavior. The test vehicle features independent suspension for

Petersen, Nicholas Conner, Robinette, Darrell

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