Browse Topic: Steering systems

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Monocular 3D Perception and Lane-Aware Bird’s-Eye-View Mapping for Autonomous Driving2026-01-0012To be published on 04/07/2026
Accurate perception of the surrounding environment is fundamental and essential to safe and reliable autonomous driving. This work presents an integrated vision-based framework that combines object detection, 3D spatial localization, and lane segmentation to construct a unified bird’s-eye-view (BEV) representation of the driving scene. The pipeline provides geometric information on object position and orientation by employing Omni3D to infer 3D bounding boxes of objects from monocular camera frames. Detections are subsequently projected onto a 2D BEV canvas, where object instances are represented with respect to the ground plane for enhanced interpretability. To complement the object-level perception, we utilized YOLOPv2 to perform lane segmentation, producing both lane masks and lane line masks in the image domain for future coordinate transformation. By adopting a pinhole camera model, the coordinate transformation of these masks from the perspective image plane into the BEV canvas
Tan, Lin, Wang, Hanchen, Li, Taozhe, Hajnorouzali, Yasaman, Burch, Collin, Lee, Victoria, Xu, Bin, Arjmanzdadeh, Ziba
Curvature-Based End-to-End Autonomous Vehicle Path Planning at Intersections2026-01-0045To be published on 04/07/2026
Autonomous vehicle navigation requires accurate prediction of driving path curvature to ensure smooth and safe trajectory planning. This paper presents an end-to-end approach to curvature prediction using deep neural networks trained on real-world driving data. We develop a comprehensive neural network architecture that directly maps high-dimensional sensor inputs to curvature predictions, eliminating the need for intermediate feature engineering steps. The model processes multi-modal inputs including vision features, vehicle state parameters, and environmental context through a deep learning pipeline. Our end-to-end approach demonstrates the feasibility of learning complex driving behaviors directly from raw sensor data, providing a more robust and generalization solution compared to traditional rule-based methods. The neural network architecture incorporates dropout regularization and adaptive learning rate scheduling to ensure stable training and optimal performance. Results show
Hajnorouzali, Yasaman, Wang, Hanchen, Li, Taozhe, Burch, Collin, Lee, Victoria, Tan, Lin, Arjmandzadeh, Ziba, Xu, Bin
Impact of Instantaneous Center of Rotation Variability on Path Planning and Performance of Park Assist Systems2026-01-0053To 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
Attention and Intrinsic Curiosity-Enhanced Deep Reinforcement Learning for Path Planning in Dynamic Environments2026-01-0044To 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
Autonomous Racing Control Using Reinforcement Learning with Racing Line Guidance2026-01-0031To 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
Navigation Integrated End-to-end Path Planning Development and Vehicle Testing2026-01-0032To 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
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
Multi-steering Mode and Path Following Control of Vehicle with Dual Modular Chassis2026-01-0625To 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
Multiple-Parameter Joint Estimation for Unmanned Mining Trucks Based on Real-Time Cornering Stiffness Identification2026-01-0618To 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
Design development and optimization of hybrid cross car beam for performance2026-01-0513To 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
Development of a model-based data-driven control algorithm for a Drive-By-Wire System for a Level 4 Automated Vehicle2026-01-0043To 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
Trajectory Prediction Model for Autonomous Vehicles in Highway Scenarios Based on Spatiotemporal Interaction Feature Extraction2026-01-0027To 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
A Control Method for Dual Motor Redundant Steer System based on Zeroing Neural Networks2026-01-0581To 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
RRT*_Heuristic_Adaptiv_maxR: A practical path planning method based on novel adaptive framework for autonomous mobile agent2026-01-0038To 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
Leveraging Machine Learning for Occupant Body Size Estimation via B-Pillar Seatbelt Systems2026-01-0559To 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
Development of Tilt Test Facility2026-01-0265To be published on 04/07/2026
Mobility, fire power and protection are the three most important characteristics of an Armoured Fighting Vehicle (AFV). Transmission system facilitates mobility to the fighting vehicle. Combat Vehicles Research and Development Establishment (CVRDE) is developing Automatic Transmission for Armoured Fighting vehicles which includes gearbox, steering system, braking system and control system. In the battle field, AFVs have to operate at different gradients & side slopes. The Automatic Transmission system being developed by CVRDE is a hydro-mechanical automatic transmission in which hydraulic oil is used for lubrication & control of various systems of it. A Tilt Test Facility (TTF) has been designed, developed, and installed at CVRDE to simulate different angles of gradients from +35° to - 35° & side slopes from +20° to -20°. The TTF enables to evaluate the functional aspects of the transmission system at different angles. The TTF consists of two tiltable platforms, Rotary actuators
V, Uma, Naik, Sheshu
OFEODM: An Onboard Fast and Efficient Object Detection and Distance Prediction Model2026-01-0017To 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
LiDAR-Driven A* Path Planning with Dynamic Obstacle Avoidance for Autonomous Navigation in ROS2026-01-0030To 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
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
Progressive optimization path planning method for intelligent mobile agent in unstructured environment2026-01-0253To be published on 04/07/2026
Due to the presence of cluttered obstacles and irregular road edges in most operation scenarios, this poses significant challenges for the autonomous mobile operation of intelligent agents. To address the challenges of such unstructured scenarios, this study proposes a progressive optimization path planning method for intelligent mobile agents. Firstly, to eliminate the blind search behavior of the traditional RRT algorithm, a dynamic target bias function is introduced to guide the RRT to search as close to the target point as possible, obtaining the initial planned path. Secondly, to improve the comprehensive performance of the path planning, an iterative artificial potential field optimization algorithm is developed to iteratively update the initial planned path to obtain a progressively optimized path. Finally, different scale scenarios are designed to verify the effectiveness of the proposed method. The result shows that the method proposed in this study can significantly improve
Zeng, Yongping, Zeng, Dequan
Intelligent Steering System to Improve Fuel Efficiency in Heavy Duty Vehicles2026-28-0103To be published on 02/12/2026
In commercial vehicles, conventional engine-driven hydraulic steering systems result in continuous energy consumption, contributing to parasitic losses and reduced overall powertrain efficiency. This study introduces an Electric Powered Hydraulic Steering (EPHS) system that decouples steering actuation from the engine and operates only on demand, thereby optimizing energy usage. Field trials conducted under loaded conditions demonstrated a 3–6% improvement in fuel economy, confirming the system’s effectiveness in real-world applications. A MATLAB-based simulation model was developed to replicate dynamic steering loads and vehicle operating conditions, with results closely aligning with field data, thereby validating the model’s predictive accuracy. The reduction in fuel consumption directly translates to lower CO₂ emissions, supporting regulatory compliance and sustainability goals, particularly in the context of tightening emission norms for commercial fleets. These findings position
T, Aravind Muthu Suthan, Mani, Kishore, Ayyappan, Rakshna, D, Senthil Kumar, S, Mathankumar
STEERING AUTOMATION FOR LANE KEEP ASSISTANCE2026-28-0117To be published on 02/12/2026
The design of advanced driver-assistance systems (ADAS) is essential to improve the safety and autonomy of vehicles in harsh conditions. This work introduces the design and development of a steering automation system for Lane Keep Assistance (LKA) in a vehicle with a parallel steering system. The system utilizes an ArduCam module to take real-time images of the ground in front, and these are processed via machine learning techniques on a Raspberry Pi in order to identify lane edges with great precision. The corrective steering maneuvers are carried out by a motorized steering actuator based on the visual data after processing, and an encoder that is built into the actuator constantly tracks the steering angle and position. This closed-loop feedback affords accurate, real-time corrections to ensure lane discipline without driver intervention. Extensive calculations for steering effort, torque, and gear design confirm the system's mechanical viability. Combining low-cost vision sensing
A R, Arundas, Sadique, Anwar, Rafeek, Aayisha
Improve Safety Balance between Women and Men in Frontal Crashes through Parametric Human Modeling and Adaptive Design Optimization2025-22-00101/23/2026
Objective: Previous studies have reported disparity in injuries between male and female drivers in the risk of certain types of injuries in frontal crashes that may be due to a myriad of sex-related differences, including body size, shape, anatomy, or sitting posture. The objectives of this study are 1) to use mesh-morphing methods to generate a diverse set of human body models (HBMs) representing a wide range of body sizes and shapes for both sexes, 2) conduct population-based frontal crash simulations, and 3) explore adaptive restraint design strategies that may lead to enhanced safety for the whole population while mitigating potential differences in injury risks between male and female drivers Method: A total of 200 HBMs with a wide range of body sizes and shapes were generated by morphing the THUMS v4.1 midsize male model into geometries predicted by the statistical human geometry models. Ten male and ten female HBMs were selected for population-based simulations. An existing
Sun, Wenbo, Hu, Jingwen, Lin, Yang-Shen, Boyle, Kyle, Reed, Matthew, Sun, Zhaonan, Hallman, Jason
Algorithm Development for AI Driven Path Planning Using Augmented Reality for Navigating in Indian Complex Road Scenarios2026-26-00381/16/2026
The road infrastructure in India has complex navigational challenges with most of the road unstructured especially in rural areas. Decision-making becomes a challenge for drivers in unpredictable environments such as narrow roads, flooded roads and heavy traffic. In this paper, an Augmented Reality based ML-Algorithm for Driver Assistance (ARMADA) has been proposed that improves awareness to safely maneuver in these conditions. The methodology for development and validation of this Augmented Reality (AR) based algorithm contains multiple steps. Firstly, extensive data collection is conducted using real time recording and benchmark datasets like Berkeley Deep Drive (BDD) and Indian Driving Dataset (IDD). Secondly, collected data are annotated and trained using an optimal machine learning (ML) model to accurately identify the complex scenario. In third step, an ARMADA algorithm is developed, integrating these models to estimate road widths, detect floods and provide seamless driver
Anandaraj, Prem Raj, Sivakumar, Vishnu, Thanikachalam, Ganesh, L, Radhakrishnan, Motoki, Yaginuma, Selvam, Dinesh Kumar
Refinement of Road Induced Steering Wheel Vibration in Electric Vehicle2026-26-03371/16/2026
Nowadays, customers expect excellent cabin insulation and superior ride comfort in electric vehicles. OEMs focus on fine tuning the suspension system in electric vehicle to isolate the road induced shocks which finally offers superior ride quality. This paper focuses on enhancing the ride comfort by reducing the road excitation which originates mainly due to road inputs. Higher steering wheel vibration is perceived on the test vehicle on rough road surfaces. To determine the predominant force transfer path, Multi reference Transfer Path Analysis (MTPA) is performed on the front and rear suspension. Based on the finding from MTPA, various recommendations are explored and the effect of each modification is discussed. Apart from this, Operational Deflection Shape (ODS) analysis is used to determine the deflection shape on the entire steering system . Based on ODS findings, recommendations like dynamic stiffness improvements on the steering column and steering wheel are explored and the
S, Nataraja Moorthy, Rao, Manchi, Selvam, Ebinezer, Raghavendran, Prasath
Digital Rack Load Estimation Methodology to Optimize Motor Sizing for Electric Power Steering2026-26-03831/16/2026
Rack load estimation during the pre-design stages is critical for the calibration of steering systems, particularly in achieving the desired steering feel and optimizing assistance strategies in Electric Power Assisted Steering (EPAS). Conventional approaches often depend on physical vehicle testing or simplified empirical equations, which may be time-consuming or lacks the fidelity required for early-stage analysis. This paper presents a 1D simulation strategy to address limitations from conventional approaches. The proposed rack force estimation model is based on multi-physics analytical equations that calculate tire-road friction forces and the resulting moments about the steering axis, delivering a physics-based yet computationally efficient solution. The rack force estimation model is further extended into EPAS system model by incorporating Direct Current (DC) brushed motor model. The rack force estimation model is validated against physical test data which demonstrates a high
Adsul, Sourabh, Iqbal, Shoaib
Path Planning and Control Strategies for a Semi-Autonomous Light Commercial Vehicle Navigating and Avoiding Static Obstacles in Urban Environments2026-26-01341/16/2026
This paper presents the design and implementation of a Semi-Autonomous Light Commercial Vehicle (LCV) capable of following a person while performing obstacle avoidance in urban and controlled environments. The LCV leverages its onboard 360-degree view camera, RTK-GNSS, Ultrasonic sensors, and algorithms to independently navigate the environment, avoiding obstacles and maintaining a safe distance from the person it is following. The path planning algorithm described here generates a secondary lateral path originating from the primary driving path to navigate around static obstacles. A Behavior Planner is utilized to decide when to generate the path and avoid obstacles. The primary objective is to ensure safe navigation in environments where static obstacles are prevalent. The LCV's path tracking is achieved using a combination of Pure Pursuit and Proportional-Integral (PI) controllers. The Pure Pursuit controller is utilized as lateral control to follow the generated path, ensuring
Ayyappan, Vimal Raj, Dhanopia, Rashmi, Ali, Ashpak, N, Ragesh, Sato, Hiromitsu
A Study on the Thermal Degradation of Chlorinated Polyethylene Rubber2026-26-02761/16/2026
Elastomeric materials are essential in advanced automotive engineering for mobility, isolation, damping, fluid transfer (cooling, steering, fuel, and brake), and sealing because of their unique physio mechanical properties. Elastomers are commonly used in both static and dynamic components, such as hoses, mounts, bushes, and tires. Engine emission standards and weight optimization have caused higher temperature exposure conditions for automotive components. The steering system uses special purpose elastomers like Chlorinated Polyethylene that can deteriorate under abnormal conditions during vehicle operation or manufacturing process due to the high temperature exposure. Therefore, it is crucial to understand the causes and consequences of thermal degradation of elastomers. Thermal degradation is a significant phenomenon that changes the physiochemical properties of elastomers, which results in a product not meeting functional requirements. This study investigates the thermal
Thiruppathi, Anandhi, Mishra, Nitish, Krishnamoorthy, Kunju
Novel Approach for Predicting Steering Rack Load Using Multi-Body Simulation2026-26-03781/16/2026
In the initial stages of a vehicle development program, the sizing of various components is a critical deliverable. The steering system, in particular, requires a precise estimation of the rack load for the appropriate sizing of the rack and assists units. Accurately predicting the load on the system during the early stages of development is challenging, especially in the absence of benchmark or legacy data. Commonly used processes for estimating parking steering effort often employ simplistic approaches that may fail to account for parameters such as tire size, vertical stiffness, and steering geometry, leading to reduced accuracy. This paper introduces an advanced methodology for predicting steering rack loads, which incorporates considerations such as contact patch size and pressure variation, as well as the tire jacking effect. The methodology involves mathematical modeling of the contact patch using mesh-grids, utilizing common inputs available in the early stages of vehicle
Shirke, Umesh, Dabholkar, Aniruddh, Bardia, Vivek, Srivastava, Harshit, Prasad, Tej Pratap
Systematic Study to Understand and Resolve Brake Pull in Commercial Vehicles Using Simulation and Proving Ground Tests2026-26-00831/16/2026
In traditional commercial vehicles with leaf spring suspension and Recirculating Ball Joint (RCBT) steering systems often experience undesirable pulling due to unsymmetrical steering mechanism during braking, especially when the suspension and steering hardpoints are not properly tuned. This work analyzes the mechanisms responsible for pulling tendencies, primarily addressing brake steer and bump steer, which occur due to misalignments in the suspension and steering geometries. Brake steer occurs when braking forces create an imbalance in torque, resulting in the vehicle deviating to one side. On the other hand, bump steer refers to the unwanted changes in the wheel alignment when the suspension undergoes travel, leading to instability or unintended steering input. These two phenomena, if not controlled, can result in undesirable vehicle handling, especially under heavy braking conditions. This work focuses on evaluating these mechanisms and suggests strategies for minimizing their
Pandhare, Vinay Ramakant, M, Anantha Padmnabhan, Nizampatnam, Balaramakrishna, Londhe, Abhijit, Doundkar, Vikas
Steering on-Center Feel and Yaw Response Enhancement through Optimization of System Level Characteristics2026-26-00821/16/2026
To export India based SUVs to European markets, change in steering position is required to suit vehicle driving condition. Ideally, RHD and LHD variants of the same vehicle should have similar levels of ride and handling performance parameters. However, due to various packaging constraints and regulations, there is a possibility of minor change in Hard-points of steering or suspension system which may lead to different behavior in terms of body roll and steering response. While cornering or double lane change maneuvers, difference in steering phase angles or steering stiffness or suspension hardpoints results in different roll behavior as well as understeer characteristics of the vehicle. The present study shows key parameters and optimization methodology to maintain same level of ride and handling performance in both RHD and LHD variants. Objective measurements and physical kinematics and compliance tests were carried out with various configurations of RHD and LHD variants to
Hussain, Inzamam Ul, Kamarthi, Ashwin, Rewale, Pratik, Nehal, S B, Rasal, Shraddhesh, Naidu, Kethireddi
Comprehensive Analysis and Mitigation Strategies to Minimize Torque Steer Phenomenon for FWD Vehicles during the Vehicle Development2026-26-00971/16/2026
Born Electric SUVs is gaining immense popularity due to enhanced ride and handling characteristics, advanced tech features elevating both performance and customer experience to an elite standard. Due to the platform constraints, the vehicle adopts a Front Wheel Drive (FWD) layout with a rear twist beam configuration, housing the electric motor at the front to deliver drive torque directly to the front wheels. Torque steer is a phenomenon often found in FWD cars, which is unsettling to driver where the steering wheel could be pulled hard to one side when there is aggressive throttle input potentially leading to deviation of the vehicle from its desired path. In contrast to internal combustion engines (ICEs), electric motors provide an instantaneous torque, something that can worsen torque steer if not well addressed. However, torque steer remains a key concern, with high torque output of electric motors especially for a front wheel drive vehicle. This paper introduces a methodology to
Prabhakara Rao, Vageesh, Wankhade, Krishna, Thakur, Pragyesh, Rasal, Shraddhesh, Asthana, Shivam
Curvature-Continuous Trajectory Refinement for Autonomous Vehicles Using a Pure Pursuit Based Path Smoothing Framework2026-26-01351/16/2026
Path planning is a key element of autonomous vehicle navigation, allowing vehicles to calculate feasible paths in challenging environments for applications like automated parking and low speed autonomous driving. Algorithms such as Hybrid A*, Reeds-Shepp, and Dubins paths are widely used and can generate collision-free paths but tend to create curvature discontinuities. These discontinuities result in sudden steering transitions, which create control instabilities, higher mechanical stress, and lower passenger comfort. To overcome these issues, this paper suggests a path-smoothing technique based on the pure-pursuit algorithm to produce smoothed curve paths appropriate for real-world driving. This method utilizes the practical approach of the original path, but removes sudden transitions that destabilize control. By ensuring smooth curvature, the vehicle undergoes fewer jerky steering actions, improved energy efficiency, less actuator wear, and improved high-speed tracking. This paper
S, Shriniyathi, A, Josana, Edwin J, Joel, T, Akshayaa, M, Senthil Vel, Kumar, Vimal
Unique Methodology to Cluster and Reuse the “Hazard Analysis and Risk Assessment” for Different Electrical/Electronic Systems of an Automobile2026-26-00041/16/2026
Modern automotive systems are becoming increasingly complex, comprising tightly integrated hardware and software components with varying safety implications. As the demand for ISO 26262 compliance grows, performing efficient and consistent Hazard Analysis and Risk Assessment (HARA) across these layers presents both methodological and practical challenges. Traditional approaches often involve performing HARA for an item (where item maybe a system or a combination of systems), which can lead to update of HARA for every new feature addition in an item, which in turn may lead to analysis of same functions in multiple HARAs leading to inconsistent risk categorization, redundancy, or even conflicting safety goals. Therefore, this paper proposes a unique HARA methodology which consolidates the list of functions from various systems and performs the HARA for the grouped functions (hereby referred to as Cluster HARAs). For example, Electrical power steering, Electric pump powered hydraulic
Somasundaram, Manickam, Vijayakumar, Melvin
Parametric Evaluation of Rolling Resistance in Bias & Radial Tyres and Influence of Key Operational Parameters under Varying Conditions2026-26-06061/16/2026
Tyre rolling resistance is a fundamental parameter in automotive engineering, directly impacting vehicle fuel efficiency and overall performance. The Rolling Resistance Coefficient (RRC) is influenced by tyre construction, material properties, and operational conditions such as inflation pressure, vehicle speed, ambient temperature, and road surface roughness. This study investigates the influence of critical parameters—including test speed, inflation pressure, temperature on the rolling resistance of tyres of various sizes. While previous research has predominantly focused on radial tyres, this paper extends the analysis to include bias-ply tyres. The findings aim to offer valuable insights for policymakers and researchers by examining the behavior of bias tyres under real-world conditions. The results will be particularly beneficial for vehicle and steering system designers, offering data-driven insights to support future tyre and vehicle development. Additionally, the study presents
Joshi, Amol, Belavadi Venkataramaiah, Shamsundara, Khairatkar, Vyankatesh
Advance Techniques to Optimize Variable Gear Ratio Steering for High Centre of Gravity Vehicles2026-26-00861/16/2026
Vehicles with a high center of gravity (CG) and moderate wheel track, like compact Sport Utility Vehicles (SUVs), have a relatively low Static Stability Factor (SSF) and thus are inherently less stable and more susceptible to rollover crashes. Moreover, to be more maneuverable in highly populated urban areas, a smaller Turning Circle Diameter (TCD) is necessary. Here, Variable Gear Ratio (VGR) steering systems have major benefits over traditional Constant Gear Ratio (CGR) systems in terms of enhancing both roll stability and agility. To adapt VGR steering systems to a particular vehicle dynamic, Full Vehicle (FV) and Driver-in-the-Loop (DIL) simulations are utilized. Using this method, exact calibration is possible according to realistic driving conditions so that the VGR steering C-factor curve is properly tuned for optimal handling in on-center, off-centre, and transitional areas of the Steering Wheel Angle (SWA). Primary performance measures—e.g., SWA gradients at different lateral
Rewale, Pratik, Kopiec, Jakub, Kumar, Deva, Rasal, Shraddhesh, Hussain, Inzamam, Nehal, S B
Methodology for Optimizing the Bench Testing of Steering I-Shaft Using Vehicle Level Data to Reduce Overall Product Development Time and Cost2026-26-05601/16/2026
Steering I-shaft with rubber coupling (or hardy disc) is an important part of complete steering system mainly in body on frame (BOF) vehicles. Hardy discs are used to dampen the vibrations that transmit to steering wheel through frame, steering gear and I-shaft. They also support to accommodate the variation between frame and BIW (Body in white) of body on frame vehicles. They are made up of rubber or other polymer composites, which have less torsional stiffness as compared to metals. The overall torsional stiffness of steering system reduces since the hardy disc is used in series in steering system, that impacts on the overall performance of steering system. So, during development of I shafts with different design, stiffness of hardy discs are used to optimize the steering and NVH performance of vehicle. Considering the development time and cost, each design of I-shaft cannot be validated at vehicle level. The torsional and axial force or displacement of hardy disc is measured at
Kabdal, Amit
A Scientific Approach to Identify the Source of Intermittent Steering Rattle Noise and Implementing the Design Solutions2026-26-03461/16/2026
Body-on-frame vehicles are well-regarded for their durability and off-road capabilities, but their structural design often makes them more vulnerable to noise, vibration, and harshness (NVH) issues. Vibrations originating from uneven roads are transmitted through the suspension and steering assemblies, sometimes resulting in rattles or other disturbances. These vibrations can be amplified by the inherent flexibility in the body-to-frame mounting system. In such vehicles, the steering system plays a critical role in driver comfort and is highly sensitive to vibrational inputs from the road surface, especially on coarse or uneven terrain. Occasionally, these inputs result in subtle rattle noises that are perceptible only to the driver and may not be detected under controlled testing environments. This poses a challenge for engineers trying to isolate and resolve such intermittent NVH phenomena. Identifying the source requires a combination of real-world driving evaluations, structural
Ramesh Chand, Karan Kumar, Gopinathan, Haridoss, Kabdal, Amit
Investigation of Fatigue Failure Mechanisms in High-Pressure Hydraulic Pipes of Power Steering Systems2026-26-05421/16/2026
The high-pressure steering hose in a hydraulic steering system carries pressurized hydraulic fluid from the power steering pump to the steering gear (or steering rack). Its main function is to transmit the force generated by the pump so that the hydraulic pressure assists the driver in turning the wheels more easily. The high-pressure hydraulic pipeline in the power steering system is a vital component for ensuring optimal performance. During warranty analysis, leakage incidents were observed at the customer end within the warranty period. The primary factors contributing to these failures include pipe material thickness, material composition, mechanical properties, and engine-induced vibrations. This study investigates fatigue-related failures through detailed material characterization and Computer-Aided Engineering (CAE) based on real world usage road load data collected. The objective is to identify the root causes by examining the influence of varying pipe thickness on fatigue life
Survade, Lalit, Koulage, Dasharath Baliram, Biswas, Kaushik
Indirect Road Departure Mitigation System for Passenger Vehicle2026-26-06691/16/2026
Road departures remain a major cause of fatal accidents in passenger vehicles, especially on highways, driving the demand for robust and affordable active safety technologies. Conventional Road Departure Mitigation Systems (RDMS) typically depend on camera- or LiDAR-based sensing, which can be cost-prohibitive and challenging to integrate across diverse vehicle platforms. The available RDMS technologies in the market focuses on road departure detection, and lacks the mitigation strategy. Although existing RDMS solutions have enhanced vehicle safety, their dependency on expensive, specialized sensors limits broader adoption, particularly in cost-sensitive market segments. This study introduces a sensor-less, cost-effective RDMS technology which has two parts, detection and mitigation. The technology utilizes existing vehicle sensors accessed through vehicle CAN channels. A decision tree based logic algorithm processes key parameters such as vehicle speed, steering angle, yaw rate, and
Iqbal, Shoaib, Adsul, Sourabh
Low-Speed Steering Returnability Analysis and Improvements through Mathematical Modeling and CAE Simulation for SUV2026-26-05731/16/2026
In driving, steering serves as the input mechanism to control the vehicle's direction. The driver adjusts the steering input to guide the vehicle along the desired path. During manoeuvres such as parking or U-turns, the steering wheel is often turned fully from lock to lock and then released. It is expected that the steering wheel quickly returns to its original position. Steering returnability is defined as the ratio of the difference between the steering wheel position at lock to lock and the steering wheel angle after 3 seconds of release, to the steering wheel angle at the lock position, under steady-state cornering conditions at 10 km/h. Industry standards dictate that the steering system should achieve 75% returnability under these conditions within 3 seconds. Achieving proper steering returnability characteristics is a critical aspect of vehicle design. Vehicles equipped with Electric Power-Assisted Steering (EPS) systems can more easily meet returnability targets since the
Singh, Ram Krishnan, ahire, Manoj, JAIN, PRIYA, Vellandi, Vikraman, SUNDARAM, RAGHUPATHI, Paua, Ketan
Risk-Aware Navigation Framework for Autonomous and Human-Driven Vehicles: Integrating Crash Probability Data for Safer Mobility12-09-03-00191/9/2026
This article presents a system to incorporate crash risk into navigation routing algorithms, enabling safety-aware path optimization for autonomous and human-driven vehicles alike. Current navigation systems optimize travel time or distance, while our approach adds crash probability as a routing criterion, allowing users to balance efficiency with safety. We transform disparate data sources, including traffic counts, crash reports, and road network data, into standardized risk metrics. Because traffic volume data only exist for a small subset of road segments, we develop a solution to project average daily traffic estimates to an entire road inventory using machine learning, achieving sufficient coverage for practical implementation. The framework computes exposure-normalized crash rates weighted by severity and integrates these metrics into routing cost functions compatible with existing navigation algorithms. The key strength of our solution is its scalability. In addition to the
Skaug, Lars, Nojoumian, Mehrdad
Research and HIL Test of Rear Wheel Steering Control Strategy Based on Zero Sideslip Angle2025-01-732312/31/2025
This paper briefly introduces the vehicle characteristics of four-wheel steering. Based on the parameters of an electric SUV, a linear two-degree-of-freedom vehicle dynamics model is established, and the transfer function of the rear wheel steering angle is derived to keep the sideslip angle at the center of gravity(CoG) constant at zero and proportional to the front wheel steering angle under steady state. The active rear wheel steering control strategy based on zero sideslip angle is established by MATLAB/Simulink, and a co-simulation model is built with CarSim and the HIL test bench to simulate and analyze the proposed control strategy. Subsequently, through classic handling stability test conditions such as the snake test, steering angle step test, and double lane change test, the influence of active rear wheel steering on vehicle dynamic response indicators such as sideslip angle, lateral acceleration, and yaw rate is studied, and the control effect is compared with that of the
Xu, Xiangfei, Qu, Yuan, Liu, Jiabao
Coordinated Control of DYC/ABS for Cornering Braking Based on Driver Intention2025-01-734012/31/2025
This paper proposes a DYC/ABS coordinated control strategy for cornering and braking based on driver intention. A hierarchical control structure is established, where the upper-level controller uses a vehicle dynamics model to calculate the additional yaw moment required by the DYC controller to track the desired yaw rate and sideslip angle, as well as the driver’s intended braking intensity. Taking multiple constraints into account, a quadratic programming algorithm is employed to optimize the distribution of braking forces among the four wheels. The lower-level ABS controller is designed with multiple thresholds and corresponding control phases to precisely regulate the hydraulic pressure of individual wheel cylinders. In emergency braking scenarios where ABS intervention may conflict with the upper-layer braking force allocation, a rule-based, stepwise diagonal pressure reduction compensation strategy is proposed. This strategy fully considers the influence of longitudinal and
Zou, Yan, Ma, Yao, Kong, Yan, Pei, Xiaofei
Centralized Control of Distributed Drive Steer-by-Wire Chassis Considering Tire Force Zoning Constraints2025-01-732912/31/2025
Distributed drive steer-by-wire chassis has significant potential for enhancing vehicle dynamics performance, while also presenting great challenges to vehicle dynamics control. To address the coordination among multiple chassis subsystems and the coupled control allocation of longitudinal and lateral tire forces, this paper proposes a centralized control framework based on optimal yaw moment control. By analyzing the impact of longitudinal and lateral tire forces on vehicle yaw moments, a method for allocating longitudinal and lateral forces with maximum yaw moment as the objective is proposed. On this basis, a hierarchical control architecture is designed, including the driver control layer, motion control layer, tire force allocation layer, and actuator execution layer, to achieve centralized domain control of longitudinal and lateral dynamics in distributed drive steer-by-wire chassis. Finally, the proposed centralized controller is validated using offline simulation and real-time
Wu, Dongmei, Guo, Chunzhi, Liu, Changsheng, Xia, Xin, Li, Miao, Liu, Wei
Modeling on Self-Learning Driver Model under Extreme Driving Conditions2025-01-731512/31/2025
Ensuring the safe and stable operation of autonomous vehicles under extreme driving conditions requires the capability to approach the vehicle’s dynamic limits. Inspired by the adaptability and trial and error learning ability of expert human drivers, this study proposes a Self-Learning Driver Model (SLDM) that integrates trajectory planning and path tracking control. The framework consists of two core modules: In the trajectory planning stage, an iterative trajectory planning method based on vehicle dynamics constraints is employed to generate dynamically feasible limit trajectories while reducing sensitivity to initial conditions; In the control stage, a neural network enhanced nonlinear model predictive controller (NN-NMPC) is designed, which incorporates a self-learning mechanism to continuously update the internal vehicle model using trial-and-error data on top of mechanistic physical constraints, thereby improving predictive accuracy and path-tracking performance. By combining
Zhang, Xinjie, Xu, Long, Guo, Konghui, Zhuang, Ye, Hu, Tiegang, Mao, JingGang, Zeng, Qingqiang
Dual Steering Gear System Applied in Commercial Vehicles with Axle Forward and Axle Back Configuration2025-36-016812/18/2025
The hydraulic steering gear, in the ball & nut configuration, was introduced in series in 1985, commonly encompassing single circuits with only one hydraulic steering. In medium-sized commercial vehicles, the torque (force) required to turn the wheels through direct mechanical connection is approximately 400 Nm when the vehicle is stationary. By using hydraulic steering, the required torque is reduced to about 50 Nm. When the load of the front axle exceeds 6.7 tons, a dual steering gear system can be used, delivering 200% of the total force. Additionally, the dual steering gear system provides a better turning radius, eliminating the need for a steering assist cylinder, thus giving more space for the front wheels to turn. This article will describe the development of a dual gear for a dual steering gear for commercial vehicles. Schematic diagrams of a dual steering gear and how the system can deliver the required output torque for the steering process it will be shown. The system is
Masunaga, Natália Sayuri, Santos, Antídio, Silva, Everton, Pedroso, Hugo, Destro, Daniel, Moura, Márcio
A Research on Path Planning of Kelp Harvesting Vessel Based on Reciprocal Traversal2025-99-040712/10/2025
min
Wang, Jie, Yang, Yue, Chen, Xin, Cui, Jiaxing
Research on Trajectory Planning for Urban Traffic Inspection Using Three-Dimensional Flight of UAVs2025-99-045212/10/2025
Objective:Methods:Results:Conclusion:
Sun, Ke, Wan, Qian, Liu, Qianqian, Li, Qiuling
Research on Control Strategy for Heterogeneous Traffic at Signalized Intersections2025-99-045312/10/2025
In order to reduce conflicts between vehicles at intersections and improve safety, an optimization model of traffic sequence allocation is studied and established for the heterogeneous traffic scenario of connected autonomous vehicles and manual vehicles. With the minimum safe traffic time as constraint, the right of way is allocated to vehicles according to the microscopic traffic characteristics of heterogeneous traffic flow fleet movement and the phase of signal lights, and the optimal trajectory planning control of each vehicle and evaluation indicators are established. A jointly simulation running environment is built using VISSIM and MATLAB. The simulation results indicate that at the micro level, collaborative control slows down the waiting time for manually driven vehicles and improves the utilization of green light travel time. At the macro level, as the penetration rate of connected autonomous vehicles increases, the sum of squares of vehicle acceleration gradually decreases
Yuan, Shoutong, Li, Zhiqiang, Liu, Tianyu, Yu, Zhengyang
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