Browse Topic: Roads and highways

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A Study on Vehicle Cornering Stiffness Estimation Based on Recursive Least Squares Method2026-01-0630To be published on 04/07/2026
This paper investigates a vehicle cornering stiffness estimation method based on recursive least squares (RLS), aiming to enhance automotive active control capabilities. Conventional parameter identification schemes reliant on onboard sensors are constrained by sensing range and cost limitations. This study explores an estimation algorithm utilizing generic motion signals, derives the theoretical relationship between yaw rate response and yaw stiffness, and designs an RLS approach for online identification of relevant model parameters. In a simulation environment, applying an ideal steering angle excitation demonstrated that the RLS algorithm converges within approximately one second and successfully estimates the cornering stiffness with an error of less than 5% relative to the set true value. Results indicate that under known vehicle basic parameters and ideal input conditions, the proposed algorithm can effectively complete cornering stiffness estimation. This work establishes an
Lang, Tao, Tan, Gangfeng, duan, xianqi, Shen, Leiming, Liang, Shuang
An Updated Correlation Study between the Full Size Wind Tunnels of General Motors, Ford Motor Company, and FCA US LLC2026-01-0612To be published on 04/07/2026
As automotive aerodynamic testing facilities evolve to capture more real-world behavior, updating the correlation between old and new technologies is essential. Recently, the three-member consortium of the United States Council for Automotive Research (USCAR) - FCA US LLC, Ford Motor Company, and General Motors - transitioned from full-size static ground plane facilities to 5-belt moving ground plane wind tunnel facilities. The primary objective of this study was to update the correlation data sets to maintain consistent and robust data sharing among companies, which is the cornerstone of USCAR efforts. To achieve this, a set of updated correlation data sets were calculated to replace the original correlation study results from 2008. Additionally, the methodology for applying correlation equations was revised from using averaged wind tunnel data to employing direct wind tunnel-to-wind tunnel correlation equations. In a two-phase correlation effort conducted in 2022 and 2025, the three
Nastov, Alexander, Lounsberry, Todd, Madin, Trevor, Langmeyer, Gregory, Fadler, Gregory, Skinner, Shaun, Horton, Damien
Advanced Tire Looseness Identification through Algorithmic Gear Error Analysis and Probabilistic Assessment2026-01-0590To 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
Research on Attitude Control and Stability of Water-Wading Vehicles2026-01-0627To 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 Degradation2026-01-0582To 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
Bias and uncertainty in the time, position, and speed data of consumer-grade GPS devices2026-01-0544To 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.
Data-Driven Objective Road-Driving Classification For Durable Design Of Vehicles2026-01-0181To be published on 04/07/2026
Durability development in the automotive industry depends on a clear understanding of how road surfaces and driving characteristics affect structural road loads and fatigue. Traditionally, road surface classification has been subjective (e.g., city, highway, rural), and done through driving instrumented vehicles over a small selection of roads. The variations in driving characteristics that are often consequent to the road surface quality is rarely accounted for in designing vehicle level durability tests. This makes it difficult to establish targets for the durability testing that accurately match the wide variations in real-world roads and driving across the market of vehicles. This paper presents a data-driven approach to objectively classify road surface and driving characteristics using metrics derived from existing vehicle and road response metrics like Vibration Dose Value (VDV), International Roughness Index (IRI) and statistical estimates of vehicle speed and acceleration
Shaurya, Shubham, Ramakrishnan, Sankaran, Demiri, Albion, Khapane, Prashant
Introduction to Catesby Aero Research Facility, CARF, the coast-down tunnel proving ground.2026-01-0611To be published on 04/07/2026
This paper reports on the Catesby Aero Research Facility (CARF), which began commercial use in 2019, and provides an overview of the facility and related technologies, particularly details on the vehicle-mounted component force measurement devices. CARF is a proving ground that was renovated from a former railway tunnel approximately 2.74km long and is now covered with high-quality tarmac. The road surface quality was designed to be at least as good as that of SUBARU's proving ground, and the standards were achieved using British construction technology. The course is almost straight, but there is a slight incline. The course specifications are: blockage 40m2, road width 6m (maximum 8.4m), flatness σ<0.5mm, and gradient 0.57%.In particular, compared to outdoor coastdown trucks, its overall length allows for continuous measurement right up to the stop, giving it a significant advantage in repeatability.At the same time, Subaru's newly developed six-component force sensor built into the
Shimoyama, Hiroshi
Planning Charging Infrastructure for Electric Freight Corridors2026-01-0469To be published on 04/07/2026
With the rapid development of electric vehicles, electric freight transportation is gradually increasing. However, the construction of charging infrastructure on expressways has lagged far behind, becoming a key bottleneck in the development of new energy freight transportation. This paper proposes an optimization system for the layout of charging stations in the rest areas of the Beijing–Hong Kong–Macao Expressway, based on freight logistics information. The system combines the Flow Capturing Location-Allocation Model (FCLM) with an improved genetic algorithm to dynamically analyze traffic flow, service area distribution, and charging demand, thereby achieving an optimized layout of charging stations. By simulating traffic flow variations under different scenarios, the study analyzes the spatiotemporal distribution of charging demand and optimizes the selection of charging station sites and charger allocation. Experimental results demonstrate that the proposed optimization method
Guo, Haifeng, Zhang, Jingzhong, Lian, Jintao
A Cooperative AFS/DYC Control for FWDIEV Based on Dissipative Energy Method2026-01-0619To 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
Evaluating the Impact of Drag Coefficient Changes on Driving Energy Using a Probability Distribution Model of Yaw Angle Based on Empirical Data from North American Highways2026-01-0615To be published on 04/07/2026
This study estimates the impact on driving energy of differences in aerodynamic characteristics for yaw angle from natural wind during North American Highway mode driving. A previous study[1] clarified the potential to estimate the fuel consumption impact of natural wind by integrating the CD yaw characteristics and yaw angle occurrence frequency. The natural wind was measured on a vehicle while driving a representative North American Highway test course[2]. The driving energy is predicted from the obtained yaw frequency and CD yaw sweep data in a wind tunnel. Measurements were conducted every weekday for 8 hours in 2023, covering 70% of the traffic volume. The validity of the measurement period was evaluated by the deviation from the annual average of wind direction and speed. Since yaw frequency varies depending on the road environment, it is necessary to weight the road environment type frequency when calculating the driving energy. The frequency was calculated using machine
Onishi, Yasuyuki, Nucera, Fortunato, Nichols, Larry, Metka, Matt
A Comparison of Road Grade Preview Signals from Lidar and Maps2026-01-0026To be published on 04/07/2026
Road grade can impact the energy efficiency, safety, and comfort associated with automated vehicle control systems. Currently, control systems that attempt to compensate for road grade are designed with one of two assumptions. Either the grade is only known once the vehicle is driving over the road segment through proprioception, or complete knowledge of the oncoming road grade is known from a pre-made map. Both assumptions limit the performance of a control system, as not having a preview signal prevents proactive grade compensation, whereas relying only on map data potentially subjects the control system to missing or outdated information. These limits can be avoided by measuring the oncoming grade in real-time using on-board lidar sensors. In this work, we use point returns accumulated during travel to estimate the grade at each waypoint along a path. The estimated grade is defined as the difference in height between the front and rear wheelbase at a given waypoint. Kalman filtering
Schexnaydre, Logan, Poovalappil, Aman, Robinette, Darrell, Bos, Jeremy
Optimization of Road Reference Profiles based on Highway Design for Connected and Automated Vehicles2026-01-0096To be published on 04/07/2026
Advances in Connected and Automated Vehicles (CAVs) have developed a level in which high-definition maps can be used to improve road safety. Data compactness and robustness on road characterization is essential for the proper handling of vehicles under curves. In this paper, an optimization scheme that relates highway-design road curvature and optimal speed of travel is defined to safely navigate through a given road. The scheme is divided in two main steps. First a nonlinear optimization problem, in which curvature profiles are fitted from a model that based on street design standards as per the American Association of State Highway and Transportation Officials (AASHTO). Secondly, the optimized curvature profile is subject to a secondary optimization problem that uses vehicle dynamics for both constraints and objective function derivation. Guidance reference parameters such as curvature and velocity, at different levels of friction are analyzed. Results show that, even in sparse
Jacome, Ricardo Osmar, Stolle, Cody, Grispos, George
Look-ahead Information based Predictive Cruise Controller for Energy Efficient Powertrain Operation of Heavy-Duty Electric Trucks2026-01-0039To be published on 04/07/2026
Heavy-duty electric trucks represent a growing innovation in the transport and logistics sector, aiming to reduce emissions and reliance on fossil fuels. A major challenge with battery electric trucks is the long recharging time which takes significantly longer than refueling conventional diesel trucks. This limitation highlights the importance of optimizing powertrain operations to reduce energy losses and maximize efficiency. One effective approach is implementing optimal speed control through a predictive cruise controller. By anticipating road conditions, traffic, and elevation changes, the predictive cruise controller can adjust the truck’s speed in real time to minimize energy consumption, enhancing the range and reducing the need for frequent charging. Many problem formulations for electric trucks focus primarily on minimizing the energy required at the wheels, often overlooking the impact of powertrain efficiencies. This simplification neglects critical factors such as the
Safder, Ahmad Hussain, Villani, Manfredi, Khuntia, Satvik, Nelson, James, Meijer, Maarten, Ahmed, Qadeer
Real-time Parameter Optimization for Eco-driving Control in Connected and Automated Vehicles Using Reinforcement Learning2026-01-0041To be published on 04/07/2026
This paper introduces a novel methodology to enhance the energy efficiency of eco-driving controllers in Connected and Automated Vehicles (CAVs) by leveraging Reinforcement Learning (RL) techniques for real-time parameter optimization. Traditional eco-driving strategies rely on fixed control parameters, which limit adaptability across diverse traffic and road conditions. To address this, we apply continuous action space RL algorithms, specifically Deep Deterministic Policy Gradient (DDPG) and Proximal Policy Optimization (PPO), to dynamically tune four key parameters within a model predictive control framework that is grounded in Pontryagin’s Maximum Principle (PMP). These parameters influence acceleration, braking, cruising, and intersection-approach behaviors, making them critical for achieving optimal eco-driving performance. Our study employs Argonne National Laboratory’s RoadRunner simulator, a Simulink-based environment designed for high-fidelity CAV analysis, incorporating
Zhang, Yaozhong, Ammourah, Rami, Han, Jihun, Moawad, Ayman, Shen, Daliang, Karbowski, Dominik
Optimal Control Analysis of Minimum-Time Maneuvers for Vehicles Recovering from Instability2026-01-0218To be published on 04/07/2026
Vehicles may enter highly unstable dynamic states due to lateral collisions, sudden loss of grip, or extreme steering disturbances. When such instability arises in congested road sections where obstacle avoidance is required, the safety risk to both the ego vehicle and surrounding traffic escalates significantly. In such scenarios, the vehicle must not only regain stability but also navigate the roadway in the shortest feasible time to prevent secondary collisions. This paper investigates the minimum-time maneuver of a vehicle starting from an unstable dynamic condition and constrained to travel within prescribed road boundaries. A single-track vehicle model with combined-slip nonlinear tire model is employed to capture the vehicle dynamics under high slip conditions. Phase-plane analysis is conducted to reveal how control inputs reshape the system’s vector field and influence the possibility and speed of stability recovery. An optimal control problem is formulated to compute the
Leng, Jiatong, Yu, Liangyao, Wang, Yongxin, You, Weijie, Li, Ziang, Jin, Zhipeng
Investigation and Reduction of Road Noise due to Transient Road Inputs in Electric Vehicle2026-26-03581/16/2026
Higher road noise is perceived in the cabin when the test vehicle encounters road irregularities like bump or pothole in the public roads. The transfer of transient road inputs inside the body caused objectionable cabin noise. Measurements are conducted at different road surfaces to identify the patch where the objective data well correlated with the noise measured at the public road. Wavelet analysis is carried out to identify the frequency zones since the events are transient in nature. TPA is carried out in time domain to identify the nature of the noise and the dominant path through which the transient road forces are transferring inside the body. Based on the outcome of TPA, various countermeasures like reduction of dynamic stiffness of suspension bushes, TMDs on the path are proposed to reduce the structure borne noise. Criteria which need to be considered for reduction of cabin noise due to transient road inputs is also discussed.
S, Nataraja Moorthy, Rao, Manchi, Selvam, Ebinezer, Raghavendran, Prasath
Design Optimization of Jounce Bumper Support Ring Based on RWUP Loading2026-26-05141/16/2026
Designing and manufacturing a support ring (POM ring -Polyoxymethylene ring) for a MacPherson strut suspension system brings unique set of challenges due to the high-performance and durability demands for Indian road application. Support ring along with the jounce bumper used in the shock absorber is designed to absorb the strong shock coming from the road inputs when suspension travel reached to the maximum limit. thereby absorbing the impact energy and preventing it from transferring it to the body. A bump stopper for a suspension of a vehicle is made of poly urethane (PU) material and is surrounded by a support ring or POM ring made up of Polyoxymethylene material. The bump stopper deflects into bellow shape during the absorption of impact energy. In the present paper, the authors have demonstrated the key challenges experienced in successfully designing the support ring post initial failure experienced in the validation phase which was unprecedented. The authors detail the failure
Koritala, Ashok Kumar, Malekar, Amit, Kulkarni, Purushottam, S, Sivashankar, Mishra, Harshit, Ganesh, Mohan Selvakumar, Patnala, Avinash, J, Ramkumar, Nayak, Bhargav, M, Sudhan
Revolutionizing Urban Mobility in India: The Emergence of the 2-3 Wheel Combi Vehicle and the L2-5 Regulatory Framework2026-26-01871/16/2026
Growing population in Indian cities has led to packed roads. People need a quick option to commute for both personal trips and business needs. The 2-3 Wheel Combination Vehicle is a new, modular solution that switches between a two-wheeler (2W) and a three-wheeler (3W). Hero has designed SURGE S32 to be a sustainable and flexible transportation option. It is world’s first class changing vehicle. The idea is to use a single vehicle for zipping through city traffic, making deliveries, or earning an income. Manufactured to deal with the challenges of modern life, this dual-battery convertible vehicle can easily transform from a two-wheeler to a three-wheeler and vice versa within three minutes. The Surge S32 is a versatile vehicle that replaces the need for multiple specialised vehicles. By lowering the number of vehicles on the road, it decreases road congestion, reduces emissions, and improves livelihoods. It powers by electricity, ensuring sustainability in all aspects. The current
Ali Khan, Feroz, Gupta, Eshan
Real-Time Helmet Detection and Closed-Loop Enforcement System for Two Wheelers2026-26-06501/16/2026
Asian countries capture a significant share of global two-wheeler usage, with India consistently ranking among the top three countries. 2 wheelers are a significant portion of road traffic and contribute heavily to the national burden of road fatalities. Despite regulatory mandates, helmet non-compliance remains widespread due to limited enforcement reach and behavioural inertia. The current strategies for enforcement, such as traffic policing or external camera-based surveillance, are reactive, infrastructure-dependent, are ineffective at scale. To address these limitations, we propose system that will detect if the user is wearing the helmet. The system is designed and packaged to be integrated into the 2-wheeler directly and then execute functions in real-time for helmet noncompliance. The software algorithm is an AI-powered, vision-based system that leverages deep learning techniques for helmet detection. This model is enforced with a custombuilt dataset accommodating cultural and
Kandimalla, Om Mahalakshmi, Shah, Ravindra, Karle, Ujjwala
Multi-Band Frequency Approach to Correlate Proving Ground and Road Simulator for an Electric Two-Wheeler2026-26-05561/16/2026
Real-world usage subjects two-wheelers to complex and varying dynamic loads, necessitating early-stage durability validation to ensure robust product development. Conducting a full life-cycle durability testing on proving grounds is time-consuming, extremely difficult for the riders involved, and costly, which is why accelerated testing using rigs such as the road simulator system have become a preferred approach. The use of road simulators necessitates, accurately measured inputs and precise simulation to ensure proper actuation of the rig, thereby enabling realistic representation of road undulations. This paper covers two important aspects essential for achieving an accurate and clear representation of road simulation in a 4-DOF road simulator, encompassing both longitudinal and vertical simulations at the front and rear of the vehicle. The first aspect involves the development of an instrumentation strategy for the two-wheeler, with careful identification of directionally sensitive
Ganju, Shubham, V, Vijayamirtharaj, Prasad, Sathish, R S, Mahenthran
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
Integrating V2V and V2I Communication for Enhanced Traffic Safety and Efficiency in Connected Vehicular Networks2026-26-02711/16/2026
This paper is a new approach to improve road safety and traffic flow by combining vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. The Study is focused on a system that connects vehicles with each other and with traffic light to share real-time data about speed and position. This work is aimed to discuss the methodology adopted for developing a system which predicts and advises the optimal speed for vehicles approaching an intersection. Inspired by the Green Light Optimized Speed Advisory (GLOSA) , the proposed system is designed to help drivers approach traffic signals at speeds that minimize unnecessary stops, reduce delays, and improve traffic efficiency. This paper contains the approach taken, the decision-making algorithm, and the simulation framework built in MATLAB/Simulink to validate the concept under real traffic conditions. Simulation results are presented to demonstrate how the system generates speed recommendations based on vehicle parameters
Pinto, Colin Aubrey, Shah, Ravindra, Karle, Ujjwala
Optimizing Suspension Joint Reliability: Overcoming Bolt Loosening and Torque Variability in Automotive Production2026-26-04921/16/2026
In modern automotive manufacturing, ensuring the integrity of suspension joints under real-world driving conditions is a critical aspect of vehicle safety and performance. These joints endure substantial transverse loads and large vibrations due to irregular road surfaces, dynamic maneuvers, and varying environmental factors. As a result, bolt loosening becomes a significant concern, compromising joint integrity and overall vehicle reliability. This paper delves into the challenges associated with maintaining joint integrity, specifically focusing on pre-load determination, torque application, and production-related issues. The pre-load generated during torquing is the primary factor that ensures a suspension joint remains securely fastened under dynamic road conditions. This pre-load is derived using road load data acquisition (RLDA) inputs, which capture the forces acting on the joint during actual driving scenarios. RLDA inputs provide critical insights into the forces experienced
Kumar, Sabeesh, Vasant Kumar, Jesse Daniel, Mishra, Harshit, Senthil Raja, T, Nayak, Bhargav, M, Sudhan, Namani, Prasad, Vibhute, Shekhar
Decision-Fatigue Mitigation in Automotive HMI System2026-26-06521/16/2026
With the advent of digital displays in driver cabins in commercial vehicles, drivers are being offered many features that convey some useful or critical information to drivers or prompt the driver to act. Due to the availability of a vast number of features, drivers face decision fatigue in choosing the appropriate features. Many are unaware of all available functionalities displayed in the Human Machine Interface (HMI) System, leading to a bare minimum usage or complete neglect of helpful features. This not only affects driving efficiency but also increases cognitive load, especially in complex driving scenarios. To alleviate the fatigue faced by drivers and to reduce the induced lethargy to choose appropriate features, we propose an AI driven recommendation agent/system that helps the driver choose the features. Instead of manually choosing between multiple settings, the driver can simply activate the recommendation mode, allowing the system to optimize selections dynamically. The
K, Sunil, Dhoot, Disha
Enhanced Methodologies for Predicting Automotive Wheel Bearing Life and Damage Using RLDA2026-26-04821/16/2026
The durability of wheel bearings is assessed in terms of raceway life and flange life. Raceway life focuses on the performance and damage tolerance of rolling elements, while flange life evaluates the structural integrity of wheel flanges under operational stresses. Traditionally, durability predictions relied on conventional design methods and analytic formulas for raceway spalling, as well as static load assumptions for flange fatigue analysis. Recently, integrating design of experiments (DOE) with traditional approaches has enhanced these methods, enabling systematic evaluation of design variables and loading conditions. This paper introduces a methodology for analyzing raceway life and damage in automotive wheel bearings using RLDA (Road Load Data Acquisition) data. The process involves acquiring raw deterministic load data, filtering it to preserve high-peaked signals, and transforming the filtered data into block cycles derived from load time histories. Each block cycle contains
Narendra, Vishwanath, Mane, Yogiraj, Paua, Ketan, Singh, Ram Krishnan, Vellandi, Vikraman
Road Noise Improvement of a Passenger Vehicle through End-to-End CAE-Simulation Using Transfer Path Analysis (TPA) Approach2026-26-04311/16/2026
Refined NVH performance of a vehicle is a mark of premium quality. Achieving the desired NVH performance in different vehicle operating conditions is always a Herculean task and early stage “CAE design recommendations” play crucial role in overall vehicle design development. This becomes tougher when the program is very much cost, weight and timeline sensitive. This paper explores simulation approach for addressing a major noise issue for a vehicle running at a constant speed on a rough road. While working on any issue, the first and the most critical step is to identify the exact root cause of the issue. Hence, we propose a detailed full vehicle level “contribution analysis (CA) + transfer path analysis (TPA)” methodology (everything done through the simulation) and then go for the design recommendations to improve the performance. We used road excitation power spectral density (PSD) as the input at all the four wheels (spindle locations) calculated through MBD software. The first
Mahajani, Mihir, Nascimento, Fabio, Adinarayana Reddy, Kodidela, Matyal, Mahantesh, Tenagi, Irappa, Sardar, Chenna
Predictive Simulation Framework for Tyre Curb Impact Durability Assessment and Design Optimization2026-26-03961/16/2026
With increased deterioration of road conditions worldwide, automotive OEMs face significant challenges in ensuring the durability of structural components. The tyre being the primary point of contact with the road is expected to endure harshest of impacts while maintaining the other performance functions such as Ride & Handling, Rolling resistance, Braking. Thus, it is considered as the most challenging component in terms of design optimization for durability. The current development method relies on physical testing of initial samples, followed by iterative construction changes to meet durability requirements, often giving trade-off in Ride & Handling performance. To overcome these challenges, a frugal simulation-based methodology has been developed for predicting tyre curb impact durability before vehicle-level testing so that corrective action can be taken during the design stage.
Sundaramoorthy, Ragasruoban, Lenka, Visweswara
Comprehensive Research Study Examining Tyre Wear and its Indian Perspective2026-26-06041/16/2026
Automobile emissions refer to the gases and particles released into the atmosphere by vehicles during their operation. These emissions contribute to environmental pollution and have an impact on human physiology and environment. This paper assimilates findings from a comprehensive research study examining tyre wear and its Indian perspective. Tyre wear understood as a factor affecting road safety, environmental health, and economic sustainability. The study identifies factors affecting tyre wear and provides overview regarding tyre wear generation in India, encompassing road infrastructure, vehicle characteristics, driving patterns, and environmental factors. Moreover, it examines the adverse effects of these particles on human health, such as respiratory ailments and cardiovascular diseases, as well as their impact on ecosystems. This paper delves measures to measure tyre wear and safeguard both environmental and public health. It also covers the tyre wear measurement methodologies to
Joshi, Amol, Khairatkar, Vyankatesh, Belavadi Venkataramaiah, Shamsundara
Generative AI Based Methodology for Road Profile Mix Creation2026-26-06741/16/2026
The acquisition of road profile data is crucial for various automotive testing applications, including vehicle dynamics analysis, chassis endurance tests, and simulation of vehicle-road interactions. This is necessary for conducting virtual tests to accelerate research and development processes and can significantly reduce testing costs. However, most of the on-road measurements lack comprehensive and relevant road profile data. Conducting on-road trials to acquire this data is a laborious and time-consuming process, often impeded by logistical and environmental challenges. This research proposes a generative AI-based methodology for creating diverse and realistic road profile mixes from the existing on-road dataset of front axle displacement and road profile measured with a laser sensor. By leveraging advanced machine learning techniques, the proposed approach seeks to generate synthetic road profiles that accurately reflect real-world conditions, thereby reducing the dependency on
Rajappan, Dinesh Kumar, Venkatesh, Anirudh Anand, R, Suresh, N, Gopi Kannan
Modelling and Simulation of Key Vehicle Dynamics Parameters for a Conceptual Race Car2026-26-00851/16/2026
Vehicle dynamics is a vital area of automotive engineering that focuses on analyzing how a vehicle responds to driver inputs and external factors like road conditions and environmental influences. Achieving optimal performance, safety, and ride comfort requires a detailed understanding of longitudinal, lateral, and vertical dynamic behavior. The objective of this paper is to develop and validate the model of a concept Race car and evaluate its vehicle dynamics behavior using IPG CarMaker, a high-fidelity virtual testing environment widely used in industry. The model incorporates a range of vehicle parameters, including suspension parameters like spring and damper characteristics, mass distribution, tire properties and powertrain parameters. The performance evaluation is done as per standard guidelines, including Constant Radius turn test, Sine Steer test and other standard tests like Acceleration, Braking along with Ride and Comfort classification. The key parameters that are
Agrewale, Mohammad Rafiq B., Vaish, Ujjwal
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
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
Machine Learning Approach to ISO Road Class Prediction Using Multiple Linear Regression2026-26-06671/16/2026
The inertial profiler methodology is traditionally employed in RLDA (Road Load Data Acquisition) to measure road profiles and classify test routes into ISO road classes. However, this approach demands significant time and effort during instrumentation. Also, during data acquisition, laser height sensor data is affected especially during adverse conditions such as rainy seasons or on surfaces with improper reflectivity. Additionally, substantial resources are required for data processing to convert raw measurements into road classifications. To address these challenges, an initial attempt was made to establish a relationship between axle acceleration responses and road profiles, enabling axle acceleration measurements during RLDA to predict ISO road classes. However, this approach relied on a simple linear model that considered only axle acceleration responses, rendering the predictions susceptible to inaccuracies due to varying parameters such as vehicle speed. To overcome these
P, Praveen Kumar, P, Dayalan, Sriramulu, Yoganandam
Regenerative Braking Control Strategy for Electric Commercial Bus under Indian Road Condition Using Artificial Neural Network2026-26-06451/16/2026
The main focus of this paper is to create a more efficient regenerative braking control strategy for electric commercial buses operating under Indian road conditions. The strategy uses Artificial Neural Networks (ANNs) to optimize regenerative braking process. Regenerative braking helps to recover energy that would otherwise be lost during braking and convert it back into usable power for the vehicle. The challenge is to design a system that works effectively on the diverse and often challenging road conditions found in India, such as varying gradients, traffic patterns, and road surface types. This study begins by collecting data (which includes vehicle speed, traffic condition, etc.) from real-world driving conditions and aims to train an Artificial Neural Network (ANN) using a large set of driving data which is collected under various conditions to predict the most efficient regenerative braking settings for different driving scenarios. This research brings a new approach to the
Saurabh, Saurabh, Bhardwaj, Rohit, Patil, Nikhil, Gadve, Dhananjay, Amancharla, Naga Chaithanya
Hierarchical Switching CBFs: A Safety Framework for Complex Lane-Changing Scenarios2025-01-733712/31/2025
Ensuring the safety and efficiency of autonomous vehicles in increasingly complex, dynamic, and structured road environments remains a key challenge. While traditional optimization-based approaches can provide safety guarantees, they often struggle to meet real-time requirements due to high computational complexity. Concurrently, although Control Barrier Functions (CBFs) can ensure instantaneous safety with minimal intervention, their inherent locality makes it difficult to consider global task objectives, potentially leading to mission failure in complex scenarios like lane-change obstacle avoidance. To address this trade-off between safety and mission completion, this paper proposes a hierarchical switching CBF safety framework. The core of this framework is to decompose complex lane-change tasks into multiple logical phases and to activate specialized, pre-designed CBF constraint sets via a top-level logic controller. Finally, we demonstrate the feasibility and safety of the
Liu, Bin, Xiao, Zhongkun, Luo, Xiao, Xu, Qing, Wang, Jianqiang, Wang, Guangwei
GP-LGFusion: Deep Fusion of Infrared-Visible Driving Images Based on Gradient Preservation and Local Guidance2025-01-730512/31/2025
Infrared and visible driving image fusion represents a pivotal technology in multi-source perception for automated driving. The objective of this technology is to generate fused images that exhibit significant targets and comprehensive road information in complex traffic scenes. However, the existing image fusion algorithms demonstrate inconsistent capacity to complement information in diverse environments. Additionally, there are limitations in their ability to extract features, such as the detailed texture of traffic targets under complex lighting conditions, including low-light scenes and multi-exposure scenes. To overcome these limitations, we propose a novel gradient-preserving and locally guided fusion method (GP-LGFusion). Our primary contribution is a Multi-scale Gradient Residual Block (MGRRB), an encoder module specifically designed to capture and retain both strong and weak texture features across different scales, a capability lacking in conventional approaches. Second, we
Meng, Zhangjie, Shi, Yicui, Chen, Yuhan, Zhou, Xiaoji, Li, Jie, Li, Guofa
Real-Time Multidimensional Vehicle Dynamic Stability Domain Calculation and Its Application in Intelligent Vehicles2025-01-732412/31/2025
Vehicle stability is fundamental to the safe operation of intelligent vehicles, and real-time, high-accuracy calculation of the stability domain is crucial for maintaining control across the full range of driving conditions. Because the real stability domain is difficult to parameterize accurately and is shaped by multiple driving factors including vehicle-dynamics parameters and environmental conditions, existing approaches fail to capture the multidimensional couplings between time-varying driving inputs and the resulting stability boundaries. Moreover, these methods remain overly conservative owing to algorithmic limitations and cautious design assumptions, thereby restricting dynamic performance in complex scenarios. To address these limitations, this paper introduces a multidimensional vehicle dynamic stability region calculation framework under time-varying driving conditions and apply it into path tracking controller of intelligent vehicle. Sum-of-squares programming (SOSP) is
Wang, Chengye, Zhang, Yu, Hu, Xuepeng, Qin, Haipeng, Wang, Guoli, Qin, Yechen
Analysis of the Structural Alignment during the System Conversion of Continuous Beam Bridges with High Piers, Long Spans and Wide Box Girders2025-99-022412/23/2025
With the rapid development of the worldwide highway transportation industry, continuous box girder bridges have many advantages, such as superior spanning capacity, reasonable force-bearing performance, and low cost, which give them significant strengths in bridge design. However, to ensure that the structural alignment of the girder meets the design and specification requirements, it is necessary to study the laws of alignment changes of cantilever structures during the construction process. This is to reasonably control the alignment of the main girder structure during construction and ensure that the alignment of the completed bridge is consistent with the design alignment. This paper takes a continuous rigid frame bridge on a certain expressway as the engineering basis. Its superstructure is a three-span prestressed concrete continuous box girder with a span of (88 + 160 + 88) m, a bridge width of 16.5 m, and a maximum pier height of 130 m. The paper analyzes the influence of each
Liu, Xingshun, Ma, Kun, Zhao, Qiang
Research Progress on Pavement Performance Prediction Models: A Review2025-99-024912/23/2025
Road maintenance plays a vital role in maintaining road conditions and ensuring safety, especially in a country with an extensive road network like China. To accurately predict pavement performance, optimize maintenance strategy, reduce cost and improve road efficiency, the paper systematically combed and evaluated the prediction model of pavement performance. Firstly, the importance of pavement maintenance and the background of pavement maintenance performance prediction model are described, and explicit models (mechanical-empirical model, stochastic process, time series analysis) and machine learning models (regression analysis, support vector machine, integrated learning, artificial neural network, deep learning) are introduced respectively. The basic principle, representative study, advantages and disadvantages of each model are introduced in detail. Comparative analysis shows that the traditional explicit model is simple and effective, easy to explain, but difficult to deal with
Ma, Muyun, Dong, Qiao, Lin, Yelong
Research on Early Warning Standard for Deformation of Surrounding Rock in Nearby New Four-Lane Tunnels2025-99-020812/23/2025
Focusing on the deformation warning criteria for a new four-lane tunnel affected by an existing tunnel, this study employs numerical simulation to analyze the ultimate strain of the equivalent rock mass. The results reveal the ultimate shear strain and ultimate tensile strain of Class V surrounding rock, offering critical insights for deformation control and early warning systems. Relying on the Maaoling Tunnel Project, the tunnel planar analysis model is established based on the finite difference FLAC3D software to analyze the deformation and strain distribution pattern of the surrounding rock of the new tunnel under different distances and reduction factors between the new and the existing tunnel. Finally, the tunnel crown settlement as an indicator, the establishment of the Maaoling Tunnel V surrounding rock conditions of different distances construction safety warning standard for the construction of large-span tunnels and early warning provides the basis for the relevant
Zhang, Yufan, Tian, Wei, Liu, Dongxing, Kang, Xiaoyue, Chen, Liming, Zheng, Xiaoqing
Analysis of Dynamic Characteristics of Half-Through Arch Bridge under Vehicle-Bridge Coupling2025-99-022312/23/2025
The half-through arch bridge, known for its efficient structural design and seamless integration with the surrounding environment, is widely utilized in urban transportation infrastructure. However, during operation, the hangers of the through and half-through arch bridge are exposed to various factors, including environmental conditions and cyclic traffic loads, which often cause the hanger of these bridges to rust and fracture, will lead to structural damage or even the collapse of the entire bridge. Therefore, investigating the dynamic performance of half-through arch bridges, both before and after hanger damage, under vehicle-bridge coupling is of paramount importance for understanding the overall performance of the bridge. In this study, a half-through arch bridge was selected as the subject of investigation. A three-dimensional finite element model of the bridge was developed based on real-world engineering projects, and a numerical simulation of the vehicle-bridge coupling
Chen, Xiaobing, Ji, Wei
Predictive Analysis of Slip Distance of Highway Loess Slopes Based on Intense Rainfall Infiltration2025-99-024112/23/2025
Based on field investigations of loess slopes along highways in the Lüliang region, a numerical infiltration model of highway loess slopes was established using the ABAQUS finite element software. The study examined the time to plastic zone coalescence and variations in infiltration range under two intense rainfall scenarios for slopes of different heights. Furthermore, a landslide numerical model of the loess slope was constructed using the FEM-SPH method, and a predictive formula for landslide runout distance of highway loess slopes was derived through data fitting.The results indicate that under the same slope height, increased rainfall intensity leads to a certain degree of reduction in landslide runout distance. Conversely, under the same rainfall condition, greater slope height significantly increases the runout distance. This study provides a theoretical foundation and methodological support for stability evaluation and runout distance prediction of loess slopes under intense
Liu, Manfeng, Li, Hong
Rapid Evaluation Method for Stability of Seismic-Damaged Loess Highway Slopes2025-99-023112/23/2025
In response to the inefficiency, slow speed, and reliance on specialized software in traditional methods for evaluating seismic stability of loess highway slopes, a simplified rapid assessment method is proposed. Based on post-earthquake landslide investigations, geotechnical surveys, and vibration table model tests, and integrates the latest research on seismic damage mechanisms of loess slopes, the potential sliding surface of seismic damage loess slope is divided into three segments: tensile fracture, shear, and anti-sliding zones, the potential sliding mass is partitioned into three blocks, and calculate the sliding force and anti-slip force of each potential sliding block from top to bottom, when the sliding force the upper sliding body is greater than its anti-sliding force, the excess sliding force is transmitted to the lower potential sliding body, and the stability of the slope is determined based on the ratio of the anti-sliding force and the sliding force of the lowest
Pu, Xiaowu, Zhang, Lizhi, Pu, Shuya, Che, Gaofeng
Study on Seismic Performance of a Prefabricated CFST Bridge Pier2025-99-020412/23/2025
This paper investigates the seismic performance of the prefabricated concrete-filled steel tubular (CFST) bridge pier in the bridge system-level. The proposed prefabricated CFST bridge pier is composed of circular thin-walled CFST double-column, precast I-shaped tie beams, and precast RC cap beam, which are assembled by simply on-stie assembly connections, with advantages in good seismic performance, convenient construction, and comparable material cost. A total of 12 two-span continuous beam bridge cases are designed, including 2 typical bridges with reinforced concrete (RC) piers and 10 bridges with CFST piers. Numerical research on the hysteretic performance of piers in bridge cases, dynamic responses of all bridge cases, and their seismic fragility. The results demonstrate that prefabricated CFST piers outperform RC piers in both load-bearing capacity and energy dissipation, and these piers exhibit reduced transversal displacement at the top and decreased maximum curvature when
Gu, Chao, Wang, Xuanding
Risk Identification and Accompanying Information Service Design of Long Downhill Road Section2025-99-025012/23/2025
In order to reduce traffic accidents and losses in long downhill sections of expressways, giving drivers reasonable prevention and control means of information induction can improve the safety of long downhill sections. The location of the accompanying information service of the driver's vehicle terminal and the rationality of the intervention information are worth studying. This study takes a high-speed long downhill road as an example, divides the risk level of the long downhill road based on the road safety risk index model, and verifies it with the help of driving behavior data. Secondly, three coverage schemes of sensing devices are designed according to the results of risk classification, and the HMI interface of accompanying information service is designed according to the different coverage degrees of sensing devices. Finally, a driving simulation experiment was carried out based on the driving simulator, and the speed control level, psychological comfort level, operational
Wang, Yuejia, Weng, Wenzhong, Luan, Sen, Dai, Yibo
Research on Prediction Methods for the Scale of Chartered Passenger Transport Capacity2025-99-022512/23/2025
Under the background of advancing the integration of urban and rural road passenger transport and the bus-oriented transformation of scheduled passenger transport, the traditional road passenger transport market has been severely impacted. There is an urgent need to promote the healthy development of chartered passenger transport to meet the public’s demand for high-quality travel. Based on the supply-demand balance theory, a prediction model for chartered passenger transport capacity scale was constructed, and the capacity scale of chartered passenger transport in a typical city was predicted as an example. Finally, countermeasures and suggestions for chartered passenger transport capacity allocation were proposed from five aspects: planning formulation, risk warning, mechanism clarification, performance evaluation, and responsibility implementation.
Zhao, Haibin, Zhao, Xiangyu, Xing, Li, Wei, Linghong, Peng, Xiao, Liao, Kai
Research on Dynamic Adjustment Mechanism of Railway Freight Pricing Based on NSGA-II Algorithm2025-99-024812/23/2025
With the implementation of the "road-shift-to-rail" policy and the intensification of competition in the freight transport market, establishing a scientific and effective dynamic pricing mechanism has become a crucial factor in enhancing the competitiveness of railway freight. To address this, this paper constructs a multi-objective dynamic pricing model that comprehensively considers the interests of railway transport enterprises, shippers, and societal externalities. A new multi-objective genetic algorithm (NSGA-II) is designed to solve the model, and an empirical analysis is conducted based on real-world data from "road-shift-to-rail" projects. The research results indicate that the proposed method aligns closely with the current pricing practices of railway transport enterprises. For goods with low time sensitivity, greater freight rate discounts should be offered to shippers, whereas for high time-sensitive goods, the time gap between rail and road transport should be minimized.
Zhang, Hengyuan, Feng, Zhichao, Wu, Xu
Experimental Research on MFL Detection Technology for Corrosion Damage of Prestressing Tendons in Bridges2025-99-020312/23/2025
Corrosion of prestressed tendons endangers the safety of bridges, but until now, there has been no effective method to solve the problem of detecting corrosion damage in prestressed tendons of concrete beams. To address this, a magnetic flux leakage detection experimental apparatus for corrosion damage in prestressed tendons based on the principle of magnetic flux leakage inspection has been developed. Using this apparatus, magnetic flux leakage tests were conducted on prestressed tendons after electrochemical corrosion, and the results were compared with simulation analysis to conduct a comparative study. In the experiments, the influence of corrosion severity, corrosion width, and the effect of stirrups on the characteristics of the magnetic flux leakage signals were studied. Magnetic signal feature values were extracted, and a quantification neural network model for corrosion damage was established, which is used to quantify the degree of corrosion damage in prestressed tendons. The
Wang, Peng, Gao, Min, Dong, Lei, Zhu, Junliang
Impact of Tire-Ground Contact Width on Pavement Roughness Evaluation2025-99-025612/23/2025
The International Roughness Index (IRI) is a key indicator for evaluating the performance of road surfaces. However, traditional measurement methods only focus on the evaluation data of a single longitudinal section and do not consider the lateral difference between the actual contact area between the tire and the road surface, which may lead to inaccurate evaluation results. In recent years, with the advancement of 3D laser scanning and digital photogrammetry technology, full-section data acquisition has brought new possibilities for roughness evaluation. However, how to find a balance between data fineness and computing efficiency has become a core problem that needs to be solved. Based on the principle of interaction between vehicles and road surfaces, this paper proposes to include only the pavement height data within the tire width range into IRI analysis, and establishes an evaluation framework based on standard tire-ground contact width. This method not only retains the key
An, Huazhen, Wang, Rui, Han, Xiaokun, Luo, Yingchao
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