Search Results (6)

This study explores the design and implementation of a control system integrating the anti-lock braking system (ABS) with frequency-modulated continuous wave (FMCW) radar technology to enhance safety and performance in autonomous vehicles. The proposed system employs a hybrid fuzzy logic controller (FLC) and proportional-integral-derivative (PID) controller to improve braking efficiency and vehicle stability under diverse driving conditions. Simulation results showed significant enhancements in stopping performance across various road conditions. The integrated system exhibited a marked improvement in braking performance, achieving significantly shorter stopping distances across all evaluated surface conditions—including dry concrete, wet asphalt, snowy roads, and icy roads—compared with scenarios without ABS. These results highlight the system’s ability to dynamically adapt braking forces to different conditions, significantly improving safety and stability for autonomous vehicles. The limitations are acknowledged, and directions for real-world validation are outlined to ensure system robustness under diverse environmental conditions. Full article

This paper conducts an in-depth study on anti-lock braking technology in electronic hydraulic braking systems, focusing on a road-surface recognition algorithm based on fitted curves and a slip-rate control method based on sliding-mode variable structure. Firstly, a road-surface recognition algorithm using fitted curves is proposed, which extracts characteristic information by fitting the μ-λ curve, achieving the accurate identification of different road-surface conditions and providing optimal slip rates for subsequent braking control. Secondly, a slip-rate control strategy based on sliding-mode variable structure is designed to achieve optimal slip-rate control during vehicle braking, ensuring braking stability and safety under varying road conditions. Through theoretical analysis and simulation experiments, the results show that the proposed road-surface recognition algorithm can effectively identify various typical road surfaces (such as dry, wet, and icy/snowy surfaces) with high accuracy. The sliding-mode variable-structure control strategy can achieve good slip-rate control under different road conditions, effectively improving vehicle braking performance. This study provides an efficient and reliable technical solution for anti-lock braking control in electronic hydraulic braking systems, with significant theoretical and practical implications for enhancing vehicle braking safety. Full article

To achieve a rapid and stable dynamic response of the drive anti-slip system for distributed electric vehicles on low-friction surfaces, this paper proposes an adaptive acceleration slip regulation control strategy based on wheel slip rate. An attachment coefficient fusion estimation algorithm based on an improved singular value decomposition unscented Kalman filter is designed. This algorithm combines Sage–Husa with the unscented Kalman filter for adaptive improvement, allowing for the quick and accurate determination of the road friction coefficient and, subsequently, the optimal slip rate. Additionally, a slip rate control strategy based on dynamic adaptive compensation sliding mode control is designed, which introduces a dynamic weight integral function into the control rate to adaptively adjust the integral effect based on errors, with its stability proven. To verify the performance of the road estimator and slip rate controller, a model is built with vehicle simulation software, and simulations are conducted. The results show that under icy and snowy road conditions, the designed estimator can reduce estimation errors and respond rapidly to sudden changes. Compared to traditional equivalent controllers, the designed controller can effectively reduce chattering, decrease overshoot, and shorten response time. Especially during road transitions, the designed controller demonstrates better dynamic performance and stability. Full article

The crucial dynamic path planning of autonomous vehicles is achieved via obstacle avoidance path planning technology. The reduction of the tire adhesion coefficient on icy and snowy roads (ISRs) increases the difficulty of autonomous vehicles’ control. In this paper, the driving characteristics of vehicles on ISRs are established, and the artificial potential field function is introduced to avoid collision risk when planning a path. A dynamic path planning algorithm for autonomous vehicles based on the artificial potential field (APF) is established. The adjustment factor is added to the gravitational potential field, and a judgment coefficient is added to the repulsive potential field to improve the artificial potential field function, based on the low adhesion of vehicles on ISRs. Moreover, a path with a continuous curvature is generated to achieve the driving comfort and driving safety of the planned path via trajectory smoothing. By establishing the Carsim/Simulink co-simulation platform, the effectiveness of dynamic path planning for autonomous vehicles under different algorithms and different obstacle models is compared. The results show that the improved APF algorithm has an obvious effect on the smoothness of the path and the reduction of the curvature mutation and can generate a safe and efficient path on icy and snowy roads. The dynamic obstacle avoidance of the improved APF algorithm improves the pre-judgment accuracy of the collision risk assessment of autonomous vehicles and shows the superiority of the improved algorithm. Full article

This study deals with the possibility of construction of a database on the braking friction coefficient for actual roads from the viewpoint of traffic safety, especially for automated driving, such as level 4 or higher. At these levels of automated driving, the controller needs to control the vehicle. However, the road surface condition, especially the road friction coefficient on wet roads and snowy or icy roads, changes greatly, and in some cases, changes by almost one order. Therefore, it is necessary for the controller to constantly collect environment information, such as the road friction coefficients, and prepare for emergencies, such as obstacle avoidance. However, at present, the measurement of the road friction coefficients is not systemically performed, and a method for accurately measuring has not been established. In order to improve this situation, this study examines a method for continuous measurement of the road friction characteristics, such as the μ-s characteristics. It is shown that the μ-s characteristics are continuously measured using the MF generally used in tire engineering, and the friction characteristics identified from the results are sufficiently satisfactory. Full article

In order to maximize the public health benefits of cycling, the negative impacts of cycling, such as the number and types of crashes, should be identified. Single-bicycle crashes, in which other road users are not collided with, are one of the main safety concerns in cycling, but comprehensive knowledge on these crashes is not available due to poor data sources. This study aimed to identify characteristics of commuters’ single-bicycle crashes in Finland. Firstly, insurance data covering 9268 commuter bicycle crashes in 2016 and 2017 were analyzed to find single-bicycle crashes. The insurance data are based on self-reported crashes. In total, 3448 single-bicycle crashes were found with crash descriptions that were informative enough for investigation of their characteristics. According to the results, 62.9% (95% confidence interval +/− 1.6%) of the crashes were related to the infrastructure. In the majority of infrastructure-related crashes, the road surface was slippery. The slippery road surface was typically due to icy or snowy conditions. The lack of proper data complicates the recognition of single-bicycle crashes, and hence policy actions and research projects are needed to develop better data sources for proper investigation of cycling safety. Full article