Forthcoming and Online First Articles

International Journal of Vehicle Design

International Journal of Vehicle Design (IJVD)

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International Journal of Vehicle Design (7 papers in press)

Regular Issues

  • This is a test paper, pleaseignore it
    by ReviewerV ReviewerC 
    Abstract: This is a test submission. Please ignore it
    Keywords: test test test test test test test test test test test test test test test test.

  • Research on active suspension control based on safety constraint reinforcement learning   Order a copy of this article
    by Lin-feng Zhao, Xiao Feng, Wen-bin Shao, Zhen Mei, Jin-fang Hu 
    Abstract: To tackle the shortcomings of conventional active suspension control algorithms, which struggle to achieve a harmonious balance between ride comfort and handling stability, as well as obvious lack of practical safety considerations for suspension systems in ordinary reinforcement learning algorithms, a Deep Deterministic Policy Gradient(DDPG) Reinforcement Learning(RL) algorithm is proposed, which utilize suspension system safety boundary constraints as its foundation, and integrates the suspension dynamic deflection's limit stroke, as well as safety range of tire dynamic deformation into the reinforcement learning algorithm, and obtains the ideal active suspension control strategy through offline training. Based on MATLAB/Simulink, simulation comparison and HIL(Hardware In the Loop) verification were conducted with Linear Quadratic Regulator (LQR) and ordinary DDPG algorithm under convex road conditions. The results clearly indicates a distinction from the LQR algorithm, in contrast to which the sprung acceleration's rms(root mean square) value using algorithm proposed in this paper is reduced by 6.41%?
    Keywords: active suspension; reinforcement learning; safe boundaries; ride comfort; convex road surface.
    DOI: 10.1504/IJVD.2024.10066193
     
  • Complete coverage path planning algorithm for multiple agricultural robots   Order a copy of this article
    by Changjie Liu, Haobo Zhang, Yangjie Ji 
    Abstract: Multi-robot complete coverage path planning (MCCPP) is an important direction in developing intelligent agricultural robots. Firstly, to address the problem that the existing region decomposition algorithm has too many subregions and contains concave subregions, this paper adopts the improved Maklink line to convexly decompose the workspace to obtain the minimum number of convex subregions. Secondly, the current MCCPP algorithm suffers from duplicate coverage of connection paths, uneven task allocation, and failure to consider the robot's extra energy consumption. This paper adopts the Dijkstra algorithm to plan the shortest non-duplicated connected paths between any subregions; improves the existing objective function by combining with the actual; and retains the high-quality gene fragments for chromosome crossover according to the breakpoints. Finally, the improved Non-dominated Sorting Genetic Algorithm (NSGA-II) is simulated in real planting areas, and the total connected paths and planting area balance were optimized compared to the traditional NSGA-II.
    Keywords: precision agriculture; multi-robots; complete coverage path planning; NSGA-II; non-dominated sorting genetic algorithm.
    DOI: 10.1504/IJVD.2024.10067304
     
  • Feedforward fuzzy LQR path tracking controller based on predictive model and vehicle road position   Order a copy of this article
    by Xinfeng Zhang, Zhiyuan Li, Huan Liu, Xiaorui Li, Juan Zhao 
    Abstract: This study endeavors to enhance the path tracking precision, maneuver stability, and ride comfort of intelligent vehicles in diverse scenarios. To achieve this, we propose a predictive modeling based fuzzy Linear Quadratic Regulator (LQR) for path tracking control, taking into account the vehicle's relative position with respect to the road To mimic human driver behavior, we introduce a predictive model that allows the vehicle to anticipate the path, thus mitigating control system delay. Addressing the issue of inadequate adaptability associated with fixed weight controllers, we introduce a fuzzy adjustment strategy for weight coefficients that takes into account changes in vehicle speed, path tracking lateral error, and path curvature. Compared to the LQR , SMC and MPC controller, under three distinct operational scenarios, the specific enhancements in path tracking accuracy manifest as follows: an increase of 67%, 87%, and 60%; 62%, 86%, and 73%; 52%, 84%, and 73%, respectively.
    Keywords: intelligent vehicle; path tracking; prediction model; lateral control; fuzzy LQR.
    DOI: 10.1504/IJVD.2024.10068413
     
  • Vehicle lane change driving intent recognition based on Bayes-XGBoost   Order a copy of this article
    by Qinghui Zhou, Sun Shunjie 
    Abstract: It is a critical technology to accurately identify the vehicle’s lane-changing intention for traffic safety in intelligent vehicles. A new method for recognizing lane change driving intent based on the Bayesian Extreme Gradient Boosting (Bayes-XGBoost) algorithm was proposed. This method constructed an XGBoost model for lane change driving intent recognition and used a Bayesian algorithm to optimise the hyperparameters of the XGBoost model. To verify the performance of the model, experiments were carried out using the Next Generation Simulation (NGSIM) traffic dataset. Compared to conventional models including XGBoost, LSTM, and SVM, the proposed method demonstrated superior effectiveness in identifying lane-change driving intent, This proves that the proposed method can identify intentions more accurately. Thus, this method has the potential to offer a more effective and significant approach in traffic safety paradigms.
    Keywords: intelligent vehicles; vehicle lane change; XGBoost; Bayesian optimisation; lane change intent recognition.
    DOI: 10.1504/IJVD.2024.10068468
     
  • Multi-mode servo braking control and experimentation of integrated electro-hydraulic braking system   Order a copy of this article
    by Houhua Jing, Liwen Dong, Qinggan Lin, Haifeng Liu 
    Abstract: As the critical problem of electric servo braking control, the relationship between hydraulic pressure, motor position and motor current is systematically analyzed. A large hysteresis exists in the pressure-position relationship. Then a multi-mode servo braking control law is proposed on the basis of experimental tests. Firstly, the influence of nonlinear friction is overcome by dither compensation to improve the smoothness of position and pressure. Secondly, the pressure-current cascade control is applied, and the feedforward is obtained based on the experimental data, which effectively avoids the nonlinear and uncertain influence of pressure-position relationship. Thirdly, position-current cascade control is applied to realize the accurate return of the motor in the release process, and overcome the influence of pressure-position large hysteresis and dead zone. Finally, the control method is comprehensively verified and analyzed based on the experimental bench. The practicability of the method is verified.
    Keywords: integrated electro-hydraulic braking; servo braking control; multi-mode control; pressure control; position control.
    DOI: 10.1504/IJVD.2024.10068496
     
  • Slope estimation of distributed electric drive mining dump truck based on multi-sensor integration   Order a copy of this article
    by Yilin Wang, Weiwei Yang, Nong Zhang 
    Abstract: The efficient, energy-saving, and unmanned operation of mines is an effective way to achieve safe production and improve efficiency. The current road slope estimation method has the shortcomings of involving more parameters and needing more accuracy. This paper proposes a road slope estimation method that integrates the slope estimation methods based on the vehicle longitudinal dynamics model, based on acceleration sensors, and based on inclination sensors with the help of the Kalman filtering algorithm based on covariance-weighted integration. Combines with the slope characteristics of the open pit mine and obtains the estimation value with an accuracy of less than 8.4% compared to the actual road slope variation. The effectiveness and real-time performance of the multi-sensor integration method for the slope estimation of the distributed electric drive mining dump truck are verified, and the solution idea for the state parameter estimation related to the vehicle control strategy research is provided.
    Keywords: distributed electric drive mining dump truck; state parameter estimation; slope estimation; multi-sensor integration; Kalman filter algorithm.
    DOI: 10.1504/IJVD.2024.10068735