International Journal of Vehicle Systems Modelling and Testing (5 papers in press)

Regular Issues

• Evaluation of the rationality of urban road traffic sign setting in Nanchang city based on real vehicle test  
  by Hui Hu, Feng He, Youzhang Yang, Yunwei Meng, Haoxiang Zhao, Guangyan Qing 
  Abstract: The content and density of road traffic signs affect the driving behaviour of drivers and the smoothness of urban traffic. There is a lack of quantitative research methods on the current information threshold of traffic signs. In order to quantitatively classify the informativeness threshold of traffic signs and better explore the reasonableness of traffic sign setting, this paper designed a real-vehicle experiment, adopts the principal component analysis (PCA) method, conducted multi-dimensional analysis of pupil area, fixation intensity, heart rate change rate and heart rate variability, quantified the traffic sign information by using the information entropy theory and introduces the comfort index S, and established regression relations. Driving visual comfort was quantitatively classified into five levels, and it was indicated that the traffic sign information density should be less than 0.373 bits/m and maximum should not exceed 0.507 bits/m.
  Keywords: urban road; traffic sign; real vehicle test; visual comfort; amount of information; information density; traffic safety; pupil area; heart rate.
  DOI: 10.1504/IJVSMT.2024.10068734
   
  
• Contact stiffness modelling and analysis of brake disc with rough geometrical topography and manufacturing deviation  
  by Hehe Kang, Xiang Liu, Qiaolei Hu, Xuan Liu, Huali Han, Yongcheng Long, Haizhou Yuan 
  Abstract: Contact stiffness plays an important role in the braking efficiency, braking squeal, and vibration response of brake system. However, various random geometrical deviations are inevitably generated in the actual contact interface, leading to the discreteness of contact stiffness. To probe into the relationship between manufacturing tolerance and fluctuation of the contact stiffness, a contact stiffness model of brake disc is established through statistical rough contact theory with elastoplastic deformation of asperity and coupling effect of manufacturing deviation. The effectiveness of presented model is validated by comparison with experimental, and statistical geometrical parameters of rough surface are measured to characterize the actual rough contact of the brake disc. A comprehensive analysis of various types of manufacturing deviations is conducted to show the influence on contact stiffness. The results indicate that the manufacturing deviations have a strong ability to change contact stiffness and weaken the contact condition of brake disc.
  Keywords: manufacturing deviation; brake disc; rough interface; contact stiffness.
  DOI: 10.1504/IJVSMT.2025.10069045
   
  
• Study on the influence of friction coefficient on the wheel-rail contact and rolling contact fatigue for the low-floor vehicle  
  by Xue Li, Yuexin Wang, Kaiyun Wang, Gao Pu 
  Abstract: The wheel-rail friction coefficient (FC) is one of the critical parameters in the wheel-rail contact. The high FC will exacerbate the wheel-rail interaction and accelerate the crack propagation. This study focuses on the wheel-rail contact and rolling contact fatigue for the low-floor vehicle under the different FC. Firstly, the dynamic model of the low-floor vehicle is developed, and the dynamic model is verified based on field tests. Then, the area of contact patch, tangential stress, creep force, and normal force as the important indicators are investigated. Finally, the superficial fatigue index on traditional wheelset (TW) and independently rotating wheel (IRW) is studied by Shakedown Diagram. And the accumulated damage of wheels is analyzed by Dang-Van criterion. The results show that the high FC will lead to a sharp increase in creep force on transition curves and circular curve segments. The superficial fatigue index of wheels is significantly affected by the FC, and the superficial fatigue index of TW is always lower than that of IRW as the radius of the curve increases.
  Keywords: vehicle system dynamics; low-floor vehicle; friction coefficient; rolling contact fatigue; wheel-rail contact.
  DOI: 10.1504/IJVSMT.2025.10069248
   
  
• Enhanced SLAM based on 2D LiDAR and RGB-D camera fusion for mobile robots navigationNavigation  
  by Jie Yu, Penghui Fu, Qingyong Zhang, Xiaolei Yan, Sheng Ye 
  Abstract: Real-time mapping and dynamic navigation for mobile robots present significant challenges, particularly due to the limitations of 2D LiDAR in environmental representation and the constraints of using a single RGB-D camera. This paper introduces a novel mapping method that enhances the traditional ORB-SLAM2 system by integrating 2D LiDAR and RGB-D camera data using Bayesian estimation. This approach enables the construction of dense maps, OctoMaps, and grid maps, improving the completeness and practicality of the mapping process. Additionally, Cartographer-SLAM is incorporated into the enhanced ORB-SLAM2 framework to further refine mapping capabilities. Comparative tests using the publicly available TUM dataset show that the proposed method reduces absolute pose error by 51.16%, with mapping trajectories closely aligning with ground truth values. The camera tracking trajectory improves by 16.2%. Experimental results demonstrate that the novel algorithm provides clearer environmental representations, increased accuracy, and higher mapping success rates.
  Keywords: SLAM; RGB-D camera; information fusion; Bayesian estimation.
  DOI: 10.1504/IJVSMT.2025.10069362
   
  
• Semantic context-induced fast fusion network based driver attention prediction in complex scenarios  
  by Jingllei Ren, Hailong Zhang, Yongjuan Zhao, Cong Lan 
  Abstract: Clarifying driving intention through the utilization of the visual selective attention mechanism remains a pivotal research question in a domain of advanced driver assistance systems and human-machine collaborative autonomous driving technology. This paper proposes a semantic context-induced fast fusion network (SCFF-Net) segmenting the RGB (Red Green Blue) video frames into images with different semantic regions and develops attention strategy to fuse the semantic context features of semantic images with the features of RGB frames to explore the complementarity among different features. A mixed model of self-attention and convolution integrated with the self-attention mechanism is further introduced by combining the global perception capability and the local feature extraction capability. Experimental results on the driver attention in driving accident scenarios dataset show that the proposed SCFF-Net can effectively improve the prediction accuracy of driver attention and the computing efficiency. It can also reduce redundant calculations.
  Keywords: driver attention prediction; AC-mix; complex driving scenarios; computer vision; deep learning.
  DOI: 10.1504/IJVSMT.2025.10069760