Subjective assessment for an advanced driver assistance system: a case study in China

被引:6
作者
Li J. [1 ]
Ao D. [2 ]
机构
[1] Department of Vehicle Engineering, School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei
[2] Department of Electromechanical Engineering, Faculty of Science and Technology, University of Macau
来源
Journal of Intelligent and Connected Vehicles | 2022年 / 5卷 / 02期
关键词
Advanced driver assistance system; Case study; Level; 2; or; 21; Six dimensions; Subjective assessment method;
D O I
10.1108/JICV-11-2021-0017
中图分类号
学科分类号
摘要
Purpose – This study aims to propose a novel subjective assessment (SA) method for level 2 or level 21 advanced driver assistance system (ADAS) with a customized case study in China. Design/methodology/approach – The proposed SA method contains six dimensions, including perception, driveability and stability, riding comfort, human–machine interaction, driver workload and trustworthiness and exceptional operating case, respectively. And each dimension subordinates several subsections, which describe the corresponding details under this dimension. Findings – Based on the proposed SA, a case study in China is conducted. Six drivers with different driving experiences are invited to give their subjective ratings for each subsection according to a predefined rating standard. The rating results show that the ADAS from Tesla outperforms the upcoming electric vehicle in most cases. Originality/value – The proposed SA method is beneficial for the original equipment manufacturers developing related technologies in the future. © Di Ao and Jialin Li. Published in Journal of Intelligent and Connected Vehicles.
引用
收藏
页码:112 / 122
页数:10
相关论文
共 21 条
[1]  
Acosta M., Kanarachos S., Blundell M., Virtual TYRE force sensors: An overview of TYRE model-based and TYRE model-less state estimation techniques, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 232, 14, pp. 1883-1930, (2018)
[2]  
Ao D., Hua X., Yu G., Guo D., Jia Z., Robust active post-impact motion control for restraining a second crash, 2020 IEEE 16Th International Conference on Automation Science and Engineering (CASE), IEEE, pp. 159-164, (2020)
[3]  
Ao D., Wong P.K., Huang W., Mei X.T., Cao Y.C., Zhao J., Analysis of co-relation between objective measurement and subjective assessment for dynamic comfort of vehicles, International Journal of Automotive Technology, 21, 6, pp. 1553-1567, (2020)
[4]  
Ao D., Huang W., Wong P.K., Li J., Robust backstepping super-twisting sliding mode control for autonomous vehicle path Following, IEEE Access, 9, pp. 123165-123177, (2021)
[5]  
Auckland R.A., Manning W.J., Carsten O.M.J., Jamson A.H., Advanced driver assistance systems: Objective and subjective performance evaluation, Vehicle System Dynamics, 46, pp. 883-897, (2008)
[6]  
Coe D.J., Kulick J.H., Milenkovic A., Etzkorn L., Virtualized in situ software update verification: Verification of over-the-air automotive software updates, IEEE Vehicular Technology Magazine, 15, 1, pp. 84-90, (2019)
[7]  
Crolla D.A., Vehicle dynamics – theory into practice, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 210, 2, pp. 83-94, (1996)
[8]  
Gil Gaomez G.L., Nybacka M., Bakker E., Drugge L., Findings from subjective evaluations and driver ratings of vehicle dynamics: Steering and handling, Vehicle System Dynamics, 53, 10, pp. 1416-1438, (2015)
[9]  
Gil Gaomez L.G., Nybacka M., Bakker E., Drugge L., Correlations of subjective assessments and objective metrics for vehicle handling and steering: A walk through history, International Journal of Vehicle Design, 72, 1, pp. 17-67, (2016)
[10]  
Gil Gaomez G.L., Nybacka M., Drugge L., Bakker E., Machine learning to classify and predict objective and subjective assessments of vehicle dynamics: The case of steering feel, Vehicle System Dynamics, 56, 1, pp. 150-171, (2018)