Influence of Lane-changing Maneuvers on Passenger Comfort of Intelligent Vehicles

被引：0
|
作者：
Guo Y.-S. [1 ,2 ]
Su Y.-Q. [1 ]
Fu R. [1 ,2 ]
Yuan W. [1 ,2 ]
机构：
[1] School of Automobile, Chang'an University, Xi'an
[2] Key Laboratory of Automobile Transportation Safety Technology, Ministry of Transport, Chang'an University, Xi'an
来源：
Zhongguo Gonglu Xuebao/China Journal of Highway and Transport | 2022年 / 35卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Automotive engineering; Comfort threshold; Intelligent driving control; Lane-changing maneuvers; Prediction model; Real vehicle test; Ride comfort;
D O I：
10.19721/j.cnki.1001-7372.2022.05.021
中图分类号：
学科分类号：
摘要：
One of the most important factors that determine the passengers' acceptance of intelligent vehicles is the ride comfort. In order to improve the comfort of intelligent vehicles and help the design and optimization of intelligent driving control algorithms, this study performed a real vehicle ride comfort test based on the subjective perception of its passengers. In the test, the driver drove a traditional vehicle performing multiple lane-changing maneuvers. Data related to the 60 passengers' assessment of comfort and vehicle motion parameters were collected. Five vehicle motion parameters were selected for this study: the maximum lateral acceleration when changing lanes, the maximum lateral acceleration when returning, the maximum lateral jerk, the conversion amplitude of lateral acceleration, and the conversion frequency of lateral acceleration, and a binary logistic regression single factor analysis was used to evaluate their influence on the ride comfort. The receiver operating characteristic (ROC) curve analysis method was used to determine the comfort thresholds of these five vehicle motion parameters for passengers with different susceptibilities to motion sickness. A ridge regression analysis was used to determine the weights of the parameters' influence on the ride comfort. The results showed that: these five vehicle motion parameters have a significant impact on the ride comfort; the comfort threshold of the passengers susceptible to motion sickness is lower than the comfort threshold of passengers not susceptible to motion sickness; the maximum lateral acceleration when changing lanes and when returning, and the conversion amplitude of lateral acceleration are the main factors affecting the ride comfort when changing lanes. Finally, a comfort prediction model based on dynamic time warping(DTW)+ K nearest neighbor (KNN) algorithm was established according to the vehicle motion parameters and passenger physiological characteristics. The prediction accuracy of the ride comfort model is 84%, which can be used for the assessment of the comfort of intelligent vehicles control algorithms. © 2022, Editorial Department of China Journal of Highway and Transport. All right reserved.
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页码：221 / 230
页数：9
相关论文
共 23 条
  • [1] BEGGIATO M, HARTWICH F, KREMS J., Physiological Correlates of Discomfort in Automated Driving, Transportation Research Part F: Traffic Psychology and Behaviour, 66, pp. 445-458, (2019)
  • [2] BELLEM H, SCHONENBERG T, KREMS J F, Et al., Objective Metrics of Comfort: Developing a Driving Style for Highly Automated Vehicles, Transportation Research Part F: Traffic Psychology and Behaviour, 41, pp. 45-54, (2016)
  • [3] GUO Y, SUN Q, SU Y, Et al., Can Driving Condition Prompt Systems Improve Passenger Comfort of Intelligent Vehicles? A Driving Simulator Study, Transportation Research Part F: Traffic Psychology and Behaviour, 81, pp. 240-250, (2021)
  • [4] LI Ke-qiang, DAI Yi-fan, LI Sheng-bo, Et al., State-of-the-art and Technical Trends of Intelligent and Connected Vehicles, Journal of Automotive Safety and Energy, 8, 1, pp. 1-14, (2017)
  • [5] SCHROEDER F, LU Zhao-lin, LI Sheng-bo, Et al., Driving Comfort Evaluation of Passenger Vehicles with Natural Language Processing and Improved AHP, Journal of Tsinghua University (Science and Technology), 56, 2, pp. 137-143, (2016)
  • [6] SCHOETTLE B, SIVAK M., Public Opinion About Self-driving Vehicles in China, India, Japan, the US, the UK, and Australia, (2014)
  • [7] BELLEM H, THIEL B, SCHRAUF M, Et al., Comfort in Automated Driving: An Analysis of Preferences for Different Automated Driving Styles and Their Dependence on Personality Traits, Transportation Research Part F: Traffic Psychology and Behaviour, 55, pp. 90-100, (2018)
  • [8] FLOYD W F, ROBERTS D F., Anatomical and Physiological Principles in Chair and Table Design, Ergonomics, 2, 1, pp. 1-16, (1958)
  • [9] HELANDER M G, ZHANG L., Field Studies of Comfort and Discomfort in Sitting, Ergonomics, 40, 9, pp. 895-915, (1997)
  • [10] POWELL J P, PALACIN R., Passenger Stability Within Moving Railway Vehicles: Limits on Maximum Longitudinal Acceleration, Urban Rail Transit, 1, 2, pp. 95-103, (2015)
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