Field operational test of advanced driver assistance systems in typical Chinese road conditions: The influence of driver gender, age and aggression

被引:37
|
作者
Li, G. [1 ]
Li, S. Eben [1 ]
Cheng, B. [1 ]
机构
[1] Tsinghua Univ, Dept Automot Engn, State Key Lab Automot Safety & Energy, Beijing 100084, Peoples R China
关键词
ADASs performance; Driver acceptance; Gender; Age; Driver aggression; Field operational test; SAFETY; ANGER;
D O I
10.1007/s12239-015-0075-5
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Although various Advanced Driver Assistance Systems (ADASs) have been developed to assist drivers, their performances and driver acceptances in China have not been well tested and analyzed. This study aims to examine how do driver gender, age, and aggression affect the performances and driver acceptances of typical ADASs by means of Field Operational Tests (FOTs), including FCW (Forward Collision Warning), LDW (Lane Departure Warning), and SBZA (Side Blind Zone Alert). Thirty-three participants were recruited to drive an equipped vehicle on the test route in and around Beijing City. Vehicle states, environmental information, and driver feedback were recorded by CAN bus, cameras, and post-drive questionnaires. The test results showed that the alert frequencies of FCWs and LDWs increase in higher speed traffic scenarios, whereas that of SBZA declines. Driver acceptance rate of SBZA ranks the highest, with FCW ranking the second and LDW being the last. Driver gender, age, and aggression effects were analyzed in details, showing their relationships with total alert times, alert times per 100 km, and driver acceptance rate of each system. The findings are helpful for future development of ADASs for automotive industry.
引用
收藏
页码:739 / 750
页数:12
相关论文
共 50 条
  • [41] Evaluating effectiveness and acceptance of advanced driving assistance systems using field operational test
    Badweeti K.N.
    Malaghan V.D.
    Pawar D.S.
    Easa S.
    Journal of Intelligent and Connected Vehicles, 2023, 6 (02): : 65 - 78
  • [42] The Impact of Explanation Detail in Advanced Driver Assistance Systems: User Experience, Acceptance, and Age-Related Effects
    Hermann, Julia
    Nierobisch, Niels
    Arndt, Robin
    Kubullek, Ann-Kathrin
    van Ledden, Sebastian
    Dogangun, Ayseguel
    PROCEEDINGS OF 2023 MENSCH UND COMPUTER, MUC 2023: Building Bridges, 2023, : 307 - 312
  • [43] Use and Perceptions of Advanced Driver Assistance Systems by Older Drivers With and Without Age-Related Macular Degeneration
    Deffler, Rebecca A.
    Xu, Jing
    Bittner, Ava K.
    Bowers, Alex R.
    Hassan, Shirin E.
    Ross, Nicole
    Cooley, San-San L.
    Doubt, Aprile
    Davidorf, Frederick H.
    Dougherty, Bradley E.
    TRANSLATIONAL VISION SCIENCE & TECHNOLOGY, 2022, 11 (03):
  • [44] Review of tracking and object detection systems for advanced driver assistance and autonomous driving applications with focus on vulnerable road users sensing
    Markiewicz, Pawel
    Dlugosz, Marek
    Skruch, Pawel
    TRENDS IN ADVANCED INTELLIGENT CONTROL, OPTIMIZATION AND AUTOMATION, 2017, 577 : 224 - 237
  • [45] Application of grey relational analysis for evaluating road traffic safety measures: advanced driver assistance systems against infrastructure redesign
    Lu, M.
    Wevers, K.
    IET INTELLIGENT TRANSPORT SYSTEMS, 2007, 1 (01) : 3 - 14
  • [46] Perceived Needs and Preferences for Use of Advanced Driver Assistance Systems by Drivers with and without Age-related Macular Degeneration
    Xu, Jing
    Hutton, Abbie
    Arsal, Guler
    Dougherty, Bradley E.
    Ni, Rui
    Bowers, Alex R.
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2021, 62 (08)
  • [47] Perceived Safety Benefits of Aftermarket Driver Support Systems: Results from a Large Scale European Field Operational Test (FOT)
    Welsh, Ruth
    Morris, Andrew
    SAFETY, 2018, 4 (04):
  • [48] Worst-case scenarios identification approach for the evaluation of advanced driver assistance systems in intelligent/autonomous vehicles under multiple conditions
    Chelbi, Nacer Eddine
    Gingras, Denis
    Sauvageau, Claude
    JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 26 (03) : 284 - 310
  • [49] Future Advanced Driver Assistance Systems based on Optimal Control: the influence of "risk functions" on overall system behavior and on prediction of dangerous situations
    Bertolazzi, E
    Biral, F
    Da Lio, M
    2004 IEEE INTELLIGENT VEHICLES SYMPOSIUM, 2004, : 386 - 391
  • [50] Transfer learning based hybrid 2D-3D CNN for traffic sign recognition and semantic road detection applied in advanced driver assistance systems
    Khaled Bayoudh
    Fayçal Hamdaoui
    Abdellatif Mtibaa
    Applied Intelligence, 2021, 51 : 124 - 142