Volume 42 Issue 2
Apr.  2024
Turn off MathJax
Article Contents
QIAN Zehao, PAN Xinfu, FAN Xinwei, YAN Xin, KE Wei, WANG Shunchao. Characteristics and a Safety Analysis of Driver's Free Lane-changing Behavior in a Virtual Reality-based Connected Environment[J]. Journal of Transport Information and Safety, 2024, 42(2): 36-48. doi: 10.3963/j.jssn.1674-4861.2024.02.004
Citation: QIAN Zehao, PAN Xinfu, FAN Xinwei, YAN Xin, KE Wei, WANG Shunchao. Characteristics and a Safety Analysis of Driver's Free Lane-changing Behavior in a Virtual Reality-based Connected Environment[J]. Journal of Transport Information and Safety, 2024, 42(2): 36-48. doi: 10.3963/j.jssn.1674-4861.2024.02.004

Characteristics and a Safety Analysis of Driver's Free Lane-changing Behavior in a Virtual Reality-based Connected Environment

doi: 10.3963/j.jssn.1674-4861.2024.02.004
  • Received Date: 2023-10-10
    Available Online: 2024-09-14
  • Traditional driving simulators need help to accurately simulate complex interactions, such as speed variations and lane changes in connected vehicle environments. The connected virtual reality (VR) driving simulator can more realistically replicate vehicle physical characteristics, traffic flow dynamics, and actual road environments using advanced sensors and real-time data processing. A driving simulation system for free lane-changing experiments is developed using traffic simulation and 3D modeling technologies, based on which a scenario library is established and further carry out experiments about free lane-changing behavior. Generalized estimating equations is adopted to establish models of gap selection and lane-changing time. An accelerated failure time model is adopted to analyze the safety impact of the connected environment on free lane-changing behavior. The results can be concluded in two aspects. In connected environments: ① Female drivers exhibit longer lane-changing gaps and need more time. Younger drivers show shorter gaps and need less time. ②An increase of 1 m/s2 in acceleration noise can reduce collision risk by 28% during lane changes, and a 1 m increase in lane-changing gap can increase collision risk by 1.1%.③Older drivers have a higher level of lane-changing safety. Middle-aged and elderly drivers (> 40 years old) show 38.3% and 64.3% higher regarding time-to-collision (TTC) than young (> 27~40 years old) and younger drivers (> 18~27 years old) do. ④Female drivers have a higher level of lane-changing safety than male drivers do, with a 20.1% higher of TTC during free lane-changes. Compared to non-connected environments: ①Drivers in connected environments show a 1.16 m increase in lane-changing gap, a 2.41 s increase in lane-changing time and a 19.72% improvement in the level of safety. ②The probability of occurring lane-changing accidents decreases with the increase of collision risk durations. Specifically, it reduces by 5.8%, 17.2%, 14.4%, and 3.0% at 1, 2, 3, and 4 s of collision risk duration, respectively. These probabilities vary significantly across drivers'genders and ages.

     

  • loading
  • [1]
    SHAWKY M. Factors affecting lane change crashes[J]. IATSS Research, 2020, 44(2): 155-161. doi: 10.1016/j.iatssr.2019.12.002
    [2]
    陈峥, 张玉果, 沈世全, 等. 城市郊区道路跟车条件下智能网联汽车速度规划[J]. 中国公路学报, 2023, 36(6): 298-310.

    CHEN Z, ZHANG Y G, SHEN S Q, et al. Speed planning for intelligent connected vehicles under car-following conditions on suburban roads[J]. China Journal of Highway and Transport, 2023, 36(6): 298-310. (in Chinese)
    [3]
    王云泽, 李英杰, 唐立. 交通运输从业者对自动驾驶接受度建模与分析[J]. 交通运输工程与信息学报, 2023, 21(2): 42-54.

    WANG Y Z, LI Y J, TANG L. Modeling and analysis of the acceptance of autonomous driving by transportation practitioners[J]. Journal of Transportation Engineering and Information, 2023, 21(2): 42-54. (in Chinese)
    [4]
    翟俊达, 鲁光泉, 陈发城, 等. 城市交叉口车路网联信息对青年驾驶人驾驶行为的影响分析[J]. 交通信息与安全, 2022, 40(1): 126-134. doi: 10.3963/j.jssn.1674-4861.2022.01.015

    ZHAI J D, LU G Q, CHEN F C, et al. Effects of information from connected vehicles and infrastructure on driving behavior of young drivers at urban intersections[J]. Journal of Transport Information and Safety, 2022, 40(1): 126-134. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2022.01.015
    [5]
    GIPPS P G. A model for the structure of lane-changing decisions[J]. Transportation Research Part B: Methodological, 1986, 20(5): 403-414. doi: 10.1016/0191-2615(86)90012-3
    [6]
    WU J, BRACKSTONE M, MCDONALD M. Fuzzy sets and systems for a motorway microscopic simulation model[J]. Fuzzy Sets and Systems, 2000, 116(1): 65-76. doi: 10.1016/S0165-0114(99)00038-X
    [7]
    ZHENG Z. Recent developments and research needs in modeling lane changing[J]. Transportation Research Part B: Methodological, 2014, 60(11): 16-32.
    [8]
    PAN T L, LAM W H K, SUMALEE A, et al. Modeling the impacts of mandatory and discretionary lane-changing maneuvers[J]. Transportation Research Part C: Emerging Technologies, 2016, 68(5): 403-424.
    [9]
    JULA H, KOSMATOPOULOS E B, IOANNOU P A. Collision avoidance analysis for lane changing and merging[J]. IEEE Transactions on Vehicular Technology, 2000, 49(6): 2295-2308. doi: 10.1109/25.901899
    [10]
    NARANJO J E, GONZÁLEZ C, GARCÍA R, et al. Cooperative throttle and brake fuzzy control for ACC + Stop & Go maneuvers[J]. IEEE Transactions on Vehicular Technology, 2007, 56(4): 1623-1630. doi: 10.1109/TVT.2007.897632
    [11]
    BARMPOUNAKIS E N, VLAHOGIANNI E I, GOLIAS J C. Decision trees and meta-algorithms for revealing powered two wheelers' overtaking patterns[R]. Washington, D.C. Transportation Research Board, 2017.
    [12]
    周红媚, 孙叶, 徐秀娟. 基于随机效用理论的城市道路车辆自由换道行为研究[J]. 交通运输研究, 2017, 3(2): 9-16.

    ZHOU H M, SUN Y, XU X J. Behavior of discretionary lane changing on urban streets based on random utility theory[J]. Transportation Research, 2017, 3(2): 9-16. (in Chinese)
    [13]
    王婉秋, 肖凌云, 马明辉, 等. 基于NSGA_Ⅱ的双车道公路弯道驾驶人模型[J]. 公路交通科技, 2021, 38(12): 131-138, 146.

    WANG W Q, XIAO L Y, MA M H, et al. Driver models in curves of two-lane highway based on NSGA_Ⅱ[J]. Journal of Highway and Transportation Research and Development, 2021, 38(12): 131-138, 146. (in Chinese)
    [14]
    田勇达. 混流环境下网联车辆换道模型研究[D]. 长春: 吉林大学, 2020.

    TIAN Y D. Research on lane change model of connected vehicles in mixed traffic environments[D]. Changchun: Jilin University, 2020. (in Chinese)
    [15]
    刘怿轩, 张慧永, 王猛, 等. 跟驰自动驾驶车时人驾车行为研究: 实证与建模[J]. 交通运输工程与信息学报, 2023, 21 (2): 14-28.

    LIU Y X, ZHANG H Y, WANG M, et al. Study on human driving behavior during car-following autonomous driving: empirical and modeling[J]. Journal of Transportation Engineering and Information, 2023, 21(2): 14-28. (in Chinese)
    [16]
    张顺, 陈焕明, 孙腾超. 车联网环境与传统环境下智能车辆换道博弈模型[J]. 汽车实用技术, 2024, 49(9): 35-42.

    ZHANG S, CHEN H M, SUN T C. Lane-changing game model of intelligent vehicle in vehicle networking environment and traditional environment[J]. Automobile Technology, 2024, 49(9): 35-42. (in Chinese)
    [17]
    涂辉招, 李振飞, 孙立军. 驾驶模拟器运动系统对自由驾驶行为的影响分析[J]. 同济大学学报(自然科学版), 2015, 43 (11): 1696-1702.

    TU H Z, LI Z F, SUN L J. Analysis of the impact of driving simulator motion systems on free driving behavior[J]. Journal of Tongji University(Natural Science), 2015, 43(11): 1696-1702. (in Chinese)
    [18]
    SHARMA A, ALI Y, SAIFUZZAMAN M, et al. Human factors in modelling mixed traffic of traditional, connected, and automated vehicles[C]. International Conference on Applied Human Factors and Ergonomics, Los Angeles, USA: Springer International Publishing, 2018.
    [19]
    ALI Y, ZHENG Z, HAQUE M M. Connectivity's impact on mandatory lane-changing behaviour: Evidences from a driving simulator study[J]. Transportation Research Part C: Emerging Technologies, 2018, 93: 292-309. doi: 10.1016/j.trc.2018.06.008
    [20]
    LEE J, PARK B. Development and evaluation of a cooperative vehicle intersection control algorithm under the connected vehicles environment[J]. IEEE Transactions on Intelligent Transportation Systems, 2012, 13(1): 81-90. doi: 10.1109/TITS.2011.2178836
    [21]
    RUDIN-BROWN C M, NOY Y I. Investigation of behavioral adaptation to lane departure warnings[J]. Transportation Research Record, 2002, 1803(1): 30-37. doi: 10.3141/1803-05
    [22]
    RUDIN-BROWN, C, JAMSON, S. Behavioural adaptation and road safety: theory, evidence and action[M]. Boca Raton: CRC Press, 2013.
    [23]
    ALI Y, ZHENG Z, HAQUE M M, et al. Understanding the discretionary lane-changing behaviour in the connected environment[J]. Accident Analysis & Prevention, 2020, 137: 105463.
    [24]
    ADELL E, VÁRHELYI A, DALLA FONTANA M. The effects of a driver assistance system for safe speed and safe distance-a real-life field study[J]. Transportation Research Part C: Emerging Technologies, 2011, 19(1): 145-155. doi: 10.1016/j.trc.2010.04.006
    [25]
    SAFFARIAN M, DE WINTER J C F, HAPPEE R. Enhancing driver car-following performance with a distance and acceleration display[J]. IEEE Transactions on Human-machine Systems, 2012, 43(1): 8-16.
    [26]
    MONTGOMERY J, KUSANO K D, GABLER H C. Age and gender differences in time to collision at braking from the 100-car naturalistic driving study[J]. Traffic Injury Prevention, 2014, 15(1): 15-20.
    [27]
    LI Y, LI Z, WANG H, et al. Evaluating the safety impact of adaptive cruise control in traffic oscillations on freeways[J]. Accident Analysis & Prevention, 2017, 104: 137-145.
    [28]
    LI Y, WANG H, WANG W, et al. Evaluation of the impacts of cooperative adaptive cruise control on reducing rear-end collision risks on freeways[J]. Accident Analysis & Prevention, 2017, 98: 87-95.
    [29]
    GU X, ABDEL-ATY M, XIANG Q, et al. Utilizing UAV video data for in-depth analysis of drivers' crash risk at interchange merging areas[J]. Accident Analysis & Prevention, 2019, 123: 159-169.
    [30]
    YOUNG K L, REGAN M A, MITSOPOULOS E. Acceptability to young drivers of in-vehicle intelligent transport systems[J]. Road & Transport Research, 2004, 13(2): 6-7.
    [31]
    DONMEZ B, BOYLE L N, LEE J D, et al. Drivers'attitudes toward imperfect distraction mitigation strategies[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2006, 9(6): 387-398. doi: 10.1016/j.trf.2006.02.001
    [32]
    GISH J A, GRENIER A, VRKLJAN B, et al. Older people driving a high-tech automobile: Emergent driving routines and new relationships with driving[J]. Canadian Journal of Communication, 2017, 42(2): 235-236. doi: 10.22230/cjc.2017v42n2a3125
    [33]
    LI G, EBEN LI S, CHENG B. Field operational test of advanced driver assistance systems in typical Chinese road conditions: the influence of driver gender, age and aggression[J]. International Journal of Automotive Technology, 2015, 16(5): 739-750. doi: 10.1007/s12239-015-0075-5
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(10)  / Tables(5)

    Article Metrics

    Article views (198) PDF downloads(22) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return