吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (6): 1716-1727.doi: 10.13229/j.cnki.jdxbgxb201706007

• 论文 • 上一篇    下一篇

雾霾天气低能见度对不同跟驰状态驾驶行为的影响

高坤1, 2, 涂辉招1, 2, 时恒1, 2, 李振飞3   

  1. 1.同济大学 道路与交通工程教育部重点实验室,上海 201804;
    2.同济大学 交通运输工程学院,上海 201804;
    3.中国建筑股份有限公司 海外事业部,北京 100037
  • 收稿日期:2016-08-29 出版日期:2017-11-20 发布日期:2017-11-20
  • 作者简介:高坤(1993-),男,博士研究生.研究方向:交通行为分析与建模.E-mail:93gaokun@tongji.edu.cn
  • 基金资助:
    国家自然科学基金项目(71271155)

Effect of low visibility in haze weather condition on longitudinal driving behavior in different car-following stages

GAO Kun1, 2, TU Hui-zhao1, 2, SHI Heng1, 2, LI Zhen-fei3   

  1. 1.Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China;
    2.College of Transportation Engineering, Tongji University, Shanghai 201804, China;
    3.Overseas Department, China State Construction Engineering Co., Ltd., Beijing 100037,China
  • Received:2016-08-29 Online:2017-11-20 Published:2017-11-20

RICH HTML

0   

PDF (PC)

167

摘要： 利用8自由度高逼真度驾驶模拟器,从工程学和人类心理学角度分析了雾霾天气低能见度对不同跟驰状态(加速、减速和平稳跟驰)驾驶行为的影响。结果表明:雾霾天气低能见度对不同跟驰状态驾驶行为的影响存在明显差异性。加速跟驰过程中,雾霾天气低能见度下驾驶员对速度差变化、距离差变化的反应敏感性和最大意愿加速度分别比晴天显著降低了29.3%、33.1%和17.4%,且驾驶行为异质性明显升高;减速跟驰过程中,雾霾天气低能见度下驾驶员对速度差变化的反应敏感性、最大意愿减速度和感知前车最大减速度分别比晴天显著提高了31.7%、17.8%和16.3%,对距离差变化的反应敏感性显著降低了32.1%,而驾驶行为异质性有所降低;平稳跟驰过程中,雾霾天气低能见度下驾驶员对速度差变化反应敏感性比晴天显著提高了41.6%,最大意愿加速度和减速度均值小于晴天,期望速度和对距离差变化的反应敏感性与晴天无显著差异。加减速反应阈值方面,驾驶员在雾霾天气低能见度下倾向于采取更加积极的加速反应来紧随前车,同时又更加谨慎地采取减速反应避免碰撞。本文研究结果为雾霾天气低能见度等紧急事件下应急疏散微观交通仿真的建立提供了理论支撑。

关键词: 交通运输系统工程, 雾霾天气低能见度, 跟驰行为, 反应阈值

Abstract: Using a high fidelity driving simulator with eight degrees of freedom, the effect of low visibility in haze weather condition on the driving behavior of three Car-Following (CF) stages (acceleration, deceleration and steady following stages) are analyzed from both engineering CF models and psychological-physiological CF model. The results show that the low visibility environment in haze weather condition has significantly different impacts on driving behavior of different CF stages. In acceleration CF stage, the drivers' sensitivity in changes of relative speed and spacing, as well as maximum desired acceleration under haze weather condition are significantly lower, 29.3%, 33.1% and 17.4% respectively, than that under clear weather condition. Meanwhile the heterogeneities in driving behavior are substantially larger in haze weather condition. In the deceleration stage, drivers' sensitivity in changes of relative speed, maximum desired deceleration and expected maximum deceleration of the leading vehicle under haze weather condition are significantly larger, 31.7%, 17.8% and 16.3% respectively, than that in clear weather condition. Whereas, the drivers' sensitivity in change of the spacing decreases by 32.1% in haze weather condition. In steady CF stage, the drivers have larger sensitivities in changes of relative speed, 41.6% higher in average in haze weather than that in clear weather, and have slightly smaller maximum desired acceleration and deceleration. However, there are no significant differences in desired speed and drivers' reaction to the change in spacing under different weather conditions. Moreover, the action points of acceleration and deceleration indicate that the drivers under low visibility in haze weather adopt quicker acceleration to follow the leading vehicle more closely, and are more cautious to take quicker braking action to avoid collision. The main findings of this paper provide references for setting-up of microscopic simulation for emergency traffic evacuation in case of low visibility in haze weather condition.

Key words: engineering of communications and transportation system, low visibility under hazy weather conditions, car-following behavior, action point

中图分类号: 

  • U491.2
[1] 台德清. 雾天高速公路交通管制方法及对策研究[D]. 成都:西南交通大学交通运输与物流学院,2011.
Tai De-qing. Traffic control method and countermeasure research of highway on foggy day[D].Chengdu: School of Transportation and Logistics, Southwest Jiaotong University,2011.
[2] 李显生,任园园,席建锋,等. 非强制性控速设施下的驾驶员速度控制模型[J]. 吉林大学学报:工学版,2010,40(增刊1):169-173.
Li Xian-sheng, Ren Yuan-yuan, Xi Jian-feng, et al. Driver's speed control model based on non-madatory speed-control facilities[J]. Journal of Jilin University(Engineering and Technology Edition),2010,40(Sup.1):169-173.
[3] 商蕾. 城市微观交通仿真及其应用[D]. 武汉:武汉理工大学交通学院,2003.
Shang Lei. Urban microscopic traffic simulation and its application[D]. Wuhan:School of Transportation, Wuhan University of Technology,2003.
[4] 金立生,Arem B V,杨双宾, 等. 高速公路汽车辅助驾驶安全换道模型[J]. 吉林大学学报:工学版,2009,39(3):582-586.
Jin Li-sheng, Arem B V, Yang Shuang-bin, et al. Safety lane change model of vehicle assistanct driving on highway[J]. Journal of Jilin University(Engineering and Technology Edition),2009,39(3):582-586.
[5] Saifuzzaman M,Zheng Z. Incorporating human-factors in car-following models: a review of recent developments and research needs[J]. Transportation Research Part C: Emerging Technologies,2014,48:379-403.
[6] Gazis D C, Herman R, Rothery R W. Nonlinear follow-the-leader models of traffic flow[J]. Operations Research,1961,9(4):545-567.
[7] Gipps P G, A behavioural car-following model for computer simulation[J]. Transportation Research Part B: Methodological,1981,15(2):105-111.
[8] Wiedemann R. Simulation des strassenverkehrsflusses[J]. Traffic Engineering,1975:66-68.
[9] Hawkins R K. Motorway traffic behaviour in reduced visibility conditions[C]//Second International Conference on Vision in Vehicles,Nottingham,United Kingdom,1988:9-18.
[10] White M E,Jeffery D J. Some aspects of motorway traffic behaviour in fog[R]. Transportation Research Record: Journal of the Transportation Research Board, Berkshire, England,1980:958.
[11] 赵佳. 基于驾驶模拟实验的雾天对驾驶行为影响的研究[D]. 北京:北京交通大学交通学院,2012.
Zhao Jia. Study of driving behavior under fog weather condition based on driving simulator experiment[D]. Beijing:School of Transportation, Beijing Jiaotong University,2012.
[12] Saffarian M, Happee R, de Winter J C F. Why do drivers maintain short headways in fog? a driving-simulator study evaluating feeling of risk and lateral control during automated and manual car following[J]. Ergonomics,2012,55(9):971-985.
[13] Hogema J, van der Horst R. Driving behaviour under adverse visibility conditions[C]//Proceedings of the First World Congress on Applications of Transport Telematics and Intelligent Vehicle-Highway Systems, Paris, 1994:1623-1630.
[14] 李晓梦,闫学东,赵佳,等. 雾天对弯道驾驶行为的影响研究[J]. 交通信息与安全,2014(5):120-125.
Li Xiao-meng, Yan Xue-dong, Zhao Jia, et al.Effects of fog conditions on driving behaviors on curves[J]. Journal of Transportation Information and Safety,2014(5):120-125.
[15] 何莎,闫学东,庞洪涛, 等. 雾天对驾驶行为的影响研究——避撞驾驶行为[J]. 交通信息与安全,2014(5):126-129,184.
He Sha, Yan Xue-dong, Pang Hong-tao, et al. Effects of fog conditions on driving behaviors-crash avoidance driving behaviors[J]. Journal of Transportation Information and Safety,2014(5):126-129,184.
[16] Broughton K L, Switzer F, Scott D. Car following decisions under three visibility conditions and two speeds tested with a driving simulator[J]. Accident Analysis & Prevention,2007,39(1):106-116.
[17] Hoogendoorn R G, Tamminga G, Hoogendoorn S, et al. Longitudinal driving behavior under adverse weather conditions: adaptation effects, model performance and freeway capacity in case of fog[C]//13th International IEEE Conference on Intelligent Transportation Systems,Portugal,2010:450-455.
[18] Hoogendoorn R G, Hoogendoorn S, Brookhuis K, et al. Adaptation longitudinal driving behavior, mental workload, and psycho-spacing models in fog[J]. Transportation Research Record: Journal of the Transportation Research Board,2011(2249):20-28.
[19] Hoogendoorn R G. Empirical research and modeling of longitudinal driving behavior under adverse conditions[D]. Delft:Delft University of Technology,2012.
[20] Tu H Z,Li Z F,Li H, et al. Driving simulator fidelity and emergency driving behavior[J]. Transportation Research Board,2015(2518):113-121.
[21] 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 Hui-zhao,Li Zhen-fei,Sun Li-jun, Effects of motion system of driving simulator on free driving behaviors[J]. Journal of Tongji University (Nature Science),2015,43(11):1696-1702.
[22] Helly W. Simulation of bottlenecks in single-lane traffic flow[C]//Proceeding of Symposium on Theory of Traffic Flow, Britain,2004:207-238.
[23] 王殿海,金盛. 车辆跟驰行为建模的回顾与展望[J]. 中国公路学报,2012,25(1):115-127.
Wang Dian-hai, Jin Sheng. Review and outlook of modeling of car following behavior[J]. China Journal of Highway and Transport,2012,25(1):115-127.
[24] Punzo V, Ciuffo B, Montanino M. Can results of car-following model calibration based on trajectory data be trusted?[J]. Transportation Research Record: Journal of the Transportation Research Board,2012(2315):11-24.
[25] Kesting A,Treiber M. Calibrating car-following models by using trajectory data: Methodological study[J]. Transportation Research Record: Journal of the Transportation Research Board, 2008(2088):148-156.
[26] Saifuzzaman M, Zheng Z, Haque M M, et al. Revisiting the task-capability interface model for incorporating human factors into car-following models[J]. Transportation Research Part B: Methodological,2015,82:1-19.
[27] Brackstone M,McDonald M. Car-following: a historical review[J]. Transportation Research Part F: Traffic Psychology and Behaviour,1999,2(4):181-196.
[28] Brackstone M, Sultan B, McDonald M. Motorway driver behaviour:studies on car following[J]. Transportation Research Part F: Traffic Psychology and Behaviour,2002,5(1):31-46.
[29] 李振飞. 基于8自由度驾驶模拟器雾霾天气下跟驰行为研究[D]. 上海:同济大学交通运输工程学院,2015.
Li Zhen-fei. Car following behavior under haze weather: simulating by 8-degree-of-freedom high fidelity driving simulator[D]. Shanghai:College of Transportation Engineering,Tongji University,2015.
[1] 陈永恒,刘芳宏,曹宁博. 信控交叉口行人与提前右转机动车冲突影响因素[J]. 吉林大学学报(工学版), 2018, 48(6): 1669-1676.
[2] 常山,宋瑞,何世伟,黎浩东,殷玮川. 共享单车故障车辆回收模型[J]. 吉林大学学报(工学版), 2018, 48(6): 1677-1684.
[3] 曲大义,杨晶茹,邴其春,王五林,周警春. 基于干线车流排队特性的相位差优化模型[J]. 吉林大学学报(工学版), 2018, 48(6): 1685-1693.
[4] 宗芳, 齐厚成, 唐明, 吕建宇, 于萍. 基于GPS数据的日出行模式-出行目的识别[J]. 吉林大学学报(工学版), 2018, 48(5): 1374-1379.
[5] 刘翔宇, 杨庆芳, 隗海林. 基于随机游走算法的交通诱导小区划分方法[J]. 吉林大学学报(工学版), 2018, 48(5): 1380-1386.
[6] 钟伟, 隽志才, 孙宝凤. 不完全网络的城乡公交一体化枢纽层级选址模型[J]. 吉林大学学报(工学版), 2018, 48(5): 1387-1397.
[7] 刘兆惠, 王超, 吕文红, 管欣. 基于非线性动力学分析的车辆运行状态参数数据特征辨识[J]. 吉林大学学报(工学版), 2018, 48(5): 1405-1410.
[8] 宗芳, 路峰瑞, 唐明, 吕建宇, 吴挺. 习惯和路况对小汽车出行路径选择的影响[J]. 吉林大学学报(工学版), 2018, 48(4): 1023-1028.
[9] 栾鑫, 邓卫, 程琳, 陈新元. 特大城市居民出行方式选择行为的混合Logit模型[J]. 吉林大学学报(工学版), 2018, 48(4): 1029-1036.
[10] 陈永恒, 刘鑫山, 熊帅, 汪昆维, 谌垚, 杨少辉. 冰雪条件下快速路汇流区可变限速控制[J]. 吉林大学学报(工学版), 2018, 48(3): 677-687.
[11] 王占中, 卢月, 刘晓峰, 赵利英. 基于改进和声搜索算法的越库车辆排序[J]. 吉林大学学报(工学版), 2018, 48(3): 688-693.
[12] 李志慧, 胡永利, 赵永华, 马佳磊, 李海涛, 钟涛, 杨少辉. 基于车载的运动行人区域估计方法[J]. 吉林大学学报(工学版), 2018, 48(3): 694-703.
[13] 陈松, 李显生, 任园园. 公交车钩形转弯交叉口自适应信号控制方法[J]. 吉林大学学报(工学版), 2018, 48(2): 423-429.
[14] 苏书杰, 何露. 步行交通规划交叉路口行人瞬时动态拥塞疏散模型[J]. 吉林大学学报(工学版), 2018, 48(2): 440-447.
[15] 孟品超, 李学源, 贾洪飞, 李延忠. 基于滑动平均法的轨道交通短时客流实时预测[J]. 吉林大学学报(工学版), 2018, 48(2): 448-453.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 《吉林大学学报(工学版)》编辑部
地址：长春市人民大街5988号　电话：+86-431-85095297　传真：+86-431-85094074　E-mail: xbgxb@jlu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发