未按规定导向车道行驶行为干预方法研究
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摘要
为保障信号交叉口的正常交通秩序,充分遏制机动车未按规定导向车道行驶行为,亟需探究该行为的影响因素及干预方法。以北京市内4个信号交叉口处共35 h的1 666条监控视频数据为基础,对未按规定导向车道行驶行为进行定义并将其分为9类,分别对频率较高的5类未按规定导向车道行驶行为构建二元Logit模型,以确定其关键影响因素,并据此提出干预方法。结果表明,排队车辆数、大车比例、时段、车流量、照明条件等因素会不同程度地影响5类未按规定导向车道行驶行为的发生概率,其中排队车辆数及时间因素影响最为显著。在此基础上,从交通工程设施及驾驶人安全意识角度,提出优化交叉口渠化设计及信号配时、采用智能标线、强化监管力度及完善交通管控设施、加强驾驶人安全教育4种未按规定导向车道行驶行为干预方法。
The paper aims at presenting some intervention methods to deal with driving in the inaccurate oriented lane by playing back the video-1666 vehicle travelling records. The data can be extracted from a record of 35 hours' traffic surveillance video of the 4 signalized intersections in Beijing,based on which,the behavior of driving in the inaccurate oriented lane can be defined and divided into 9 categories. Among them,5 high frequency categories were put forward,including the left-turn and right-turn driving in the straight lane,the right-turn and straight driving in the non-motorized vehicle lane,and the straight driving in the left-turn lane. In the given paper,we have also developed a binary Logit model for the above mentioned 5 high frequency behaviors. Furthermore,we have suggested and well-prepared the corresponding intervention and prevention measures. The results show that,driving in the inaccurate oriented lane can be variously affected by the following factors,such as,the number of vehicles in a queue,the great number of heavy transportation vehicles,the time period and the traffic flow,the lighting conditions and others. And,particularly speaking,the number of vehicles in waiting line and time period are the most significant. In answering to the above influential factors in terms of the traffic control rules and the vehicular facilities,as well as the drivers' own safety awareness,the paper has proposed the following 4 intervention proposals,saying,the optimized channelization layout and the precise signal-indicating alteration at the signal-indicating alternating spots,which can help to reduce and even eliminate the impact of a great number of queued vehicles. Intelligent layout of the proper markings can also help greatly to adjust the direction of the guiding lanes as to the regard of the traffic flow during different travelling hours of a day. Besides,it is also possible to reduce the traffic violation liabilities,for example,by regulating the lighting conditions,setting necessary artificial sensors,installing the needed barriers between the motorized and non-motorized vehicle lanes,and so on. Furthermore,it is also essential to strengthen the safety education of the vehicle drivers as well as the road-across travelers to heighten their traffic safety consciousness. Thus,the aforementioned findings can be expected to provide a theoretical foundation for preventing the motorized vehicles from driving the inaccurate oriented lane and improving the traffic order at the signalized intersections.
The paper aims at presenting some intervention methods to deal with driving in the inaccurate oriented lane by playing back the video-1666 vehicle travelling records. The data can be extracted from a record of 35 hours' traffic surveillance video of the 4 signalized intersections in Beijing,based on which,the behavior of driving in the inaccurate oriented lane can be defined and divided into 9 categories. Among them,5 high frequency categories were put forward,including the left-turn and right-turn driving in the straight lane,the right-turn and straight driving in the non-motorized vehicle lane,and the straight driving in the left-turn lane. In the given paper,we have also developed a binary Logit model for the above mentioned 5 high frequency behaviors. Furthermore,we have suggested and well-prepared the corresponding intervention and prevention measures. The results show that,driving in the inaccurate oriented lane can be variously affected by the following factors,such as,the number of vehicles in a queue,the great number of heavy transportation vehicles,the time period and the traffic flow,the lighting conditions and others. And,particularly speaking,the number of vehicles in waiting line and time period are the most significant. In answering to the above influential factors in terms of the traffic control rules and the vehicular facilities,as well as the drivers' own safety awareness,the paper has proposed the following 4 intervention proposals,saying,the optimized channelization layout and the precise signal-indicating alteration at the signal-indicating alternating spots,which can help to reduce and even eliminate the impact of a great number of queued vehicles. Intelligent layout of the proper markings can also help greatly to adjust the direction of the guiding lanes as to the regard of the traffic flow during different travelling hours of a day. Besides,it is also possible to reduce the traffic violation liabilities,for example,by regulating the lighting conditions,setting necessary artificial sensors,installing the needed barriers between the motorized and non-motorized vehicle lanes,and so on. Furthermore,it is also essential to strengthen the safety education of the vehicle drivers as well as the road-across travelers to heighten their traffic safety consciousness. Thus,the aforementioned findings can be expected to provide a theoretical foundation for preventing the motorized vehicles from driving the inaccurate oriented lane and improving the traffic order at the signalized intersections.
引文
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[20] QIAN Hongbo(钱红波),HAN Hao(韩皓). Influence of countdown of green signal on traffic safety at crossing[J]. China Safety Science Journal(中国安全科学学报),2010,20(3):9-13.
[21] WANG Yan(王岩),YANG Xiaoguang(杨晓光). Discussion on setting traffic signals with counting down display unit at intersection based on traffic safety[J]. China Safety Science Journal(中国安全科学学报),2006,16(3):55-70.
[22] QIAN Hongbo(钱红波),LI Keping(李克平). Study on the influence of traffic light intervals on the crossing traffic[J]. China Safety Science Journal(中国安全科学学报),2008,18(6):166-169.
[23] XU Liangjie(徐良杰),LIU Zhi(刘志). Improving the guidance system of intersections based on lane selection[J]. Journal of East Jiaotong University(华东交通大学学报),2018,35(1):14-19.
[24] LI Can(李灿),ZHAO Xin(赵欣). Study on threshold condition of variable steering lane at signal intersection[J]. Journal of Wuhan University of Technology:Traffic Science and Engineering(武汉理工大学学报:交通科学与工程版),2016,40(6):1078-1082.
[2] WANG Y,CHEN K,PEI Y,et al. Integrating before and after crash features into measuring the effectiveness of intersection safety improvement project in Harbin[J].Transport,2011,26(1):111-120.
[3] LIU Zhiqiang(刘志强),GONG Biao(龚标). Statue and countermeasure of traffic safety of China[J]. Journal of Safety and Environment(安全与环境学报),2004,4(6):76-78.
[4] ZHOU S,SUN Z,LI K P,et al. Development of a root cause degree procedure for measuring intersection safety factors[J]. Safety Science,2013,51(1):257-266.
[5] Road Traffic Safety Research Center of the Ministry of Public Security(公安部道路交通安全研究中心). Research report on road traffic development in large cities of China No. 4(中国大城市道路交通发展研究报告之四)[M]. Beijing:China Building Industry Press,2018:73.
[6] ATTIYAH M. Characteristics of red light running violations in urban areas in Tabuk,Kingdom of Saudi Arabia[J]. IATSS Research,2014,37(2):119-123.
[7] BLAZEJ P,PATRICIA D. A simulator study of factors influencing drivers’behavior at traffic lights[J]. Transportation Research Part F:Traffic Psychology and Behaviour,2016,37:107-118.
[8] NOOR E,YAN X,ESSAM R,et al. Classification analysis of driver’s stop/go decision and red-light running violation[J]. Accident Analysis and Prevention,2010,42(1):101-111.
[9] LUM K,TAN Y. Driver response at a signalized T-intersection during an amber blackout[J]. Transportation Research Part F:Traffic Psychology and Behaviour,2003,6(3):183-195.
[10] LIU Yan(刘岩),FU Chuanyun(付川云). Classification and characteristic analysis of red light running behaviors of motorized vehicles[J]. Journal of Kunming University of Science and Technology:Natural Science(昆明理工大学学报:自然科学版),2018,43(4):115-123.
[11] PAPAIOANNOU P. Driver behaviour,dilemma zone and safety effects at urban signalised intersections in Greece[J]. Accident Analysis and Prevention,2007,39(1):147-158.
[12] LU G Q,WANG Y P,WU X K,et al. Analysis of yellow-light running at signalized intersections using high-resolution traffic data[J]. Transportation Research Part A:Policy and Practice,2015,73:39-52.
[13] CAO Yi(曹弋),YANG Zhongzhen(杨忠振),ZUO Zhongyi(左忠义). Influence of countdown signal of green light on driving behavior[J]. China Safety Science Journal(中国安全科学学报),2015,25(2):77-82.
[14] MCCARTT A,HU W. Effects of red light camera enforcement on red light violations in Arlington County,Virginia[J]. Journal of Safety Research,2014,48:57-62.
[15] LIN X,CHENG L. Engineering countermeasures to reducing unintentional yellow-light running owing to dilemma zone[J]. Procedia—Social and Behavioral Science,2013,96:900-904.
[16] CONTINI L,BASYOUNY K. Lesson learned from the application of intersection safety devices in Edmonton[J]. Accident Analysis and Prevention,2016,94:127-134.
[17] YOH K,OKAMOTO T,INOI H,et al. Comparative study on foreign drivers'characteristics using traffic violation and accident statistics in Japan[J]. IATSS Research,2017,41(2):94-105.
[18] SCHIROKOFF A,SIHVOLA EP,SIHVOLA N. Assessing the safety impacts of intersection safety system[J].Procedia—Social and Behavioral Science,2012,48:1515-1524.
[19] ISLAM M,WYMAN A,HURWITZ D. Safer driver responses at intersections with green signal countdown timers[J]. Transportation Research Part F:Traffic Psychology and Behaviour,2017,51:1-13.
[20] QIAN Hongbo(钱红波),HAN Hao(韩皓). Influence of countdown of green signal on traffic safety at crossing[J]. China Safety Science Journal(中国安全科学学报),2010,20(3):9-13.
[21] WANG Yan(王岩),YANG Xiaoguang(杨晓光). Discussion on setting traffic signals with counting down display unit at intersection based on traffic safety[J]. China Safety Science Journal(中国安全科学学报),2006,16(3):55-70.
[22] QIAN Hongbo(钱红波),LI Keping(李克平). Study on the influence of traffic light intervals on the crossing traffic[J]. China Safety Science Journal(中国安全科学学报),2008,18(6):166-169.
[23] XU Liangjie(徐良杰),LIU Zhi(刘志). Improving the guidance system of intersections based on lane selection[J]. Journal of East Jiaotong University(华东交通大学学报),2018,35(1):14-19.
[24] LI Can(李灿),ZHAO Xin(赵欣). Study on threshold condition of variable steering lane at signal intersection[J]. Journal of Wuhan University of Technology:Traffic Science and Engineering(武汉理工大学学报:交通科学与工程版),2016,40(6):1078-1082.