Study on formation mechanism of blind spot for truck turning right and safety of intersection

doi:10.16265/j.cnki.issn1003-3033.2017.05.018

Abstract

Abstract: In order to explore the formation mechanism of truck drivers' blind area when the truck is turning right, and the influence of truck turning right on safety of the road intersection, a right-turn model was built by using the Matlab software. Based on analyzing the characteristics of truck's inner wheel difference, the results of test of model car and results of large trucks turning tests, and fixing trajectory turning, the turning process of truck was simulated accurately. A method was worked out for calculating the visual blind area. A index was putforward for road intersection safety evaluation. A truck right-turn blind spot area based evaluation of safety was made for right-turn separation, slow turn interaction and sharp turn interaction. The results show that the blind area is 40.39 m² for six-axle truck turning right, and that right-turn separation crossing has higher safety.

Key words: heavy truck, visual blind spot, simulation track, mechanization, intersection evaluation

CLC Number:

X913.4

WANG Qingzhou, XU Lingxuan, FAN Xin, GUO Kai. Study on formation mechanism of blind spot for truck turning right and safety of intersection[J]. China Safety Science Journal, 2017, 27(5): 99-104.

References

[1] 公安部交管局.部分货车车型违规生产问题突出货车运输安全隐患严重[EB/OL].(2017-01-17). http://www.mps.gov.cn/.
Traffic Management Bureau of The Public Security Ministry. The problem of part of vehicle models drived against traffic regulations is obvious and latent danger of truck transportation is serious[EB/OL]. (2017-01-17). http://www.mps.gov.cn/.
[2] 吴佳林,孔军. 汽车后视镜盲区及预测方法[J]. 武汉理工大学学报:信息与管理工程版,2010, 32(6):958-961.
WU Jialin, KONG Jun. Blind area and prediction method of automobile' rearview mirror[J]. Journal of Wuhan University of Technology:Information& Management Engineering, 2010, 32(6):958-961.
[3] PITCHIPOO P, VINCENT D S, RAJINI N, et al. COPRAS decision model to optimize blind spot in heavy vehicles: a comparative perspective [J]. Procedia Engineering, 2014, 97: 1 049-1 059.
[4] BLOWER D.Truck mirrors, fields of view, and serious truck crashes[R]. University of Michigan, Transportation Research Institute, 2007.
[5] 曹瑾鑫,高志军. 城市道路交叉口机动车与非机动车冲突和仿真研究[J]. 中国安全科学学报,2015,25(6):29-34.
CAO Jinxin, GAO Zhijun. Research on conflicts between motor and non-motor vehicles at city road intersection and simulation of improvement measures [J]. China Safety Science Journal, 2015, 25(6):29-34.
[6] 褚正清,刘家保,宋星. 货车右转弯内轮差的建模研究[J]. 河北北方学院学报:自然科学版,2015,31(5):49-52.
CHU Zhengqing, LIU Jiabao, SONG Xing. Modeling study on inner wheel difference for truck turning right[J]. Journal of Hebei North University:Natural Science Edition, 2015,31(5):49-52.
[7] 孙国君. 基于大货车转向轮差面积的估算及安全分析[J]. 自动化与仪器仪表,2016,36(3):98-99.
SUN Guojun. Estimation and safety analysis of blind area based on large truck turning[J]. Automation & Instrumentation, 2016, 36(3):98-99.
[8] 陈思嘉,巫宇霞,杨平. 汽车转弯时由内轮差引发的交通事故原因建模与分析[J]. 数学通报,2013,52(12):55-57.
CHEN Sijia, WU Yuxia, YANG Ping. Modeling and analysis of traffic accidents caused by internal wheel deviation in vehicle turning[J]. Mathematical Bulletin, 2013, 52(12):55-57.
[9] 范朔. 车辆内轮差问题的优化分析[J]. 科技视界,2016(9):32-34.
FAN Shuo.Optimal analysis of inner wheels difference [J]. Science & Technology Vision, 2016(9): 32-34.
[10] 白子建, 王晓华, 赵巍. 车辆转弯轮差对交叉口缘石设计的影响研究[C].科技创新绿色交通:第十一次全国城市道路交通学术会议论文集,2011:117-120.
BAI Zijian, WANG Xiaohua, ZHAO Wei. Study on the influence of vehicle turning wheel difference differential on intersection curb design[C]. Green Transportation of Science and Technology Innovation:Proceedings of the 11^th National Conference on Urban Road Traffic, 2011:117-120.
[11] 张清峰. 大型车右转弯车祸频发现象分析及对策研究[J]. 铁道建筑技术,2014,31(12):90-94.
ZHANG Qingfeng. Analysis and countermeasure research on the frequent phenomenon of the right turn traffic accident in large scale vehicle[J]. Railway Construction Technology, 2014,31(12):90-94.

[1]	WANG Tiedan, MU Yiqiang, PENG Dinghong. Hesitant fuzzy method with variable weight for HAZOP risk sorting [J]. China Safety Science Journal, 2022, 32(5): 61-67.
[2]	PENG Yaxiong, LIU Guangjin, HUANG Zhigang, LYU Hubo, WU Li. Study on catastrophe instability criterion of surrounding rock in tunnels blasting crossing water-rich fault zones [J]. China Safety Science Journal, 2022, 32(5): 104-111.
[3]	LIU Jiahao, YU Yang, ZHANG Zhenxing, YU Jianxing, WANG Weiwei, FU Yiqin. Risk assessment method of risers based on two-dimensional cloud model and BN [J]. China Safety Science Journal, 2022, 32(5): 147-154.
[4]	LYU Zhen, QI Chunhua, ZHU Shoulin. Dynamic visual characteristics and load of drivers during overtaking maneuvers on prairie highways [J]. China Safety Science Journal, 2022, 32(4): 15-22.
[5]	HU Xiaobing, LI Jiaru, LIU Chengyue, LI Hang, ZHOU Hang. An improved betweenness for importance assessment of network nodes and links [J]. China Safety Science Journal, 2022, 32(3): 33-40.
[6]	LUO Fuzhou, YUAN Huiqing, ZHANG Yang. Assessment on fire safety resilience of old industrial building regeneration projects [J]. China Safety Science Journal, 2022, 32(3): 167-173.
[7]	LUO Zhengshan, DUAN Yuanzhe, WANG Xiaowan, ZHANG Xinsheng. Evaluation on sealing performance of mudstone caprocks of gas reservoir-type gas storage in high temperature environment [J]. China Safety Science Journal, 2022, 32(2): 74-82.
[8]	ZHANG Ge. Pneumoconiosis risk assessment method based on cumulative dust exposure [J]. China Safety Science Journal, 2022, 32(2): 200-206.
[9]	SHI Juan, CHANG Dingyi, ZHENG Peng. An early warning model of unsafe behaviors of construction workers based on BP neural network [J]. China Safety Science Journal, 2022, 32(1): 27-33.
[10]	LIU Zhuofan, ZHOU Xingchi, LIU Tong, WU Fuwei. Impact of visual distraction degree on car following state [J]. China Safety Science Journal, 2022, 32(1): 58-64.
[11]	SONG Yinghua, BAI Mingxuan, MA Yaping, LYU Wei, HUO Feizhou. Optimal model for fair dispatch of emergency materials considering regional disaster classification [J]. China Safety Science Journal, 2022, 32(1): 172-179.
[12]	YANG Tianzi, WANG Tieli, PENG Hengming, DUAN Hailin. Evaluation on emergency response vulnerability for work safety accidents in small and micro enterprises [J]. China Safety Science Journal, 2021, 31(12): 176-183.
[13]	YU Jianxing, FAN Haizhao, CHEN Haicheng, WU Shibo, HAN Fang, LIU Shaoqing. Risk factors analysis method of marine riser failure and its application [J]. China Safety Science Journal, 2021, 31(11): 47-53.
[14]	SONG Yinghua, WANG Yaxin, MA Yaping, LYU Wei. Research on multi-mode cooperative emergency evacuation scheduling considering types of disaster victims [J]. China Safety Science Journal, 2021, 31(11): 135-140.
[15]	YAN Hongqiao, CHEN Yiyue, TIAN Kun, HU Jinqiu, MAO Yaming, ZHOU Jingtong. Research on key index system and risk evaluation model of enterprise work safety [J]. China Safety Science Journal, 2021, 31(9): 21-28.