交通违法事故时空分布特征及其影响因素——以广州市为例
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摘要
为了深入研究我国城市交通事故的时空分布特征及其影响因素,通过对2010年广州市交通事故原始数据的处理与分析,结合GIS技术及系统聚类法,本文从道路特征,基础设施情况,以及白天和工作日交通事故比例等方面进行实证分析影响城市交通违法事故的风险因素;并在此基础上,结合广州市未来发展规划提出相关政策建议.结果表明:中心城区交通违法事故密集度最高,呈点状密集分布;交通违法事故的道路分布特征为干道多,支路少;上下班高峰时段,交通违法事故分布存在明显区别;从9个交通违法事故高发区域归纳出3大类区域,道路复杂、人多车多的商业地区,高速公路沿线和高架桥附近区域,以及设施齐全、出行方便的市中心.
Towards more in-depth research for temporal-spatial characteristics and potential influencing factors of traffic accidents in urban cities, this paper analyzes the traffic accident data of Guangzhou city in 2010. Using geographic information system(GIS) technique and hierarchical cluster analysis, this paper analyzes the risk factors associated with at-fault crashes, including characteristics of the road, infrastructure situation and the accident rate on weekdays and during the daytime. According to the analysis results and future development plan of Guangzhou, several proposals are put forward to improve the road safety situation in Guangzhou. Analysis results show that the highest incidence of at-fault crashes occurs in the central city with a spotty distribution. For road features, more at-fault crashes occur on main roads rather than on accessory ones, and the distribution of atfault accidents during the morning peak is significantly different from that during the afternoon peak. Through examining the identified nine crash hotspots in Guangzhou, this paper identifies three main patterns of at-fault crashes. The first one is the crowded business district with complex roads. The second one is close to expressways and trestles. The third one displays downtown characteristics including well-equipped facilities and convenient transportation.
Towards more in-depth research for temporal-spatial characteristics and potential influencing factors of traffic accidents in urban cities, this paper analyzes the traffic accident data of Guangzhou city in 2010. Using geographic information system(GIS) technique and hierarchical cluster analysis, this paper analyzes the risk factors associated with at-fault crashes, including characteristics of the road, infrastructure situation and the accident rate on weekdays and during the daytime. According to the analysis results and future development plan of Guangzhou, several proposals are put forward to improve the road safety situation in Guangzhou. Analysis results show that the highest incidence of at-fault crashes occurs in the central city with a spotty distribution. For road features, more at-fault crashes occur on main roads rather than on accessory ones, and the distribution of atfault accidents during the morning peak is significantly different from that during the afternoon peak. Through examining the identified nine crash hotspots in Guangzhou, this paper identifies three main patterns of at-fault crashes. The first one is the crowded business district with complex roads. The second one is close to expressways and trestles. The third one displays downtown characteristics including well-equipped facilities and convenient transportation.
引文
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[2]周素红,郑重,柳林.城市交通消散期事故高峰现象及成因[J].地理科学, 2012,32(6):649-657.[ZHOU S H, ZHENG Z, LIU L. Spatio-temporal analysis of peak traffic accidents in the city of Huizhou[J]. Scientia Geographica Sinica, 2012, 32(6):649-657.]
[3]马壮林,张宏璐,谭晓伟.高速公路连续下坡路段交通事故时空分布特征研究[J].中国安全科学学报,2014, 24(5):85-91.[MA Z L, ZHANG H L, TAN X W. Temporal-spatial distribution characteristics of traffic accidents on freeway continuous downgrade segment[J]. China Safety Science Journal, 2014, 24(5):85-91.]
[4] DE ANDRADE L, VISSOCI J R N, Rodrigues C G, et al.Brazilian road traffic fatalities:A spatial and environmental analysis[J]. PloS One, 2014, 9(1):e87244.
[5] YAO S, LOO B P Y, LAM W W Y. Measures of activitybased pedestrian exposure to the risk of vehiclepedestrian collisions:Space-time path vs potential path tree methods[J]. Accident Analysis&Prevention, 2015(75):320-332.
[6] ZHANG G N, YAU K W, CHEN G H. Risk factors associated with traffic violations and accident severity in China[J]. Accident Analysis and Prevention, 2013(59):18-25.
[7]邓敏,刘启亮,李光强,等.空间聚类分析及应用[M].北京:科学出版社, 2011.[DENG M, LIU Q L, LI G Q,et al. Spatial clustering analysis and application[M].Beijing:Science Press, 2011.]
[8]陈俊,蔡付斌,肖碧云.基于系统聚类的江西旅游发展研究[J].对外经贸, 2013(1):66-68.[CHEN J, CAI F B,XIAO B Y. Study of tourism industry in Jiangxi based on system clustering[J]. Foreign Economic Relations&Trade, 2013(1):66-68.]