Factors Associated with Traffic Violations and Accident Severity in China

Transcription

1 Factors Associated with Traffic Violations and Accident Severity in China Accident Analysis & Prevention 59, 1825, Guangnan Zhang et al. Associate Professor, Sun Yatsen University, Guangzhou, China Mobile:

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3 Rank in Category: Accident Analysis & Prevention

4 Table of Content Background Database Methodology: Logistic Regression Model Result: Adjusted Odds Ratios Higher Risk of BOTH Violations AND Severity Higher Risk of EITHER Violations OR Severity Projects in Progress

5 Background Economy and use of automobiles boom in China Traffic accidents: leading cause of death 65,225 deaths (2010) USD 143 million in direct property losses

6 Q: Factors Associated with Traffic Violations and Accident Severity in China?

7 Database Period in Guangdong Province, China. Case Report from Guangdong Provincial Public Safety Department By the traffic police who conducted onscene assessments Provided feedback within 24 hours Why using Guangdong province data? Important and urgent: traffic accident are the highest Representative: highest percent (30%) of floating population Prospective: Pioneer of national reform Contain 7722, 7511, 7459, 7261 and 7387 annual samples from respectively. The only officially available, most detailed, abundant and reliable source of traffic crash data in China.

8 Methodology: Logistic Regression Model Dependent variables: traffic violation serious injury/fatality '1' = yes and '0' = no Risk factors: Human Vehicle Road Environment Table: Adjusted odds ratios in stepwise logistic regression

9 Higher Risk of BOTH Violations AND Severity

10 HUMAN Factors Driver s gender (base: female) Traffic Violations Serious Injury/Fatality Male Driver s age (base: 56) Driver s driving experience (base: 21) Driver s hukou origin (base: urban hukou) Rural hukou Driver s occupation (base: farmers) Military and police General staffs Workers Civil servants Selfemployed Migrant workers Unemployed Other occupations

11 VEHICLE Factors Vehicle type (base: motor cycles) Private vehicles Goods vehicles Traffic Violations Serious Injury/Fatality Vehicle safety status (base: fit safety statue) Unfit safety statue Vehicle overload condition (base: not overload) Overload Whether the vehicle had any compulsory third party insurance (base: no) Yes Whether the vehicle was a commercial vehicle (base: no) Yes

12 ROAD Factors Traffic Violations Serious Injury/Fatality Types of traffic lanes (base: other lanes) Sharedlanes Road type (base: the first class highways) Expressways Secondclass highways Thirdclass highways Fourthclass highways Fifthclass highways Urban expressways Urban ordinary highways Urban other highways

13 ENVIORMENT Factors Streetlight condition (base: daylight) Good streetlighting No streetlighting Traffic Violations Serious Injury/Fatality Weather condition (base: good) Bad weather Visibility level (base: good) Bad visibility Whether it was a weekend (base: no) Yes Whether it was a public holiday (base: no) Yes Time (base: 9:0011:59) 00:006:59 07:008:59 12:0016:59 17:0019:59 20:0023:59 Seasons (base: autumn) Spring Summer Winter

14 Higher Risk of EITHER Violations OR Severity

15 HUMAN Factors Driver s gender (base: female) Traffic Violations Serious Injury/Fatality Male Driver s age (base: 56) Driver s driving experience (base: 21) Driver s hukou origin (base: urban hukou) Rural hukou Driver s occupation (base: farmers) Military and police General staffs Workers Civil servants Selfemployed Migrant workers Unemployed Other occupations

16 VEHICLE Factors Vehicle type (base: motor cycles) Private vehicles Goods vehicles Traffic Violations Serious Injury/Fatality Vehicle safety status (base: fit safety statue) Unfit safety statue Vehicle overload condition (base: not overload) Overload Whether the vehicle had any compulsory third party insurance (base: no) Yes Whether the vehicle was a commercial vehicle (base: no) Yes

17 ROAD Factors Traffic Violations Serious Injury/Fatality Types of traffic lanes (base: other lanes) Sharedlanes Road type (base: the first class highways) Expressways Secondclass highways Thirdclass highways Fourthclass highways Fifthclass highways Urban expressways Urban ordinary highways Urban other highways

18 ENVIORMENT Factors Streetlight condition (base: daylight) Good streetlighting No streetlighting Traffic Violations Serious Injury/Fatality Weather condition (base: good) Bad weather Visibility level (base: good) Bad visibility Whether it was a weekend (base: no) Yes Whether it was a public holiday (base: no) Yes Time (base: 9:0011:59) 00:006:59 07:008:59 12:0016:59 17:0019:59 20:0023:59 Seasons (base: autumn) Spring Summer Winter

19 Factors Years (base: 2006) Traffic Violations Serious Injury/Fatality Traffic violations (base: other traffic violations behaviors) Speeding Drunkdriving Illegal meeting Not giving way according to stipulations NA NA NA NA Model prediction measures r(p_corr) ROC N

20 Projects in Progress 1. Guangnan Zhang, Kelvin K.W. Yau, Xiangpu Gong, Traffic violations in Guangdong Province of China: Speeding and drunk driving. Accident Analysis & Prevention(SSCI), Volume 64, 2014, Guangnan Zhang, Guangzhong Li, Tiancheng Cai, David M. Bishai, Changxu Wu, Zeyi Chan, Factors contributing to hitandrun crashes in China, Transportation Research Part F: Traffic Psychology and Behaviour(SSCI), Volume 23, March 2014, Guangnan Zhang, Kelvin K.W. Yau, Xun Zhang, Analyzing fault and severity in pedestrian motor vehicle accidents in China, Accident Analysis & Prevention(SSCI), Volume 73, 2014, Guangnan Zhang, Kelvin K.W. Yau, Xun Zhang, Yanyan Li, Traffic Accidents Caused by Fatigue Driving and Their Extent of Casualties, Guangnan Zhang, Yanyan Li, Mark J. King, Risk factors and impacts of vehicle overloading in China, SYSU WORKING PAPER, Guangnan Zhang, Ying Tan, RongChang Jou, Factors Influencing Traffic Signal Violations by Car Drivers, Bicyclists, and Pedestrians in China, 2015

21 Risk factors and impacts of vehicle overloading in China Guangnan Zhang, Yanyan Li, Mark J. King Based on the 7,984 accidents recorded during provided by the Traffic Management Bureau, Ministry of Public Security, PRC, we analyzed the effects of driver characteristics, vehicle characteristics, road characteristics and environment characteristics on overloading behavior and the resulting casualties using the logistic model. Our results reveal that vehicles driven by 2635yearold males from rural households and factors such as vehicles with unsafe conditions, nonfirstclass highways, and mountain areas are likely to be overloaded and involved in accidents with severe casualties. In addition, if overloaded vehicles speed, the risk of severe accident casualties increases.

22 A Comprehensive Database to Explore 4. Accident Type 11headon collision 12side collision 90bump against animals 28.Injured Position 1head 2neck 7multiple position 5. Scene of the Accident 1unaltered 3hit and run 6secondary site 29.Cause of Death 1craniocerebral injury 2belly injury 5burned

23 Looking Forward to Collaborating with You!

24 Factors Associated with Traffic Violations and Accident Severity in China Accident Analysis & Prevention 59, 1825, Guangnan Zhang et al. Associate Professor, Sun Yatsen University, Guangzhou, China Mobile: