TY - GEN
T1 - Analysis on the Impact of Illegal Driver Behaviors on Road Traffic Accidents Case Study on China
AU - Li, Xia
AU - Zhuge, Chengxiang
AU - Yu, Bingying
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Road traffic accidents in China result in more than 50,000 fatalities annually. There are many risk factors that are related to accidents, loss of lives and heavy property damage. Driver behavior was universally accepted as main reason for road traffic accidents. This paper aims to assess the impact of illegal driver behaviors on road traffic accidents with statistical data in China. Firstly, the correlation between different factors resulted in road accidents and four indices of road accident is analyzed. Secondly, the statistical indicators of road traffic accidents such as accident numbers, fatality, injury, and direct economic loss are recognized as independent variables and the statistical number of road accidents caused by 13 types of illegal driver behaviors is taken as independent variables; and then partial least square regression was used to analyze the relationship between them. Results show that refusal to give a way to others; illegal reverse, illegal parking, drunk driving, and speeding are identified as high risk behaviors.
AB - Road traffic accidents in China result in more than 50,000 fatalities annually. There are many risk factors that are related to accidents, loss of lives and heavy property damage. Driver behavior was universally accepted as main reason for road traffic accidents. This paper aims to assess the impact of illegal driver behaviors on road traffic accidents with statistical data in China. Firstly, the correlation between different factors resulted in road accidents and four indices of road accident is analyzed. Secondly, the statistical indicators of road traffic accidents such as accident numbers, fatality, injury, and direct economic loss are recognized as independent variables and the statistical number of road accidents caused by 13 types of illegal driver behaviors is taken as independent variables; and then partial least square regression was used to analyze the relationship between them. Results show that refusal to give a way to others; illegal reverse, illegal parking, drunk driving, and speeding are identified as high risk behaviors.
KW - illegal driver behavior
KW - partial least square
KW - road traffic accidents
KW - traffic safety
UR - http://www.scopus.com/inward/record.url?scp=85078316142&partnerID=8YFLogxK
U2 - 10.1109/IHMSC.2019.00065
DO - 10.1109/IHMSC.2019.00065
M3 - Conference contribution
AN - SCOPUS:85078316142
T3 - Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019
SP - 250
EP - 253
BT - Proceedings - 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2019
Y2 - 24 August 2019 through 25 August 2019
ER -
