Study on motorcycle drivers' intention to run red light

doi:10.16265/j.cnki.issn1003-3033.2018.02.004

Abstract

Abstract: In order to improve the road safety, this paper studies red light running behavior intentions of motorcycle users by employing TPB. A survey questionnaire was designed and 160 valid responses were received. Best subset method was used to gain a best variable subset including attitude, perceived risk, past behavior, anticipated affect, license status and history of traffic accidents. Hierarchical regression was constructed to understand the explanatory power of the best subset with respect to red light running behavior intention, and related traffic safety interventions were presented. The results revealed that the best subset can explain 29.6% of the variance of the intention, attitude has the most significant positive effect on the intention, perceived risk has a significant negative effect on intention, and past behavior and license status also have significant positive effects at 0.1 signicance level, and that traffic safety intervention measures should be formulated by focusing on attitude and perceived risk of motorcycle users towards RLR behavior and regulations coming from traffic management departments.

Key words: traffic safety, theory of planned behavior(TPB), motorcycle, red light running behavior intention, best subset selectio

CLC Number:

X910

YANG Hongtai, SU Fan, LIU Xiaohan, PU Li, LI Yanlai, LIU Yugang. Study on motorcycle drivers' intention to run red light[J]. China Safety Science Journal, 2018, 28(2): 21-27.

References

[1] 三成交通事故祸起摩托车且今年以来已死亡230人[EB/OL]. [2013-05-29]. http://roll.sohu.com/20130529/n377344098.shtml.
[2] 邹铁方,刘雨,李平凡,等. 汽车-摩托车碰撞事故车速及碰撞位置预估方法[J].中国安全科学学报, 2015, 25(1): 105-110.
ZOU Tiefang,LIU Yu,LI Pingfan,et al. A method for evaluating impact velocity and impact position in car-motorcycle accidents[J]. China Safety Science Journal, 2015, 25(1): 105-110.
[3] 李春阳,赵海深,黄合来. 摩托车驾驶员伤害程度影响因素分析[J]. 伤害医学:电子版, 2016, 5(1): 30-35.
LI Chunyang, ZHAO Haishen, HUANG Helai. The factors influencing the severity of injured motorcycle drivers[J]. Injury Medicine: Electronic Edition, 2016, 5(1): 30-35.
[4] 李彦章. 重庆市摩托车事故特点及心理影响因素研究[D].重庆: 第三军医大学, 2006.
LI Yanzhang. Characters of motorcycle crashes and psychological factors influencing motorcyclists in Chongqing city[D]. Chongqing: Third Military Medical University, 2006.
[5] CHORLTON K, CONNER M, JAMSON S. Identifying the psychological determinants of risky riding: an application of an extended theory of planned behaviour[J]. Accident Analysis & Prevention, 2012, 49: 142-153.
[6] EVANS D,NORMAN P. Predicting adolescent pedestrians' road-crossing intentions: an application and extension of the theory of planned behaviour[J]. Health Education Research, 2003, 18(3): 267-277.
[7] ZHOU Ronggang, HORREY W J, YU Ruifeng. The effect of conformity tendency on pedestrians' road-crossing intentions in China: an application of the theory of planned behavior[J]. Accident Analysis & Prevention, 2009, 41(3): 491-497.
[8] ZHOU Hongmei, ROMERO S B, QIN Xiao. An extension of the theory of planned behavior to predict pedestrians' violating crossing behavior using structural equation modeling[J]. Accident Analysis & Prevention, 2016, 95(10): 417-424.
[9] 曹慧娟, 古仁华, 姚舒仪, 等. “中国式过马路”行为意向成因分析及预测[J]. 中国安全科学学报, 2014, 24(11): 47-52.
CAO Huijuan, GU Renhua, YAO Shuyi, et al. An analysis and prediction of behavioral intention of Chinese style of crossing road[J]. China Safety Science Journal, 2014, 24(11): 47-52.
[10] ZHOU Ronggang, HORREY W J. Predicting adolescent pedestrians' behavioral intentions to follow the masses in risky crossing situations[J]. Transportation Research Part F Traffic Psychology & Behavior, 2010, 13(3): 153-163.
[11] MOAN I S,RISE J. Predicting intentions not to “drink and drive” using an extended version of the theory of planned behavior [J]. Accident Analysis & Prevention, 2011, 43(4): 1 378-1 384.
[12] ELLIOTT M A. Testing the capacity within an extended theory of planned behavior to reduce the commission of driving violations [J]. Transportmetrica, 2012, 8(5): 321-343.
[13] ALI M, SAEED M M, ALI M M, et al. Determinants of helmet use behavior among employed motorcycle riders in Yazd, Iran based on theory of planned behavior[J]. Injury-International Journal of the Care of the Injured, 2011, 42(9): 864-869.
[14] AJZEN I. The theory of planned behavior[J]. Research in Nursing & Health, 1991, 14(2): 137-144.
[15] ARMITAGE C J,CONNER M. Extending the theory of planned behavior: a review and avenues for further research[J]. Journal of Applied Social Psychology, 1998, 28(15): 1 429-1 464.
[16] JAMES G, WITTEN D, HASTIE T, et al. An introduction to statistical learning: with applications in R[M]. New York: Springer, 2014: 205-251.
[17] FORWARD S E. The theory of planned behavior: the role of descriptive norms and past behavior in the prediction of drivers' intentions to violate[J]. Transportation Research Part F Traffic Psychology & Behavior, 2009, 12(3): 198-207.