Pedestrian crashes, making up a large proportion of road casualties, are more likely to occur at signalized intersections in China. This paper aims to study the different pedestrian behaviors of regular users, late starters, sneakers, and partial sneakers. Behavior information was observed manually in the field study. After that, the survey team distributed a questionnaire to the same participant who has been observed, to acquire detailed demographic and socioeconomic characteristics as well as attitude and preference indicators. Totally, 1878 pedestrians were surveyed at 16 signalized intersections in Nanjing. First, correlation analysis is performed to analyze each factor’s effect. Then, five latent variables including safety, conformity, comfort, flexibility, and fastness are obtained by structure equation modeling (SEM). Moreover, based on the results of SEM, a multinomial logit model with latent variables is developed to describe how the factors influence pedestrians’ behavior. Finally, some conclusions are drawn from the model: (1) for the choice of being late starters, arrival time, the presence of oncoming cars, and crosswalk length are the most important factors; (2) gender has the most significant effect on the pedestrians to be sneakers; and (3) age is the most important factor when pedestrians choose to be partial sneakers. 1. Introduction Due to high population density, rapid urbanization, and lack of adherence to traffic regulations by both drivers and pedestrians, traffic accidents involving pedestrians have become a major safety problem all over the world, particularly in developing countries. For example, in 2009, 16683 pedestrians were killed in traffic crashes in China, representing 24.62% of all traffic fatalities [1]. However, 4092 pedestrians were killed in traffic crashes, accounting for only 12.10% of the fatalities sustained in police-reported motor vehicle crashes in the US in 2009 [2]. Crashes involving pedestrians are most likely to occur when pedestrians are crossing roads, especially crossing at signalized intersections. In China, more than 50% of pedestrian crashes occurred at signalized intersections [1, 3]. However, illegal pedestrian behavior is common and widespread in China. Yang et al. claimed that, in developing cities like Xi’an, if a pedestrian is waiting at a signalized intersection, in most cases they are waiting for an acceptable gap in traffic and not for the green signal [4]. According to our study on the behaviors of 6628 pedestrians at 102 signalized crosswalks, the average compliance rate is only 62.8%.
References
[1]
TABC, Statistics of Road Traffic Accidents in China (2009), Traffic Administration Bureau of China State Security Ministry, Beijing, China, 2010.
[2]
National Highway Traffic Safety Administration, “Traffic safety facts 2006,” Report DOT HS 811 402, National Highway Traffic Safety Administration, Washington, DC, USA, 2009.
[3]
TABC, Statistics of Road Traffic Accidents in PR in China (2008), Traffic Administration Bureau of China, Ministry of Public Security, Beijing, China, 2009.
[4]
J. Yang, W. Deng, J. Wang, Q. Li, and Z. Wang, “Modeling pedestrians' road crossing behavior in traffic system micro-simulation in China,” Transportation Research A, vol. 40, no. 3, pp. 280–290, 2006.
[5]
G. Ren, Z. Zhou, W. Wang, Y. Zhang, and W. Wang, “Crossing behaviors of pedestrians at signalized intersections: observational study and survey in China,” Transportation Research Record, no. 2264, pp. 65–73, 2011.
[6]
J. Bergeron, J. P. Thouez, H. Bélanger, R. Bourbeau, D. Lord, and A. Rannou, “Study on conflicts among pedestrians and drivers,” in Proceedings of the 9th PRI World Congress, Madrid, Spain, 2002.
[7]
O. Keegan and M. O'Mahony, “Modifying pedestrian behaviour,” Transportation Research A, vol. 37, no. 10, pp. 889–901, 2003.
[8]
X. Chu, M. Guttenplan, and M. R. Baltes, “Why people cross where they do: the role of street environment,” in Transportation Research Record: Journal of Transportation Research Board, vol. 1878, pp. 3–10, Transportation Research Board of National Academics, Washington, DC, USA, 2004.
[9]
G. Tiwari, S. Bangdiwala, A. Saraswat, and S. Gaurav, “Survival analysis: pedestrian risk exposure at signalized intersections,” Transportation Research F, vol. 10, no. 2, pp. 77–89, 2007.
[10]
T. Rosenbloom, D. Nemrodov, and H. Barkan, “For heaven's sake follow the rules: pedestrians' behavior in an ultra-orthodox and a non-orthodox city,” Transportation Research F, vol. 7, no. 6, pp. 395–404, 2004.
[11]
M.-A. Granié, “Gender differences in preschool children's declared and behavioral compliance with pedestrian rules,” Transportation Research F, vol. 10, no. 5, pp. 371–382, 2007.
[12]
C. Holland and R. Hill, “The effect of age, gender and driver status on pedestrians' intentions to cross the road in risky situations,” Accident Analysis and Prevention, vol. 39, no. 2, pp. 224–237, 2007.
[13]
E. Moyano Díaz, “Theory of planned behavior and pedestrians' intentions to violate traffic regulations,” Transportation Research F, vol. 5, no. 3, pp. 169–175, 2002.
[14]
I. M. Bernhoft and G. Carstensen, “Preferences and behaviour of pedestrians and cyclists by age and gender,” Transportation Research F, vol. 11, no. 2, pp. 83–95, 2008.
[15]
M. M. Hamed, “Analysis of pedestrians' behavior at pedestrian crossings,” Safety Science, vol. 38, no. 1, pp. 63–82, 2001.
[16]
N. Guéguen and N. Pichot, “The influence of status on pedestrians' failure to observe a road-safety rule,” Journal of Social Psychology, vol. 141, no. 3, pp. 413–415, 2001.
[17]
D. C. Schwebel, J. Severson, K. K. Ball, and M. Rizzo, “Individual difference factors in risky driving: the roles of anger/hostility, conscientiousness, and sensation-seeking,” Accident Analysis and Prevention, vol. 38, no. 4, pp. 801–810, 2006.
[18]
D. A. Santor, D. Messervey, and V. Kusumakar, “Measuring peer pressure, popularity, and conformity in adolescent boys and girls: predicting school performance, sexual attitudes, and substance abuse,” Journal of Youth and Adolescence, vol. 29, no. 2, pp. 163–182, 2000.
[19]
T. Rosenbloom, “Crossing at a red light: Behaviour of individuals and groups,” Transportation Research F, vol. 12, no. 5, pp. 389–394, 2009.
[20]
R. Zhou, W. J. Horrey, and R. Yu, “The effect of conformity tendency on pedestrians' road-crossing intentions in China: an application of the theory of planned behavior,” Accident Analysis and Prevention, vol. 41, no. 3, pp. 491–497, 2009.
[21]
V. P. Sisiopiku and D. Akin, “Pedestrian behaviors at and perceptions towards various pedestrian facilities: an examination based on observation and survey data,” Transportation Research F, vol. 6, no. 4, pp. 249–274, 2003.
[22]
M. F. Yá?ez, S. Raveau, and J. D. D. Ortúzar, “Inclusion of latent variables in Mixed Logit models: modelling and forecasting,” Transportation Research A, vol. 44, no. 9, pp. 744–753, 2010.
[23]
T. A. Domencich and D. McFadden, Urban Travel Demand: A Behavioral Analysis, North-Holland, Amsterdam, The Netherlands, 1975.
[24]
M. E. Ben-Akiva, J. L. Walker, A. T. Bernardino, D. A. Gopinath, and T. Morikawa, “Integration of choice and latent variable models,” in Perpetual Motion: Travel Behavior Research Opportunities and Challenges, H. S. Mahmassani, Ed., Pergamon Press, Amsterdam, The Netherlands, 2002.
[25]
K. Ashok, W. R. Dillon, and S. Yuan, “Extending discrete choice models to incorporate attitudinal and other latent variables,” Journal of Marketing Research, vol. 39, no. 1, pp. 31–46, 2002.
[26]
M. Vredin Johansson, T. Heldt, and P. Johansson, “The effects of attitudes and personality traits on mode choice,” Transportation Research A, vol. 40, no. 6, pp. 507–525, 2006.