Pedestrian gap acceptance for mid-block street crossing

Abstract This paper investigates pedestrians' traffic gap acceptance for mid-block street crossing in urban areas. A field survey was carried out at an uncontrolled mid-block location in Athens, Greece. Pedestrians' decisions and traffic conditions were videotaped in terms of the size of traffic gaps rejected or accepted, waiting times and crossing attempts and vehicle speeds. A lognormal regression model was developed to examine pedestrian gap acceptance. It was found that gap acceptance was better explained by the distance from the incoming vehicle, rather than its speed. Other significant effects included illegal parking, presence of other pedestrians and incoming vehicles’ size. A binary logistic regression model was developed to examine the effect of traffic gaps and other parameters on pedestrians' decisions to cross the street or not. The results reveal that this decision is affected by the distance from the incoming vehicles and the waiting times of pedestrians.

[1]  Julian Hine,et al.  Traffic barriers and pedestrian crossing behaviour , 1993 .

[2]  R B Isler,et al.  Child pedestrians' crossing gap thresholds. , 1998, Accident; analysis and prevention.

[3]  Ross H Day,et al.  Crossing roads safely: an experimental study of age differences in gap selection by pedestrians. , 2005, Accident; analysis and prevention.

[4]  Charles F. Manski,et al.  Walk or wait? An empirical analysis of street crossing decisions , 2005 .

[5]  John van der Kamp,et al.  Visual timing and adaptive behavior in a road-crossing simulation study. , 2005, Accident; analysis and prevention.

[6]  Mark D. Uncles,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1987 .

[7]  M. Hamed Analysis of pedestrians’ behavior at pedestrian crossings , 2001 .

[8]  Carol Holland,et al.  The effect of age, gender and driver status on pedestrians' intentions to cross the road in risky situations. , 2007, Accident; analysis and prevention.

[9]  Viola Cavallo,et al.  Age-related differences in street-crossing decisions: the effects of vehicle speed and time constraints on gap selection in an estimation task. , 2007, Accident; analysis and prevention.

[10]  Timothy C. Coburn,et al.  Statistical and Econometric Methods for Transportation Data Analysis , 2004, Technometrics.

[11]  F Mannering,et al.  Analysis of injury severity and vehicle occupancy in truck- and non-truck-involved accidents. , 1999, Accident; analysis and prevention.

[12]  G. Tiwari,et al.  Survival analysis: Pedestrian risk exposure at signalized intersections , 2007 .

[13]  Yair Mundlak,et al.  Estimation in Lognormal Linear Models , 1970 .

[14]  Michael R. Baltes,et al.  Pedestrian Level of Service for Midblock Street Crossings , 2002 .

[15]  C. Daganzo Estimation of gap acceptance parameters within and across the population from direct roadside observation , 1981 .

[16]  B Fildes,et al.  Differences in traffic judgements between young and old adult pedestrians. , 1997, Accident; analysis and prevention.

[17]  George Yannis,et al.  A critical assessment of pedestrian behaviour models , 2009 .

[18]  M. King,et al.  Illegal pedestrian crossing at signalised intersections: incidence and relative risk. , 2009, Accident; analysis and prevention.

[19]  Carol Holland,et al.  Gender differences in factors predicting unsafe crossing decisions in adult pedestrians across the lifespan: a simulation study. , 2010, Accident; analysis and prevention.

[20]  Lucy Johnston,et al.  An investigation of road crossing in a virtual environment. , 2003, Accident; analysis and prevention.

[21]  Gudmundur F. Ulfarsson,et al.  Differences in male and female injury severities in sport-utility vehicle, minivan, pickup and passenger car accidents. , 2004, Accident; analysis and prevention.

[22]  Fred L. Mannering,et al.  An exploratory multinomial logit analysis of single-vehicle motorcycle accident severity , 1996 .

[23]  R. O’Brien,et al.  A Caution Regarding Rules of Thumb for Variance Inflation Factors , 2007 .

[24]  M. Baltes,et al.  Why People Cross Where They Do: The Role of Street Environment , 2002 .

[25]  D. Hosmer,et al.  Goodness of fit tests for the multiple logistic regression model , 1980 .

[26]  Zhaoan Wang,et al.  Modeling pedestrians’ road crossing behavior in traffic system micro-simulation in China , 2006 .

[27]  George Yannis,et al.  Measuring accident risk exposure for pedestrians in different micro-environments. , 2007, Accident; analysis and prevention.

[28]  Satish V. Ukkusuri,et al.  Modeling of Motorist-Pedestrian Interaction at Uncontrolled Mid-block Crosswalks , 2003 .

[29]  George Yannis,et al.  Mobile phone use by young drivers: effects on traffic speed and headways , 2010 .

[30]  William J. Horrey,et al.  Predicting adolescent pedestrians' behavioral intentions to follow the masses in risky crossing situations , 2010 .

[31]  R Kulmala,et al.  An application of logit models in analysing the behaviour of pedestrians and car drivers on pedestrian crossings. , 1988, Accident; analysis and prevention.