The effect of zonal factors in estimating crash risks by transportation modes: Motor vehicle, bicycle and pedestrian

Abstract

ObjectivesThis paper aimed to (i) differentiate the effects of contributory factors on crash risks related to different transportation modes, i.e., motor vehicle, bicycle and pedestrian; (ii) explore the potential contribution of zone-level factors which are traditionally excluded or omitted, so as to track the source of heterogeneous effects of certain risk factors in crash-frequency models by different modes. MethodsTwo analytical methods, i.e. negative binomial models (NB) and random parameters negative binomial models (RPNB), were employed to relate crash frequencies of different transportation modes to a variety of risk factors at intersections. Five years of crash data, traffic volume, geometric design as well as macroscopic variables at traffic analysis zone (TAZ) level for 279 intersections were used for analysis as a case study. ResultsAmong the findings are: (1) the sets of significant variables in crash-frequency analysis differed for different transportation modes; (2) omission of macroscopic variables would result in biased parameters estimation and incorrect inferences; (3) the zonal factors (macroscopic factors) considered played a more important role in elevating the model performance for non-motorized than motor-vehicle crashes; (4) a relatively smaller buffer width to extract macroscopic factors surrounding the intersection yielded better estimations.