This paper aims to jointly analyze road, traffic and human factors of pedestrian crossing behavior, through the development of Integrated Choice and Latent Variables (ICLV) models. The analysis uses recent research as a starting point, in which a two-stage approach was successfully tested, including a separate estimation of human factors and choice models. Data from a dedicated field survey are used, in which pedestrian field observations of road crossing behavior in different road and traffic scenarios were combined with a questionnaire on pedestrian attitudes, perceptions, motivations and declared behaviors. ICLV models were developed for four different road types, namely major urban arterials, main roads, secondary roads and residential roads. The results suggest that the effect of traffic conditions on pedestrian crossing choices was more important on main and secondary urban roads, while on major urban arterials and on residential roads it was non-significant. As regards the effects of human factors, a ‘risk’ latent variable was found to enhance the explanatory power of most of the models. This variable was estimated on the basis of different indicators in each case, reflecting a clear ‘risk-taking’ tendency on major and main roads and an ‘optimization tendency’ on minor roads. Overall, it is indicated that the integration of human factors in pedestrian crossing models provides meaningful and insightful results, and may be advantageous compared to the two-stage approach.
|Tags||pedestrians, road infrastructure, statistical modelling, traffic management|