Urban street space is often contested with competition and coordination between multiple road users and transport modes. Understanding how pedestrians decide to enter the carriageway can help inform how to plan and manage street space and is increasingly relevant as autonomous vehicles mature. In this paper, we present a description of pedestrian road crossing behaviour using a novel sequential sampling modelling approach implemented in a spatial agent-based model. The model explicitly represents the gradual process of deliberation between discrete road crossing choice alternatives resulting in a choice of crossing location. The model reproduces some characteristic pedestrian road crossing behaviours such as trade offs between vehicle exposure and journey time, non-compliant crossing (jaywalking), and dependence of crossing choice on the proximity of crossing alternatives. CCS CONCEPTS • Computing methodologies → Modeling and simulation; • Applied computing → Transportation.

Pedestrian navigation decisions take place simultaneously at multiple spatial scales. Yet most models of pedestrian behaviour focus either on local physical interactions or optimisation of routes across a road network. We present a novel hierarchical pedestrian route choice framework that integrates dynamic, perceptual decisions at the street level with abstract, network-based decisions at the neighbourhood level. The framework is based on construal level theory which states that decision makers construe decisions based on their psychological distance from the object of the decision. We implement this route choice framework in a spatial agent-based model in which pedestrian and vehicle agents complete trips in an urban environment. Using global sensitivity analysis techniques, we demonstrate the interaction between route choice components representing decision making at different spatial and temporal scales. Additionally, through comparison to a least cost network model, we demonstrate the increased route heterogeneity produced by this approach. This work could form the basis of an alternative method for producing pedestrian route alternatives. The granularity and scale of the modelled pedestrian trajectories could also help improve appraisals of street infrastructure.