A discrete-continuous multi-vehicle anticipation model of driving behaviour in heterogeneous disordered traffic conditions

摘要

This study proposes a multi-vehicle anticipation-based discrete-continuous choice modelling framework for describing driver behaviour in heterogeneous disordered traffic (HDT) conditions. To incorporate multi-vehicle anticipation, the concept of an influence zone around a vehicle (subject vehicle) is introduced. Vehicles within the influence zone can potentially influence the subject vehicle's driving behaviour. Further, driving decisions are characterized as combination of discrete and continuous components. The discrete component involves the decision to accelerate, decelerate, or maintain constant speed and the continuous component involves the decision of how much to accelerate or decelerate. A copula-based joint modelling framework that allows dependencies between discrete and continuous components is proposed. Such a joint modelling framework recognizes that the discrete and continuous decisions are made simultaneously, and common unobserved factors influence both decisions. Additionally, truncated distributions are employed for the continuous model components to avoid the prediction of unrealistically high acceleration or deceleration values. The parameters of the proposed model are estimated using a trajectory dataset from Chennai, India. The empirical results underscore (a) the importance of considering multi-vehicle anticipation for describing driving behaviour in HDT conditions, and (b) the efficacy of the joint discrete-continuous system for modelling driving behaviour. Further, not all traffic environment variables found to influence the discrete decisions were found influential on continuous decisions and vice versa. Moreover, the influence of several variables was found to be stronger on the decision to accelerate or decelerate than on the decision of how much to accelerate or decelerate.