Unravelling travellers' route choice behaviour at full-scale urban network by focusing on representative OD pairs in computer experiments.

Humberto González Ramírez,Jean Krug,Cécile Becarie,Ludovic Leclercq,Nicolas Chiabaut

doi:10.1371/journal.pone.0225069

Abstract

In a city-scale network, trips are made in thousands of origin-destination (OD) pairs connected by multiple routes, resulting in a large number of alternatives with diverse characteristics that influence the route choice behaviour of the travellers. As a consequence, to accurately predict user choices at full network scale, a route choice model should be scalable to suit all possible configurations that may be encountered. In this article, a new methodology to obtain such a model is proposed. The main idea is to use clustering analysis to obtain a small set of representative OD pairs and routes that can be investigated in detail through computer route choice experiments to collect observations on travellers behaviour. The results are then scaled-up to all other OD pairs in the network. It was found that 9 OD pair configurations are sufficient to represent the network of Lyon, France, composed of 96,096 OD pairs and 559,423 routes. The observations, collected over these nine representative OD pair configurations, were used to estimate three mixed logit models. The predictive accuracy of the three models was tested against the predictive accuracy of the same models (with the same specification), but estimated over randomly selected OD pair configurations. The obtained results show that the models estimated with the representative OD pairs are superior in predictive accuracy, thus suggesting the scaling-up to the entire network of the choices of the participants over the representative OD pair configurations, and validating the methodology in this study.

Highlights

Urban congestion occurs when traffic demand locally exceeds the network capacity
The results of the above methodology are that the models estimated with the observations over the representative OD pair configurations are better in predicting the route choices on unseen OD pairs, i.e., on OD pairs not used for the estimation process. These results demonstrate how a careful selection of OD pairs for experiments on route choice behaviour can improve the results of a choice model in a broader set of OD pairs and, on the other hand, that cluster analysis can be used to find these OD pair configurations
In terms of the purpose of this article, choosing a small number of k has the risk of sub-representing the OD-routes in the network and, more important, a small number of OD-routes in the route choice experiments implies that the variability in the route attributes is small, posing a problem in estimating a route choice model

Summary

Introduction

Urban congestion occurs when traffic demand locally exceeds the network capacity. The local demand is the combination of the global travel demand between the different origins and destinations and the travellers’ route choices, which define how many trips are made at the same place in a given time window. At a city-scale level, i.e., considering all the OD pairs and links in the network, route choice is a key determinant of urban transportation network. Route choice behaviour at full-scale urban network

Methods

Results

Conclusion