Estimating origin–destination-matrices depending on the time of the day from high frequent pedestrian entry and exit counts

Abstract

This study proposes the estimation of origin–destination (OD)-matrices depending on the time of the day from high frequent entry and exit counts at a pedestrian infrastructure. These matrices are important input for infrastructure management both for pedestrian flow simulations in the planning stage as well as crowd control in the real-time application. Estimation is based on explicit models for the temporal dependence for long-term observations, where the models are adapted from the dynamic freeway OD-matrix estimation approach. Since pedestrian counts currently are subject to non-negligible measurement errors, the estimation uses the generalised method of moments estimation scheme to account for the errors-in-variables problem. Assumptions under which the method produces consistent and asymptotically normal estimators are provided, which are in line with empirically derived characteristics of pedestrian counters. In addition an approximation is provided, which shows superior finite sample properties in return for an asymptotic bias. The suitability of the method is demonstrated using a simulation study as well as a real-world application.