Modelling Traveller Behaviour under Emergency Evacuation Conditions

Pel, Adam; Bliemer, Michiel; Hoogendoorn, Serge · 2011 · Crossref

DOI: 10.18757/ejtir.2011.11.2.2921

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This paper addresses limitations in existing dynamic traffic simulation models used for emergency evacuation planning, specifically regarding how traveller behaviour is modelled under conditions of uncertainty and mandatory instructions. The authors argue that standard models often rely on user-equilibrium assumptions, which presuppose that travellers anticipate future traffic conditions—a behavior unlikely during emergencies where prior experience is absent. Furthermore, existing models frequently assume full compliance with evacuation instructions, ignoring the empirical reality of partial compliance. To resolve these issues, the authors propose a new macroscopic model framework called EVAQ, designed to simulate the trade-off between complying with prescribed evacuation plans and following preferred travel behaviors based on real-time traffic information. The EVAQ model operates through a single execution of dynamic network loading rather than an iterative convergence process. It integrates three components: departure time choice, destination/route choice, and traffic flow propagation. Departure times are modelled as a weighted combination of instructed departure windows and preferred departure times, with the compliance fraction treated as an exogenous parameter. Preferred departures are estimated using sequential binary Logit models or sigmoid curves based on hazard dynamics. For route choice, travellers are initially assigned to instructed routes but may switch en-route if perceived travel times on alternative routes deviate significantly from their current route’s expected time. This switching behavior is governed by a generalized cost function that includes travel time and an additional disutility term for non-compliance. This disutility is proportional to the deviation of the new route from the instructed route and a perceived cost parameter, allowing the model to simulate full compliance, no compliance, or any intermediate state. The authors illustrate the face-validity of the EVAQ framework using a hypothetical test example on a small network. The results demonstrate that capturing compliance levels and traffic information availability significantly impacts evacuation efficiency. The model shows that travellers respond to changing traffic conditions without anticipating future states, relying instead on instantaneous information. The findings highlight that ignoring partial compliance and information constraints can lead to inaccurate predictions of traffic flow and evacuation outcomes. The study confirms that the proposed mathematical formulation successfully relaxes the rigid assumptions of traditional models, providing a more realistic representation of traveller decision-making during disasters. The significance of this work lies in its contribution to the conceptual and mathematical foundations of evacuation modelling. By providing a framework that endogenously models partial compliance and myopic route switching, the EVAQ model offers planners a more robust tool for evaluating evacuation strategies. It allows for the testing of robustness against uncertainties in traveller behavior and helps in designing traffic management measures that account for realistic human responses. The authors note that while the model is macroscopic to ensure scalability and computational efficiency, future work must address the calibration and validation challenges posed by the lack of detailed empirical data on evacuation behavior.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• mental model of traffic