Memory effects in microscopic traffic models and wide scattering in flow-density data

2003/04/15 by Martin Treiber, Dirk Helbing · 9 citations
Engineering · Physics and Astronomy · Social Sciences · #Traffic Prediction and Management Techniques #Traffic control and management #Transportation Planning and Optimization #cond-mat.soft #cond-mat.stat-mech

paper · pdf · doi:10.1103/physreve.68.046119

published as Physical Review E 68, 046119 (2003) · 8 pages, submitted to Physical Review E

arxiv created 2003/04/15 · openalex publication_date 2003/10/21 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

By means of microscopic simulations we show that non-instantaneous adaptation of the driving behaviour to the traffic situation together with the conventional measurement method of flow-density data can explain the observed inverse-λ shape and the wide scattering of flow-density data in ``synchronized'' congested traffic. We model a memory effect in the response of drivers to the traffic situation for a wide class of car-following models by introducing a new dynamical variable describing the adaptation of drivers to the surrounding traffic situation during the past few minutes (``subjective level of service'') and couple this internal state to parameters of the underlying model that are related to the driving style. % For illustration, we use the intelligent-driver model (IDM) as underlying model, characterize the level of service solely by the velocity and couple the internal variable to the IDM parameter ``netto time gap'', modelling an increase of the time gap in congested traffic (``frustration effect''), that is supported by single-vehicle data. % We simulate open systems with a bottleneck and obtain flow-density data by implementing ``virtual detectors''. Both the shape, relative size and apparent ``stochasticity'' of the region of the scattered data points agree nearly quantitatively with empirical data. Wide scattering is even observed for identical vehicles, although the proposed model is a time-continuous, deterministic, single-lane car-following model with a unique fundamental diagram.

Citations

• Congested Traffic States in Empirical Observations and Microscopic Simulations
• Cellular automata approach to three-phase traffic theory

Cited by

• Driving Behaviour: Models and Challenges
• Calibration and validation of models describing the spatiotemporal evolution of congested traffic patterns
• Markov Regime-Switching Intelligent Driver Model for Interpretable Car-Following Behavior
• Cellular Automaton Models in the Framework of Three-Phase Traffic Theory
• Car following behavioral stochasticity analysis and modelling: Perspective from wave travel time
• Understanding widely scattered traffic flows, the capacity drop, and platoons as effects of variance-driven time gaps
• Synchronization in the presence of memory
• Are work zones and connected automated vehicles ready for a harmonious coexistence? A scoping review and research agenda
• Experimental study of short-range interactions in vehicular traffic

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