Determination of interaction potentials in freeway traffic from steady-state statistics

Milan Krbalek and Dirk Helbing

Physica A: Statistical Mechanics and its Applications, 2004, vol. 333, issue C, 370-378

Abstract: Many-particle simulations of vehicle interactions have been quite successful in the qualitative reproduction of observed traffic patterns. However, the assumed interactions could not be measured, as human interactions are hard to quantify compared to interactions in physical and chemical systems. We show that progress can be made by generalizing a method from equilibrium statistical physics we learned from random matrix theory. It allows one to determine the interaction potential via distributions of the netto distances s of vehicles. Assuming power-law interactions, we find that driver behavior can be approximated by a forwardly directed 1/s potential in congested traffic, while interactions in free traffic are characterized by an exponent of α≈4. This is relevant for traffic simulations and the assessment of telematic systems.

Keywords: Freeway traffic; Power law interaction potential; Random matrix theory: Dyson's gas; Adaptive driver behavior; Optimal velocity model; Approximate Hamiltonian; Distance distribution; Velocity distribution (search for similar items in EconPapers)
Date: 2004
References: View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:333:y:2004:i:c:p:370-378

DOI: 10.1016/j.physa.2003.10.059

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