. . "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 alphaapproximate to4. This is relevant for traffic simulations and the assessment of telematic systems." . . "0378-4371" . "Krb\u00E1lek, Milan" . "Determination of interaction potentials in freeway traffic from steady-state statistics"@cs . "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 alphaapproximate to4. This is relevant for traffic simulations and the assessment of telematic systems."@cs . "Determination of interaction potentials in freeway traffic from steady-state statistics"@cs . . . "RIV/68407700:21340/04:04105352!RIV09-MSM-21340___" . "NL - Nizozemsko" . "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 alphaapproximate to4. This is relevant for traffic simulations and the assessment of telematic systems."@en . . . . "9"^^ . "RIV/68407700:21340/04:04105352" . . "Determination of interaction potentials in freeway traffic from steady-state statistics"@en . . "CONGESTION; FLOW; PHASE-TRANSITIONS"@en . . . "Determination of interaction potentials in freeway traffic from steady-state statistics" . "333" . "2" . "Z(MSM 210000018)" . "21340" . "Helbing, D." . "Determination of interaction potentials in freeway traffic from steady-state statistics"@en . . "Physica A: Statistical Mechanics and Its Applications" . "[4B2D1EC3C6CF]" . "2"^^ . "1"^^ . "560078" . "Determination of interaction potentials in freeway traffic from steady-state statistics" . . . "000188758600026" .