A multi-agent system for on-line simulations based on real-world traffic data

Presents and reviews a framework for online simulations and predictions which are based on the combination of real-world traffic data and a multi-agent traffic flow model. The agent architecture consists of two layers which distinguish the different tasks that road users have to perform. The framework is applied to the urban road network of Duisburg and the freeway network of North Rhine-Westphalia. On the basis of historical data, heuristics are derived, which can be combined with the dynamic data of the simulations to provide a short-term traffic forecast. The necessity for an anticipatory traffic forecast, which includes decision-making and route choice behavior of the road users, is discussed.

[1]  Hubert Rehborn,et al.  Forecasting of Traffic Congestion , 2000 .

[2]  R. Berkemer.  Modal Split and Social Dilemmas , 2000 .

[3]  Hussein Dia,et al.  An object-oriented neural network approach to short-term traffic forecasting , 2001, Eur. J. Oper. Res..

[4]  Michael Schreckenberg,et al.  A dynamic route guidance system based on real traffic data , 2001, Eur. J. Oper. Res..

[5]  M. Schreckenberg,et al.  THREE CATEGORIES OF TRAFFIC DATA : HISTORICAL, CURRENT, AND PREDICTIVE , 2000 .

[6]  Peter Wagner,et al.  Parallel real-time implementation of large-scale, route-plan-driven traffic simulation , 1996 .

[7]  Michael Schreckenberg,et al.  A cellular automaton model for freeway traffic , 1992 .

[8]  Dirk Helbing,et al.  Granular and Traffic Flow ’99: Social, Traffic, and Granular Dynamics , 2000 .

[9]  Michael Schreckenberg,et al.  Simulation of traffic in large road networks , 2001, Future Gener. Comput. Syst..

[10]  W. Knospe,et al.  CA Models for Traffic Flow: Comparison with Empirical Single-Vehicle Data , 2000 .

[11]  S. Griffis.  EDITOR , 1997, Journal of Navigation.

[12]  Roland Chrobok,et al.  On-Line Simulation of the Freeway Network of North Rhine-Westphalia , 2000 .

[13]  Haris N. Koutsopoulos,et al.  Investigation of Route Guidance Generation Issues by Simulation with DynaMIT , 1999 .

[14]  Ana L. C. Bazzan,et al.  Anticipatory Traffic Forecast Using Multi-Agent Techniques , 2000 .

[15]  Moshe Ben-Akiva,et al.  Dynamic network models and driver information systems , 1991 .

[16]  Ana L. C. Bazzan,et al.  Agents in Traffic Modelling - From Reactive to Social Behaviour , 1999, KI.

[17]  Mark Dougherty,et al.  A REVIEW OF NEURAL NETWORKS APPLIED TO TRANSPORT , 1995 .

[18]  M. Schreckenberg,et al.  Microscopic Simulation of Urban Traffic Based on Cellular Automata , 1997 .

[19]  A. Schadschneider,et al.  Statistical physics of vehicular traffic and some related systems , 2000, cond-mat/0007053.

[20]  A. Schadschneider,et al.  Single-vehicle data of highway traffic: a statistical analysis. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[21]  B. Kerner.  THE PHYSICS OF TRAFFIC , 1999 .

[22]  A. Schadschneider.  The Nagel-Schreckenberg model revisited , 1999, cond-mat/9902170.

[23]  Rafael H. Bordini,et al.  Wayward agents in a commuting scenario (personalities in the minority game) , 2000, Proceedings Fourth International Conference on MultiAgent Systems.

[24]  Kai Nagel,et al.  Two-lane traffic rules for cellular automata: A systematic approach , 1997, cond-mat/9712196.

[25]  Kai Nagel,et al.  LARGE-SCALE TRAFFIC SIMULATIONS FOR TRANSPORTATION PLANNING , 2000 .

[26]  José Cuena,et al.  Knowledge-based models for adaptive traffic management systems , 1995 .

[27]  F. Kluegl,et al.  Decision dynamics in a traffic scenario , 2000 .

[28]  Victor J. Blue,et al.  Toward the design of intelligent traveler information systems , 1998 .

[29]  Boris S. Kerner,et al.  Phase Transitions in Traffic Flow , 2000 .

[30]  Kai Nagel,et al.  INDIVIDUAL ADAPTATION IN THE PATH-BASED SIMULATION OF THE FREEWAY NETWORK OF NORTHRHINE-WESTFALIA , 1996, adap-org/9705001.