Information in Intelligent Transportation Systems

In this work potential benefits and drawbacks of providing information to road users are discussed. To model the complex behaviour of road users multi-agent-techniques are used. A special agent-architecture is proposed and discussed. To consider the impact of pre-trip-information, coordination games, like the El-Farol problem and the minority game, are studied and interpreted in the context of route choice scenarios. Additionally, the impact of en-route information is studied by simulating a basic two-route scenario with dynamic and static agents. A correlation analysis yields that the traffic system is destabilised by en-route information. The overall performance of the system is reduced by the effect of concentration. Different types and ways of generating current information are tested. It is found that the nature of the information influences the potential benefits of the information system strongly. As potential application an Advanced Traveller Information System is introduced, which comprises an agent-based simulator, which is coupled to a stream of on-line data. The framework provides network-wide information about the current traffic state. It is applied to the freeway network of the felderal state of North-Rhine Westfalia (NRW). Results are presented and further applications are discussed. To provide predictive information different methods to forecast traffic are analysed and discussed. Heuristics generated by an statistical analysis of historical data are studied. The daily traffic demand is classified with regard to daily, seasonal characteristics, as well as special events or directional flow. To provide a prediction for arbitrary horizons heuristics are merged with a constant model. The model delivers good predictions for a short and long-term traffic forecast.

[1]  W. Hamilton,et al.  The Evolution of Cooperation , 1984 .

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

[3]  Ana L. C. Bazzan,et al.  The impact of real-time information in a two-route scenario using agent-based simulation , 2002 .

[4]  J L Adler,et al.  Emergent Fundamental Pedestrian Flows from Cellular Automata Microsimulation , 1998 .

[5]  B. Schürmann,et al.  Application of Neural Networks for Predictive and Control Purposes , 2000 .

[6]  Jens Rasmussen,et al.  Information Processing and Human-Machine Interaction: An Approach to Cognitive Engineering , 1986 .

[7]  Peter Bonsall,et al.  DRIVERS' REVEALED RESPONSE TO ACTIVE VMS IN LONDON , 1999 .

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

[9]  Jaume Barceló,et al.  Modelling Advanced Transport Telematic Applications with Microscopic Simulators: The Case of AIMSUN2 , 1999 .

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

[11]  Jürgen Lind,et al.  Transportation Scheduling and Simulation in a Railroad Scenario: A Multi-Agent Approach , 1999 .

[12]  Harilaos N. Koutsopoulos,et al.  A microscopic traffic simulator for evaluation of dynamic traffic management systems , 1996 .

[13]  A. Schadschneider,et al.  Metastable states in cellular automata for traffic flow , 1998, cond-mat/9804170.

[14]  Markos Papageorgiou,et al.  Freeway ramp metering: an overview , 2002, IEEE Trans. Intell. Transp. Syst..

[15]  G. Christiansen,et al.  A mesoscopic model for passenger evacuation in a virtual ship-sea environment and performance-based evaluation , 2002 .

[16]  Maurizio Bielli,et al.  New operations research and artificial intelligence approaches to traffic engineering problems , 1996 .

[17]  Victor J. Blue,et al.  Cellular Automata Microsimulation of Bidirectional Pedestrian Flows , 1999 .

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

[19]  Gunnar G. Løvås,et al.  On performance measures for evacuation systems , 1995 .

[20]  Jörg P. Müller,et al.  Sophisticated and distributed: The transportation domain: Exploring emergent functionality in a real-world application , 1995 .

[21]  T Lotan,et al.  Effects of familiarity on route choice behavior in the presence of information , 1997 .

[22]  Jürgen Lind,et al.  Using a multi-agent approach to optimise the train coupling and sharing system , 2001, Eur. J. Oper. Res..

[23]  P. M. Hui,et al.  Volatility and agent adaptability in a self-organizing market , 1998, cond-mat/9802177.

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

[25]  Pak Ming Hui,et al.  Effects of Announcing Global Information in a Two-Route Traffic Flow Model , 2001 .

[26]  Peter Bonsall.  The influence of route guidance advice on route choice in urban networks , 1992 .

[27]  Kai Nagel,et al.  TRAFFIC AT THE EDGE OF CHAOS , 1994, adap-org/9502005.

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

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

[30]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[31]  Mohamed Abdel-Aty,et al.  USING STATED PREFERENCE DATA FOR STUDYING THE EFFECT OF ADVANCED TRAFFIC INFORMATION ON DRIVERS' ROUTE CHOICE , 1997 .

[32]  Ludger Santen,et al.  LETTER TO THE EDITOR: Towards a realistic microscopic description of highway traffic , 2000 .

[33]  Hani S. Mahmassani,et al.  DYNAMICS OF COMMUTER BEHAVIOUR: RECENT RESEARCH AND CONTINUING CHALLENGES , 1997 .

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

[35]  A. Schadschneider,et al.  Boundary-induced phase transitions in traffic flow , 2000 .

[36]  H. W. Hamacher,et al.  Mathematical Modelling of Evacuation Problems: A State of Art , 2001 .

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

[38]  A. Schadschneider,et al.  Empirical evidence for a boundary-induced nonequilibrium phase transition , 2001 .

[39]  T. Nagatani,et al.  Jamming transition in two-dimensional pedestrian traffic , 2000 .

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

[41]  Hani S. Mahmassani,et al.  DYNAMIC INTERACTIVE SIMULATOR FOR STUDYING COMMUTER BEHAVIOR UNDER REAL-TIME TRAFFIC INFORMATION SUPPLY STRATEGIES , 1993 .

[42]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[43]  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.

[44]  Mike McDonald,et al.  Car-following: a historical review , 1999 .

[45]  L. Henderson,et al.  Sexual Differences in Human Crowd Motion , 1972, Nature.

[46]  J. Hartmanis,et al.  Co-ordination in Artificial Agent Societies , 1999 .

[47]  Kay W. Axhausen,et al.  Effects of information in road transport networks with recurrent congestion , 1995 .

[48]  Peter Bonsall,et al.  Driver response to variable message signs: a stated preference investigation , 1997 .

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

[50]  R. Nagel.  Unraveling in Guessing Games: An Experimental Study , 1995 .

[51]  M Aleksic,et al.  AUTOMATIC TRACING AND FORECASTING OF MOVING TRAFFIC JAMS USING PREDICTABLE FEATURES OF CONGESTED TRAFFIC FLOW. , 2000 .

[52]  Iisakki Kosonen.  HUTSIM: SIMULATION TOOL FOR TRAFFIC SIGNAL CONTROL PLANNING , 1996 .

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

[54]  Klaus Fischer,et al.  Holonic transport scheduling with teletruck , 2000, Appl. Artif. Intell..

[55]  Yasunori Iida,et al.  Experimental analysis of dynamic route choice behavior , 1992 .

[56]  Birgit Burmeister,et al.  Agent-oriented traffic simulation , 1997 .

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

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

[59]  H. Wallentowitz,et al.  Effects of New Vehicle and Traffic Technologies — Analysis of Traffic Flow, Fuel Consumption and Emissions with PELOPS , 1999 .

[60]  Roland Chrobok,et al.  A Microscopic Simulator for Freeway Traffic , 2002 .

[61]  Robert F. Stengel,et al.  Principled negotiation between intelligent agents: a model for air traffic management , 1998, Artif. Intell. Eng..

[62]  Randolph W. Hall,et al.  ROUTE CHOICE AND ADVANCED TRAVELER INFORMATION SYSTEMS ON A CAPACITATED AND DYNAMIC NETWORK , 1996 .

[63]  Yi-Cheng Zhang,et al.  Emergence of cooperation and organization in an evolutionary game , 1997 .

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

[65]  Lutz Neubert,et al.  Statistische Analyse von Verkehrsdaten und die Modellierung von Verkehrsfluss mittels zellularer Automaten , 2000 .

[66]  Ronghui Liu,et al.  An agent-based framework for the assessment of drivers' decision-making , 2000, ITSC2000. 2000 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.00TH8493).

[67]  Jon Alan Bottom,et al.  Consistent anticipatory route guidance , 2000 .

[68]  Kay W. Axhausen,et al.  The potential of information provision in a simulated road transport network with non-recurrent congestion , 1995 .

[69]  P. Nijkamp,et al.  Variable message signs and radio traffic information: An integrated empirical analysis of drivers' route choice behaviour , 1996 .

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

[71]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[72]  Yoshihiro Ishibashi,et al.  Self-Organized Phase Transitions in Cellular Automaton Models for Pedestrians , 1999 .

[73]  B. Kerner.  EXPERIMENTAL FEATURES OF SELF-ORGANIZATION IN TRAFFIC FLOW , 1998 .

[74]  Nick T. Thomopoulos,et al.  Applied Forecasting Methods , 1980 .

[75]  G. J. Rodgers,et al.  The Hamming Distance in the Minority Game , 1999, adap-org/9902001.

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

[77]  P. Todd,et al.  Simple Heuristics That Make Us Smart , 1999 .

[78]  Michael Schreckenberg,et al.  Online Traffic Simulation with Cellular Automata , 1999 .

[79]  J. Horowitz.  The stability of stochastic equilibrium in a two-link transportation network , 1984 .

[80]  D. S. Jones,et al.  Elementary information theory , 1979 .

[81]  Peter Nijkamp,et al.  Telematics and Transport Behaviour , 1996 .

[82]  N. Johnson,et al.  Self-Organized Segregation within an Evolving Population , 1998, cond-mat/9810142.

[83]  Afsaneh Haddadi,et al.  Communication and Cooperation in Agent Systems , 1995, Lecture Notes in Computer Science.

[84]  M. Marchesi,et al.  Scaling and criticality in a stochastic multi-agent model of a financial market , 1999, Nature.

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

[86]  Anand S. Rao,et al.  Decision Procedures for BDI Logics , 1998, J. Log. Comput..

[87]  B Leerkamp.  Erhebungs- und Hochrechnungsverfahren des Kfz-Verkehrs fuer kommunale Planungsaufgaben , 1999 .

[88]  M Danech-Pajouh,et al.  24 OR 48 HOUR ADVANCE TRAFFIC FORECAST IN URBAN AND PERIURBAN ENVIRONMENTS: THE EXAMPLE OF PARIS , 1997 .

[89]  Moshe Ben-Akiva,et al.  TRAVEL SIMULATORS FOR DATA COLLECTION ON DRIVER BEHAVIOR IN THE PRESENCE OF INFORMATION , 1995 .

[90]  D A Roozemond.  USING AUTONOMOUS INTELLIGENT AGENTS FOR URBAN TRAFFIC CONTROL SYSTEMS , 1999 .

[91]  Randall Davis,et al.  Frameworks for Cooperation in Distributed Problem Solving , 1988, IEEE Transactions on Systems, Man, and Cybernetics.

[92]  L. F. Henderson,et al.  The Statistics of Crowd Fluids , 1971, Nature.

[93]  Victor J. Blue,et al.  Cellular automata microsimulation for modeling bi-directional pedestrian walkways , 2001 .

[94]  A. Schadschneider,et al.  Open boundaries in a cellular automaton model for traffic flow with metastable states. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[95]  José Cuena,et al.  A structure of problem-solving methods for real-time decision support in traffic control , 1998, Int. J. Hum. Comput. Stud..

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

[97]  J. Wardrop,et al.  A METHOD OF ESTIMATING SPEED AND FLOW OF TRAFFIC FROM A MOVING VEHICLE. , 1954 .

[98]  Mordechai Haklay,et al.  STREETS: an agent-based pedestrian model , 1999 .

[99]  André de Palma,et al.  Does providing information to drivers reduce traffic congestion , 1991 .

[100]  Ian Palmer,et al.  Validating the results of a route choice simulator Transportation Research C 5 , 1997 .

[101]  W. Arthur.  Inductive Reasoning and Bounded Rationality , 1994 .

[102]  C. A. Desoer,et al.  Nonlinear Systems Analysis , 1978 .

[103]  Harald Gorr.  Die Logik der individuellen Verkehrsmittelwahl , 1997 .

[104]  Paul Tucker.  INTELLIGENT TRANSPORT SYSTEMS : A REVIEW OF TECHNOLOGIES, PLAYERS AND MARKET PROSPECTS , 1998 .

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

[106]  Franziska Klügl-Frohnmeyer.  Aktivitätsbasierte Verhaltensmodellierung und ihre Unterstützung bei Multiagentensimulationen , 2000 .

[107]  Yicheng Zhang,et al.  On the minority game: Analytical and numerical studies , 1998, cond-mat/9805084.

[108]  Rafael H. Bordini,et al.  Evolving Populations of Agents with Personalities in the Minority Game , 2000, IBERAMIA-SBIA.

[109]  Ana L. C. Bazzan,et al.  Evolution of Coordination as a Metaphor for Learning in Multi-Agent Systems , 1996, ECAI Workshop LDAIS / ICMAS Workshop LIOME.

[110]  Jeffrey L. Adler,et al.  IN-LABORATORY EXPERIMENTS TO INVESTIGATE DRIVER BEHAVIOR UNDER ADVANCED TRAVELER INFORMATION SYSTEMS (ATIS) , 1993 .

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

[112]  Hani S. Mahmassani,et al.  Transferring insights into commuter behavior dynamics from laboratory experiments to field surveys , 2000 .

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

[114]  Hans Levenbach.  The J of Policy. Applied Forecasting Methods, Thomopoulos, Nick T., Englewood Cliffs, N.J.: Prentice‐Hall, 1980 , 1982 .

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

[116]  Danko A. Roozemond.  Using intelligent agents for pro-active, real-time urban intersection control , 2001, Eur. J. Oper. Res..

[117]  Nicholas R. Jennings,et al.  A Roadmap of Agent Research and Development , 2004, Autonomous Agents and Multi-Agent Systems.

[118]  Hussein Dia,et al.  MODELLING THE IMPACTS OF ADVANCED TRAVELLER INFORMATION SYSTEMS USING INTELLIGENT AGENTS , 1999 .

[119]  Michael Schreckenberg,et al.  A cellular automaton traffic flow model for online simulation of traffic , 2001, Parallel Comput..

[120]  Michael Schreckenberg,et al.  Microscopic Simulation of Evacuation Processes on Passenger Ships , 2000, ACRI.

[121]  Hussein Dia.  Towards sustainable transportation - The intelligent transportation systems approach , 2000 .

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

[123]  Hani S. Mahmassani,et al.  DYNAMICS OF COMMUTING DECISION BEHAVIOR UNDER ADVANCED TRAVELER INFORMATION SYSTEMS , 1999 .

[124]  Moshe Ben-Akiva,et al.  Game-Theoretic Formulations of Interaction Between Dynamic Traffic Control and Dynamic Traffic Assignment , 1998 .

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

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

[127]  S. Sastry.  Nonlinear Systems: Analysis, Stability, and Control , 1999 .

[128]  N-E El Faouzi.  COMBINING PREDICTIVE SCHEMES IN SHORT-TERM TRAFFIC FORECASTING , 1999 .

[129]  Harry J. P. Timmermans,et al.  A Multi-Agent Cellular Automata System for Visualising Simulated Pedestrian Activity , 2000, ACRI.

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