Multi-Agent Based Chaotic Traffic Simulation for Cairo Ring Road

Abstract:

Transportation simulations are an important part of today’s decision making process for transport infrastructure and management. While proposed changes are getting more and more complex, tools supporting the decision making process are struggling to keep up. Traditional, flow-based traffic assignment tools are limited in the number of different person groups that can be distinguished and do in most cases not offer fully time-dynamic results. Newer technologies like agent-based simulations overcome those problems. This paper presents a novel traffic simulation scheme capable of modeling chaotic motorway traffic. Different from other lane-based or following-based approaches, the proposed approach models traffic as a large navigational problem in an agent based simulation context. In addition, the approach is efficiently able to handle hard cases like overtaking, behavior at turning and aggressive driving behavior. The simulation was demonstrated at real-time rates using MATSim applied to Cairo Ring Road. It has been described as well how MATSim simulation was extended to incorporate aggressive and careless drivers' behavior.

• Periodical: Key Engineering Materials (Volume 613)
• Pages: 363-373
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.613.363
• Online since: May 2014
• Authors: Sherif E. Hussein, Sarwat Zahwi*
• Keywords: Chaotic Behavior, Multi-Agent System (MAS), Traffic Simulation

References

[1] David Handford, Alex Rogers, Kevin Cross, Agent-Based Traffic Operator Training Environments for Evacuation Scenarios, Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on, pp.438-441, August (2011).

DOI: 10.1109/wi-iat.2011.202

[2] Tomas Potuzak, Comparison of Road Traffic Network Division Based on Microscopic and Macroscopic Simulation, Computer Modeling and Simulation, International Conference on, pp.409-414, April (2011).

DOI: 10.1109/uksim.2011.84

[3] Toyotaro Suzumura, Hiroki Kanezashi, Highly Scalable X10-Based Agent Simulation Platform and Its Application to Large-Scale Traffic Simulation, 2012 IEEE/ACM 16th International Symposium on Distributed Simulation and Real Time Applications (DS-RT), pp.243-250, October (2012).

DOI: 10.1109/ds-rt.2012.44

[4] David Wilkie, Jason Sewall, Ming C. Lin, Transforming GIS Data into Functional Road Models for Large-Scale Traffic Simulation, IEEE Transactions on Visualization and Computer Graphics, pp.890-901, June (2012).

DOI: 10.1109/tvcg.2011.116

[5] Marianne Hatzopoulou, Jiang Y. Hao, Eric J. Miller (2011) Simulating the impacts of household travel on greenhouse gas emissions, urban air quality, and population exposure Transportation, p.38: 871–887, (2011).

DOI: 10.1007/s11116-011-9362-9

[6] Paruchuri, P., 2002. Multi agent simulation of unorganized traffic, AAMAS '02: Proceedings of the first international joint conference on Autonomous agents and multiagent systems, ACM Press, pp.176-183, (2002).

DOI: 10.1145/544741.544786

[7] Chang, G. and Junchaya, T., 1993. Simulating network traffic flows with a massively parallel computing architecture, WSC '93: Proceedings of the 25th conference on Winter simulation, ACM Press, pp.762-770, (1993).

DOI: 10.1145/256563.256840

[8] AL-Shihabi, T. and Mourant, R.R., 2001. A framework for modelling human-like driving behaviours for autonomous vehicles in driving simulators, AGENTS '01: Proceedings of the fifth international conference on Autonomous agents, ACM Press, pp.286-291, (2001).

DOI: 10.1145/375735.376310

[9] Lemessi, M., 2001. An SLX-based microsimulation model for a two-lane road section, WSC '01: Proceedings of the 33rd conference on Winter simulation, IEEE Computer Society pp.1064-1071, (2001).

DOI: 10.1109/wsc.2001.977415

[10] Gao, W., M. Balmer and E.J. Miller (2010) Comparisons between MATSim and EMME/2 on the Greater Toronto and Hamilton Area Network Transportation Research Record, Journal of the Transportation Research Board, No. 2197, p.118–128, (2010).

DOI: 10.3141/2197-14

[11] Müller, K. and K.W. Axhausen, Population synthesis for microsimulation: State of the art, the 9th Annual Meeting of the Transportation Research Board, Washington, D.C., January (2011).

[12] Joubert, W.J., P.J. Fourie and K.W. Axhausen (2010) Large-Scale Agent-Based Combined Traffic Simulation of Private Cars and Commercial Vehicles Transportation Research Record, Vol. 2168, pp.24-32, (2010).

DOI: 10.3141/2168-04

[13] Horni, A., D. M. Scott, M. Balmer and K. W. Axhausen (2009) Location Choice Modeling for Shopping and Leisure Activities With MATSim: Combining Micro-simulation and Time Geography Transportation Research Record, Vol. 2135, pp.87-95, (2009).

DOI: 10.3141/2135-11