Evaluation of Network Performance under Provision of Short Predictive Traffic Information

Authors

  • Apirath PHUSITTRAKOOL School of Management Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani 12120
  • Chawalit JEENANUNTA School of Management Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani 12120
  • Passakon PRATHOMBUTR National Electronics and Computer Technology Center, Pathum Thani 12120

Keywords:

Advanced traveler information systems, predictive traffic information, traffic simulation, routing strategies

Abstract

Traffic information systems have been considered to play an important role in reducing traffic congestion. Understanding the effects of information provision to the network performance is crucial before real implementation of the systems. In this paper, we investigated the effect of provision of predictive information with short prediction horizon. A traffic simulation model was developed to evaluate the efficiency of the information. The simulations were conducted on a test grid network. The network performances in term of average trip travel times were compared with other traffic information types. In addition, sensitivity analyses of level of market penetration and update intervals are also presented. The results obtained indicate that the predictive information can improve the overall network performance even though the prediction horizon is short.

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Author Biography

Chawalit JEENANUNTA, School of Management Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani 12120

Assistant Professor,

Head of the School of Management Technology, and Chair of Management Technology Curriculum,

Head of Logistics and Supply Chain Systems Engineering (LogEn) Research Unit

References

T Toledo and R Beinhaker. Evaluation of the potential benefits of advanced traveler information systems. J. Intell. Transport. Syst. 2006; 10, 173-83.

M Ben-Akiva and I Kaysi. Dynamic network models and driver information systems. Transport. Res. A-Pol. 1991; 25, 251-66.

M Ben-Akiva, A de Palma and I Kaysi. The Impact of Predictive Information on Guidance Efficiency: An Analytical Approach. In: L Bianco P and Toth (eds.). Advanced Methods in Transportation Analysis. Springer-Verlag, Berlin, 1996, p. 413-32.

I Kaysi, ME Ben-Akiva and H Koutsopoulos. Integrated approach to vehicle routing and congestion prediction for real-time driver guidance. Transport. Res. Record. 1993; 1408, 66-74.

CC Lu and TH Yang. Comparing network performance under the provision of predictive and prevailing travel information. In: IEEE/INFORMS International Conference on Service Operations, Logistics and Informatics, IEEE, Chicago. 2009, p. 255-60.

J Dong, HS Mahmassani and CC Lu. How reliable is this route?: Predictive travel time and reliability for anticipatory traveler information systems. Transp. Res. Record. 2006; 1980, 117-25.

HS Mahmassani, CC Lu and J Dong. Value of information: Provision of anticipatory descriptive travel information through a real-time traffic estimation and prediction system. In: Proceedings of the 12th World Congress on Intelligent Transportation Systems, San Francisco, California, 2005, p. 1-12.

BL Smith and RK Oswald. Meeting real-time traffic flow forecasting requirements with imprecise computations. Comput. Aided Civ. Infrastruct. Eng. 2003; 18, 201-13.

Y Zhang. Special issue on short-term traffic flow forecasting. Transport. Res. C-Emer. 2014; 43, 1-2.

RH Emmerink, KW Axhausen, P Nijkamp and P Rietveld. Effects of information in road transport networks with recurrent congestion. Transportation 1996; 22, 21-53.

J Wahle, A Bazzan, F Klügl and M Schreckenberg. The impact of real-time information in a two-route scenario using agent-based simulation. Transport. Res. C-Emer. 2002; 10, 399-417.

HS Mahmassani. Dynamic network traffic assignment and simulation methodology for advanced system management applications. Netw. Spat. Econ. 2001; 1, 267-92.

S Sundaram, HN Koutsopoulos, M Ben-Akiva, C Antoniou and R Balakrishna. Simulation-based dynamic traffic assignment for short-term planning applications. Simul. Model. Pract. Th. 2011; 19, 450-62.

C Antoniou, HN Koutsopoulos, M Ben-Akiva and AS Chauhan. Evaluation of diversion strategies using dynamic traffic assignment. Transport. Plan. Tech. 2011; 34, 199-216.

J Bottom, M Ben-Akiva, M Bierlaire, I Chabini, H Koutsopoulos and Q Yang. Investigation of Route Guidance Generation Issues by Simulation with DynaMIT. In: A Ceder (ed.). Transportation and Traffic Theory: Proceedings of the 14th International Symposium on Transportation and Traffic Theory. Pergamon, New York, 1999, p. 577-600.

RH Emmerink, KW Axhausen, P Nijkamp and P Rietveld. The potential of information provision in a simulated road transport network with non-recurrent congestion. Transport. Res. C-Emer. 1995; 3, 293-309.

R Balakrishna, HN Koutsopoulos, M Ben-Akiva, BMF Ruiz and M Mehta. Simulation-based evaluation of advanced traveler information systems. Transp. Res. Record. 2005; 1910, 90-8.

M Ben-Akiva, M Bierlaire, HN Koutsopoulos and R Mishalani. Real Time Simulation of Traffic Demand-Supply Interactions within DynaMIT. In: M Gendreau and M Lucotte (eds.). Transportation and Network Analysis: Current Trends. Springer US, 2002, p. 19-36.

L Smith, R Beckman, D Anson, K Nagel and ME Williams. TRANSIMS: Transportation analysis and simulation system. In: Proceedings of the 5th National Transportation Planning Methods Applications Conference, Seattle, Washington, 1995, p. 1-10.

K Nagel and M Schreckenberg. A cellular automaton model for freeway traffic. J. Phys. I. 1992; 2, 2221-9.

P Mirchandani and H Soroush. Generalized traffic equilibrium with probabilistic travel times and perceptions. Transport. Sci. 1987; 21, 133-52.

YC Chiu, J Bottom, M Mahut, A Paz, R Balakrishna, T Waller and J Hicks. Dynamic traffic assignment: A primer. Transport. Res. E-Circular. 2011; E-C153, 1-62.

HS Mahmassani, T Hu, S Peeta and A Ziliaskopoulos. 1994, Development and testing of dynamic traffic assignment and simulation procedure for ATIS/ATMS applications, Technical Report DTFH61-90-R-00074-FG, Center for Transportation Research, The University of Texas at Austin.

M Ben-Akiva, M Bierlaire, D Burton, HN Koutsopoulos and R Mishalani. Network state estimation and prediction for real-time transportation management applications. Netw. Spat. Econ. 2001; 1, 291-318.

S Peeta and HS Mahmassani. System optimal and user equilibrium time-dependent traffic assignment in congested networks. Ann. Oper. Res. 1995; 60, 81-113.

A Bazzan and F Klügl. Re-routing Agents in an Abstract Traffic Scenario. Advances in Artificial Intelligence-SBIA 2008. In: Proceedings of the 19th Brazilian Symposium on Artificial Intelligence Savador, Brazil, 2008, p. 63-72.

HM Al-Deek, AJ Khattak and P Thananjeyan. A combined traveler behavior and system performance model with advanced traveler information systems. Transport. Res. A-Pol. 1998; 32, 479-93.

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Published

2015-06-05

How to Cite

PHUSITTRAKOOL, A., JEENANUNTA, C., & PRATHOMBUTR, P. (2015). Evaluation of Network Performance under Provision of Short Predictive Traffic Information. Walailak Journal of Science and Technology (WJST), 13(6), 433–450. Retrieved from https://wjst.wu.ac.th/index.php/wjst/article/view/1506

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Section

Research Article