Traveler information has the potential to reduce travel times and improve their reliability. Studies have verified that driver overreaction from the dissemination of information can be eliminated through prediction-based route guidance that uses short-term forecasts of network state. Critical off-line tests of advanced dynamic traffic assignment–based prediction systems have been limited, since the system being evaluated has also been used as the test bed. This paper outlines a detailed simulation-based laboratory for the objective and independent evaluation of advanced traveler information systems, a laboratory with the flexibility to analyze the impacts of various design parameters and modeling errors on the quality of the generated guidance. MITSIMLab, a system for the evaluation of advanced traffic management systems, is integrated with Dynamic Network Assignment for the Management of Information to Travelers (DynaMIT), a simulation-based decision support system designed to generate prediction-based route guidance. Evaluation criteria and requirements for the closed-loop integration of MITSIMLab and DynaMIT are discussed. Detailed case studies demonstrating the evaluation methodology and sensitivity of DynaMIT's guidance are presented.
Get full access to this article
View all access options for this article.
References
1.
Ben-AkivaM., BierlaireM., KoutsopoulosH. N., and MishalaniR.Real-Time Simulation of Traffic Demand–Supply Interactions Within DynaMIT. In Transportation and Network Analysis: Current Trends. (GendreauM. and MarcotteP., eds.), Kluwer Academic Publishers, Dordrecht, Netherlands, 2002, pp. 19–36.
2.
MahmassaniH. S.Dynamic Network Traffic Assignment and Simulation Methodology for Advanced System Management Applications. Presented at 81st Annual Meeting of the Transportation Research Board, Washington, D.C., 2002.
3.
Dynamic Traffic Assignment Project.FHWA, U.S. Department of Transportation.www.dynamictrafficassignment.org. Accessed March 11, 2005.
4.
Ben-AkivaM., de PalmaA., and KaysiI.Dynamic Network Models and Driver Information Systems. Transportation Research A, Vol. 25, No. 5, 1991, pp. 251–266.
5.
Ben-AkivaM. E., de PalmaA., and KaysiI.The Impact of Predictive Information on Guidance Efficiency: An Analytical Approach. In Advanced Methods in Transportation Analysis (BiancoL. and TothP., eds.), Springer-Verlag, Berlin, 1996, pp. 413–432.
6.
BottomJ., Ben-AkivaM. E., BierlaireM., and ChabiniI.Generation of Consistent Anticipatory Route Guidance. Presented at TRISTAN III Symposium, San Juan, Puerto Rico, 1998.
7.
Ben-AkivaM., BierlaireM., BurtonD., KoutsopoulosH. N., and MishalaniR.Network State Estimation and Prediction for Real-Time Transportation Management Applications. Networks and Spatial Economics, Vol. 1, No. 3–4, 2001, pp. 293–318.
8.
MahmassaniH. S., and JayakrishnanR.System Performance and User Response Under Real-Time Information in a Congested Traffic Corridor. Transportation Research A, Vol. 25, No. 5, 1991, pp. 293–307.
9.
YangQ., and KoutsopoulosH. N.A Microscopic Traffic Simulator for Evaluation of Dynamic Traffic Assignment Systems. Transportation Research C, Vol. 4, No. 3, 1996, pp. 113–129.
10.
YangQ., KoutsopoulosH. N., and Ben-AkivaM. E.Simulation Laboratory for Evaluating Dynamic Traffic Management Systems. In Transportation Research Record: Journal of the Transportation Research Board, No. 1710, Transportation Research Board of the National Academies, Washington, D.C., 2000, pp. 122–130.
11.
BalakrishnaR., Ben-AkivaM., and KoutsopoulosH. N.Simulation-Based Evaluation of DynaMIT's Route Guidance and Its Impact on Network Travel Times.Proc., 10th World Conference on Transport Research, July 4–8, 2004, Istanbul, Turkey.
12.
AshokK., and Ben-AkivaM.Alternative Approaches for Real-Time Estimation and Prediction of Time-Dependent Origin–Destination Flows. Transportation Science, Vol. 34, No. 1, 2000, pp. 21–36.
13.
AntoniouC., Ben-AkivaM. E., BierlaireM., MishalaniR.Demand Simulation for Dynamic Traffic Assignment.Proc., 8th IFAC/IFIP/IFORS Symposium on Transportation Systems, Chania, Greece, June 16–18, 1997.
14.
Ben-AkivaM., and BierlaireM.Discrete Choice Models with Applications to Departure Time and Route Choice. In Handbook of Transportation Science, 2nd ed. (HallR., ed.), Kluwer Academic Publishers, Dordrecht, Netherlands, 2003.
15.
RammingS. M.Network Knowledge and Route Choice. Ph.D. thesis. Massachusetts Institute of Technology, Cambridge, 2002.
16.
BalakrishnaR., KoutsopoulosH. N., and Ben-AkivaM.Evaluation of the Estimation and Prediction Capability of a Dynamic Traffic Assignment System. Accepted for presentation and publication for the 16th International Symposium on Transportation and Traffic Theory, College Park, Md., July 18–21, 2005.
17.
HuynhN., ChiuY.-C., and MahmassaniH. S.Finding Near-Optimal Locations for Variable Message Signs for Real-Time Network Traffic Management. In Transportation Research Record: Journal of the Transportation Research Board, No. 1856, Transportation Research Board of the National Academies, Washington, D.C., 2003, pp. 34–53.
18.
MurrayP. M., MahmassaniH. S., and AbdelghanyK. F.Methodology for Assessing High-Occupancy Toll-Lane Usage and Network Performance. In Transportation Research Record: Journal of the Transportation Research Board, No. 1765, TRB, National Research Council, Washington, D.C., 2001, pp. 8–15.
19.
DoanD. L., ZiliaskopoulosA., and MahmassaniH.On-Line Monitoring System for Real-Time Traffic Management Applications. In Transportation Research Record: Journal of the Transportation Research Board. No. 1678, TRB, National Research Council, Washington, D.C., 1999, pp. 142–149.
20.
ChiuY.-C., and MahmassaniY. S.Hybrid Real-Time Dynamic Traffic Assignment Approach for Robust Network Performance. In Transportation Research Record: Journal of the Transportation Research Board, No. 1783, Transportation Research Board of the National Academies, Washington, D.C., 2002, pp. 89–97.
21.
SmithS. A., and PerezC.Evaluation of INFORM: Lessons Learned and Application to Other Systems. In Transportation Research Record 1360, TRB, National Research Council, Washington, D.C., 1992, pp. 62–65.
22.
MillerM.TravInfo Evaluation: Traveler Information Center Study. Technical Report UCB-ITS-PWP-98-21. University of California, Berkeley, Sept. 1998.
23.
SaricksC. L., SchoferJ. L., SootS., and BelellaP. A.Evaluating Effectiveness of Real-Time Advanced Traveler Information Systems Using a Small Test Vehicle Fleet. In Transportation Research Record 1588, TRB, National Research Council, Washington, D.C., 1997, pp. 41–48.
24.
YauchP. J., GrayJ. C., and LewisW. A.Using NETSIM to Evaluate the Effects of Drawbridge Openings on Adjacent Signalized Intersections. ITE Journal, Vol. 58, No. 3, pp. 35–44, 1988.
25.
StephanedesY. J., KwonE., and MichalopoulosP.Demand Diversion for Vehicle Guidance, Simulation, and Control in Freeway Corridors. In Transportation Research Record 1220, TRB, National Research Council, Washington, D.C., 1989, pp. 12–20.
26.
JayakrishnanR., MahmassaniH. S., and HuY.An Evaluation Tool for Advanced Traffic Information and Management Systems in Urban Networks. Transportation Research C, Vol. 2, No. 3, 1994, pp. 129–147.
27.
HaboianK. A.A Case for Freeway Mainline Metering. In Transportation Research Record 1494, TRB, National Research Council, Washington, D.C., 1995, pp. 11–20.
28.
HasanM., JhaM., and Ben-AkivaM.Evaluation of Ramp Control Algorithms Using Microscopic Traffic Simulation. Transportation Research C, Vol. 10, No. 3, pp. 229–256, 2002.
29.
ScarizaJ. R., ToledoT., and Ben-AkivaM.Evaluation of Coordinated and Local Ramp Metering Algorithms Using Microscopic Traffic Simulation.Proc., 10th World Conference for Transport Research, Istanbul, Turkey, July 4–8, 2004.
30.
Fernandez RuizB. M.Architecture for the Integration of Dynamic Traffic Management Systems. Master's thesis. Massachusetts Institute of Technology, Cambridge, 2000.
31.
BottomJ., Ben-AkivaM., BierlaireM., ChabiniI., KoutsopoulosH. N., and YangQ.Investigation of Route Guidance Generation Issues by Simulation with DynaMIT.Proc., 14th International Symposium on Transportation and Traffic Theory (A. Ceder, ed.), Pergamon, 1999, pp. 577–600.
