Split-Cycle Offset Optimization Technique and Coordinated Actuated Traffic Control Evaluated through Microsimulation

Abstract

Traffic signal timings can be optimized with offline or online tools. Offline tools, such as Synchro, take a macroscopic approach, whereas genetic algorithm (GA) formulations rely on a close interaction with traffic microsimulators. Online tools, such as the Split-Cycle Offset Optimization Technique (SCOOT), optimize in real time. Offline optimization tools have the luxury of time for repetitive computation, whereas SCOOT must work quickly as it responds to traffic detected on the streets. A comparison of the best offline tools and adaptive signal control is presented. The signal timing plans are first derived from the Synchro macroscopic optimization tool. A genetic algorithm (GA)-based formulation, which is essentially stochastic, resides in the VISSIM traffic simulation software; the GA component is known as VISGAOST. The latest version of SCOOT (MC3) is modeled with upstream and stop line detectors to enable both phase skipping and overlaps. The test bed is closely modeled on a 14-intersection network in Park City, Utah. The quality of signal timings is evaluated for two traffic demand types: expected (no significant variation) and unexpected (random variations). Results indicate that the offline GA formulation provides the optimal signal timing plans, robust enough to accommodate even randomly changing traffic demand. Similar in performance to Synchro, SCOOT delivers a creditable quality of optimization for an online optimization tool.

Get full access to this article

View all access options for this article.

References

Hunt

P. B.

Robertson

D. I.

Bretherton

R. D.

and Winton

R. I.

SCOOT: Traffic Responsive Method of Coordinating Signals. Laboratory Report 1014. Transport and Road Research Lab, Crowthorne, Berkshire, United Kingdom, 1981.

Lowrie

P. R.

The Sydney Coordinated Adaptive Traffic System: Principles, Methodology, Algorithms. In Proc., International Conference on Road Traffic Signaling, Institution of Electrical Engineers, London, 1982, pp. 67–70.

Gartner

N. H.

OPAC: A Demand-Responsive Strategy for Traffic Signal Control. In Transportation Research Record 906, TRB, National Research Council, Washington, D.C., 1983, pp. 75–81.

Luk

J. Y. K.

Sims

A. G.

and Lowrie

P. R.

SCATS: Application and Field Comparison With a TRANSYT Optimised Fixed Time System. In Proc., International Conference on Road Traffic Signaling, Institution of Electrical Engineers, London, 1982, pp. 71–74.

Powell

R. J.

SCOOT in Southampton. In Proc., PTRC Annual Summer Meeting, Seminar M, P269, Brighton, United Kingdom, 1985, pp. 97–110.

Jayakrishnan

Mattingly

S. P.

and McNally

M. G.

Performance Study of SCOOT Traffic Control System with Non-Ideal Detectorization: Field Operational Test in the City of Anaheim.

Presented at 80th Annual Meeting of the Transportation Research Board, Washington D.C., 2001.

Mazzamatti

M. V.

Netto

D. V. V. F.

Villanova

L. M.

and Ming

S. H.

Benefits Gained by Responsive and Adaptive Systems in São Paulo. In Proc., IEE Road Transport and Information Control Conference, Institution of Electrical Engineers, London, April 21–23, 1998.

Tarnoff

P. J.

and Ordonez

Signal Timing Practices and Procedures: State of the Practice. FHWA-HOP-05-015. Institute of Transportation Engineers, Washington, D.C., 2004.

Park

B. B.

and Yun

Stochastic Optimization Method for Coordinated Actuated Signal Systems. Research Report UVACTS-15-0-102, University of Virginia, Charlottesville, January 2006.

10.

Stevanovic

Martin

P. T.

and Stevanovic

VISGAOST: VISSIM-Based Genetic Algorithm Optimization of Signal Timings. In Transportation Research Record: Journal of the Transportation Research Board, No. 2035, Transportation Research Board of the National Academies, Washington, D.C., 2007, pp. 59–68.

11.

Taale

Fransen

W. C. M.

and Dibbits

The Second Assessment of the SCOOT System in Nijmegen. In Proc., IEE Road Transport and Information Control Conference, Institution of Electrical Engineers, London, April 21–23, 1998.

12.

Quan

B. Y.

Greenough

J. C.

and Kelman

W. L.

The Metropolitan Toronto SCOOT Demonstration Project.

Presented at 72nd Annual Meeting of the Transportation Research Board, Washington D.C., 1993.

13.

Peck

Gorton

P. T. W.

and Liren

The Application of SCOOT in Developing Countries. In Proc., 3rd International IEE Conference on Road Traffic Control, Institution of Electrical Engineers, London, 1990, pp. 104–109.

14.

Martin

P. T.

and Hansen

B. G.

Online Testing of SCOOT Using CORSIM: Development of a CORSIM Run-Time Extension. Report No. UTL-1198-017. University of Utah Traffic Laboratory, Salt Lake City, 1999.

15.

Jhaveri

C. H.

Perrin

and Martin

P. T.

SCOOT Adaptive Signal Control: Evaluation of Its Effectiveness Over a Range of Congestion Intensities. In TRB 82nd Annual Meeting Compendium of Papers, Transportation Research Board of the National Academies, Washington, D.C., 2003.

16.

Chilukuri

B. R.

Perrin

Jr. and Martin

P. T.

SCOOT and Incidents: Performance Evaluation in Simulated Environment. In Transportation Research Record: Journal of the Transportation Research Board, No. 1867, Transportation Research Board of the National Academies, Washington, D.C., 2004, pp. 224–232.

17.

Bretherton

R. D.

and Bowen

G. T.

Recent Enhancements to SCOOT: SCOOT Version 2.4. In Proc., 3rd IEE International Conference on Road Traffic Control, Institution of Electrical Engineers, London, 1990, pp. 95–98.

18.

Bretherton

Current Developments in SCOOT: Version 3. In Transportation Research Record: Journal of the Transportation Research Board, No. 1554, Transportation Research Board of the National Academies, Washington, D.C., 1996, pp. 48–52.

19.

Bretherton

Wood

and Bowen

G. T.

SCOOT Version 4. Traffic Engineering and Control, Vol. 39, No. 7 1998, pp. 425–427.

20.

SCOOT User Guide: Version 4.2. Siemens Traffic Controls Ltd., Poole, Dorset, United Kingdom, 2003.

21.

Park

B. B.

Rouphail

N. M.

Hochanadel

J. P.

and Sacks

Evaluating Reliability of TRANSYT-7F Optimization Schemes. Journal of Transportation Engineering, Vol. 127, No. 4 2001, pp. 319–326.

22.

Rouphail

N. M.

Park

B. B.

and Sacks

Direct Signal Timing Optimization: Strategy Development and Results. Technical Report No 109, National Institute of Statistical Sciences, Research Triangle Park, N.C., 2000. www.niss.org/technicalreports/tr109.pdf. Accessed Apr. 5, 2004.

23.

Foy

M. D.

Benekohal

R. F.

and Goldberg

D. E.

Signal Timing Determination Using Genetic Algorithms. In Transportation Research Record 1365, TRB, National Research Council, Washington, D.C., 1992, pp. 108–115.

24.

Goldberg

D. E.

Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading, Mass., 1989.

25.

Hale

Traffic Network Study Tool: TRANSYT-7F. U.S. Version T7F10. McTrans Center, University of Florida, Gainesville, 2005.

26.

Husch

and Albeck

Synchro 6, Traffic Signal Software: User Guide. Trafficware Corporation, Albany, Calif., 2003.