This paper presents the development and evaluation of a procedure for determining optimal break points for time-of-day based coordinated actuated traffic signal operations. The proposed procedure uses a feature vector of optimal cycle length per time interval instead of traffic volume itself. Initial break points determined by the proposed feature vector are used in the greedy search algorithm to obtain optimal break points. By using the greedy search algorithm the number of evaluations in the search are dramatically reduced when compared to an exhaustive search or other common heuristic search methods such as a genetic algorithm. The proposed procedure was evaluated using a hypothetical network consisting of four signalized intersections and the results indicated that the proposed procedure effectively improved the performance of the coordinated actuated signal control. In addition, sensitivity analyses results on randomly varying demand conditions up to ±20% and randomly increased demand conditions up to 30% indicated that the newly developed break points were robust for such varying demand fluctuations.
[1]
Brian Lee Smith,et al.
Data-Mining Tools for the Support of Signal-Timing Plan Development
,
2001
.
[2]
Darcy M. Bullock,et al.
ACS-Lite Algorithmic Architecture: Applying Adaptive Control System Technology to Closed-Loop Traffic Signal Control Systems
,
2003
.
[3]
Ilsoo Yun,et al.
Optimization of Time-of-Day Breakpoints for Better Traffic Signal Control
,
2004
.
[4]
Keechoo Choi,et al.
Evaluation of microscopic simulation tools for coordinated signal system deployment
,
2004
.
[5]
Xiaodong Wang,et al.
Using k-means clustering to identify time-of-day break points for traffic signal timing plans
,
2005,
Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..
[6]
Darcy M. Bullock,et al.
Transition methods in traffic signal control
,
2006
.