Name
Abstract | ||
|---|---|---|
Traffic signals are not only useful facilities to ensure the safety at an intersection, but also an important traffic management tool to improve the urban traffic network performance. Many traffic signal strategies have been presented to increase the throughput of an urban network and reduce the total delay. The difficulty is that a successful local optimization does not mean a better global performance and that the high complexity makes centralized coordinated strategies usually not efficient for a large network. To overcome these drawbacks, some promising distributed strategies are presented, such as the back-pressure algorithm. Whereas the back-pressure algorithm overcomes the main fundamental problems, some practical issues are not considered. Firstly, the original back-pressure algorithm does not take the all red time into consideration. Secondly, the algorithm relies strongly on the loop detector, which decreases the robustness. Therefore, this paper shows a dynamic green time approach which overcomes these drawbacks of the back-pressure algorithm. In the approach, the green time length depends on two elements: the back-pressure at the intersection and the upstream queue length. Meanwhile the green time for each phase is restricted to durations between 15 seconds and 65 seconds to ensure the robustness. The method is tested in a simulation. This shows that optimal dynamic green time approach shows the best performance among other green time mechanisms, such as fixed green time approach. The green time approach not only makes the back-pressure more practical, but also keeps the good network performance of the original algorithm. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ITSC.2016.7795593 | 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC) |
Keywords | Field | DocType |
optimal dynamic green time,distributed signal control,urban network,back-pressure algorithm,fixed green time approach,traffic signal strategies | Control theory,Computer science | Conference |
ISBN | Citations | PageRank |
978-1-5090-1890-1 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kai Yuan | 1 | 0 | 1.35 |
| Victor L. Knoop | 2 | 21 | 7.16 |
| Serge P. Hoogendoorn | 3 | 186 | 38.38 |