Name
Abstract | ||
|---|---|---|
In this paper, we mainly focus on a comparison of three types of dynamic programming based algorithms for optimal and near-optimal solutions of traffic signal control problem. The algorithms are backward dynamic programming (BDP), forward dynamic programming (FDP), and approximate dynamic programming (ADP). The traffic signal control model at isolated intersection is formulated by discrete-time Markov decision process in stochastic traffic environment. Optimal solutions by BDP and FDP algorithms are considered in traffic system for stochastic state transition and deterministic state transition, respectively. A near-optimal solution by ADP for problem control adopts a linear function approximation in order to overcome computational complexity. In simulation, these three control algorithms are compared in different traffic scenarios with performances of average traffic delay and vehicle stops. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/CIST.2016.7804957 | 2016 4th IEEE International Colloquium on Information Science and Technology (CiSt) |
Keywords | Field | DocType |
dynamic programming based algorithms,traffic signal control system,backward dynamic programming,BDP,forward dynamic programming,FDP,approximate dynamic programming,ADP,discrete-time Markov decision process,stochastic traffic environment,stochastic state transition,deterministic state transition,linear function approximation,computational complexity,average traffic delay,vehicle stops | Dynamic programming,Approximation algorithm,Algorithm design,Computer science,Markov decision process,Algorithm,Stochastic process,Control system,Linear function,Computational complexity theory | Conference |
ISSN | ISBN | Citations |
2327-185X | 978-1-5090-0752-3 | 0 |
PageRank | References | Authors |
0.34 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Biao Yin | 1 | 4 | 3.12 |
| Mahjoub Dridi | 2 | 22 | 7.05 |
| Abdellah El Moudni | 3 | 153 | 26.13 |