TY - GEN
T1 - A comparison of approximate dynamic programming and simple genetic algorithm for traffic control in oversaturated conditions - Case study of a simple symmetric network
AU - Medina, Juan C.
AU - Hajbabaie, Ali
AU - Benekohal, Rahim F.
PY - 2011
Y1 - 2011
N2 - The performance of two algorithms for finding traffic signal timings in a small symmetric network with oversaturated conditions was analyzed. The two algorithms include an approximate dynamic programming approach using a "post-decision" state variable (ADP) and a simple genetic algorithm (GA). Results were found by using microscopic simulation and compared based on typical measures of performance (delay, throughput, number of stops) and also on measures that considered the efficiency of green time utilization and queue occupancy of the links. The symmetric characteristics of the small network allowed a straightforward analysis of the operation of the signals, providing some insights on the quality of the solutions. Results showed that even though the solutions from ADP were very different from those in GA, the network performance for both methods was similar, used green time efficiently preventing queue backups, and served all approaches according to current demands. The potential of ADP using the "post-decision" state variable is currently under further analysis using more challenging conditions, additional constraints, and domain knowledge as part of the algorithm formulation.
AB - The performance of two algorithms for finding traffic signal timings in a small symmetric network with oversaturated conditions was analyzed. The two algorithms include an approximate dynamic programming approach using a "post-decision" state variable (ADP) and a simple genetic algorithm (GA). Results were found by using microscopic simulation and compared based on typical measures of performance (delay, throughput, number of stops) and also on measures that considered the efficiency of green time utilization and queue occupancy of the links. The symmetric characteristics of the small network allowed a straightforward analysis of the operation of the signals, providing some insights on the quality of the solutions. Results showed that even though the solutions from ADP were very different from those in GA, the network performance for both methods was similar, used green time efficiently preventing queue backups, and served all approaches according to current demands. The potential of ADP using the "post-decision" state variable is currently under further analysis using more challenging conditions, additional constraints, and domain knowledge as part of the algorithm formulation.
UR - http://www.scopus.com/inward/record.url?scp=83755196408&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=83755196408&partnerID=8YFLogxK
U2 - 10.1109/ITSC.2011.6082999
DO - 10.1109/ITSC.2011.6082999
M3 - Conference contribution
AN - SCOPUS:83755196408
SN - 9781457721984
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 1815
EP - 1820
BT - 2011 14th International IEEE Conference on Intelligent Transportation Systems, ITSC 2011
T2 - 14th IEEE International Intelligent Transportation Systems Conference, ITSC 2011
Y2 - 5 October 2011 through 7 October 2011
ER -