TY - GEN
T1 - Development of a stochastic genetic algorithm for traffic signal timings optimization
AU - Ezzat, Ahmed A.
AU - Farouk, Hala A.
AU - El-Kilany, Khaled S.
AU - Abdelmoneim, Ahmed F.
PY - 2014
Y1 - 2014
N2 - Traffic Management of over-saturated urban networks is a great challenge in large metropolitan areas. Over-saturation is a severe traffic condition when excessive unbalance between the vehicular demand and the road network's capacity takes place, generating serious inflation of queuing lengths, waiting times, spillbacks and risk of accidents. Other environmental, psychological and economic aspects could also be related to the problem. However, adequate traffic management can successfully handle the demand in both space and time, and overcome the arising congestion dilemma. A mathematical model representing the traffic control stochastic environment has been developed. The optimum/near-optimum traffic signal timing values have been determined through the application of a genetic algorithm that feeds these values into a developed simulation model to obtain the corresponding queuing parameters. The generated signal timings significantly enhance the traffic performance and alleviate the choke points over a multiple-junction urban network. The developed approach has been applied on a network consisting of two consecutive junctions in Alexandria, Egypt using actual field data. Although the solution has not been implemented in reality; nevertheless, optimization results are very promising and show that the proposed model can drastically improve the queuing parameters of the vehicular flow.
AB - Traffic Management of over-saturated urban networks is a great challenge in large metropolitan areas. Over-saturation is a severe traffic condition when excessive unbalance between the vehicular demand and the road network's capacity takes place, generating serious inflation of queuing lengths, waiting times, spillbacks and risk of accidents. Other environmental, psychological and economic aspects could also be related to the problem. However, adequate traffic management can successfully handle the demand in both space and time, and overcome the arising congestion dilemma. A mathematical model representing the traffic control stochastic environment has been developed. The optimum/near-optimum traffic signal timing values have been determined through the application of a genetic algorithm that feeds these values into a developed simulation model to obtain the corresponding queuing parameters. The generated signal timings significantly enhance the traffic performance and alleviate the choke points over a multiple-junction urban network. The developed approach has been applied on a network consisting of two consecutive junctions in Alexandria, Egypt using actual field data. Although the solution has not been implemented in reality; nevertheless, optimization results are very promising and show that the proposed model can drastically improve the queuing parameters of the vehicular flow.
KW - Genetic Algorithms
KW - Mathematical Modeling
KW - Modeling and Simulation
KW - Traffic Management
UR - http://www.scopus.com/inward/record.url?scp=84910048647&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84910048647&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84910048647
T3 - IIE Annual Conference and Expo 2014
SP - 1740
EP - 1749
BT - IIE Annual Conference and Expo 2014
PB - Institute of Industrial Engineers
T2 - IIE Annual Conference and Expo 2014
Y2 - 31 May 2014 through 3 June 2014
ER -