DocumentCode :
3399285
Title :
Rule-based multi-constraint transit signal priority control strategy
Author :
Dong Yu-pu
Author_Institution :
Sch. of Transp. Eng., Tongji Univ., Shanghai, China
fYear :
2011
fDate :
19-22 Aug. 2011
Firstpage :
2476
Lastpage :
2479
Abstract :
In order to carry out the purpose of transit signal priority, by giving priority to transit, while not increasing negative impact on social vehicles, and improving operability, efficiency and effectiveness of the strategy, a rule-based multi-constraint transit signal priority control strategy is designed. The strategy consists of seven constraints, in order to solve conflicts between constraints maximum red times are set to ensure the benefits of non-priority vehicles. And two basic rules are designed for priority phase and non-priority phase, which can improve the effectiveness of transit through intersection. It is conducted from the results of VISSIM simulation that: under low, medium and high load of traffic volumes, there are nearly no differences of average delay per vehicle and person delay between two control strategies, while compared to actuated control strategy, the bus stopped delay of rule-based multi-constraint TSP control strategy are significantly reduced by 35%, 21% and 24%.
Keywords :
control engineering computing; knowledge based systems; traffic control; traffic engineering computing; VISSIM simulation; rule-based multiconstraint TSP control; rule-based multiconstraint transit signal priority control; social vehicle; Analytical models; Delay; Educational institutions; Green products; Load modeling; Telecommunication traffic; Vehicles; multi-constraint; rule-based; traffic engineering; traffic simulation; transit signal priority control strategy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on
Conference_Location :
Jilin
Print_ISBN :
978-1-61284-719-1
Type :
conf
DOI :
10.1109/MEC.2011.6025994
Filename :
6025994
Link To Document :
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