Biobjective Optimization and Evaluation for Transit Signal Priority Strategies at Bus Stop-to-Stop Segment

This paper proposes a new optimization framework for the transit signal priority strategies in terms of green extension, red truncation, and phase insertion at the stop-to-stop segment of bus lines. The optimization objective is to minimize both passenger delay and the deviation from bus schedule si...

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Bibliographic Details
Published in:Mathematical Problems in Engineering 2016-01, Vol.2016 (2016), p.76-87
Main Authors: Li, Rui, Ran, Bin, Jin, Peter J.
Format: Article
Language:English
Subjects:
Algorithms
Bus stops
Buses
Buses (vehicles)
Business metrics
Delay
Deviation
Neural networks
Optimization
Passengers
Peak hour traffic
Performance evaluation
Priorities
Schedules
Segments
Studies
Traffic congestion
Traffic delay
Traffic flow
Traffic signals
Traffic volume
Traveling salesman problem
Urban transportation
Vehicles
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Summary:This paper proposes a new optimization framework for the transit signal priority strategies in terms of green extension, red truncation, and phase insertion at the stop-to-stop segment of bus lines. The optimization objective is to minimize both passenger delay and the deviation from bus schedule simultaneously. The objective functions are defined with respect to the segment between bus stops, which can include the adjacent signalized intersections and downstream bus stops. The transit priority signal timing is optimized by using a biobjective optimization framework considering both the total delay at a segment and the delay deviation from the arrival schedules at bus stops. The proposed framework is evaluated using a VISSIM model calibrated with field traffic volume and traffic signal data of Caochangmen Boulevard in Nanjing, China. The optimized TSP-based phasing plans result in the reduced delay and improved reliability, compared with the non-TSP scenario under the different traffic flow conditions in the morning peak hour. The evaluation results indicate the promising performance of the proposed optimization framework in reducing the passenger delay and improving the bus schedule adherence for the urban transit system.
ISSN:1024-123X
1563-5147
DOI:10.1155/2016/1054570