Transit signal priority optimization for urban traffic network considering arterial coordinated signal control

Li, Rui; Jin, Peter J.

doi:10.1177/1687814017700594

Cited by 9 publications

(3 citation statements)

References 15 publications

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“…One is to continuously increase investment and construction of urban basic traffic facilities, and the other is to improve the efficiency in traffic control of urban road networks [5]. However, the development rate of urban infrastructure cannot keep up with the growth rate of people's demand for traffic, rendering the road capacity unable to bear the traffic pressure; therefore, the method cannot effectively solve the traffic problems [3].…”

Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Regional Traffic Signal Control Optimization Model based on Quantum Genetic Algorithm

Wu,

Zhou,

Tan

et al. 2023

Preprint

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The paper proposes, for the first time in the field of optimizing regional traffic signals, a model based on a quantum genetic algorithm to solve the problem of traffic congestion at intersections under the existing infrastructure conditions. The model introduces four evaluation criteria: vehicle waiting time, standard deviation, collision percentage, and algorithm execution time. It conducts simulation experiments on three typical intersection types: cross intersections, roundabouts, and diamond intersections. A more optimal regional traffic signal control scheme is proposed. In order to verify the effectiveness of the scheme, a large number of subsequent simulation experiments are conducted. The results demonstrate that, compared to other traditional intelligent algorithms, the algorithm presented in this paper performs better at alleviating traffic congestion at intersections.

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Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Regional Traffic Signal Control Optimization Model based on Quantum Genetic Algorithm

Wu,

Zhou,

Tan

et al. 2023

Preprint

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“…Wu et al proposed to optimize the holding time at bus stops, signal timings, and bus speed in order to minimize bus delay so that buses can pass through signalized intersections without stopping [4]. Li and Jin regarded intersection and the downstream bus stop as a control unit and established an optimization model of bus priority green signal duration considering passenger delay at intersection and bus stops [5]. Considering the in uence of bus priority strategy on nonpriority phase, Wang et al established a bi-level programming model with the upper-level model aiming at minimizing the vehicle delay in the nonpriority direction and the lower-level model aiming at minimizing the average passenger delay in the entire intersection [6].…”

Section: Literature Reviewmentioning

confidence: 99%

Bus Priority Signal Control Considering Delays of Passengers and Pedestrians of Adjacent Intersections

Liu

Yang

et al. 2020

Journal of Advanced Transportation

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In this paper, a bus priority signal control (BPSC) method based on delays of passengers and pedestrians at adjacent intersections, is proposed. The influences of BPSC on passenger and pedestrian delay at adjacent intersections under the condition of coordinated control of green waves are studied. The implementation of BPSC at intersections not only reduces the delay of bus passengers, social vehicle passengers and pedestrians, but also improves the traffic flow of priority buses and social vehicles at downstream intersections. This study takes the green phase extension as an example of the active BPSC strategy, and analyzes three cases of priority vehicles reaching downstream intersection. Firstly, passenger and pedestrian delays at adjacent intersections are calculated under different traffic situations. Secondly, models with the goal of maximizing the reduced total delays are established. Thirdly, three algorithms are used to solve the problem to obtain the optimal signal timing adjustment scheme at upstream intersections. Ultimately, the result shows that the BPSC can effectively reduce pedestrian delays at intersections, protect the rights and interests of pedestrians, reduce the delays of priority vehicles, and maximize the reduced total delay.

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“…Liu and Qiu [35] minimized the weighted sum of the signal control delay and transit vehicle delay through trade-off optimizations. Li and Jin [36] adopted a simulation method with the objective of reducing both the total passenger travel delay and passenger waiting time at downstream bus stops within a network level. To date, multiobjective optimization is an appropriate method to deal with the trade-off between transit and private vehicles in TSP problems.…”

Section: Introductionmentioning

confidence: 99%

Conditional Transit Signal Priority Optimization at Stop-to-Stop Segments to Improve BRT On-Time Performance

2022

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Bus rapid transit (BRT) as a valid means of public transportation for overpopulated country of China is an especial mode of travel to relieve traffic congestion. Despite utilizing exclusive bus line, BRT constantly experiences delay at intersections when encountering a red signal. Transit signal priority (TSP) considered as a promising control strategy to improve the operation efficiency of BRT has been widely used at isolated intersections or arterials to reduce travel delay. However, as a transport with schedule, the unexpected arrival time of transit vehicle at stop lines of consecutive intersections inevitably affects the operation reliability of the BRT system. To solve the problem, this study develops an optimization model of conditional TSP for bus rapid transit with the objective of improving the on-time performance of the BRT system while mitigating adverse impacts on private vehicles. A stop-to-stop segment is established with both road sections and intersections for the consideration of the transit operation reliability. The constraints on the degree of saturation and queue overflow were considered for mitigating adverse impacts of TSP. A mixed-integer non-linear programming procedure is adopted to formulate the optimization model. The mathematical model is linearized and solved by the branch-and-bound method. Extensive numerical analyses are conducted, and the proposed conditional TSP strategy is compared with unconditional TSP and no-TSP control to evaluate its performance under various traffic and signal conditions. A case study of a BRT line in Shanghai, China, was selected to illustrate the effectiveness of the proposed model. For the tested scenarios, the transit on-time performance was improved by 21%, with an incurred cost of 3.4% increase in the delay of private vehicles. This indicates that the proposed model performs well in maintaining the reliability of the transit system with the least impact on general traffic.INDEX TERMS Bus rapid transit (BRT), mixed-integer-linear-programing (MILP), on-time performance, stop-to-stop segment, transit signal priority (TSP).

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Transit signal priority optimization for urban traffic network considering arterial coordinated signal control

Cited by 9 publications

References 15 publications

WITHDRAWN: Regional Traffic Signal Control Optimization Model based on Quantum Genetic Algorithm

WITHDRAWN: Regional Traffic Signal Control Optimization Model based on Quantum Genetic Algorithm

Bus Priority Signal Control Considering Delays of Passengers and Pedestrians of Adjacent Intersections

Conditional Transit Signal Priority Optimization at Stop-to-Stop Segments to Improve BRT On-Time Performance

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