@article{HU2023, 
author = {Xinghua HU and Xinghui CHEN and Ran WANG and Bing LONG and Jiang WU},
title = {Optimization Model of Bus Priority Control Considering Carbon Emissions with Stochastic Characteristics},
year = {2023},
journal = {Journal of South China University of Technology (Natural Science Edition)},
volume = {51},
number = {10},
pages = {160-170},
keywords = {urban traffic, carbon emissions, bus priority control, speed guidance, probability density function},
url = {https://www.sciopen.com/article/10.12141/j.issn.1000-565X.230178},
doi = {10.12141/j.issn.1000-565X.230178},
abstract = {In the context of the construction of a country with a strong transportation network, vigorously developing urban public transportation and promoting sustainable urban development has become an inevitable requirement for urban transportation development. Transit signal priority control, as an active priority strategy, can effectively reduce the carbon emissions and delays generated by buses at signal intersections, and improve the quality of bus service. A bus speed probability density function was introduced to study the effect of bus priority control strategy on traffic carbon emission, based on the speed stochastic characteristics of intersection. The effect of main parameters such as delay, stopping times, and speed on traffic carbon emission was analyzed. A bi-level optimization model of single-intersection bus priority control was established using the combination strategy of speed guidance and green extension. The model took the optimal carbon emission reduction of buses and cars with different fuel types in the upstream section of the intersection and the intersection control area as the upper-level objective, the optimal total people delay reduction as the lower-level objective, and the guidance speed as well as the compressed green time of the non-bus-priority phases as the decision variables. The Gauss-Seidel iterative algorithm was used to solve the model. Finally, the established model was applied to the calculation cases for analysis, and the results indicated that under the guidance acceleration and green extension strategy, the overall carbon emission and total passenger delay reduction of the intersection could reach 25.63% and 36.27%, respectively. The model effectively reduced carbon emissions and total passenger delays in the upstream sections of the intersection and the intersection control area, and optimized the overall traffic benefit of the intersection while promoting sustainable development.}
}