Abstract
In urban scenarios, the issues of traffic congestion keep disturbing governments and individuals, especially in complex road networks. It seems urgent to improve road utilization for alleviating the traffic congestion. In this paper, we first propose an optimization model to improve the road utilization, which not only considers the traffic breakdown probability but also the spontaneous traffic flow. Traffic breakdown occurs during the transition from free flow to spontaneous flow and may probably cause traffic congestion. By considering traffic flow, more drivers can avoid traffic breakdown and the road utilization will be increasing. Secondly, in order to decrease the complexity and redundancy, this paper uses a big traffic flow condition and Taylor series to simplify the objective function and obtain an optimal result with accuracy. Finally, the simulations that use real urban traffic scenario of Songjiang University Town in ShangHai evaluate the proposed algorithm’s performance. Our proposed algorithm outperforms other existing path-planning algorithm.
This work is supported by the NSF of China under Grant No. 71171045, No. 61772130, and No. 61301118; the Innovation Program of Shanghai Municipal Education Commission under Grant No. 14YZ130; and the International S&T Cooperation Program of Shanghai Science and Technology Commission under Grant No. 15220710600.
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Xu, M., Li, D., Zhang, G., Cao, M., Liao, S. (2018). A Path Planning Approach with Maximum Traffic Flow and Minimum Breakdown Probability in Complex Road Network. In: Chen, X., Sen, A., Li, W., Thai, M. (eds) Computational Data and Social Networks. CSoNet 2018. Lecture Notes in Computer Science(), vol 11280. Springer, Cham. https://doi.org/10.1007/978-3-030-04648-4_8
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DOI: https://doi.org/10.1007/978-3-030-04648-4_8
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