• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 30 Issue 4
Jul.  2017
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Article Contents
XIA Jingxin, TAO Yumeng, JIAO Tiantian. Optimization Methods for Bidirectional Green Wave Control Based on Speed Volatility Interval[J]. Journal of Southwest Jiaotong University, 2017, 30(4): 802-809. doi: 10.3969/j.issn.0258-2724.2017.04.020
Citation: XIA Jingxin, TAO Yumeng, JIAO Tiantian. Optimization Methods for Bidirectional Green Wave Control Based on Speed Volatility Interval[J]. Journal of Southwest Jiaotong University, 2017, 30(4): 802-809. doi: 10.3969/j.issn.0258-2724.2017.04.020

Optimization Methods for Bidirectional Green Wave Control Based on Speed Volatility Interval

doi: 10.3969/j.issn.0258-2724.2017.04.020
  • Received Date: 21 Sep 2015
  • Publish Date: 25 Aug 2017
  • In order to overcome the drawbacks of traditional arterial signal coordination methods that apply parallel and equal green wave bandwidth and ignore the speed volatility of segments between intersections, a non-parallel and unequal green wave band representation is introduced here based on the segment speed volatility intervals. Additionally, a bidirectional green wave optimization control method was proposed. The optimization objective of the proposed method is to maximize the bandwidth of green waves between adjacent intersections so as to satisfy the traffic demands of the non-coordinated signal phases. Moreover, the relative offset between two adjacent intersections can be adjusted by constructing a maximum bandwidth model. An overlap test was used as a constraint condition to prevent the fracture of green waves, which realize the bidirectional green wave control for the arterial traffic signals. Taking Changjiang Road in Kunshan City as an example, Indexes in terms of efficiency were selected to evaluate the performance of the proposed bidirectional green wave optimization control method. Evaluation results show that the proposed method can effectively increase the green wave bandwidth by 11.8% and reduce traffic delays and vehicle queue lengths of the green wave phases by 15.34% and 10.86%, respectively, compared to the traditional green wave control method.

     

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