Optimization modeling of coordinated traffic signal control and its stochastic extension: Network modeling approach

2018 Fiscal Year Final Research Report

• Project/Area Number: 16K18163
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Civil engineering project/Traffic engineering
• Research Institution: The University of Tokyo
• Principal Investigator: Wada Kentaro 東京大学, 生産技術研究所, 助教 (20706957)
• Project Period (FY): 2016-04-01 – 2019-03-31
• Keywords: 交通信号 / 系統制御 / 信号制御 / 交通流 / 変分理論 / 組合せ最適化

Outline of Final Research Achievements

This study considers an optimal coordinated traffic signal control under both deterministic and stochastic demands. We first present a new mixed integer linear programming (MILP) for the deterministic signal optimization wherein traffic flow is modeled based on the variational theory and the constraints on a signal control pattern are linearly formulated. The resulting MILP has a clear network structure and requires fewer binary variables and constraints as compared with those in the existing formulations. We then extend the problem so as to treat the stochastic fluctuations in traffic demand. We here develop an accurate and efficient approximation method of expected delays and a solution method for the stochastic version of the signal optimization by exploiting the network structure of the problem. Using a set of proposed methods, we finally examine the optimal control parameters for deterministic and stochastic coordinated signal controls and discuss their characteristics.

Free Research Field

交通工学

Academic Significance and Societal Importance of the Research Achievements

本研究の枠組みは，交通信号群最適化の学術研究において全く考えられてこなかった「最適信号制御 = ネットワーク最適化」という視点を与えるところに特色がある．ネットワーク最適化は膨大な研究の蓄積があるため，そのアルゴリズムを活用することにより効率的な最適化手法の開発が期待できる．また，本研究の提案問題は，実用面を重視した（3種類の）信号パラメータの段階決定という実態に対して，最適制御という一貫した考え（同時最適化）に基づく指針を提供できる．さらに，本研究の知見は，シミュレーションベースの最適化手法のベンチマークとすることができる．そのため，学術研究としてのみならず，工学的，実務的にも意義がある．