Robust optimization model for arterial signal coordination control considering travel time fluctuation

To improve the operational efficiency of the urban street arterial, a robust optimization model for coordinated signal control was proposed to remedy the gap in the traditional model that the travel time fluctuation was not considered. First, based on the license plate recognition data, the travel time distribution of vehicles not affected by signal delay was extracted with the consideration of flow directions. Then, the scenario set was constructed based on the road travel time, and the scenario-based robust optimization model was established using green wave bandwidth as the indicator of the conditional risk value. The travel time distribution was integrated into the model through scenario occurrence probability. The objective function was to minimize the conditional risk value of green wave bandwidth. The constraints, such as green wave bandwidth, cycle length, signal offset, internal logic relation of signal timing parameters, and parameter non-negativity, were considered. During model solving, the model was linearized and transformed into a mixed-integer linear model by adding auxiliary variables, and then was solved by the branch and bound method. The optimal solution was obtained in 3 minutes when the number of scenarios was 100. Finally, a case study of Xinghu Street in Suzhou Industrial Park was carried out to verify the availability and effectiveness of the model. The results show that the proposed robust optimization model outperforms the MAXBAND scheme in average green wave bandwidth, minimum green wave bandwidth, and 90% green wave bandwidth. The 90% green wave bandwidth and minimum green wave bandwidth are improved by 17.4% and 19.0%, respectively, while the conditional risk value is reduced by 8.9%. © 2023, Central South University Press. All rights reserved.