A data-driven bi-level program for knowledge-based signal control system under uncertainty

Abstract

A data-driven knowledge based system (DDKS) is considered for urban signal control with hazardous material (hazmat) transportation. A data-driven bi-level program (DDBP) is presented to determine generalized travel cost for hazmat carriers and regular traffic flows. A risk-averse (RA) signal control is developed for DDKS with uncertain risk in the presence of hazmat transportation. Since DDBP is generally non-convex, a stochastic program using two-stage approach is proposed to find local optimal solutions. Numerical computations using a real-data city network are made and good results are obtained. As compared with conventional signal controls such as delay-minimizing (DM) and risk-neutral (RN) signal control, the proposed RA exhibits considerable advantage on mitigation of public risk exposure whilst incurred less cost loss as compared to other data-driven alternatives in all cases.