A risk-averse signal setting policy for regulating hazardous material transportation under uncertain travel demand

- A risk-averse signal setting policy for hazmat network design is proposed.
- A min-max bi-level programming model is presented.
- A bundle-like solution method is presented.
- Numerical evaluations are made with various scenarios of transport policy.

To effectively regulate risk associated with hazmat transportation and minimize travel cost over road network under uncertain travel demand, a min-max bi-level programming problem (MMBLPP) is proposed to determine traffic signal settings. A risk-averse signal setting policy using budget of uncertainty (BOU) is presented against the worst-case realization of uncertainty in travel demand. A risk-averse model determining system optimum routes for hazmat carriers is presented where travel delay incurred by regular traffic at downstream junctions has been taken into account. A min-max single-level model (MMX) and a bundle-like solution method are proposed to determine risk-averse signal settings under BOU-based travel demand. To investigate the effectiveness of proposed model, numerical evaluations using real-world road network are empirically made with various scenarios of transport policies. These results reported obviously indicate that the proposed model achieved relatively better results than did traditional one against high-consequence scenarios of uncertain travel demand while substantially mitigating risk in the worst cases.