In this paper, we tackle the problem of risk-averse route planning in a transportation network with time-dependent and stochastic costs. To solve this problem, we propose an adaptation of the A* algorithm that accommodates any risk measure or decision criterion that is monotonic with first-order stochastic dominance. We also present a case study of our algorithm on the Manhattan, NYC, transportation network.
['Dajian Li', 'Paul Weng', 'Orkun Karabasoglu']
Finding Risk-Averse Shortest Path with Time-dependent Stochastic Costs