Finding Risk-Averse Shortest Path with Time-dependent Stochastic Costs
  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.
