This thesis models dynamic routing behaviors for connected and autonomous vehicles under stochastic situation of receiving incident information. Markov decision process for a single CAV and related model assumptions are introduced by the freeway instance. We formulate a generalized model based on the freeway instance and employ the value iteration algorithm to solve the problem by finding optimal policy. Numerical experiments, which are conducted on different networks, reveal the similar results about MDP model for a single CAV: if the vehicle gets the incident information, the best actions are always to travel the alternative routes to avoid the increased link cost. While for the uncertain states without receiving incident information, the best actions are always to travel on the direct links.Civil, Architectural, and Environmental Engineerin
