Transportation systems are stochastic and dynamic systems. The road capacities and the travel demand are fluctuating from time to time within a day and at the same time from day to day. For road users, the travel time and travel costs experienced over time and space are stochasti
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Transportation systems are stochastic and dynamic systems. The road capacities and the travel demand are fluctuating from time to time within a day and at the same time from day to day. For road users, the travel time and travel costs experienced over time and space are stochastic, thus desire reliable travel times and low travel costs by altering routes or departure times. Road authorities and designers aim to design road networks such that they provide efficient and reliable services to the road users. Travelers’ choice behavior under stochastic travel times/costs and the design of the road networks are mutually affecting each other. Travelers’ choice behavior under stochastic travel times, especially route/departure time choice behaviors has attracted increasing attentions in the last decade. However, in most studies on network design problems with stochastic capacity or travel demand, travelers’ choice behavior, especially their departure time choice behavior under stochastic travel times are not considered. Instead, static traffic assignment is followed in most network design studies with stochastic travel times, which from our point of view is not realistic in terms of network performance assessments. This motivated our research direction. We aim to establish a network design approach with which dynamic traffic assignment is followed to capture the dynamics in flow propagations and spillback effects. Travelers’ departure time/route choice behavior under stochastic travel times is explicitly modeled. Travel time reliability is taken into account on both the individual choice behavior and network performance evaluation with stochastic networks. Discrete network design problem is dealt with, where numbers of lanes on a set of potential links are the design variables. This dissertation firstly works on the modeling of travelers’ departure time/route choice behavior under stochastic capacities. A generalized travel cost function is proposed to model travelers’ departure time/route choice behavior under uncertainty. The derived generalized travel cost function, which is more behaviorally sound and flexible, is adopted to model the reliability-based long term user equilibrium with departure time choices. A reliability-based dynamic network design approach is proposed and formulated of which numbers of lanes on all the potential links are the design variables. A combined road network-oriented Genetic Algorithm and set evaluation algorithm is proposed to solve the dynamic network design problem. A new systematic approach is proposed to eliminate the infeasible, unconnected and illogical lane designs in order to reduce the solution space and to save computation time. The proposed reliability-based dynamic network design approach is applied to a hypothetical network, and its solutions are compared to a corresponding static network design approach. It is concluded that the static network design approach may lead to poor designs. In general static traffic assignment underestimates the overall total network travel time and total network travel costs. Dynamic network design approach appears to derive a fairly good allocation of road capacity over space and makes the best utilization of the network capacity over time. A version of Braess paradox appears in case of reliability-based cost functions in both static and dynamic networks.