Public Private Partnerships (PPP) are one of the ways to provide public works and services around the world. For transportation projects under the PPP scheme, a common difficulty encountered in the determination of the concession period is the estimation of risks and uncertainties involved. This thesis proposes a methodology which integrates stochastic simulations, a traffic assignment algorithm, a toll pricing and adjustment method, and a pavement maintenance optimization programming to solve a concession period determination problem. In particular, stochastic simulation combines the critical path method and Monte Carlo simulation technique in an effort to quantify construction risks; traffic assignment models are used to forecast the traffic demand and mitigate the traffic risks due t...[ Read more ]

Public Private Partnerships (PPP) are one of the ways to provide public works and services around the world. For transportation projects under the PPP scheme, a common difficulty encountered in the determination of the concession period is the estimation of risks and uncertainties involved. This thesis proposes a methodology which integrates stochastic simulations, a traffic assignment algorithm, a toll pricing and adjustment method, and a pavement maintenance optimization programming to solve a concession period determination problem. In particular, stochastic simulation combines the critical path method and Monte Carlo simulation technique in an effort to quantify construction risks; traffic assignment models are used to forecast the traffic demand and mitigate the traffic risks due to transportation network expansion; and pavement maintenance optimization programming involves pavement performance prediction and optimal maintenance strategy selection which aims to avoid unnecessary maintenance actions and reduce operation risks.