Optimal road pricing scheme design
There are two main approaches to designing road pricing schemes. The first is judgmental in nature and focuses on the acceptability and practicality of the scheme. The second is based on theory concentrating on the optimality and performance of the scheme. This research aimed to integrate these two approaches into a single framework and to develop a tool to aid the decision maker in designing a practical and optimal road pricing scheme. A review of the practical design criteria and a survey with six local authorities in the U. K. were conducted to clarify the concept of the judgmental design. A simple charging scheme like a charging cordon is believed to be the most practical charging regime due to its simple structure. The decision on the boundary and structure of the cordon is based largely on public acceptability and possible adverse impacts. Road pricing is used to serve several objectives including congestion reduction, revenue generation, and increase in efficiency of the transport system. The framework for the theoretical optimal toll design problem adopted was a Stackelberg game where the travellers' behaviour were assumed to follow the concept of Wardrop's user equilibrium. This problem can also be formed as a Mathematical Program with Equilibrium Constraint (MPEC). After reviewing various methods for solving the MPEC problem, three possible methods (the merit function method, improved cutting plane algorithm, and Genetics Algorithm (GA) based algorithm) were developed and tested with the optimal toll problem. The GA based algorithm was found to be the most appropriate for the development of the design algorithm with practical constraints. Three different features of the judgmental design were included into the optimisation algorithm: the closed cordon formation, constraints on the outcomes of the scheme, and the allowance for multiple objectives. An algorithm was developed to find the optimal cordon with an optimal uniform toll. It is also capable of designing a scheme with multiple cordons. The algorithms for solving the constrained optimal cordon design problem and the multiobjective cordon design problem were also developed. The algorithm developed for the multiobjective problem allows the application of the posterior and progressive preference articulation approach by generating the set of non-dominated solutions. The algorithms were tested with a network of Edinburgh. The results revealed several policy implications. Adopting a judgmental cordon with a simple uniform toll may be less effective. A variable optimised toll around the judgmental cordon can generate around 70% more benefit than the optimal uniform toll. The optimised location of a cordon generated about 80% higher benefit compared to the best judgmental cordon. Additional constraints such as a maximum of total travel time decreased the level of the benefit of the scheme by 90%. Different objectives may require different designs for the charging cordon scheme. The welfare maximisation cordon should focus on those trips contributing most to the social welfare function which are mainly in the congested areas with an appropriate toll level. The revenue maximisation cordon should impose a higher number of crossing points and minimise possible diversion routes to avoid the tolls which should be high. The equity cordon should cover a wider area of the network with low toll level to ensure a good distribution of the cost and benefit to all origin-destination pairs. The algorithms developed can offer support to the decision maker in developing a charging cordon scheme by formalising the process of charging cordon design. This will increase the transferability of the technique and the transparency of the decision process.