Abstract In this paper, we consider the problem of expanding bicycle networks over time. The expansion of the network at a given point in time is based on the societal cost–benefit performance, which entails system-wide effects from previous expansions. The problem is challenging due to non-linearities of travel time benefits and the dimension of the problem, which is a consequence of the combinatorial complexity of the networks and the planning horizon. It rules out the use of conventional bottom-up cost–benefit analysis as evaluating even a small set of possible solutions becomes computationally infeasible. To circumvent this problem, we introduce a novel reverse geographical mapping approach where the monetary benefits are assigned back onto the network. This allows a more detailed geographical planning breakdown at the level of network links and makes it possible to apply a more stringent optimization approach with respect to the timing and prioritization of network expansions. Based on a linear approximation of travel time savings, we propose several variants of mathematical integer programs to solve the problem. This allows us to consider the case of growing a cycle superhighway network in the Copenhagen region over a time horizon of 50 years. We show that our approximations of travel time savings are largely similar to those obtained through actual traffic assignment. Furthermore, the optimization approach renders a development plan, which yields a net present value that is ten times larger than that of the actual infrastructure upgrades implemented since 2019. In a long-term scenario, it is shown that our solution returns an accumulated benefit–cost ratio of 2.7 over the period, which is a significant improvement over previous findings. This underlines the importance of optimal prioritization schemes of where and when to invest in bicycle network expansions.
Highlights A societal cost–benefit framework for expansion of large-scale transport networks. Formulation of the problem as a sequence of binary linear programming problems. Novel reverse geographical mapping that assigns consumer surplus to the network. Application to a full expansion of the Copenhagen cycle superhighway network. Optimal solution has societal benefits 10 times higher than the actual development.
Societally optimal expansion of bicycle networks
2023-06-07
Article (Journal)
Electronic Resource
English