Societally optimal expansion of bicycle networks

In this paper, the authors 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, the authors 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, the authors 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. The authors show that their 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 their 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.


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  • Accession Number: 01889945
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Aug 14 2023 8:44AM