Cycling Network Projects: A Decision-Making Aid Approach

Efficient and clean urban mobility is a key factor in quality of life and sustainability of towns and cities. Traditionally, cities have focused on cars and other fuel-based vehicles as transport means. However, several problems are directly linked to massive car use, particularly in terms of air pollution and traffic congestion. Several works reckon that vehicle emissions produce over 90% of air pollution. One way to reduce the use of fuel-based vehicles (and thus the emission of pollutants) is to create efficient, easily accessible and secure bike lane networks which, as many studies show, promote cycling as a major mean of conveyance. In this regard, this paper presents an approach to design and calculate bike lane networks based on the use of open data about the historical use of a urban bike rental services. Concretely, we model this task as a network design problem (NDP) and we study four different optimisation strategies to solve it. We test these methods using data of the city of Valencia (Spain). Our experiments conclude that an optimisation approach based on genetic programming obtains the best performance. The proposed method can be easily used to improve or extend bike lane networks based on historic bike use data in other cities.