The Bicycle Network Improvement Problem: Optimization Algorithms and A Case Study in Atlanta

Lim, Jisoon; Dalmeijer, Kevin; Guhathakurta, Subhrajit; Hentenryck, Pascal Van

Using a bicycle for commuting is still uncommon in US cities, although it brings many benefits to both the cyclists and to society as a whole. Cycling has the potential to reduce traffic congestion and emissions, increase mobility, and improve public health. To convince people to commute by bike, the infrastructure plays an important role, since safety is one of the primary concerns of potential cyclists. This paper presents a method to find the best way to improve the safety of a bicycle network for a given budget and maximize the number of riders that could now choose bicycles for their commuting needs. This optimization problem is formalized as the Bicycle Network Improvement Problem (BNIP): it selects which roads to improve for a set of traveler origin-destination pairs, taking both safety and travel distance into account. The BNIP is modeled as a mixed-integer linear program that minimizes a piecewise linear penalty function of route deviations of travelers. The MIP is solved using Benders decomposition to scale to large instances. The paper also presents an in-depth case study for the Midtown area in Atlanta, GA, using actual transportation data. The results show that the Benders decomposition algorithm allows for solving realistic problem instances and that the network improvements may significantly increase the share of bicycles as the commuting mode.