  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. Multiple practical aspects are considered as well, including sequential
road improvements, uneven improvement costs, and how to include additional
data.
