Algorithmics for Safe Bicycle Network Design with Bounded Detours in Rural Areas
2026-08-10 • Data Structures and Algorithms
Data Structures and AlgorithmsMultiagent Systems
AI summaryⓘ
The authors study a problem called Safe Bicycle Network with Bounded Detours (SBNBD), where the goal is to upgrade unsafe roads to safe ones so that certain pairs of locations can be connected without too much extra travel. They show this problem is very hard to solve in general but give some efficient solutions for simpler cases like trees or low-degree graphs. They also find ways to simplify the problem using graph properties and test their methods on real road data, showing that allowing slightly longer routes can reduce upgrade costs. Their work uses graph theory and optimization to help design safer bike networks in rural areas.
Safe Bicycle NetworkBounded DetoursGraph TheoryNP-hardnessParameterized ComplexityFeedback Edge SetTreewidthInteger Linear ProgrammingDetour FactorRoad Network Upgrade
Authors
Till Fluschnik
Abstract
We introduce the \emph{Safe Bicycle Network with Bounded Detours} (\emph{SBNBD}) problem, motivated by upgrading rural road networks for bicycle traffic. Given an undirected graph with safe and unsafe edges, edge lengths, upgrade costs, terminal pairs, a budget, and a detour factor $α$, the task is to upgrade unsafe edges so that each terminal pair is connected by a safe path of length at most $α$ times its shortest-path distance in the original network. We study SBNBD from a parameterized perspective. We prove strong NP-hardness on restricted graph classes, including planar graphs of treewidth two, graphs with feedback vertex set number one, and graphs of maximum degree three, and complement these lower bounds with polynomial-time algorithms for trees and graphs of maximum degree two. We show fixed-parameter tractability for the number of unsafe edges and prove matching SETH-based lower bounds, a polynomial-kernel lower bound, and W-hardness for natural parameters. Our main structural result maps any instance to an equivalent instance with $O(\mathrm{fes}+p)$ vertices and edges, where $\mathrm{fes}$ is the feedback edge number and $p$ the number of terminal pairs; this yields fixed-parameter tractability for $\mathrm{fes}+p$. Finally, we evaluate ILP-based algorithms on OpenStreetMap road networks for small German municipalities and their surroundings. The instances have small treewidth upper bounds and moderate feedback edge structure. Preprocessing based on the $\mathrm{fes}+p$ reduction and tree-decomposition-based cut generation both improve exact solving, especially on harder instances. Experiments with different detour factors show that increasing $α$ can reduce the upgraded-edge length, revealing trade-offs between upgrade cost and allowed relative detours. Overall, structural graph parameters provide a useful algorithmic lens for safe bicycle-network design.