A Risk‐Map‐Based Framework for Designing eVTOL Route Networks that Balance Safety and Efficiency

Rising urban transportation demand is placing increasing pressure on surface transport systems and has stimulated interest in urban air mobility (UAM) as a complementary mode. This paper proposes a risk‐map‐based network construction and segment‐level flow‐allocation framework for electric vertical take‐off and landing (eVTOL) aircraft. The framework integrates spatial risk assessment, hierarchical hub‐and‐spoke network construction, and multiobjective flow‐allocation optimization to balance safety and operational efficiency. An integrated environment‐air‐ground risk map is first constructed to quantify spatial hazards. A hierarchical node screening mechanism then combines partitioning around medoids (PAM) clustering and density‐based spatial clustering of applications with noise (DBSCAN) to identify strategic hubs, regional hubs, and end nodes, forming a nonstrict hub‐and‐spoke architecture. Candidate network segments are generated using Delaunay triangulation and adjusted through no‐fly‐zone avoidance. Based on the generated fixed network topology, a biobjective flow‐allocation model minimizes total segment risk and flow‐weighted transport time and is solved using the nondominated sorting genetic algorithm III (NSGA‐III) to obtain Pareto‐optimal traffic distributions. A case study in Nanjing’s Xuanwu District shows that the minimum‐risk solution reduces total risk by 32.08% compared with the baseline assignment, while the balanced solution achieves a 25.01% risk reduction and retains 90.59% of the baseline edge‐based network throughput. The results demonstrate that the proposed framework can support risk‐aware low‐altitude network construction and operational flow‐allocation decisions for early‐stage urban eVTOL deployment.