Year: 2026
Type: dissertation
Abstract: Urban pedestrians are routinely exposed to vehicle emissions because standard routing algorithms optimise purely for travel time, ignoring pollution. This thesis develops a data-driven framework to measure and reduce that exposure, unifying three core contributions. First, it builds a road-level exposure pipeline from vehicular traces and microscopic emission models, with graph-based imputation for missing data and dispersion to pedestrian links. Second, it proposes exposure-aware pedestrian routing balancing travel time against pollutant intake. We evaluate global and local trade-off strategies via hypervolume maximisation over Pareto-optimal routes. Using Pisa, we demonstrate substantial exposure reductions with modest time penalties. Third, it extends to joint vehicle-pedestrian optimisation, where co-routing both modes in a shared emission field unlocks superior mitigation over single-mode baselines. The thesis concludes with structural limitations and future directions for routing-based interventions.
Author: ALIYEV, GURBAN
Language: Italian
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7223718450