Optimization of Exposure-Aware Routing for Vehicles and Pedestrians
| Title | Optimization of Exposure-Aware Routing for Vehicles and Pedestrians |
| Publication Type | Conference Paper |
| Year of Publication | 2025 |
| Authors | Aliyev, G |
| Conference Name | Proceedings of the 19th International Symposium on Spatial and Temporal Data (SSTD '25) |
| Publisher | Association for Computing Machinery |
| Conference Location | Osaka, Japan |
| Abstract | Vehicular traffic is a significant source of air pollution in cities, exposing city residents and tourists to harmful emissions. To tackle this issue, our PhD research investigates how exposure to vehicular emissions in urban areas can be estimated and how this exposure can be mitigated through green routing. The work builds on three research questions: how to estimate car emissions and their dispersion; how to reduce pedestrian exposure through rerouting with a reasonable trade-off; and how to jointly simulate pedestrians and vehicles that dynamically adapt to each other. In line with these questions, we developed a pipeline to estimate vehicular emissions and dispersion, simulated exposure-aware pedestrian routing, and demonstrated its effectiveness in reducing exposure with minimal travel-time cost. Our most recent contribution is a joint simulation of pedestrians and vehicles, tested on real-world data, which achieved over 95\% reduction in emissions along pedestrian-dense roads. We are planning to extend the framework by considering static resident populations in the co-evolutionary simulation. Additionally, a systematic comparison of the framework’s performance across diverse urban environments is necessary to assess its generalizability. Furthermore, we aim to investigate how variations in vehicle speed influence emission levels and, consequently, affect the outcomes of our exposure-aware routing simulations. Finally, we plan to analyze how emission-aware routing impacts fairness in exposure distribution across both non-moving residents and moving pedestrians. |
| URL | https://doi.org/10.1145/3748777.3748808 |
| DOI | 10.1145/3748777.3748808 |