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Balancing Mobility Efficiency and Environmental Exposure During Mega Events: A Multi-agent Routing Framework — arXiv:2610.37702

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.37702
License (as archived): CC0-1.0
Archived: 2026-10-31T06:06:38.501Z
SHA-256 of the archived text: fcdc2bf348b988784faf366011d11c2d98d01cbdc1b04b3467f0d94b88fe3642
Stable URL of this page: https://metraipolis.com/documento/dc_dc06bb2c452c

How to cite

Balancing Mobility Efficiency and Environmental Exposure During Mega Events: A Multi-agent Routing Framework — arXiv:2610.37702 — arXiv (en), https://arxiv.org/abs/2610.37702 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_dc06bb2c452c (Metraipolis archive dc_dc06bb2c452c, sha256 fcdc2bf348b988784faf366011d11c2d98d01cbdc1b04b3467f0d94b88fe3642)

BibTeX

@misc{dcdc06bb2c452c,
  title = {Balancing Mobility Efficiency and Environmental Exposure During Mega Events: A Multi-agent Routing Framework — arXiv:2610.37702},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.37702},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_dc06bb2c452c; sha256 fcdc2bf348b988784faf366011d11c2d98d01cbdc1b04b3467f0d94b88fe3642},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.37702. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Mega events can generate concentrated travel demand, intensifying congestion around venues and increasing travelers' environmental exposure. Existing traffic management strategies focus on travel efficiency, with limited attention to exposure risks. Taking mega-event travel as a short-term high-demand scenario, this study develops an exposure-aware multi-agent routing framework integrating road-network conditions, event-induced demand, background traffic, and environmental data within a unified simulation environment. Motorized travelers optimize travel efficiency, whereas micro-mobility travelers consider travel time and dynamic exposure to traffic-related PM2.5 and noise. We compare the framework with shortest-distance, congestion-aware, and exposure-aware routing baselines. Results show that, under high demand, the SARSA-based framework reduces vehicle travel time by 34.59% and cumulative environmental exposure by 58.65%, while micro-mobility travel time remains nearly unchanged. Exposure reduction is jointly driven by vehicle-side congestion mitigation and low-exposure routing. The framework provides quantitative support for vehicle diversion, low-exposure route guidance, and health-oriented traffic management in short-term high-demand scenarios.

Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv cs.MA, nuovi lavori del giorno).
Categorie arXiv: Multiagent Systems (cs.MA) ; Computers and Society (cs.CY).
Pagina del lavoro: https://arxiv.org/abs/2610.37702 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-31T06:06:38.402Z dalla pagina https://arxiv.org/list/cs.MA/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).