Abstract

Emergency vehicle passage in congested urban networks poses a dual challenge: ensuring rapid response while minimizing disruption to surrounding traffic. This study addresses this challenge in the context of Connected Autonomous Emergency Vehicles (CA-EVs), proposing SafePass , a lightweight distributed framework for seamless CA-EV passage through decentralized, cooperative maneuvering of surrounding Connected Autonomous Non-Emergency Vehicles (CA-NEVs). At its core, SafePass employs the Target Lane Potential (TLP), a novel utility-based metric combining lane-choice utility with probabilistic gap acceptance, augmented by a cascade-aware penalty that suppresses upstream shockwaves triggered by gap-creation maneuvers. Evaluated in Simulation of Urban Mobility (SUMO) using synthetic traffic and real-world trajectory data from the Next Generation Simulation (NGSIM) US-101, Wuhan University Next Generation Simulation (WUT-NGSIM), and modified Waymo Open datasets, SafePass consistently clears lanes well before the CA-EV's Estimated Time of Arrival (ETA), reducing CA-EV travel time by up to 30% compared to baselines while lowering surrounding vehicle travel time by 8%–10%, demonstrating that safety and efficiency need not be traded off.

Department(s)

Computer Science

Publication Status

Open Access

Keywords and Phrases

CAVs; Cooperative maneuvering; Emergency vehicles; Lane changing; Politeness factor; SUMO; Utility model

International Standard Serial Number (ISSN)

2590-1982

Document Type

Article - Journal

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2026 Elsevier, All rights reserved.

Creative Commons Licensing

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Publication Date

01 May 2026

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