Reinforcement Learning Based Control Scheme for Emergency Vehicle Preemption with Edge Computing

Rosayyan, Prakash; Paul, Jasmine; Subramaniam, Sreeramanan; Ilango, G. Saravana

doi:10.1007/s13177-022-00334-0

Cited by 2 publications

(1 citation statement)

References 28 publications

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“…Thirdly, due to long transmission distances, the communication process between EMVs and TSCs or other SVs might be hindered by communication delays in the V2X environment [107]. However, limited studies have considered this factor [87,107,108].…”

Section: Discussionmentioning

confidence: 99%

Every Second Counts: A Comprehensive Review of Route Optimization and Priority Control for Urban Emergency Vehicles

Hao,

Wang,

Yang

2024

Sustainability

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Emergency vehicles (EMVs) play an important role in saving human lives and mitigating property losses in urban traffic systems. Due to traffic congestion and improper priority control strategies along the rescue route, EMVs may not be able to arrive at rescue spots on time, which also increases traffic risk and has a negative impact on social vehicles (SVs). The greater the negative impact on SVs, such as increased delay times and queue length, the more profound the negative impacts on urban environmental sustainability. Proper rescue route selection and priority control strategies are essential for addressing this problem. Consequently, this paper systematically reviews the studies on EMV routing and priority control. First, a general bibliometric analysis is conducted using VOSviewer. This study also classifies the existing studies into three parts: EMV travel time prediction (EMV-TTP), EMV routing optimization (EMV-RO), and EMV traffic priority control (EMV-TPC). Finally, this study provides future research suggestions on five aspects: 1. uncovering authentic demand characteristics through EMV data mining, 2. incorporating the distinct characteristics of EMV in EMV-RO models, 3. implementing active EMV-TPC strategies, 4. concentrating more on the negative impacts on SVs, and 5. embracing the emerging technologies in the future urban traffic environment.

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