A Survey on Emergency Vehicle Preemption Methods Based on Routing and Scheduling

Kamble, Shridevi Jeevan; Kounte, Manjunath R

doi:10.22247/ijcna/2022/211623

Cited by 19 publications

(17 citation statements)

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“…If an EV is given preemption when driving on a low-priority call, it can cause unnecessary delay for the surrounding traffic. The risks of negative effects on the surrounding traffic must therefore be considered when implementing EVP ( 52 – 54 ). One method to mitigate the negative impact on the surrounding traffic is to consider the traffic density for each direction of the intersection ( 55 ).…”

Section: Resultsmentioning

confidence: 99%

Potential of Cooperative Intelligent Transport System Services to Mitigate Risk Factors Associated With Emergency Vehicle Accidents

Weibull

Lidestam

Prytz

2022

Transportation Research Record: Journal of the Transportation R

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Emergency vehicles (EVs) are at high risk of accidents during emergency driving. To make use of countermeasures to mitigate these risks, it is important to understand under what circumstances EV-related accidents occur. The common risk factors for EV-related accidents were examined through a systematic literature review. A total of 22 articles were examined for risk factors associated with EV-related accidents. The most reported risk factors were, in order of frequency, intersections, daytime, dry roads, clear weather, urban roads, traffic signals, and angular collisions. The articles were also reviewed for suggested countermeasures to mitigate the risk factors. The most commonly suggested countermeasures were driver training for EV operators, educating the public, exercising caution at intersections, wearing a seatbelt, and intelligent vehicle technologies. Cooperative intelligent transport systems (C-ITSs) have the potential to mitigate the risks of EV-related accidents. Therefore, three C-ITS services were investigated: EV approaching, EV preemption, and geofencing. They could all be used to inform, warn, or control aspects of driving. Each suggested service has the potential to decrease risk factors for EV-related accidents. The current literature review provides guidance on under what circumstance and in what form C-ITSs could be beneficial to prevent EV-related accidents. Further research is needed to examine behavior when drivers are introduced to C-ITSs.

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Section: Resultsmentioning

confidence: 99%

Potential of Cooperative Intelligent Transport System Services to Mitigate Risk Factors Associated With Emergency Vehicle Accidents

Weibull

Lidestam

Prytz

2022

Transportation Research Record: Journal of the Transportation R

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“…The model effectively reduces the number of relay vehicles, resulting in significant bandwidth savings in dense network environments. By implementing various pre-emption techniques, such as those outlined in [8], the model prioritizes routing decisions in a way that minimizes delay.…”

Section: Literature Review On Fuzzy Logic Model and Cwmentioning

confidence: 99%

“…III) Assessment of Link Stability (ALS): The difference in the value of CW of a node with respect to time gives information about its link stability. Since a stable value of CW is a sign of stable link quality, any absolute change in the CW of a node with time is considered a deterioration of link stability, which can be expressed as in (8). The higher the difference in CW value, the worse the link stability between the nodes.…”

Section: ) F-etxmentioning

confidence: 99%

Optimization of Contention Window and Relay Selection for Efficient Routing Using Fuzzy Logic Model

Septa¹,

Wagh²

2023

IEEE Access

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The rapid increase in vehicle density on roads owing to urbanization and motorization has led to increased risks of roadblocks, traffic jams, and accidents. To ensure the reliability of transportation, it is crucial to have stable and timely transmission of safety messages through Vehicle Ad-hoc Networks (VANETs). However, frequent vehicle movement and changes in the network topology may cause link breakage and packet loss. This paper proposes a solution that uses a fuzzy logic system in both the Medium Access Control (MAC) layer and the network layer to broadcast safety messages efficiently. The proposed rule-based model optimizes the Contention Window (CW) and relay selection process to adapt to different traffic conditions. The dynamic CW MAC (DYCW-MAC) model selects the optimum size of CW based on network parameters such as density, velocity, and link quality factor. For multi-hop communication, the model determines the next forwarding relay by considering factors such as direction, velocity difference, coverage factor, and Fast-Expected Transmission Count (F-ETX) between the sender vehicle and surrounding vehicles within its transmission range. The simulation results indicate that the DYCW-MAC model enhances the network throughput and decreases the average packet delay in comparison to other models.

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“…Therefore, IoV has evolved in the network environment, and it becomes a hot research topic in research institutions, vehicle monitoring companies, and the government 4,5 . A major important factor to be noticed in IoT is the exchange of messages among vehicles to increase road safety 6–8 . The vehicles transmit the messages by wireless communication 9–11 .…”

Section: Introductionmentioning

confidence: 99%

Fractional mayfly optimization algorithm‐based Infrastructure‐to‐Vehicle and Vehicle‐to‐Vehicle scheduling for service message transmission in IoV‐fog

Lohat

Jain

Kumar

2023

Int J Communication

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Summary For the rising number of vehicles, and the advancement of communication and computation technologies, the perception of Internet of Vehicles (IoV) is introduced. It is utilized to capture vehicle‐based information that includes road description, road congestion, vehicle speed, and location. However, this information is important, and it showed more benefits in different ways, like route selection and message dissemination. IoV is the self‐structured network composed with vehicles lies in the road and the road side units (RSUs). It offers Infrastructure‐to‐Vehicle (I2V), as well as Vehicle‐to‐Vehicle (V2V) data transmission mechanism for transmitting service messages. To reliably broadcast the service information to the intended recipient in the IoV network still faced issues. Hence, an efficient service message transmission protocol is developed using the proposed fractional mayfly optimization algorithm (FMA) for selecting the relay vehicle and cooperative vehicle for transmitting service messages to the destination vehicle from RSU through the process of I2V and V2V scheduling. The RSU selects the relay vehicle for every service message using the proposed algorithm and allocates the cooperative vehicle by RSU for scheduling V2V transmission. The simulation results showed that the proposed scheduling method obtains the best channel quality indicator (CQI), delay, distance, packet delivery ratio (PDR), and throughput value of 0.92 for 150 vehicles and 0.005891, 6.060731, 83.45%, and 171.50 Mbps for 100 vehicles.

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A Survey on Emergency Vehicle Preemption Methods Based on Routing and Scheduling

Cited by 19 publications

References 0 publications

Potential of Cooperative Intelligent Transport System Services to Mitigate Risk Factors Associated With Emergency Vehicle Accidents

Potential of Cooperative Intelligent Transport System Services to Mitigate Risk Factors Associated With Emergency Vehicle Accidents

Optimization of Contention Window and Relay Selection for Efficient Routing Using Fuzzy Logic Model

Fractional mayfly optimization algorithm‐based Infrastructure‐to‐Vehicle and Vehicle‐to‐Vehicle scheduling for service message transmission in IoV‐fog

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