An Optimization Approach for Emergency Vehicles Dispatching and Traffic Lights Adjustments in Response to Emergencies in Smart Cities

Rangel, Elivelton O.; Costa, Daniel G.; Peixoto, Maycon L. M.

doi:10.1109/sbesc53686.2021.9628243

Cited by 5 publications

(3 citation statements)

References 25 publications

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“…In emergency vehicle dispatching, researchers mainly focus on the control and dispatching methods, such as achieving optimal dispatching and signal priority control in environments like CVIS [29]- [31] , IoT [34] , and ITS [32]- [33] . To ensure that emergency vehicles complete their tasks safely and efficiently, Long, et al [29] , based on the cooperative vehicle infrastructure system (Figure 2), solved emergency vehicles pass through intersections without stopping by coordinating signal timing and guiding vehicle speed, which effectively enhanced the efficiency of emergency vehicles passing through intersections and saved valuable time for rescue.…”

Section: Emergency Resource Dispatchingmentioning

confidence: 99%

“…Chen et al [32] designed an integrated dispatching system for emergency vehicles, including emergency vehicle path planning and lane reservation, so as to speed up emergency response. Elivelton et al [33] considered a combination of special algorithms and intelligent transportation system for rapid dispatch of emergency vehicles with traffic signals for priority control. Similarly, Krishnendu [34]…”

Section: Emergency Resource Dispatchingmentioning

confidence: 99%

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Digital emergency response technologies research of transportation infrastructure network: a review and prospects

Jiang

2022

International Conference on Smart Transportation and City Engineering (STCE 2022)

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Nowadays, the rise of various unexpected incidents on a global scale makes the management and control of emergency transportation popular research in the field of the transportation infrastructure network. The development of digital technologies has injected new impetus into emergency traffic management in recent years. Such advancement poses a significant impact on the efficiency of evacuation, resource dispatching, and supplies technical support for the construction of emergency transportation system. In this study, we review recent literature on digital emergency disposal technologies of the transportation infrastructure network, including geographic information system (GIS), Internet of things (IoT), cooperative vehicle infrastructure system (CVIS), big data technology, and intelligent transportation system (ITS), etc. It is found that digital technologies have unique advantages and application potential in the prevention, early warning, and rescue of unexpected accidents than traditional emergency transportation management. Finally, we summarize the characteristics of the current effort and propose future research directions.

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Section: Emergency Resource Dispatchingmentioning

confidence: 99%

Section: Emergency Resource Dispatchingmentioning

confidence: 99%

Digital emergency response technologies research of transportation infrastructure network: a review and prospects

Jiang

2022

International Conference on Smart Transportation and City Engineering (STCE 2022)

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“…Our proposed system is designed to significantly reduce, if not entirely eliminate, delays encountered by Ambulances in an Emergency (AIAEs) at traffic lights, in particular in one-way street restrictions or roadwork. Contributions by Rangel et al [4] highlight the critical impact of traffic light delays on ambulance response times, underscoring the need for effective solutions. By enabling a rapid green light sequence for ambulances, our system aims at enhancing the overall efficiency of emergency medical services, thereby improving patient survival rates and response effectiveness in urban and sub-urban settings.…”

Section: Introductionmentioning

confidence: 99%

RTAIAED: A Real-Time Ambulance in an Emergency Detector with a Pyramidal Part-Based Model Composed of MFCCs and YOLOv8

Mecocci,

Grassi

2024

Sensors

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In emergency situations, every second counts for an ambulance navigating through traffic. Efficient use of traffic light systems can play a crucial role in minimizing response time. This paper introduces a novel automated Real-Time Ambulance in an Emergency Detector (RTAIAED). The proposed system uses special Lookout Stations (LSs) suitably positioned at a certain distance from each involved traffic light (TL), to obtain timely and safe transitions to green lights as the Ambulance in an Emergency (AIAE) approaches. The foundation of the proposed system is built on the simultaneous processing of video and audio data. The video analysis is inspired by the Part-Based Model theory integrating tailored video detectors that leverage a custom YOLOv8 model for enhanced precision. Concurrently the audio analysis component employs a neural network designed to analyze Mel Frequency Cepstral Coefficients (MFCCs) providing an accurate classification of auditory information. This dual-faceted approach facilitates a cohesive and synergistic analysis of sensory inputs. It incorporates a logic-based component to integrate and interpret the detections from each sensory channel, thereby ensuring the precise identification of an AIAE as it approaches a traffic light. Extensive experiments confirm the robustness of the approach and its reliable application in real-world scenarios thanks to its predictions in real time (reaching an fps of 11.8 on a Jetson Nano and a response time up to 0.25 s), showcasing the ability to detect AIAEs even in challenging conditions, such as noisy environments, nighttime, or adverse weather conditions, provided a suitable-quality camera is appropriately positioned. The RTAIAED is particularly effective on one-way roads, addressing the challenge of regulating the sequence of traffic light signals so as to ensure a green signal to the AIAE when arriving in front of the TL, despite the presence of the “double red” periods in which the one-way traffic is cleared of vehicles coming from one direction before allowing those coming from the other side. Also, it is suitable for managing temporary situations, like in the case of roadworks.

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Mobility Sensing and V2X Communication for Emergency Services

et al. 2022

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Palavras-chavevanet, mobilidade veículos de emergência, sensorização em tempo real ResumoAo longo dos anos, a população mundial que vive em cidades tem vindo a crescer, levantando vários problemas de gestão de mobilidade. Os tempos de viagem, o número de acidentes e a poluição gerada têm vindo a aumentar. Com a evolução das smart cities, do desenvolvimento de sensores, da comunicação IoT e veicular, torna-se possível o processamento de dados em tempo real, assim como a comunicação entre veículos que permite não apenas o melhoramento da mobilidade nas cidades, mas também da segurança nas estradas. Esta dissertação propõe um sistema que recolhe, processa e dissemina dados em tempo real dentro de uma rede veicular, integrando dados de diferentes sensores relacionados com a mobilidade, e desenvolvendo um serviço de disseminação para o alerta de emergências, tendo como foco contribuir para a redução do tempo de resposta de veículos de emergência. Com o auxílio de RADARs e de mensagens enviadas por veículos, que são recolhidos e processados em tempo real, é possível obter informações sobre o congestionamento das vias, permitindo a geração de alertas de trânsito e alertas de emergência que serão disseminados por veículos e outros nós de uma smart city, mais particularmente no aviso de aproximação de veículos de emergência. Os sistemas desenvolvidos foram testados em laboratório e num cenário real de cidade, utilizando uma infraestrutura já implementada (Aveiro Tech City Living Lab) na cidade de Aveiro, Portugal. Com esta abordagem, os resultados obtidos demonstram a possibilidade de transmissão de informações em tempo real entre veículos e unidades rodoviárias para envio de avisos sobre a aproximação de veículos de emergência. Comparando os modos de comunicação infraestrutura-para-veículo, veículo-para-veículo, ou uma abordagem híbrida em que ambas as comunicações são simultaneamente usadas, houve uma redução de um máximo de 80% para 20% de perdas de comunicação na disseminação de avisos, quando a solução hibrida é utilizada.

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An Optimization Approach for Emergency Vehicles Dispatching and Traffic Lights Adjustments in Response to Emergencies in Smart Cities

Cited by 5 publications

References 25 publications

Digital emergency response technologies research of transportation infrastructure network: a review and prospects

Digital emergency response technologies research of transportation infrastructure network: a review and prospects

RTAIAED: A Real-Time Ambulance in an Emergency Detector with a Pyramidal Part-Based Model Composed of MFCCs and YOLOv8

Mobility Sensing and V2X Communication for Emergency Services

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