Scorpion: A Solution Using Cooperative Rerouting to Prevent Congestion and Improve Traffic Condition

Souza, Allan M. de; Yokoyama, Roberto Sadao; Botega, Leonardo Castro; Meneguette, Rodolfo I.; Villas, Leandro A.

doi:10.1109/cit/iucc/dasc/picom.2015.71

Cited by 37 publications

(29 citation statements)

References 13 publications

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“…VANETs have also been considered [27][28][29][30]. In [27] an Ant-based Vehicle Congestion Avoidance System (AVCAS) has been proposed.…”

Section: Route Planning Methods That Consider Real-time Traffic Informentioning

confidence: 99%

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Centralized simulated annealing for alleviating vehicular congestion in smart cities

Amer

Al-Kashoash

Hawes

et al. 2019

Technological Forecasting and Social Change

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“…VANETs have also been considered [27][28][29][30]. In [27] an Ant-based Vehicle Congestion Avoidance System (AVCAS) has been proposed.…”

Section: Route Planning Methods That Consider Real-time Traffic Informentioning

confidence: 99%

“…Then it uses the dynamic Dijkstra's algorithm to find different shortest paths to re-route the vehicles. In [28] and [29], two approaches have proposed to reduce the vehicular traffic congestion in smart cities. The first one is a centralized and the second one is a decentralized framework.…”

Section: Route Planning Methods That Consider Real-time Traffic Informentioning

confidence: 99%

Centralized simulated annealing for alleviating vehicular congestion in smart cities

Amer

Al-Kashoash

Hawes

et al. 2019

Technological Forecasting and Social Change

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show abstract

“…In recent years, several works have explored this problem. 13,[21][22][23][24][25][26][27] However, until now, there is no adequate real-time service that provides useful information to the vehicle about what is happening in the streets as well as information captured by the mobile device drivers to perform efficient monitoring and suggesting new routes based on the streets status information.…”

Section: Related Workmentioning

confidence: 99%

ITSMEI: An intelligent transport system for monitoring traffic and event information

Quessada

Pereira

Revejes

et al. 2020

International Journal of Distributed Sensor Networks

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The disorderly growth of urban centers can lead to serious socioeconomic disadvantages, such as health problems, due to long-term exposure to toxic gases and also monetary losses due to time stopped in congestion. Thus, there is a need for systems that help in the management and control of the flow of vehicles on the roads, seeking to reduce the damage resulting from a faulty transportation system and also avoiding the use of an inefficient system of information dissemination of urban roads. In this scenario, innovative systems are being developed to analyze the conjunction of road conditions to supervise and provide routes as needed for drivers to provide greater comfort and safety to vehicle traffic on urban roads. Thus, in this work, we propose the development of a system to monitor vehicle traffic, informing about events that are taking place on the roads in real time. The system can recommend new routes to drivers or allow drivers to take action based on information received from a particular road. As well as, the system uses driver location information for traffic monitoring, which will later be available for any devices, either a mobile device (smartphone) or a desktop. For the evaluation of the proposed system, a user case was developed for the Catanduva city in which we performed a test with the proposed system and was possible to verify a reduction in vehicle stopping time by 42% and a shorter travel time of 50% with an average speed of 33 km/h.

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“…The simulations carried out in a realistic Manhattan scenario showed a reduction of 9% to 26% of ATT. SCORPION [9] (A Solution using Cooperative Rerouting to Prevent Congestion and Improve Traffic Condition) uses vehicle-to-infrastructure (V2I) communications. All vehicles send their information (id, current position, route, and destination) using 4G and LTE technologies to the nearest road side unit (RSU), which uses the k-nearest neighbor algorithm to classify street congestion.…”

Section: Related Workmentioning

confidence: 99%

Deep Learning System for Vehicular Re-Routing and Congestion Avoidance

et al. 2019

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Delays in transportation due to congestion generated by public and private transportation are common in many urban areas of the world. To make transportation systems more efficient, intelligent transportation systems (ITS) are currently being developed. One of the objectives of ITS is to detect congested areas and redirect vehicles away from them. However, most existing approaches only react once the traffic jam has occurred and, therefore, the delay has already spread to more areas of the traffic network. We propose a vehicle redirection system to avoid congestion that uses a model based on deep learning to predict the future state of the traffic network. The model uses the information obtained from the previous step to determine the zones with possible congestion, and redirects the vehicles that are about to cross them. Alternative routes are generated using the entropy-balanced k Shortest Path algorithm (EBkSP). The proposal uses information obtained in real time by a set of probe cars to detect non-recurrent congestion. The results obtained from simulations in various scenarios have shown that the proposal is capable of reducing the average travel time (ATT) by up to 19%, benefiting a maximum of 38% of the vehicles.

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Scorpion: A Solution Using Cooperative Rerouting to Prevent Congestion and Improve Traffic Condition

Cited by 37 publications

References 13 publications

Centralized simulated annealing for alleviating vehicular congestion in smart cities

Centralized simulated annealing for alleviating vehicular congestion in smart cities

ITSMEI: An intelligent transport system for monitoring traffic and event information

Deep Learning System for Vehicular Re-Routing and Congestion Avoidance

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