scholarly journals Towards Personal Virtual Traffic Lights

Information ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 32 ◽  
Author(s):  
Vanessa Martins ◽  
João Rufino ◽  
Luis Silva ◽  
João Almeida ◽  
Bruno Miguel Fernandes Silva ◽  
...  
Keyword(s):  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Communication Systems ◽  
Field Tests ◽  
Transportation Systems ◽  
Smart Devices ◽  
Vehicular Communication ◽  
Traffic Light ◽  
Correct Operation ◽  
Traffic Lights

Traffic control management at intersections, a challenging and complex field of study, aims to strike a balance between safety and efficient traffic control. Nowadays, traffic control at intersections is typically done by traffic light systems which are not optimal and exhibit several drawbacks, such as poor efficiency and real-time adaptability. With the advent of Intelligent Transportation Systems (ITS), vehicles are being equipped with state-of-the-art technology, enabling cooperative decision-making which will certainly overwhelm the available traffic control systems. This solution strongly penalizes users without such capabilities, namely pedestrians, cyclists, and other legacy vehicles. Therefore, in this work, a prototype based on an alternative technology to the standard vehicular communications, Bluetooth Low Energy (BLE), is presented. The proposed framework aims to integrate legacy and modern vehicular communication systems into a cohesive management system. In this framework, the movements of users at intersections are managed by a centralized controller which, through the use of networked retransmitters deployed at intersections, broadcasts alerts and virtual light signalization orders. Users receive the aforementioned information on their own smart devices, discarding the need for dedicated light signalization infrastructures. Field tests, carried out with a real-world implementation, validate the correct operation of the proposed framework.

Employing Traffic Lights as Road Side Units for Road Safety Information Broadcast

2015 ◽  
pp. 143-159
Author(s):  
Navin Kumar ◽  
Luis Nero Alves ◽  
Rui L. Aguiar
Keyword(s):  
Traffic Safety ◽  
Intelligent Transportation Systems ◽  
Safety Information ◽  
Visible Light Communication ◽  
Transportation Systems ◽  
Vehicular Communication ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Road ◽  
Smooth Flow

There is great concern over growing road accidents and associated fatalities. In order to reduce accidents, improve congestion and offer smooth flow of traffic, several measures, such as providing intelligence to transport, providing communication infrastructure along the road, and vehicular communication, are being undertaken. Traffic safety information broadcast from traffic lights using Visible Light Communication (VLC) is a new cost effective technology which assists drivers in taking necessary safety measures. This chapter presents the VLC broadcast system considering LED-based traffic lights. It discusses the integration of traffic light Roadside Units (RSUs) with upcoming Intelligent Transportation Systems (ITS) architecture. Some of the offered services using this technology in vehicular environment together with future directions and challenges are discussed. A prototype demonstrator of the designed VLC systems is also presented.

Employing Traffic Lights as Road Side Units for Road Safety Information Broadcast

2012 ◽  
pp. 118-135 ◽  
Author(s):  
Navin Kumar ◽  
Luis Nero Alves ◽  
Rui L. Aguiar
Keyword(s):  
Traffic Safety ◽  
Intelligent Transportation Systems ◽  
Safety Information ◽  
Visible Light Communication ◽  
Transportation Systems ◽  
Vehicular Communication ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Road ◽  
Smooth Flow

There is great concern over growing road accidents and associated fatalities. In order to reduce accidents, improve congestion and offer smooth flow of traffic, several measures, such as providing intelligence to transport, providing communication infrastructure along the road, and vehicular communication, are being undertaken. Traffic safety information broadcast from traffic lights using Visible Light Communication (VLC) is a new cost effective technology which assists drivers in taking necessary safety measures. This chapter presents the VLC broadcast system considering LED-based traffic lights. It discusses the integration of traffic light Roadside Units (RSUs) with upcoming Intelligent Transportation Systems (ITS) architecture. Some of the offered services using this technology in vehicular environment together with future directions and challenges are discussed. A prototype demonstrator of the designed VLC systems is also presented.

Fog-based Intelligent Transportation System for Traffic Light Optimization

2021 ◽  
Vol 58 (S) ◽  
pp. 29-35
Author(s):  
Muhammad Rusyadi Ramli ◽  
Riesa Krisna Astuti Sakir ◽  
Dong-Seong Kim
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Accidents ◽  
Intelligent Transportation System ◽  
Optimization Problems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Traffic Light ◽  
Traffic Condition ◽  
Dilemma Zone ◽  
Traffic Lights

This paper presents fog-based intelligent transportation systems (ITS) architecture for traffic light optimization. Specifically, each intersection consists of traffic lights equipped with a fog node. The roadside unit (RSU) node is deployed to monitor the traffic condition and transmit it to the fog node. The traffic light center (TLC) is used to collect the traffic condition from the fog nodes of all intersections. In this work, two traffic light optimization problems are addressed where each problem will be processed either on fog node or TLC according to their requirements. First, the high latency for the vehicle to decide the dilemma zone is addressed. In the dilemma zone, the vehicle may hesitate whether to accelerate or decelerate that can lead to traffic accidents if the decision is not taken quickly. This first problem is processed on the fog node since it requires a real-time process to accomplish. Second, the proposed architecture aims each intersection aware of its adjacent traffic condition. Thus, the TLC is used to estimate the total incoming number of vehicles based on the gathered information from all fog nodes of each intersection. The results show that the proposed fog-based ITS architecture has better performance in terms of network latency compared to the existing solution in which relies only on TLC.

scholarly journals Smart Cities and Data Analytics for Intelligent Transportation Systems: An Analytical Model for Scheduling Phases and Traffic Lights at Signalized Intersections

2021 ◽  
Vol 11 (15) ◽  
pp. 6816
Author(s):  
Fatih Gunes ◽  
Selim Bayrakli ◽  
Abdul Halim Zaim
Keyword(s):  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Transportation Systems ◽  
Signalized Intersections ◽  
Effective Control ◽  
Main Role ◽  
Smart Transportation ◽  
Traffic Lights ◽  
Service Rates

This paper is intended to improve the performance of signalized intersections, one of the most important systems of traffic control explained within the scope of smart transportation systems. These structures, which have the main role in ensuring the order and flow of traffic, are alternative systems depending on the different methods and techniques used. Determining the operation principles of these systems requires an extremely careful and planned study, considering their important role. Performance outputs obtained from the queue analyses made in previous studies formed the input of this study. The most important techniques are used in the effective control of intersections, such as signal timing: in particular, the use of effective green time and order of the transitions between phases. In this research, a traffic-sensitive signalized intersection control system was designed with the suggested methods against these two problems. The sample intersections were selected from three cities with the highest population density as the case study area. In the analysis of the performance of the connection arms of the selected intersections, flow intensity data were taken into consideration, as well as the arrival and service rates. Based on this, the outputs of the two proposed models regarding the use of phase transitions and effective green durations were compared with two other adaptive control systems and their positive results were shared. The results showed that signalized intersections, operating with a well-planned and correctly chosen technique, better regulate density and queuing.

scholarly journals A Multiagent Approach to Autonomous Intersection Management

2008 ◽  
Vol 31 ◽  
pp. 591-656 ◽  
Author(s):  
K. Dresner ◽  
P. Stone
Keyword(s):  
Intelligent Transportation Systems ◽  
Autonomous Vehicles ◽  
Multiagent System ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Alternative Mechanism ◽  
Traffic Light ◽  
Traffic Lights ◽  
Stop Sign ◽  
Intersection Control

Artificial intelligence research is ushering in a new era of sophisticated, mass-market transportation technology. While computers can already fly a passenger jet better than a trained human pilot, people are still faced with the dangerous yet tedious task of driving automobiles. Intelligent Transportation Systems (ITS) is the field that focuses on integrating information technology with vehicles and transportation infrastructure to make transportation safer, cheaper, and more efficient. Recent advances in ITS point to a future in which vehicles themselves handle the vast majority of the driving task. Once autonomous vehicles become popular, autonomous interactions amongst multiple vehicles will be possible. Current methods of vehicle coordination, which are all designed to work with human drivers, will be outdated. The bottleneck for roadway efficiency will no longer be the drivers, but rather the mechanism by which those drivers' actions are coordinated. While open-road driving is a well-studied and more-or-less-solved problem, urban traffic scenarios, especially intersections, are much more challenging. We believe current methods for controlling traffic, specifically at intersections, will not be able to take advantage of the increased sensitivity and precision of autonomous vehicles as compared to human drivers. In this article, we suggest an alternative mechanism for coordinating the movement of autonomous vehicles through intersections. Drivers and intersections in this mechanism are treated as autonomous agents in a multiagent system. In this multiagent system, intersections use a new reservation-based approach built around a detailed communication protocol, which we also present. We demonstrate in simulation that our new mechanism has the potential to significantly outperform current intersection control technology -- traffic lights and stop signs. Because our mechanism can emulate a traffic light or stop sign, it subsumes the most popular current methods of intersection control. This article also presents two extensions to the mechanism. The first extension allows the system to control human-driven vehicles in addition to autonomous vehicles. The second gives priority to emergency vehicles without significant cost to civilian vehicles. The mechanism, including both extensions, is implemented and tested in simulation, and we present experimental results that strongly attest to the efficacy of this approach.

scholarly journals Implementation and Evaluation of a Traffic Light Assistance System Based on V2I Communication in a Simulation Framework

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Cristina Olaverri-Monreal ◽  
Javier Errea-Moreno ◽  
Alberto Díaz-Álvarez
Keyword(s):  
Intelligent Transportation Systems ◽  
Road Safety ◽  
Traffic Management ◽  
Transportation Systems ◽  
Traffic Light ◽  
Phase Duration ◽  
Traffic Lights ◽  
Real Time Traffic ◽  
Timing Data ◽  
Cooperative Intelligent Transportation Systems

Cooperative Intelligent Transportation Systems (C-ITS) make the exchange of information possible through cooperative systems that broadcast traffic data to enhance road safety. Traffic light assistance (TLA) systems in particular utilize real-time traffic light timing data by accessing the information directly from the traffic management center. To test the reliability of a TLA system based on networked intervehicular interaction with infrastructure, we present in this paper an approach to perform theoretical studies in a lab-controlled scenario. The proposed system retrieves the traffic light timing program within a range in order to calculate the optimal speed while approaching an intersection and shows a recommended velocity based on the vehicle’s current acceleration and speed, phase state of the traffic light, and remaining phase duration. Results show an increase in driving efficiency in the form of improvement of traffic flow, reduced gas emissions, and waiting time at traffic lights after the drivers adjusted their velocity to the speed calculated by the system.

scholarly journals Multiagent Based Decentralized Traffic Light Control for Large Urban Transportation System

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Yang Xu ◽  
Yulin Zhang ◽  
Ming Liu
Keyword(s):  
Traffic Control ◽  
Large Scale ◽  
Urban Transportation ◽  
Transportation System ◽  
Transportation Systems ◽  
Communication Overhead ◽  
Traffic Light ◽  
Traffic Lights ◽  
Joint Activities ◽  
Green Transportation

Intelligent traffic control is an important issue of the modern transportation system. However, in large-scale urban transportation systems, traditional centralized coordination methods suffer bottlenecks in both communication and computation. Decentralized control is hard if there is very limited observation to the whole network as evidences to support joint traffic coordination decisions. In this paper, we proposed a novel decentralized, multiagent based approach for massive traffic lights coordination to promote the large-scale green transportation. Considering that only the traffic from the adjacent intersections may affect the state of a given intersection one time ahead, the key of our approach is using the observations of a local intersection and its neighbors as evidences to support the traffic light coordination decisions. Therefore, we can model the interactions as decentralized agents coordinating with a decision theoretical model. Within a local intersection, constraint optimizing agents are designed to efficiently search for joint activities of the lights. Since this approach involves only local intersection cooperation, it is well scalable and easily implemented with small communication overhead. In the last section, we present our software design on this approach and based on our simulation, this approach is feasible to a large urban transportation system.

scholarly journals Lightweight PVIDNet: A Priority Vehicles Detection Network Model Based on Deep Learning for Intelligent Traffic Lights

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6218
Author(s):  
Rodrigo Carvalho Barbosa ◽  
Muhammad Shoaib Ayub ◽  
Renata Lopes Rosa ◽  
Demóstenes Zegarra Rodríguez ◽  
Lunchakorn Wuttisittikulkij
Keyword(s):  
Deep Learning ◽  
Traffic Control ◽  
Detection System ◽  
Lightweight Design ◽  
Vehicle Detection ◽  
Activation Function ◽  
Urban Traffic ◽  
Vehicle Classification ◽  
Traffic Light ◽  
Traffic Lights

Minimizing human intervention in engines, such as traffic lights, through automatic applications and sensors has been the focus of many studies. Thus, Deep Learning (DL) algorithms have been studied for traffic signs and vehicle identification in an urban traffic context. However, there is a lack of priority vehicle classification algorithms with high accuracy, fast processing, and a lightweight solution. For filling those gaps, a vehicle detection system is proposed, which is integrated with an intelligent traffic light. Thus, this work proposes (1) a novel vehicle detection model named Priority Vehicle Image Detection Network (PVIDNet), based on YOLOV3, (2) a lightweight design strategy for the PVIDNet model using an activation function to decrease the execution time of the proposed model, (3) a traffic control algorithm based on the Brazilian Traffic Code, and (4) a database containing Brazilian vehicle images. The effectiveness of the proposed solutions were evaluated using the Simulation of Urban MObility (SUMO) tool. Results show that PVIDNet reached an accuracy higher than 0.95, and the waiting time of priority vehicles was reduced by up to 50%, demonstrating the effectiveness of the proposed solution.

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