scholarly journals Modelling green waves for emergency vehicles using connected traffic data

10.29007/sj1m ◽  
2019 ◽  
Author(s):  
Laura Bieker-Walz ◽  
Michael Behrisch
Keyword(s):  
Negative Impact ◽  
Important Task ◽  
Optimal Timing ◽  
Emergency Vehicle ◽  
Traffic Data ◽  
Vehicular Communication ◽  
Traffic Light ◽  
Vehicle Traffic ◽  
Traffic Lights ◽  
Emergency Vehicles

For emergency vehicle drivers it is an important task to reach the incident location as fast as possible. Therefore a self-organizing green wave could help emergency vehicles to accomplish this goal. This study presents an approach how emergency vehicle can be prioritized at traffic lights and simulates the possible benefit for the emergency vehicle. Traffic data from vehicular communication can be used to find the optimal timing for the traffic light to modify the existing traffic phases and reduce the possible negative impact on other traffic participants.

scholarly journals Automatic traffic light controller for emergency vehicle using peripheral interface controller

2019 ◽  
Vol 9 (3) ◽  
pp. 1788 ◽  
Author(s):  
Norlezah Hashim ◽  
Fakrulradzi Idris ◽  
Ahmad Fauzan Kadmin ◽  
Siti Suhaila Jaapar Sidek
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Emergency Situation ◽  
Light Signal ◽  
Emergency Vehicle ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Road ◽  
Light Area ◽  
On The Road

Traffic lights play such important role in traffic management to control the traffic on the road. Situation at traffic light area is getting worse especially in the event of emergency cases. During traffic congestion, it is difficult for emergency vehicle to cross the road which involves many junctions. This situation leads to unsafe conditions which may cause accident. An Automatic Traffic Light Controller for Emergency Vehicle is designed and developed to help emergency vehicle crossing the road at traffic light junction during emergency situation. This project used Peripheral Interface Controller (PIC) to program a priority-based traffic light controller for emergency vehicle. During emergency cases, emergency vehicle like ambulance can trigger the traffic light signal to change from red to green in order to make clearance for its path automatically. Using Radio Frequency (RF) the traffic light operation will turn back to normal when the ambulance finishes crossing the road. Result showed the design is capable to response within the range of 55 meters. This project was successfully designed, implemented and tested.

scholarly journals Ant Colony Optimization for Real Time Traffic Lights Control on a Single Intersection

2020 ◽  
Vol 14 (02) ◽  
pp. 196 ◽  
Author(s):  
Nouha Rida ◽  
Mohammed Ouadoud ◽  
Aberrahim Hasbi
Keyword(s):  
Road Traffic ◽  
Green Light ◽  
Optimal Solution ◽  
Ant Colony ◽  
Traffic Data ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Road ◽  
Real Time Traffic ◽  
On The Road

In this paper, we present a new scheme to intelligently control the cycles and phases of traffic lights by exploiting the road traffic data collected by a wireless sensor network installed on the road. The traffic light controller determines the next phase of traffic lights by applying the Ant Colony Optimazation metaheuristics to the information collected by WSN. The objective of this system is to find an optimal solution that gives the best possible results in terms of reducing the waiting time of vehicles and maximizing the flow crossing the intersection during the green light. The results of simulations by the SUMO traffic simulator confirm the preference of the developed algorithm over the predefined time controller and other dynamic controllers.

scholarly journals An Optimised Traffic Control Scheme with Preference to Emergency Vehicles Leveraging RFID

2021 ◽  
pp. 74-89
Author(s):  
Kenneth Akpado ◽  
Samuel Usoro ◽  
Nneka Ezeani
Keyword(s):  
Control System ◽  
Traffic Control ◽  
Research Work ◽  
Control Points ◽  
Emergency Vehicle ◽  
Test Bed ◽  
Traffic Light ◽  
Emergency Vehicles ◽  
Traffic Control System ◽  
New System

Emergency Vehicles (EV) such as ambulances, fire fighting vehicles, Road safety vehicles and other emergency vehicles encounter delays on their missions at traffic light control points due to traffic jams. The direct consequence of these delays results in unwarranted loss of lives and properties.  This research work proposes and implements an improved traffic control system with preference to emergency vehicles leveraging RFID technology and a novel Dynamic Traffic Sequence Algorithm (DTSA). Atmega 328 was used to actualize the novel DTSA, control the RFID and the entire traffic control system. The distance of RFID signal transmitted by the emergency vehicle was determined by physically measuring the distance of clearer signal obtained at various distances from the test bed. MATLAB was used to plot the response time of the RFID, thereby helping in the choice of RFID used. It was observed at 100 meters distance between the RFID transmitter in the emergency vehicle (EV) and the traffic light system, a clearer signal was obtained. Therefore at 100 meters the emergency vehicle will be detected and the traffic system will reset its normal routine to give right of way to the particular lane that the emergency vehicle is detected. Comparing the old and the new system it was observed that in the new system the EV will be 12minutes faster than the EV in the old system. From the result obtained, the RFID best suited for this application is active RFID. The results obtained proved that the system will effectively mitigate and almost completely eradicate the delay encountered by emergency vehicles at traffic control points.  The system will be deployed in any many cities in Nigeria that have traffic control systems installed.

scholarly journals Emergency Vehicle Priority Based System

2021 ◽  
pp. 377-382
Author(s):  
Sarfraz Ahmad ◽  
K. C. Maurya
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Green Light ◽  
Emergency Vehicle ◽  
Current Case ◽  
Traffic Lights ◽  
Current State ◽  
Emergency Vehicles ◽  
Vehicle Information ◽  
Police Cars

Every country's vehicular traffic is increasing, growing, and there is terrible traffic congestion at intersections. In the current case, most traffic lights have a fixed light sequence, so green light sequence is to determine with-out taking priority vehicles into account. As a result, priority crews such as police cars, ambulances, fire engines are still unable to perform, get stuck in traffic and come in late, which can result in the loss of valuable property and life, which does happen on occasion. The green light sequence is evaluated given the current state of traffic, without taking into account the existence of emergency vehicles. Our aim to this paper is to present a mechanism for scheduling emergency vehicles. It is provided to important such as access control protocol to convey emergency vehicle information to the Traffic Management Center (TMC) with time delay and to all alerts while using GPS techniques for acquiring emergency vehicle information. Only then is the emergency vehicle quickly dispatched, and the destination is reached on time. It would be helpful in the future for the prominence of casual vehicles.

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.

scholarly journals Influences of Waiting Time on Driver Behaviors While Implementing In-Vehicle Traffic Light for Priority-Controlled Unsignalized Intersections

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Bo Yang ◽  
Rencheng Zheng ◽  
Tsutomu Kaizuka ◽  
Kimihiko Nakano
Keyword(s):  
Waiting Time ◽  
Driving Simulator ◽  
Lateral Acceleration ◽  
Traffic Light ◽  
Road Vehicles ◽  
Maximum Acceleration ◽  
Vehicle Traffic ◽  
Traffic Lights ◽  
Unsignalized Intersections ◽  
Minor Road

In-vehicle traffic lights that assist drivers in crossing intersections are in development; however, the availability of the in-vehicle traffic light will be limited if the waiting time of a vehicle is not considered in actual traffic conditions, especially at priority-controlled unsignalized intersections that normally consist of one major and two minor roads. The present study therefore investigated the effects of the waiting time on driver behaviors to improve the in-vehicle traffic light for the priority-controlled unsignalized intersections. Gap acceptance theory that considers the waiting time was adopted in the implementation of the in-vehicle traffic light, to assist minor-road drivers in passing through the intersections by selecting appropriate major-road gaps. A driving simulator experiment involving 12 participants was performed for the minor and major roads, by applying the in-vehicle traffic light with and without the consideration of waiting time. Results demonstrate that the maximum acceleration strokes of minor-road vehicles were significantly reduced, indicating a lower possibility of aggressive driving when the in-vehicle traffic light was applied while considering the waiting time. Meanwhile, an improved steering stability was observed from the driver behaviors at the intersections, as the maximum lateral acceleration of minor-road vehicles significantly decreased when the waiting time was considered.

scholarly journals A Genetic Algorithm Approach for Expedited Crossing of Emergency Vehicles in Connected and Autonomous Intersection Traffic

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Qiang Lu ◽  
Kyoung-Dae Kim
Keyword(s):  
Genetic Algorithm ◽  
Emergency Vehicle ◽  
Travel Times ◽  
Traffic Light ◽  
Main Challenge ◽  
Emergency Vehicles ◽  
Intersection Area ◽  
Traffic Volumes ◽  
Genetic Algorithm Approach ◽  
Optimal Ordering

This paper proposes an intersection control algorithm which aims to determine an efficient vehicle-passing sequence that allows the emergency vehicle to cross an intersection as soon as possible while the travel times of other vehicles are minimally affected. When there are no emergency vehicles within the intersection area, the vehicles are controlled by the DICA that we proposed in our earlier work. When there are emergency vehicles entering the communication range, we prioritize emergency vehicles through optimal ordering of vehicles. Since the number of possible vehicle-passing sequences increases rapidly with the number of vehicles, finding an efficient sequence of vehicles in a short time is the main challenge of the study. A genetic algorithm is proposed to solve the optimization problem which finds the optimal vehicle sequence that gives the emergency vehicles the highest priority. The efficiency of the proposed approach for expedited crossing of emergency vehicles is validated through comparisons with DICA and a reactive traffic light algorithm through extensive simulations. The results show that the proposed genetic algorithm is able to decrease the travel times of emergency vehicles significantly in light and medium traffic volumes without causing any noticeable performance degradation of normal vehicles.

scholarly journals Improving traffic and emergency vehicle clearence at congested intersections using fuzzy inference engine

2021 ◽  
Vol 11 (4) ◽  
pp. 3176
Author(s):  
Aditi Agrawal ◽  
Rajeev Paulus
Keyword(s):  
Control System ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Fuzzy Inference ◽  
Heavy Traffic ◽  
Green Light ◽  
Emergency Vehicle ◽  
Traffic Light ◽  
Traffic Condition ◽  
Traffic Lights

Traffic signals play an important role in controlling and coordinating the traffic movement in cities especially in urban areas. As the traffic is exponentially increasing in cities and the pre-timed traffic light control is insufficient in effective timing of the traffic lights, it leads to poor traffic clearance and ultimately to heavy traffic congestion at intersections. Even the Emergency vehicles like Ambulance and Fire brigade are struck at such intersections and experience a prolonged waiting time. An adaptive and intelligent approach in design of traffic light signals is desirable and this paper contributes in applying fuzzy logic to control traffic signal of single four-way intersection giving priority to the Emergency vehicle clearance. The proposed control system is composed of two parallel controllers to select the appropriate lane for green signal and also to decide the appropriate green light time as per the real time traffic condition. Performance of the proposed system is evaluated by using simulations and comparing with pre-timed control system in changing traffic flow condition. Simulation results show significant improvement over the pre-timed control in terms of traffic clearance and lowering of Emergency vehicle wait time at the intersection especially when traffic intensity is high.

scholarly journals Driver Assistance System using in-vehicle Traffic Lights and Signs

2018 ◽  
Vol 7 (2.24) ◽  
pp. 527
Author(s):  
Vaibhav Jain ◽  
Tanay . ◽  
Saransh Gangele ◽  
K Kalimuthu
Keyword(s):  
Traffic Congestion ◽  
Driver Assistance System ◽  
Road Traffic ◽  
Obstacle Detection ◽  
Assistance System ◽  
Vehicular Communication ◽  
Driver Assistance ◽  
Traffic Light ◽  
Traffic Lights ◽  
Road Signs

In recent years, with the advancement of vehicular communication, it is possible to detect various road signs and provide traffic light information to the driver inside the vehicle with the application of heads-up display (HUD). It detects road signs, does basic classifications and accordingly directs the driver to slow down or stop the vehicle. The vehicle’s heads-up display keeps the driver focused by providing road warnings, speed limit, traffic signals and some vital navigation information in the driver’s line of sight(LOS). This system has 4 phases, Image recognition, wireless communication, obstacle detection and driver mechanism. This system aims to create a prototype of a smart driver assistance system which provides better road traffic and driver’s safety in countries with high traffic congestion where fully automated vehicles cannot function effectively. This system can be easily implemented in real time scenarios to reduce accidents and enhance the convenience of driving. 

scholarly journals Deep Reinforcement Learning Model to Mitigate Congestion in Real-Time Traffic Light Networks

2021 ◽  
Vol 6 (10) ◽  
pp. 138
Author(s):  
Fábio de Souza Pereira Borges ◽  
Adelayda Pallavicini Fonseca ◽  
Reinaldo Crispiniano Garcia
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
Traffic Control ◽  
High Volume ◽  
Urban Traffic ◽  
Traffic Data ◽  
Traffic Light ◽  
Urban Network ◽  
Traffic Demand ◽  
Traffic Lights

Urban traffic congestion has a significant detrimental impact on the environment, public health and the economy, with at a high cost to society worldwide. Moreover, it is not possible to continually modify urban road infrastructure in order to mitigate increasing traffic demand. Therefore, it is important to develop traffic control models that can handle high-volume traffic data and synchronize traffic lights in an urban network in real time, without interfering with other initiatives. Within this context, this study proposes a model, based on deep reinforcement learning, for synchronizing the traffic signals of an urban traffic network composed of two intersections. The calibration of this model, including training of its neural network, was performed using real traffic data collected at the approach to each intersection. The results achieved through simulations were very promising, yielding significant improvements in indicators measured in relation to the pre-existing conditions in the network. The model was able to deal with a broad spectrum of traffic flows and, in peak demand periods, reduced delays and queue lengths by more than 28% and 42%, respectively.

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