Intelligent Traffic Light Management: Arterial Simulation & Optimization (original) (raw)

Traffic Lights Management Using Optimization Tool

Procedia - Social and Behavioral Sciences, 2018

The increase of traffic is one of today's problems. Numerous cities are affected by traffic congestion and the increase of emissions from fuel use. They have a negative impact on economy, environment and overall on the quality of life. It is necessary to find intelligent solutions for road traffic management. The interest for intelligent traffic systems appeared at the beginning of the 20 th century. There are various methods available for traffic management such as inductive loop detection, infrared sensors, video data analysis etc. The purpose of this paper is to present an approach of optimization tool using in order to decrease the traffic congestion and the crossing time of a road network.

A dynamic and automatic traffic light control expert system for solving the road congestion problem

Expert Systems with Applications, 2008

Traffic congestion is a severe problem in many modern cities around the world. To solve the problem, we have proposed a framework for a dynamic and automatic traffic light control expert system combined with a simulation model, which is composed of six submodels coded in Arena to help analyze the traffic problem. The model adopts interarrival time and interdeparture time to simulate the arrival and leaving number of cars on roads. In the experiment, each submodel represents a road that has three intersections. The simulation results physically prove the efficiency of the traffic system in an urban area, because the average waiting time of cars at every intersection is sharply dropped when the red light duration is 65 s and the green light time duration is 125 s. Meanwhile, further analysis also shows if we keep the interarrival time of roads A, B, and C, and change that of roads D, E, and F from 1.7 to 3.4 s and the interdeparture times at the three intersections on roads A, B, and C are equal to 0.6 s, the total performance of the simulation model is the best. Finally, according to the data collected from RFID readers and the best, second and third best traffic light durations generated from the simulation model, the automatic and dynamic traffic light control expert system can control how long traffic signals should be for traffic improvement.

Aurora Arterial Modeler – a Macroscopic Tool for Urban Traffic Signal Control

12th IFAC Symposium on Control in Transportation Systems, 2009

This paper describes a macroscopic simulation model for urban signal control based on the Aurora Road Network Modeler (RNM) software package. The paper first presents the implementation of pre-timed and actuated signal controllers in a cell transmission model based simulator. Then a case study with wireless sensor traffic data is carried out to test the performance of the model. The results show that the macroscopic model produces good estimates of arterial travel time, as compared to predictions of the Highway Capacity Manual. The actuated controller produces significantly higher delay than its pre-timed counterpart, which agrees with our previous findings using micro-simulation. This research should contribute to the area of arterial traffic signal simulation and control as the proposed model is more computationally efficient than the more widely used microscopic simulation models.

Optimization Using Simulation of Traffic Light Signal Timings

Traffic congestion has become a great challenge and a large burden on both the governments and the citizens in vastly populated cities. The main problem, originally initiated by several factors, continues to threaten the stability of modern cities and the livelihood of its habitants. Hence, improving the control strategies that govern the traffic operations is a powerful solution that can solve the congestion problem. These improvements can be achieved by enhancing the traffic control performance through adjusting the traffic signal timings. This paper focuses on finding various solutions for the addressed problem through the optimization using simulation of traffic signal timings under oversaturated conditions. The system under study is an actual road network in Alexandria, Egypt; where, numerous data have been collected in different time intervals. A series of computer simulation models to represent the actual system as well as proposed solutions have been developed using the ExtendSim simulation environment. Furthermore, an evolutionary optimizer is utilized to attain a set of optimum/near-optimum signal timings to minimize the total time in system of the vehicles, resulting in an improved performance of the road network. Analysis of experimentation results shows that the adopted methodology optimizes the vehicular flow in a multiple-junction urban traffic network.

Intelligent traffic light control

2004

Abstract Vehicular travel is increasing throughout the world, particularly in large urban areas. Therefore the need arises for simulating and optimizing traffic control algorithms to better accommodate this increasing demand. In this paper we study the simulation and optimization of traffic light controllers in a city and present an adaptive optimization algorithm based on reinforcement learning.

Adaptive Traffic Light Control System

There are many problems of congestion due to traditional traffic light system and increasing traffic density in many cities. Because of the increasing traffic density flow in urban areas there is a need for efficient performance of traffic light control system. The primary intention of this paper is to describe an approach of reinforcement learning applied to the optimization of traffic light configurations, and introduce a new approach especially emphasis on ambulance. When there is emergency case at traffic light intersection such as ambulance, police vans, fire brigade adaptive signal system is designed for such situations. The possibilities of traffic jams caused by traffic light can reduce by this method which is represented by software simulation in VHDL using Xilinx software. The intention of this method is to switch from normal mode to emergency mode after triggering by the sensors. This system is especially designed for medical emergencies such as ambulance. Many times ambulance stuck in traffic jams due to conventional traffic light control system that results into number of deaths. The aim of this paper is to design adaptive traffic light control system that will avoid such situations. The system that provides the traffic control of four way or a junction of modern traffic light has been simulated. There are two modes of traffic light sequence in this system. One is the normal sequence and the other is the emergency sequence. Adaptive traffic light control system can be implemented using PIC microcontroller, LED drivers and Control switches on Radio Frequencies (RF)

Urban Traffic Optimization with Real Time Intelligence Intersection Traffic Light System

International Journal of Intelligent Systems and Applications in Engineering

Traffic system is a complex system where a lot of smart components which include signals, vehicles, sensor and pedestrian have communication skills with together on local level and act in a particular manner on high level. Insufficient traffic light control system on intersections brings about unnecessary delays and waste of time, extremely oil firing of engine which run idle mode on lights and increasing greenhouse gas emission. Various systems have been developed in order to overcome these traffic problems. These are the primary developed methods for the traffic optimization systems: fixed time period systems of lighting where time is predetermined , green wave lighting system and real time optimization system of traffic light. In this paper we suggested a real time intersection traffic optimization system. Real data has been gathered on Karabuk-Safranbolu route to test above systems for different data density. There are 7 lighted junctions on the route and there are traffic congestion in these junctions with the existing fixed time systems. The results of these tests on data show that real time traffic light optimization systems get better results than fixed time period and green wave lighting systems.

Optimization of traffic signals on urban arteries through a platoon-based simulation model

… and Computers in …, 2009

The paper describes an optimization procedure to synchronize traffic signals along an urban road artery. The solution procedure applies first a genetic algorithm and then a hill climbing algorithm for local adjustments. The fitness function is evaluated by means of a traffic model that simulates platoon progression along the links, their combination and possible queuing at nodes. The potential benefits of the synchronization procedure have been assessed by simulating a real urban artery through the micro-simulation model Transmodeler.

An Intelligent Traffic Light Controlling System

Citation/Export MLA Shubhada P. Mone, Sachin Wankhede, Rohini Kadam, Aditya Mahakulkar, Poonam Kauthale, “An Intelligent Traffic Light Controlling System”, March 15 Volume 3 Issue 3 , International Journal on Recent and Innovation Trends in Computing and Communication (IJRITCC), ISSN: 2321-8169, PP: 940 - 943, DOI: 10.17762/ijritcc2321-8169.150309 APA Shubhada P. Mone, Sachin Wankhede, Rohini Kadam, Aditya Mahakulkar, Poonam Kauthale, March 15 Volume 3 Issue 3, “An Intelligent Traffic Light Controlling System”, International Journal on Recent and Innovation Trends in Computing and Communication (IJRITCC), ISSN: 2321-8169, PP: 940 - 943, DOI: 10.17762/ijritcc2321-8169.150309

Smart Traffic: Intelligent Traffic Light Control

2019

The Study group participants for the Intelligent Traffic Light Control assignment were tasked with investigating the use of autonomous traffic light controls for a network of road intersections such as the road map of a city. Smart Traffic, the software used and designed by our client Sweco, is designed to control a single intersection. Our task involved optimising the traffic flow without the need for global (e.g. city wide) governance of all traffic lights. This would both fit with the existing approach in Smart Traffic, avoids bad experiences in the past, and mathematically avoids a huge explosion of the state space. Unfortunately, the Smart Traffic software was not available for use and study, and this somewhat limited the approaches we considered. Instead, the software was treated as a black-box, for which we only knew an idealised version of the cost function that the software tried to optimise. We therefore focused on finding a method to have multiple instances of this contro...