INTELLIGENT OPTIMAL CONTROL OF URBAN TRAFFIC LIGHTS BASED ON FUZZY CONTROL

2020 ◽  
Vol 79 (7) ◽  
pp. 613-621
Author(s):  
Y. H. Zhao ◽  
R. X. Li ◽  
J. Li
Keyword(s):  
Optimal Control ◽  
Fuzzy Control ◽  
Urban Traffic ◽  
Traffic Lights

Proposal of a Fuzzy Control System for the Management of Traffic lights

2013 ◽  
Vol 46 (7) ◽  
pp. 456-461
Author(s):  
C.A. Teixeira ◽  
E.R.L. Villarreal ◽  
M.E. Cintra ◽  
N.W.B. Lima
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Control System ◽  
Traffic Lights

scholarly journals Do Functionally Fit Elderly Community-Dwelling Subjects Have Enough Time to Safely Cross the Road?

1970 ◽  
Vol 25 (1) ◽  
pp. 55-62 ◽  
Author(s):  
Darija Rugelj ◽  
Marija Tomšič ◽  
France Sevšek
Keyword(s):  
Dual Task ◽  
Walking Speed ◽  
Community Dwelling ◽  
Urban Traffic ◽  
Gait Velocity ◽  
Dual Task Condition ◽  
Traffic Lights ◽  
The Road ◽  
Spatio Temporal ◽  
Task Conditions

Elderly people are the most vulnerable group in urban traffic and a large proportion of them are as pedestrians victims of traffic accidents. The majority of these happen while crossing the road. Crossing a busy road at an intersection with traffic lights or without them is a typical dual task condition requiring a motor task i.e. walking and a cognitive task such as monitoring traffic. The purpose of present study was to compare the walking speed and the related spatio-temporal gait variables of fallers and non-fallers in three walking conditions against the speeds required by regulations in Slovenia for safe street crossing. To assess the spatio-temporal characteristics of gait we used a 7m instrumented walkway.The general results showed that the spatio-temporal gait parameters did not differ between the two groups at the self-selected speed. But as soon as a constraint, such as fast walking speed, was imposed on the subjects the differences between the groups became evident. Fallers demonstrated a significantly slower mean gait velocity and shorter stride length while the cadence and the base of support did not differ between the two groups. In dual task conditions the difference between the two groups reached 25 percent. The fallers group gait velocity dropped to 0.99 m/s. The observed walking speed was slower than considered by the guidelines for the design of traffic light equipped road crossing.In conclusion, the results of walking speed under dual task conditions could be a useful parameter for planning of optimal pedestrian crossing in urban areas. These results will serve for the design of a population based study in Ljubljana.

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.

Hierarchical optimal control of oversaturated urban traffic networks

1981 ◽  
Vol 33 (4) ◽  
pp. 727-737 ◽  
Author(s):  
J. H. LIM ◽  
S. H. HWANG ◽  
I. H. SUH ◽  
Z. BIEN
Keyword(s):  
Optimal Control ◽  
Urban Traffic ◽  
Traffic Networks ◽  
Urban Traffic Networks

scholarly journals Multi-Agent System for Intelligent Urban Traffic Management Using Wireless Sensor Networks Data

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 208
Author(s):  
Maria Viorela Muntean
Keyword(s):  
Traffic Management ◽  
Nearest Neighbor ◽  
Smart Cities ◽  
City Council ◽  
Urban Traffic ◽  
Multi Agent System ◽  
K Nearest Neighbor ◽  
Agent System ◽  
Traffic Lights ◽  
Multi Agent

Intelligent traffic management is an important issue for smart cities. City councils try to implement the newest techniques and performant technologies in order to avoid traffic congestion, to optimize the use of traffic lights, to efficiently use car parking, etc. To find the best solution to this problem, Birmingham City Council decided to allow open-source predictive traffic forecasting by making the real-time datasets available. This paper proposes a multi-agent system (MAS) approach for intelligent urban traffic management in Birmingham using forecasting and classification techniques. The designed agents have the following tasks: forecast the occupancy rates for traffic flow, road junctions and car parking; classify the faults; control and monitor the entire process. The experimental results show that k-nearest neighbor forecasts with high accuracy rates for the traffic data and decision trees build the most accurate model for classifying the faults for their detection and repair in the shortest possible time. The whole learning process is coordinated by a monitoring agent in order to automate Birmingham city’s traffic management.

scholarly journals Traffic Optimization at Junctions to Improve Vehicular Flows

2011 ◽  
Vol 2011 ◽  
pp. 1-19 ◽  
Author(s):  
A. Cutolo ◽  
C. D'Apice ◽  
R. Manzo
Keyword(s):  
Kinetic Energy ◽  
Average Velocity ◽  
Fluid Dynamic ◽  
Urban Traffic ◽  
Traffic Lights ◽  
Right Of Way ◽  
Stop And Go ◽  
Global Performance ◽  
Traffic Optimization ◽  
Velocity Average

The aim of this work is to improve urban traffic viability through an appropriate choice of yielding and stop signs or red and green phases for traffic lights in junctions with two entering and one exiting roads (junctions of 2×1 type). We consider a macroscopic fluid-dynamic model able to capture the traffic evolution. We analyze different functionals measuring networks performance in terms of average velocity, average traveling time, total flux, density, stop and go waves, average traveling time, weighted with the number of cars moving on roads, and kinetic energy. Right of way parameters which optimize the latter two functionals are obtained. Simulations of simple junctions of 2×1type have been used to test the correctness of the analytical results. Then, global performance of optimization procedures has been investigated on Re di Roma Square, in Italy. In particular, we discuss cases in which the functionals are optimized locally at each junction for different values of right of way parameters. We show that for the chosen initial data the only algorithm for the maximization of velocity assures globally the best performance for the network, also in terms of average traveling times and kinetic energy.

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