scholarly journals Choice of the rational regimes of traffic light control for traffic and pedestrian flows

2021 ◽  
Vol 30 (1) ◽  
pp. 38-50
Author(s):  
Yevhen Fornalchyk ◽  
Oleh Hrytsun ◽  
Ivan Kernytskyy ◽  
Yuriy Royko
Keyword(s):  
Queue Length ◽  
Road Network ◽  
Light Control ◽  
Traffic Light ◽  
The Road ◽  
Capacity Ratio ◽  
Simultaneous Impact ◽  
Traffic Light Control ◽  
Light Signals ◽  
And Control

The method for the choice of rational regimes of traffic light control is developed based on the minimization of the number of violations the requirements of traffic light signals by pedestrians depending on the volume-capacity ratio of traffic lanes and control of vehicular queue on the approach to the stop-line. Assessment of rationality is carried out considering the simultaneous impact of such factors as roadway volume-capacity ratio, traffic light restrictive signal duration, the number of violations of the traffic rules by pedestrians, and maximal queue length of vehicles. The model of the change of the number of violations of the rules of crossing the roadway by pedestrians depending on the volume-capacity ratio of different intersection types is developed in this paper. The model of determining the maximal vehicular queue length before intersections depending on the volume-capacity ratio and the share of the restrictive signal on the lane in the control cycle is developed. Recommendations about the choice of rational regimes of traffic light control depending on traffic delay, planning parameters of the road network, and pedestrian behavior are proposed.

Driver's Reaction Time in Evaluation of the Road Capacity

2015 ◽  
Vol 725-726 ◽  
pp. 1212-1217 ◽  
Author(s):  
Anastasiya Shevtsova ◽  
Ivan Novikov ◽  
Alexey Borovskoy
Keyword(s):  
Reaction Time ◽  
Road Network ◽  
Light Regulation ◽  
Light Control ◽  
Traffic Light ◽  
The Road ◽  
Road Section ◽  
Road Capacity ◽  
Traffic Light Control ◽  
On The Road

The paper gives an overview of researches of foreign scientists to change the driver's reaction time, depending on various road conditions, namely regarding the change of studied magnitude when using traffic-light signalization. Previously, the authors have carried out researches of capacity of road section with traffic light regulation, which allowed to establish the dependence of this parameter from the driver's reaction time. This paper proposes calculation of the road capacity using a variety values of the driver's reaction time derived from the analysis. The values obtained allow us to conclude that the inclusion of psychophysiological characteristics of drivers (such as reaction time) will affect both on road capacity and on the different methods of organization/reorganization of road networks sectors, which use the value of road capacity in their implementation.This article analyzes foreign researches devoted to changing the reaction time of drivers on the road conditions. Besides, the effect of changing the driver's reaction time on capacity of the road network sector with traffic-light control was considered.

Optimalisasi Lampu Lalu Lintas dengan Fuzzy Logic

2013 ◽  
Vol 5 (2) ◽  
pp. 58-62 ◽  
Author(s):  
Adhitya Yoga Yudanto ◽  
Marvin Apriyadi ◽  
Kevin Sanjaya
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Inference ◽  
System Control ◽  
Light Control ◽  
Traffic Light ◽  
Inference System ◽  
Traffic Lights ◽  
The Road ◽  
Traffic Light Control

The traffic lights problem is already commonly found in large cities. The traffic lights are supposed to control the flow of the road, but sometimes causes a congestion. This happens because the distribution of the time are all the same for all lines, without seeing the condition of the density of each lane. There’s one effort that can be done to overcome this problem, is to create a traffic light control system. With this system, the congestion that occurs around the traffic lights can be reduced. This system is using fuzzy logic. Fuzzy logic is one of computer science that studies about the value of truth that worth a lot. For example, a air conditioning system control subway Sendai in Japan. As for making a traffic light control system, the author using Fuzzy Inference System (FIS) that already exist in the application of MATLAB R2013a with Mamdani method. Index Terms —fuzzy logic, traffic lights, MATLAB.

scholarly journals Reinforcement Learning Agent under Partial Observability for Traffic Light Control in Presence of Gridlocks

10.29007/bdgn ◽  
2019 ◽  
Author(s):  
Thanapapas Horsuwan ◽  
Chaodit Aswakul
Keyword(s):  
Reinforcement Learning ◽  
Road Network ◽  
Road Traffic ◽  
Learning Approaches ◽  
Light Control ◽  
Traffic Light ◽  
Rapid Urbanization ◽  
Partial Observability ◽  
Traffic Light Control ◽  
Network Area

Bangkok is notorious for its chronic traffic congestion due to the rapid urbanization and the haphazard city plan. The Sathorn Road network area stands to be one of the most critical areas where gridlocks are a normal occurrence during rush hours. This stems from the high volume of demand imposed by the dense geographical placement of 3 big educational institutions and the insufficient link capacity with strict routes. Current solutions place heavy reliance on human traffic control expertises to prevent and disentangle gridlocks by consecutively releasing each queue length spillback through inter-junction coordination. A calibrated dataset of the Sathorn Road network area in a microscopic road traffic simulation package SUMO (Simulation of Urban MObility) is provided in the work of Chula-Sathorn SUMO Simulator (Chula-SSS). In this paper, we aim to utilize the Chula-SSS dataset with extended vehicle flows and gridlocks in order to further optimize the present traffic signal control policies with reinforcement learning approaches by an artificial agent. Reinforcement learning has been successful in a variety of domains over the past few years. While a number of researches exist on using reinforcement learning with adaptive traffic light control, existing studies often lack pragmatic considerations concerning application to the physical world especially for the traffic system infrastructure in developing countries, which suffer from constraints imposed from economic factors. The resultant limitation of the agent’s partial observability of the whole network state at any specific time is imperative and cannot be overlooked. With such partial observability constraints, this paper has reported an investigation on applying the Ape-X Deep Q-Network agent at the critical junction in the morning rush hours from 6 AM to 9 AM with practically occasional presence of gridlocks. The obtainable results have shown a potential value of the agent’s ability to learn despite physical limitations in the traffic light control at the considered intersection within the Sathorn gridlock area. This suggests a possibility of further investigations on agent applicability in trying to mitigate complex interconnected gridlocks in the future.

Traffic Light Control Based on the Road Image Analysis

2015 ◽  
pp. 669-685
Author(s):  
Obada M. A. Bani Issa ◽  
Venus W. Samawi ◽  
Jehad Q. Alnihoud
Keyword(s):  
Image Analysis ◽  
Light Control ◽  
Traffic Light ◽  
The Road ◽  
Traffic Light Control ◽  
On The Road

scholarly journals ANALYSIS OF THE PROCESS OF ENTERING A SPECIALIZED LEFT-STEERING PHASE REGULATION

2021 ◽  
Vol 4 (4) ◽  
pp. 51-63
Author(s):  
Sergei Dorohin ◽  
Dmitrii Lihachev ◽  
Sergei Bogdanov ◽  
Aleksei Sorokin
Keyword(s):  
Queue Length ◽  
Design Parameters ◽  
Light Control ◽  
Traffic Light ◽  
Basic Principles ◽  
Left Turn ◽  
Traffic Delays ◽  
Traffic Light Control ◽  
Phase Regulation

The paper analyzes the foreign and Russian approach to the calculation of a controlled intersection, defines the basic principles and approaches used in the construction of phase-by-phase crossing schemes. The classification of the ap-proaches used is carried out taking into account foreign and domestic experience. In the course of the analysis of regulatory sources, it was found that there are many approaches to the choice of the organization of the traffic scheme in regulated areas. Particular attention in this matter is paid to the introduction of a specialized phase for performing a left turn, basically this choice is made by a design engineer, based mainly on the demand for performing a left turn, without analyzing the main characteristics of the traffic flow, namely the queue length, speed and traffic delays. funds. The main design parameters used to determine the need to enter a specialized left-turn phase when using traffic light control have been determined.

scholarly journals Distributed Cooperative Backpressure-Based Traffic Light Control Method

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Shenxue Hao ◽  
Licai Yang ◽  
Li Ding ◽  
Yajuan Guo
Keyword(s):  
Queue Length ◽  
Control Method ◽  
Urban Traffic ◽  
Traffic Information ◽  
Computation Method ◽  
Light Control ◽  
Traffic Light ◽  
Light Phase ◽  
Phase Switching ◽  
Traffic Light Control

On the foundation of the original backpressure-based traffic light control algorithm, a distributed cooperative backpressure-based traffic light control method is proposed in this paper. The urban traffic network is modeled as a smart agent-controlled queuing network, in which the intersection agents exchange the queue length information and the selected activating light phase information of neighboring intersections through communications and determine the activating light phase at each time slot according to local traffic information. The improved phase pressure computation method considers the phase state of downstream intersections instead of only the queue length of the local intersections. Light phase switching coordination among adjacent intersections is achieved using the consensus-based bundle algorithm, in which the cooperative light phase switching problem is viewed as a task assignment issue among adjacent intersections. Simulation results illustrated that the proposed cooperative backpressure-based traffic light control method obtained better performance than the original backpressure-based and fixed-time traffic control methods.

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