scholarly journals Traffic Control Prediction Design Based on Fuzzy Logic and Lyapunov Approaches to Improve the Performance of Road Intersection

Processes ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 2205
Author(s):  
Sadiqa Jafari ◽  
Zeinab Shahbazi ◽  
Yung-Cheol Byun
Keyword(s):  
Traffic Control ◽  
Fuzzy Controller ◽  
Fixed Time ◽  
Urban Traffic ◽  
Urban Transport ◽  
Traffic Light ◽  
Traffic System ◽  
Input Variables ◽  
Space Dynamics ◽  
Takagi Sugeno

Due to the increasing use of private cars for urbanization and urban transport, the travel time of urban transportation is increasing. People spend a lot of time in the streets, and the queue length of waiting increases accordingly; this has direct effects on fuel consumption too. Traffic flow forecasts and traffic light schedules were studied separately in the urban traffic system. This paper presents a new stable TS (Takagi–Sugeno) fuzzy controller for urban traffic. The state-space dynamics are utilized to formulate both the vehicle’s average waiting time at an isolated intersection and the length of queues. A fuzzy intelligent controller is designed for light control based upon the length of the queue, and eventually, the system’s stability is proved using the Lyapunov theorem. Moreover, the input variables are the length of queue and number of input or output vehicles from each lane. The simulation results describe the appearance of the proposed controller. An illustrative example is also given to show the proposed method’s effectiveness; the suggested method is more efficient than both the conventional fuzzy traffic controllers and the fixed time controller.

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.

Traffic Management Parameters from Single Inductive Loop Detectors

2000 ◽  
Vol 1719 (1) ◽  
pp. 112-120 ◽  
Author(s):  
Tom Cherrett ◽  
Hugh Bell ◽  
Mike McDonald
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Fixed Time ◽  
Urban Traffic ◽  
Flow Conditions ◽  
Inductive Loop ◽  
Loop Detectors ◽  
Time Period ◽  
S Period ◽  
Urban Traffic Control

Investigated are potential new uses for the digital output produced by single inductive loop detectors (2 m x 1.5 m and 2 m x 6.5 m) used in most European urban traffic control systems. Over a fixed time period, the average loop-occupancy time per vehicle (ALOTPV) for a detector being sampled every 250 ms is determined by taking the number of 250-ms occupancies and dividing by the number of vehicles. In a similar way, the average headway time between vehicles (AHTBV) is determined by taking the number of 250-ms vacancies and dividing by the number of vehicles. Over a 30-s period, the minimum and maximum values of ALOTPV and AHTBV ranged from 1 to 120 (an ALOTPV of 1 and an AHTBV of 120 representing free-flow conditions, an ALOTPV of 120 and an AHTBV of 1 representing a stationary queue). Identifying periods when a link was operating under capacity and at capacity and when it had become saturated could be more clearly identified by using plots of ALOTPV and AHTBV data over time compared to the more traditional percentage occupancy output. ALOTPV also was used to successfully identify long vehicles from cars down to speeds of 15 km/h.

scholarly journals Designing a Smart Traffic Light Algorithm (HMS) Based on Modified Round Robin Algorithm

2017 ◽  
Vol 2 (1) ◽  
pp. 27-30
Author(s):  
Hozan Khalid Hamarashid ◽  
Miran Hama Rahim Saeed ◽  
Soran Saeed
Keyword(s):  
Traffic Congestion ◽  
Fixed Time ◽  
Traffic Load ◽  
Traffic Light ◽  
Traffic Jam ◽  
Traffic Lights ◽  
Traffic System ◽  
Light System ◽  
Smart Traffic ◽  
Fixed System

Nowadays, traffic light system is very important to avoid car crashes and arrange traffic load. In the Sulaimani City / Iraq, there are many traffic problems such as traffic congestion or traffic jam and the amount of time provided manually to the traffic light system. This is the main difficulty that we try to solve. The traffic lights exist but still do not manage traffic congestion due to the fixed time provided for each lane regardless of their different load. Therefore, we are proposing to change the traditional traffic system to smart traffic system (adaptive system). This paper Focuses on the existing system (fixed system), then propose the adaptive one. The main crucial side effects of the existing system are:   Emergency cases: congested traffics might block the way of emergencies for instance ambulance, which transports people to the hospital Wasting time of people generally and specially Delays, which lead people to not to be punctual, this means people arrive late to the work  Wasting more fuels as staying more in the traffics, which affects the environment by increasing pollution.

scholarly journals Bi-Level Optimization Model for Urban Traffic Control

2021 ◽  
Vol 21 (3) ◽  
pp. 108-126
Author(s):  
Krasimira Stoilova ◽  
Todor Stoilov ◽  
Stanislav Dimitrov
Keyword(s):  
Traffic Control ◽  
Optimization Model ◽  
Dynamical Behavior ◽  
Control Variable ◽  
Green Light ◽  
Urban Traffic ◽  
Traffic Light ◽  
Urban Network ◽  
Traffic Lights ◽  
Urban Traffic Control

Abstract The urban traffic control optimization is a complex problem because of the interconnections among the junctions and the dynamical behavior of the traffic flows. Optimization with one control variable in the literature is presented. In this research optimization model consisting of two control variables is developed. Hierarchical bi-level methodology is proposed for realization of integrated optimal control. The urban traffic management is implemented by simultaneously control of traffic light cycles and green light durations of the traffic lights of urban network of crossroads.

Traffic Microsimulation for Flexible Utilization of Urban Roadways

2019 ◽  
Vol 2673 (10) ◽  
pp. 92-104 ◽  
Author(s):  
Aleksandar Stevanovic ◽  
Nikola Mitrovic
Keyword(s):  
Traffic Control ◽  
Simulation Models ◽  
Current Method ◽  
Fixed Time ◽  
Urban Traffic ◽  
Future Research ◽  
Major Barrier ◽  
Urban Networks ◽  
Traffic Efficiency ◽  
Traffic Systems

The current method of organizing traffic flows in urban networks uses directional right-of-way links to move traffic between urban intersections. Conflict resolution between vehicles is almost exclusively exercised at the intersections, which turns them into bottlenecks of our urban traffic systems. Even an attempt to model a different organization of traffic hits a major barrier, because the traditional simulation models do not offer enough flexibility to model bidirectional traffic on individual links in the network. This paper presents flexible arterial utilization simulation modeling (FAUSIM), a novel microsimulation platform designed to address this deficiency of traditional tools. The outputs from this tool are validated, successfully, in comparison with a commonly utilized Vissim model. The paper then illustrates the ability of FAUSIM to model conventional and unconventional traffic control scenarios. A combined alternate-direction lane assignment and reservation-based intersection control (CADLARIC) scenario is where directional driving paths are altered between neighboring lanes to align vehicles for decreased conflict for left and right turns at intersections where a reservation-based algorithm is utilized to process conflicts. This is compared with a conventional fixed-time (FT) control. The results of the experiments, executed on a small three-intersection corridor, show that CADLARIC significantly outperforms conventional driving with the FT control in relation to traffic efficiency (delays and stops). While the FT control generates fewer (potential) conflicting events, the CADLARIC confidently handles conflicting situations inside and outside the intersections. Future research should further validate the FAUSIM platform and investigate several other unconventional traffic scenarios with connected and automated vehicles.

Evaluation of SCATSIM–RTA Adaptive Traffic Network Simulation Model

1996 ◽  
Vol 1566 (1) ◽  
pp. 8-19 ◽  
Author(s):  
V. Ngoc Nguyen
Keyword(s):  
Simulation Model ◽  
Traffic Control ◽  
Network Simulation ◽  
Fixed Time ◽  
Traffic Network ◽  
Oxides Of Nitrogen ◽  
Traffic System ◽  
Traffic Conditions ◽  
South Wales ◽  
Network Simulation Model

The traffic network simulation model, SCATSIM, was developed by the Roads and Traffic Authority of New South Wales, Australia, as an aid to the development and improvement of the Sydney Coordinated Adaptive Traffic System (SCATS). It is capable of simulating traffic under different control techniques (such as fixed-time and SCATS adaptive control). Other traffic control systems, with known control algorithms, can also be simulated by SCATSIM. This paper is aimed at evaluating SCATSIM performance against a well-accepted analytical model, TRANSYT. Test runs demonstrate that SCATSIM is capable of simulating comprehensive traffic conditions derived from real world situations. It indicates that SCATSIM can simulate (a) traffic delay, vehicle stops, and fuel consumption within 11 percent of those predicted by TRANSYT; and (b) vehicle pollution emission (carbon monoxide, hydrocarbons, and oxides of nitrogen) within 5 percent of what is derived from TRANSYT results.

Multiagent Learning on Traffic Lights Control

2009 ◽  
pp. 307-321 ◽  
Author(s):  
Denise de Oliveira ◽  
Ana L.C. Bazzan
Keyword(s):  
Traffic Control ◽  
Multiagent System ◽  
Partial Information ◽  
Urban Traffic ◽  
Multiagent Learning ◽  
Traffic Lights ◽  
Traffic System ◽  
Exchange Of Information ◽  
Urban Traffic Control

In a complex multiagent system, agents may have different partial information about the system’s state and the information held by other agents in the system. In a distributed urban traffic control, where each junction has an independent controller, agents that learn can benefit from exchanging information, but this exchange of information may not always be useful. In this chapter the authors analyze how agents can benefit from sharing information in an urban traffic control scenario and the consequences of this cooperation in the performance of the traffic system.

scholarly journals Regulation Models of Crossroad Based on Wireless Sensor Networks and Notions of the Fluid Mechanics

2020 ◽  
Vol 9 (3) ◽  
pp. 2536-2541
Keyword(s):  
Traffic Control ◽  
Traffic Congestion ◽  
Information Technologies ◽  
Smart Cities ◽  
Urban Traffic ◽  
Wireless Sensor ◽  
Effective Control ◽  
Control Mechanisms ◽  
Traffic Light ◽  
Traffic Lights

The permanent growth of the population in smart cities has increased the number of vehicles. Consequently the problem of traffic congestion has become one of the main problems to be solved by today's traffic control systems, especially at traffic intersections. In fact, the traditional method which avoids the congestion in a crossroads is the classic command (Timing) by means of traffic lights. However, the traffic light management modes are sometimes based on classic models which make them unsuitable for the treatment of different experienced situations in traffic (either dense or fluid traffic). Fortunately, thanks to the significant progress made, especially the use of New Information Technologies and Communications for example Wireless Sensor Network, for the regulation of traffic, are solutions become central in the field of urban traffic management. They have made it possible to propose more effective control mechanisms to reduce the effects of traffic congestion. In this article, we will present the continuation of our work [1], the objective is to offer to the users of the road a crossing time as long as possible, while preventing the car cap to propagate over a distance that is set between two wireless sensors, to do this, we can act on the setting of the traffic light to regulate traffic in intersections.

scholarly journals Urban Traffic Signals Timing at Four-Phase Signalized Intersection Based on Optimized Two-Stage Fuzzy Control Scheme

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Taiping Jiang ◽  
Zili Wang ◽  
Fuyang Chen
Keyword(s):  
Fuzzy Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Differential Evolution Algorithm ◽  
Arrival Rate ◽  
Fixed Time ◽  
Urban Traffic ◽  
Two Stage ◽  
Phase Selection ◽  
Vehicle Delay

This paper proposes a signal timing scheme through a two-stage fuzzy logic controller. The controller first determines the signal phase and then adjusts the green time. At the first stage, the adaptive membership function of vehicle arrival rate is improved to adapt to the changing traffic flow. In addition to arrival rate and queue vehicles, a specific phase order rule is considered to avoid disordered phase selection in fuzzy control. At the second stage, the green time detection module decides whether to extend the current green time or switch phases every few seconds and the vehicle arrival rate is not required as the input to controller in real-time detection. Differential evolution algorithm with low space complexity and fast convergence is applied to optimize the fuzzy rules for avoiding artificial uncertainty. Simulation experiments are designed to compare traditional fuzzy controller, fixed-time controller, and fuzzy controller without flow prediction. Results show that the current proposed method in this paper can reduce vehicle delay significantly.

scholarly journals An Application-Driven Modular Traffic Light Control System Using Lean Supply Chain

2021 ◽  
Author(s):  
Sudha Rajesh ◽  
Sonia R ◽  
Amudhavalli P ◽  
Karthikeyan S ◽  
Beulah Jackson ◽  
...  
Keyword(s):  
Supply Chain ◽  
Control System ◽  
Traffic Control ◽  
Red Light ◽  
Green Light ◽  
Fixed Time ◽  
Traffic Light ◽  
Management Philosophy ◽  
Traffic Efficiency ◽  
Lean Supply Chain

Abstract Lean is an endless journey to develop and excel the business. Any company would like to build and deal with the whole world pace should adopt lean. Though, in the vast majority of the companies the management philosophy or mentality of people is not so great to adopt change. Lean typically deals with superior quality, lowest cost and quicker lead time. Lean Supply chain technology in the traffic control system has supplied intelligent green interval responses to control the incapability of standard fixed traffic controllers. The researchers have implemented the technology of lean supply chain to boost up the performance of traffic light and control the traffic jam. The limitations of traditional passing vehicles have been solved by the set of rules. The two set of guidance have been monitored the traffic light system by dynamic system; the vehicle, upstream and downstream lane follows red light and the number of vehicles have passed through a green light. These kinds of vehicles have dynamically controlled the timing of red and green. The dynamic traffic controller and a fixed time controller have shown the differences in performance through the Lean supply chain theory. The researchers have compared and stimulate the data of the performance of their algorithm with the undeveloped one. The results have shown that the algorithm has much better than undeveloped one, because it increases the traffic efficiency and decreases the waiting time by 45 minutes.

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