scholarly journals A Fuzzy Logic Supported Multi-Agent System For Urban Traffic And Priority Link Control

2021 ◽  
Vol 27 (10) ◽  
pp. 1026-1045
Author(s):  
Abdelouafi Ikidid ◽  
Abdelaziz El Fazziki ◽  
Mohammed Sadgal
Keyword(s):  
Fuzzy Logic ◽  
Road Traffic ◽  
Smart Cities ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Regulation System ◽  
Traffic Light ◽  
The Road ◽  
Traffic Regulation ◽  
Communication And Coordination

Artificial technologies are rapidly becoming one of the most powerful and popular technologies for solving complicated problems involving distributed systems. Nevertheless, their potential for application to advanced artificial transportation systems has not been sufficiently explored. This paper presents a traffic optimization system based on agent technology and fuzzy logic that aims to manage road traffic, prioritize emergency vehicles, and promote collective modes of transport in smart cities. This approach aims to optimize traffic light control at a signalized intersection by acting on the length and order of traffic light phases in order to favor priority flows and fluidize traffic at an isolated intersection and for the whole multi-intersection network, through both inter- and intra-intersection collaboration and coordination. Regulation and prioritization decisions are made on real-time monitoring through cooperation, communication, and coordination between decentralized agents. The performance of the proposed system is investigated by implementing it in the AnyLogic simulator, using a section of the road network that contains priority links. The results indicate that our system can significantly increase the efficiency of the traffic regulation system.

scholarly journals Using Probe Vehicle Data for Automatic Extraction of Road Traffic Parameters

2016 ◽  
Vol 12 (4) ◽  
pp. 36-45
Author(s):  
Maria Alexandra Roman Popescu
Keyword(s):  
Waiting Time ◽  
Road Traffic ◽  
Smart Cities ◽  
Road Transportation ◽  
Traffic Light ◽  
Time Dynamic ◽  
Horizon 2020 ◽  
National Network ◽  
Traffic Lights ◽  
The Road

Abstract Through this paper the author aims to study and find solutions for automatic detection of traffic light position and for automatic calculation of the waiting time at traffic light. The first objective serves mainly the road transportation field, mainly because it removes the need for collaboration with local authorities to establish a national network of traffic lights. The second objective is important not only for companies which are providing navigation solutions, but especially for authorities, institutions, companies operating in road traffic management systems. Real-time dynamic determination of traffic queue length and of waiting time at traffic lights allow the creation of dynamic systems, intelligent and flexible, adapted to actual traffic conditions, and not to generic, theoretical models. Thus, cities can approach the Smart City concept by boosting, efficienting and greening the road transport, promoted in Europe through the Horizon 2020, Smart Cities, Urban Mobility initiative.

LIGHT REGULATION SYSTEMS IMPROVEMENT ANALYSIS TO FORECAST THE TRANSPORT FLOWS IN ALMATY

2021 ◽  
Vol 116 (1) ◽  
pp. 299-304
Author(s):  
Assel Aliyadynovna Sailau
Keyword(s):  
Environmental Pollution ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Light Regulation ◽  
Transport Network ◽  
Traffic Flows ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Road ◽  
Transport Telematics

The number of vehicles on the roads of Almaty, Kazakhstan is growing from year to year. This brings about an increasing intensity and density of traffic flows in the streets which leads to congestion, decreasing speed of the traffic flow, increasing environmental pollution caused by car emissions, and which can potentially lead to the road traffic accidents (RTA), including fatalities. While the number of injuries grows up mainly due to drivers’ non-compliance with the speed limit, the environmental pollution is caused by longer traffic jams. Therefore, to reduce the level of road traffic injuries and emissions into the environment it is necessary to ensure the uniform movement of traffic flows in cities. Currently, one of the effective ways to do it is the use of transport telematics systems, in particular, control systems for road signs, road boards and traffic lights. The paper presents an analysis of existing systems and methods of traffic light regulation. The  analyses of the systems and methods are based on the use of homogeneous data, that is the data on standard parameters of traffic flows. The need in collecting and analyzing additional semi-structured data on the factors that have a significant impact on the traffic flows parameters in cities is shown as well. The work is dedicated to solving the problem of analysis and forecast of traffic flows in the city of Almaty, Kazakhstan. GPS data on the location of individual vehicles is used as the initial data for solving this problem. By projecting the obtained information onto the graph of the city's transport network, as well as using additional filtering, it is possible to obtain an estimate of individual parameters of traffic flows. These parameters are used for short-term forecast of the changes in the city's transport network.

Make More Connections: Urban Traffic Flow Forecasting with Spatiotemporal Adaptive Gated Graph Convolution Network

2022 ◽  
Vol 13 (2) ◽  
pp. 1-25
Author(s):  
Bin Lu ◽  
Xiaoying Gan ◽  
Haiming Jin ◽  
Luoyi Fu ◽  
Xinbing Wang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Large Scale ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Propagation Mechanism ◽  
Urban Road ◽  
The Road ◽  
Traffic Flow Forecasting ◽  
Gating Mechanism

Urban traffic flow forecasting is a critical issue in intelligent transportation systems. Due to the complexity and uncertainty of urban road conditions, how to capture the dynamic spatiotemporal correlation and make accurate predictions is very challenging. In most of existing works, urban road network is often modeled as a fixed graph based on local proximity. However, such modeling is not sufficient to describe the dynamics of the road network and capture the global contextual information. In this paper, we consider constructing the road network as a dynamic weighted graph through attention mechanism. Furthermore, we propose to seek both spatial neighbors and semantic neighbors to make more connections between road nodes. We propose a novel Spatiotemporal Adaptive Gated Graph Convolution Network ( STAG-GCN ) to predict traffic conditions for several time steps ahead. STAG-GCN mainly consists of two major components: (1) multivariate self-attention Temporal Convolution Network ( TCN ) is utilized to capture local and long-range temporal dependencies across recent, daily-periodic and weekly-periodic observations; (2) mix-hop AG-GCN extracts selective spatial and semantic dependencies within multi-layer stacking through adaptive graph gating mechanism and mix-hop propagation mechanism. The output of different components are weighted fused to generate the final prediction results. Extensive experiments on two real-world large scale urban traffic dataset have verified the effectiveness, and the multi-step forecasting performance of our proposed models outperforms the state-of-the-art baselines.

An Advanced Fuzzy Logic Based Traffic Controller

2014 ◽  
Vol 5 (1) ◽  
pp. 31-40
Author(s):  
Bilal Ahmed Khan ◽  
Nai Shyan Lai
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Traffic Management ◽  
Fuzzy Logic Controller ◽  
Current Model ◽  
Traffic Signals ◽  
Processing Technique ◽  
Urban Traffic ◽  
Image Processing Technique ◽  
Traffic Light

Traffic light plays an important role in the urban traffic management. Therefore, it is necessary to improve the traffic controller for effective traffic management and better traffic flow leading to greener environment. In this paper, an advanced and intelligent traffic light controller is proposed, utilising the fuzzy logic technology and image processing technique. A fuzzy logic control has been implemented to provide the attribute of intelligence to the system. For real-time image acquisition, the process is further linked to the fuzzy logic controller which generates a unique output for each input pattern. Here image processing and fuzzy logic tool boxes of MATLAB are used where the final output is sent to Peripheral Interface Controller (PIC) microcontroller to drive the traffic signals in the desired manner. The results obtained show an improvement of 44% in the overall outcome of traffic management as compared to the conventional traffic controller, marking great feasibility and practicality of the current model.

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 Data Dissemination Based on Fuzzy Logic and Network Coding in Vehicular Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Xiaolan Tang ◽  
Zhi Geng ◽  
Wenlong Chen ◽  
Mojtaba Moharrer
Keyword(s):  
Fuzzy Logic ◽  
Network Coding ◽  
Vehicular Networks ◽  
Data Dissemination ◽  
Smart Cities ◽  
High Reliability ◽  
Transportation Systems ◽  
Delivery Ratio ◽  
Velocity Change ◽  
Backbone Network

Vehicular networks, as a significant technology in intelligent transportation systems, improve the convenience, efficiency, and safety of driving in smart cities. However, because of the high velocity, the frequent topology change, and the limited bandwidth, it is difficult to efficiently propagate data in vehicular networks. This paper proposes a data dissemination scheme based on fuzzy logic and network coding for vehicular networks, named SFN. It uses fuzzy logic to compute a transmission ability for each vehicle by comprehensively considering the effects of three factors: the velocity change rate, the velocity optimization degree, and the channel quality. Then, two nodes with high abilities are selected as primary backbone and slave backbone in every road segment, which propagate data to other vehicles in this segment and forward them to the backbones in the next segment. The backbone network helps to increase the delivery ratio and avoid invalid transmissions. Additionally, network coding is utilized to reduce transmission overhead and accelerate data retransmission in interbackbone forwarding and intrasegment broadcasting. Experiments show that, compared with existing schemes, SFN has a high delivery ratio and a short dissemination delay, while the backbone network keeps high reliability.

scholarly journals Opportunities to improve road traffic on short-length road connections by correlating intersection traffic lights

2022 ◽  
Vol 960 (1) ◽  
pp. 012020
Author(s):  
A Boroiu ◽  
E Neagu ◽  
A A Boroiu
Keyword(s):  
Road Traffic ◽  
Central Area ◽  
Green Light ◽  
Traffic Light ◽  
City Center ◽  
Traffic Lights ◽  
The Road ◽  
Micro Simulation ◽  
Road Intersections ◽  
The City

Abstract The paper aims to explore the possibilities of improving road traffic in the central area of cities characterized by a longitudinal arrangement of the street network, with application for the case of Pitesti, where the road network in the central area consists of two main roads arranged longitudinally, having one-way regulated traffic, interconnected by several streets. A special traffic problem is reported in the city center: on the main road connecting the two boulevards, the vehicle storage space is insufficient - because the distance between the two road intersections is too small and there is no correlation between the Green phases of traffic lights in the two intersections. The research, based on traffic measurements performed with DataFromSky software and micro-simulation traffic analyses performed with Vissim PTV software, indicated that the best solution is the partial or total correlation of the green time from the traffic light intersections that delimit the connecting road artery. As, almost exclusively, the works dedicated to the correlation of green light of traffic lights treat the problem only along the road arteries, this paper raises a special issue and reveals the possibility of simple solutions, by correlating the traffic lights at the intersections connecting the main arteries.

scholarly journals New Transportation Systems for Smart Cities

2016 ◽  
pp. 1569-1593
Author(s):  
Christos G. Cassandras
Keyword(s):  
Traffic Management ◽  
Smart Cities ◽  
Transportation Systems ◽  
Urban Environments ◽  
Gradient Estimates ◽  
Light Cycle ◽  
Traffic Light ◽  
Cycle Lengths ◽  
Smart Parking ◽  
Charging Stations

Poor traffic management in urban environments is responsible for congestion, unnecessary fuel consumption and pollution. Based on new wireless sensor networks and the advent of battery-powered vehicles, this chapter describes three new systems that affect transportation in Smart Cities. First, a Smart Parking system which assigns and reserves an optimal parking space based on the driver's cost function, combining proximity to destination and parking cost. Second, a system to optimally allocate electric vehicles to charging stations and reserve spaces for them. Finally, we address the traffic light control problem by viewing the operation of an intersection as a stochastic hybrid system. Using Infinitesimal Perturbation Analysis (IPA), we derive on-line gradient estimates of a cost metric with respect to the controllable green and red cycle lengths and iteratively adjust light cycle lengths to improve (and possibly optimize) performance, as well as adapt to changing traffic conditions.

Smart Cities: Study and Comparison of Traffic Light Optimization in Modern Urban Areas Using Artificial Intelligence

2018 ◽  
Vol 8 (2) ◽  
pp. 10
Author(s):  
Mustapha Kabrane ◽  
Salah-ddine Krit ◽  
Lahoucine El Maimouni
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Road Network ◽  
Smart Cities ◽  
Optimization Techniques ◽  
Traffic Light ◽  
Large Cities ◽  
Traffic Lights ◽  
The Road ◽  
Road Signs

In large cities, the increasing number of vehicles private, society, merchandise, and public transport, has led to traffic congestion. Users spend much of their time in endless traffic congestion. To solve this problem, several solutions can be envisaged. The interest is focused on the  system of road signs: The use of a road infrastructure is controlled by a traffic light controller, so it is a matter of knowing how to make the best use of the controls of this system (traffic lights) so as to make traffic more fluid. The values of the commands computed by the controller are determined by an algorithm which is ultimately, only solves a mathematical model representing the problem to be solved. The objective is to make a study and then the comparison on the optimization techniques based on artificial intelligence1 to intelligently route vehicle traffic. These techniques make it possible to minimize a certain function expressing the congestion of the road network. It can be a function, the length of the queue at intersections, the average waiting time, also the total number of vehicles waiting at the intersection

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