A multi-agent based cellular automata model for intersection traffic control simulation

2021 ◽  
pp. 126356
Author(s):  
Jinghui Wang ◽  
Wei Lv ◽  
Yajuan Jiang ◽  
Shuangshuang Qin ◽  
Jiawei Li
Keyword(s):  
Cellular Automata ◽  
Traffic Control ◽  
Cellular Automata Model ◽  
Agent Based ◽  
Control Simulation ◽  
Multi Agent

Biocomplexity of deforestation in the Caparo tropical forest reserve in Venezuela: An integrated multi-agent and cellular automata model

2007 ◽  
Vol 22 (5) ◽  
pp. 664-673 ◽  
Author(s):  
Niandry Moreno ◽  
Raquel Quintero ◽  
Magdiel Ablan ◽  
Rodrigo Barros ◽  
Jacinto Dávila ◽  
...  
Keyword(s):  
Cellular Automata ◽  
Tropical Forest ◽  
Forest Reserve ◽  
Cellular Automata Model ◽  
Multi Agent

scholarly journals Multi-Agent Based Traffic Signal Optimization under Fully Actuated Control

2019 ◽  
Vol 8 (11) ◽  
pp. 2255-2262
Keyword(s):  
Traffic Control ◽  
Control Method ◽  
Control Model ◽  
Traffic Signal ◽  
Signal Control ◽  
Light Phase ◽  
Agent Based ◽  
Effective Manner ◽  
Multi Agent ◽  
On The Road

This paper presents a multi-agent based distributed traffic control model to optimize the traffic signal for multiple intersections. Previous works in the area of traffic signal control suffer from a number of inadequacies, including the use of fixed cycle length, centralized mode of operations and dependency on historical data. Considering these, the aim of this work is to control the traffic signal timings by adjusting the phase sequence in order to minimize the delay in traffic at the intersections. To model the traffic network, a three-tier multi-agent system has been adopted in distributed mode. In addition, a fully actuated signal control algorithm is designed and it utilizes state-space equations to formulate the queue length at the green light phase and red light phase. The proposed model is simulated with SUMO simulator and a comparative analysis has been made between adaptive control method, multi-agent method based on collective learning and multi-agent based fully actuated control method on a similar platform. The results spectacle the proposed traffic control model outperforms that of other existing control methods in all condition; hence it can be deployed to control the tremendous traffic on the road network and to optimize the traffic signal in more effective manner.

scholarly journals Generating urban structures: A method for urban planning supported by multi-agent systems and cellular automata

2018 ◽  
Author(s):  
Reinhard Koenig
Keyword(s):  
Urban Planning ◽  
Cellular Automata ◽  
Three Dimensional ◽  
Simulation Method ◽  
Multi Agent Systems ◽  
Agent Based ◽  
Generative Process ◽  
Urban Structures ◽  
Urban Patterns ◽  
Multi Agent

This work is based on the concept that the structure of a city can be defined by six basic urban patterns. To enable more complex urban planning as a long-term objective I have developed a simulation method for generating these basic patterns and for combining them to form various structures. The generative process starts with the two-dimensional organisation of streets followed by the parceling of the remaining areas. An agent-based diffusion-contact model is the basis of these first two steps. Then, with the help of cellular automata, the sites for building on are defined and a three-dimensional building structure is derived. I illustrate the proposed method by showing how it can be applied to generate possible structures for an urban area in the city of Munich.

scholarly journals Real-Time Traffic Controlling System Using Multi-Agent Technology

2021 ◽  
Vol 54 (4) ◽  
pp. 633-640
Author(s):  
Randi Thakshila Wakkumbura ◽  
Budditha Hettige ◽  
Ananda Edirisuriya
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Traffic Management ◽  
Dynamic Environment ◽  
Agent Technology ◽  
Transport Sector ◽  
Agent Based ◽  
Real Time Traffic ◽  
Controlling System ◽  
Multi Agent

With the development, almost all the sectors, countries tend to grow adapting to latest technologies. The transport sector also has a huge impact on this development sphere. When it comes to traffic, it is a huge problem in the world. In Sri Lanka traffic is a problem that exists for a long period. Annually there is a loss of Rs. 400 billion due to traffic congestions. Over the past years various solutions have been proposed using different methods for traffic control. These solutions are based on different trending technologies such as machine learning, image processing, fuzzy logic and the Internet of Things. However, those systems are not able to handle traffic congestions problems in complex environments. Therefore, a real-time traffic controlling system with the ability to handle traffic congestions in dynamic environment is highly valued. This study aims to design and build a real-time traffic management system using Multi Agent technology. Simulations for both existing system and Agent-Based system are implemented using NetLogo simulation tool and compared for various traffic situations. According to the results obtained from the two simulations, Agent-Based systems provide more accuracy and efficiency than the existing fixed scheduling systems.

Cellular automata model of self-organizing traffic control in urban networks

2010 ◽  
Vol 58 (3) ◽  
pp. 435-441
Author(s):  
J. Szklarski
Keyword(s):  
Cellular Automata ◽  
Traffic Control ◽  
Green Light ◽  
Optimal Solution ◽  
Optimal Strategies ◽  
Optimal Switching ◽  
Cellular Automata Model ◽  
Urban Networks ◽  
Ca Model ◽  
Self Organizing

Cellular automata model of self-organizing traffic control in urban networksA model of city traffic based on Nagel-Schreckenberg cellular automaton (CA) model is presented. Traffic control is realized at intersections with two conflicting streams each (at any time at most one stream can have "green light" assigned to it). For simple and regular lattice-like networks which are considered, it is easy to find optimal switching periods giving maximum possible flow rates. These optimal strategies are compared with a self-controlling approach proposed by [1], which has not been implemented in a CA model until now. Previous work proved that generally this method gives superior results when compared to classical methods. In this paper we show that for deterministic scenario such control leads to self-organization, and that the solution always quickly converges to the optimal solution which is known in this case. Moreover, we consider also non-deterministic case, in the sense that possibility of turning with given probability is allowed. It is shown that the self-controlling strategy always gives better results than any solution based on fixed cycles with green waves.

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