Study of Traffic Flow Controlled with Independent Agent-Based Traffic Signals

Author(s):  
Enrique Onieva ◽  
Vicente Milanés ◽  
Joshué Pérez ◽  
Javier Alonso ◽  
Teresa de Pedro ◽  
...  
2021 ◽  
Vol 11 (5) ◽  
pp. 2057
Author(s):  
Abdallah Namoun ◽  
Ali Tufail ◽  
Nikolay Mehandjiev ◽  
Ahmed Alrehaili ◽  
Javad Akhlaghinia ◽  
...  

The use and coordination of multiple modes of travel efficiently, although beneficial, remains an overarching challenge for urban cities. This paper implements a distributed architecture of an eco-friendly transport guidance system by employing the agent-based paradigm. The paradigm uses software agents to model and represent the complex transport infrastructure of urban environments, including roads, buses, trolleybuses, metros, trams, bicycles, and walking. The system exploits live traffic data (e.g., traffic flow, density, and CO2 emissions) collected from multiple data sources (e.g., road sensors and SCOOT) to provide multimodal route recommendations for travelers through a dedicated application. Moreover, the proposed system empowers the transport management authorities to monitor the traffic flow and conditions of a city in real-time through a dedicated web visualization. We exhibit the advantages of using different types of agents to represent the versatile nature of transport networks and realize the concept of smart transportation. Commuters are supplied with multimodal routes that endeavor to reduce travel times and transport carbon footprint. A technical simulation was executed using various parameters to demonstrate the scalability of our multimodal traffic management architecture. Subsequently, two real user trials were carried out in Nottingham (United Kingdom) and Sofia (Bulgaria) to show the practicality and ease of use of our multimodal travel information system in providing eco-friendly route guidance. Our validation results demonstrate the effectiveness of personalized multimodal route guidance in inducing a positive travel behavior change and the ability of the agent-based route planning system to scale to satisfy the requirements of traffic infrastructure in diverse urban environments.


Author(s):  
Naheem Olakunle Adesina ◽  
◽  
Abiodun Alani Ogunseye ◽  
Akindele Opeyemi Areegbe ◽  
Thomas Kokumo Yesufu

2019 ◽  
Vol 151 ◽  
pp. 858-863 ◽  
Author(s):  
Felipe de Souza ◽  
Omer Verbas ◽  
Joshua Auld

2019 ◽  
Vol 136 ◽  
pp. 01008
Author(s):  
Zhao Wang ◽  
Mengjie Wang ◽  
Wenqiang Bao

As the number of car ownership increases, road traffic flow continues to increase. At the same time, traffic pressure at intersections is increasing as well. At present, most of the traffic lights in China are fixed cycle control. This timing control algorithm obviously cannot make timely adjustments according to changes in traffic flow. In this case, a large number of transportation resources would be wasted. It is very necessary to establish a dynamic timing system for Big data intelligent traffic signals. In this research, the video recognition method was used to acquire the number of vehicles at the intersection in real time, and the obtained data was processed by the optimization algorithm to make a reasonable dynamic timing of the traffic signals. The test results show that after using the big data intelligent traffic signal dynamic timing optimization control platform, in the experimental area, the overall total delay time was reduced by 23%, and the travel time was reduced by 15%. During the off-peak period, the overall total delay time in the experimental region was reduced by 17% and travel time was reduced by 10%. The big data intelligent traffic signal dynamic timing optimization platform would improve the operational efficiency and traffic supply capacity of the existing transportation infrastructure, and could provide real convenience for citizens.


Author(s):  
Satoshi Kurihara ◽  
◽  
Ryo Ogawa ◽  
Kosuke Shinoda ◽  
Hirohiko Suwa ◽  
...  

Traffic congestion is a serious problem for people living in urban areas, causing social problems such as time loss, economical loss, and environmental pollution. Therefore, we propose a multi-agent-based traffic light control framework for intelligent transport systems. Achieving consistent traffic flow necessitates the real-time adaptive coordination of traffic lights; however, many conventional approaches are of the centralized control type and do not have this feature. Our multi-agent-based control framework combines both indirect and direct coordination. Reaction to dynamic traffic flow is attained by indirect coordination, whereas green-wave formation, which is a systematic traffic flow control strategy involving several traffic lights, is attained by direct coordination. We present the detailed mechanism of our framework and verify its effectiveness using simulation to carry out a comparative evaluation.


2009 ◽  
Vol 3 (1) ◽  
pp. 39-45
Author(s):  
Peter A. Jarvis ◽  
Shawn R. Wolfe ◽  
Maarten Sierhuis ◽  
Robert A. Nado ◽  
Francis Y. Enomoto

2003 ◽  
Vol 1852 (1) ◽  
pp. 175-182 ◽  
Author(s):  
V. Thamizh Arasan ◽  
Shiraj Hussain Kashani

The quality of progression of a road traffic stream is one of the critical characteristics that must be quantified for operational analysis of traffic signals, particularly on urban roads. The parameter that has been found to best describe this characteristic of traffic streams is the arrival type. Though precise quantification of arrival type has been found to be difficult, the platoon ratio is a useful measure for this purpose. Thus, the quality of arrival of a traffic stream can be assessed by knowing the corresponding value of the platoon ratio. Study of arrival type over a wide range of traffic characteristics warrants theoretical modeling of traffic flow. In the study reported, an attempt was made to model heterogeneous traffic flow using an innovative technique. The developed model was used to study the arrival type of traffic streams, queue accumulation, and queue dissipation on approaches to traffic signals. The dispersal pattern of traffic platoons after vehicles pass a traffic signal was studied in detail. The effect of variation in traffic composition on traffic platoons was also analyzed.


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