scholarly journals Multiagent Model of Rail-Road Intersection with Connected Vehicles

2021 ◽  
Vol 2 (1) ◽  
pp. 17-24
Author(s):  
Aleš Janota ◽  
Vojtech Šimák ◽  
Jozef Hrbček
Keyword(s):  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Collective Intelligence ◽  
Communication Technologies ◽  
Complex Problem ◽  
Transportation Systems ◽  
Comprehensive Overview ◽  
Vehicle Communication ◽  
Is Implementation ◽  
Cooperating Agents

The multiagent approach to modelling, traditionally dedicated for distributed systems, can be applied on any platform where there are more processes or control threads. The world of surface transport is a typical example of such a situation where high numbers of dynamic entities (agents) interacting with each other represent a complex problem to solve, analyse and visualise. The main focus of this paper is on functional description of the traffic control problem at the rail-road intersection. Unlike conventional approaches, this model assumes usage of modern (infrastructure-to-vehicle, vehicle-to-vehicle) communication technologies  as an essential base of cooperative intelligent transportation systems. The authors use the development toolkit NetLogo, explaining step-by-step the key programming details, to get a comprehensive overview of the operation of the entire system through simple definitions of a number of simple cooperating agents. The introduced model is implementation free and shows newly offered functionalities on the principal level, while a minimum theory of collective intelligence hidden in the background is needed.

Reinforcement learning: Introduction to theory and potential for transport applications

2003 ◽  
Vol 30 (6) ◽  
pp. 981-991 ◽  
Author(s):  
Baher Abdulhai ◽  
Lina Kattan
Keyword(s):  
Reinforcement Learning ◽  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Traffic Engineering ◽  
Transportation Systems ◽  
Transport Systems ◽  
Transportation Engineering ◽  
Research Subjects ◽  
Comprehensive Overview ◽  
Learning Machine

The aim of this paper is to develop insight into the potential of reinforcement learning (RL) agents and distributed reinforcement learning agents in the domain of transportation and traffic engineering and specifically in Intelligent Transport Systems (ITS). This paper provides a crystallized, comprehensive overview of the concept of RL and presents related successful applications in the field of traffic control and transportation engineering. It is divided into two parts: the first part provides a thorough overview of RL and its related methods and the second part reviews most recent applications of RL algorithms to the field of transportation engineering. Finally, it identifies many open research subjects in transportation in which the use of RL seems to be promising.Key words: reinforcement learning, machine learning, traffic control, artificial intelligence, intelligent transportation systems.

Potential Using Vehicle to Vehicle Communication Based on Wireless Fidelity (Wi-Fi) for Supporting Intelligent Transportation Systems (ITS)

2021 ◽  
pp. 61-76
Author(s):  
إسراء عصام بن موسى ◽  
عبدالسلام صالح الراشدي
Keyword(s):  
Intelligent Transportation Systems ◽  
Ad Hoc ◽  
Real Life ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
The Road ◽  
Vehicle Communication ◽  
Vehicle To Vehicle ◽  
Vehicle To Vehicle Communication ◽  
Wireless Fidelity

Vehicular Ad-hoc Network (VANET) becomes one of the most popular modern technologies these days, due to its contribution to the development and modernization of Intelligent Transportation Systems (ITS). The primary goal of these networks is to provide safety and comfort for drivers and passengers in roads. There are many types of VANET that are used in ITS, in this paper, we particularly focus on the Vehicle to Vehicle communication (V2V), which each vehicle can exchange information to inform drivers of other vehicles about the current state of the road flow, in the event of any emergency to avoid accidents, and reduce congestion on roads. We proposed V2V using Wi-Fi (wireless fidelity); the reason of its unique characteristics that distinguish it from other types. There are many difficulties and the challenges in implementing most types of V2V, and the reason is due to the lack of devices and equipment needed for real implementation. To prove the possibility of applying this type in real life, we made a prototype contains a modified toy car, a 12-volt power supply, sensors, visual, audible alarm, a visual “LED” devices, and finally a 12-volt DC relay unit. As a conclusion, the proposed implementation in spite of minimal requirements and use simple equipment, we have achieved the most important main objectives of the paper: preventing vehicles from collision, early warning, and avoiding congestion on the roads.

scholarly journals A Bidirectional Searching Strategy to Improve Data Quality Based on K-Nearest Neighbor Approach

Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 815 ◽  
Author(s):  
Minghui Ma ◽  
Shidong Liang ◽  
Yifei Qin
Keyword(s):  
Data Quality ◽  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Nearest Neighbor ◽  
Transportation Systems ◽  
Traffic Data ◽  
K Nearest Neighbor ◽  
Time Dimension ◽  
Nearest Neighbor Searching ◽  
Searching Strategy

Traffic data are the basis of traffic control, planning, management, and other implementations. Incomplete traffic data that are not conducive to all aspects of transport research and related activities can have adverse effects such as traffic status identification error and poor control performance. For intelligent transportation systems, the data recovery strategy has become increasingly important since the application of the traffic system relies on the traffic data quality. In this study, a bidirectional k-nearest neighbor searching strategy was constructed for effectively detecting and recovering abnormal data considering the symmetric time network and the correlation of the traffic data in time dimension. Moreover, the state vector of the proposed bidirectional searching strategy was designed based the bidirectional retrieval for enhancing the accuracy. In addition, the proposed bidirectional searching strategy shows significantly more accuracy compared to those of the previous methods.

Proactive Decision Making for ITS Communication

2020 ◽  
pp. 197-226 ◽  
Author(s):  
Rodrigo Silva ◽  
Christophe Couturier ◽  
Thierry Ernst ◽  
Jean-Marie Bonnin
Keyword(s):  
Decision Making ◽  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Transportation Systems ◽  
Network Resources ◽  
Communication Architecture ◽  
Cooperative Vehicles ◽  
Near Future ◽  
Cooperative Intelligent Transportation Systems ◽  
Exchange Data

Demand from different actors for extended connectivity where vehicles can exchange data with other vehicles, roadside infrastructure, and traffic control centers have pushed vehicle manufacturers to invest in embedded solutions, which paves the way towards cooperative intelligent transportation systems (C-ITS). Cooperative vehicles enable the development of an ecosystem of services around them. Due to the heterogeneousness of such services and their specific requirements, as well as the need for network resources optimization for ubiquitous connectivity, it is necessary to combine existing wireless technologies, providing applications with a communication architecture that hides such underlying access technologies specificities. Due to vehicles' high velocity, their connectivity context can change frequently. In such scenario, it is necessary to take into account the short-term prevision about network environment; enabling vehicles proactively manage their communications. This chapter discusses about the use of near future information to proactive decision-making process.

scholarly journals Analytic architecture to overcome real time traffic control as an intelligent transportation system using big data

2018 ◽  
Vol 7 (2.18) ◽  
pp. 7 ◽  
Author(s):  
Venkata Ramana N ◽  
Seravana Kumar P. V. M ◽  
Puvvada Nagesh
Keyword(s):  
Big Data ◽  
Real Time ◽  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Control Logic ◽  
Systematic Analysis ◽  
Real Time Traffic

Big data is a term that describes the large volume of data – both structured and unstructuredthat includes a business on a day-to-day basis including Intelligent Transportation Systems (ITS). The emerging connected technologies created around ubiquitous digital devices have opened unique opportunities to enhance the performance of the ITS. However, magnitude and heterogeneity of the Big Data are beyond the capabilities of the existing approaches in ITS. Therefore, there is a crucial need to develop new tools and systems to keep pace with the Big Data proliferation. In this paper, we propose a comprehensive and flexible architecture based on distributed computing platform for real-time traffic control. The architecture is based on systematic analysis of the requirements of the existing traffic control systems. In it, the Big Data analytics engine informs the control logic. We have partly realized the architecture in a prototype platform that employs Kafka, a state-of-the-art Big Data tool for building data pipelines and stream processing. We demonstrate our approach on a case study of controlling the opening and closing of a freeway hard shoulder lane in microscopic traffic simulation. 

scholarly journals Smart Cities and Data Analytics for Intelligent Transportation Systems: An Analytical Model for Scheduling Phases and Traffic Lights at Signalized Intersections

2021 ◽  
Vol 11 (15) ◽  
pp. 6816
Author(s):  
Fatih Gunes ◽  
Selim Bayrakli ◽  
Abdul Halim Zaim
Keyword(s):  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Transportation Systems ◽  
Signalized Intersections ◽  
Effective Control ◽  
Main Role ◽  
Smart Transportation ◽  
Traffic Lights ◽  
Service Rates

This paper is intended to improve the performance of signalized intersections, one of the most important systems of traffic control explained within the scope of smart transportation systems. These structures, which have the main role in ensuring the order and flow of traffic, are alternative systems depending on the different methods and techniques used. Determining the operation principles of these systems requires an extremely careful and planned study, considering their important role. Performance outputs obtained from the queue analyses made in previous studies formed the input of this study. The most important techniques are used in the effective control of intersections, such as signal timing: in particular, the use of effective green time and order of the transitions between phases. In this research, a traffic-sensitive signalized intersection control system was designed with the suggested methods against these two problems. The sample intersections were selected from three cities with the highest population density as the case study area. In the analysis of the performance of the connection arms of the selected intersections, flow intensity data were taken into consideration, as well as the arrival and service rates. Based on this, the outputs of the two proposed models regarding the use of phase transitions and effective green durations were compared with two other adaptive control systems and their positive results were shared. The results showed that signalized intersections, operating with a well-planned and correctly chosen technique, better regulate density and queuing.

Overview of Intelligent Transportation System Safety Countermeasures for Wrong-Way Driving

2021 ◽  
pp. 036119812110513
Author(s):  
Parisa Hosseini ◽  
Mohammad Jalayer ◽  
Huaguo Zhou ◽  
Md Atiquzzaman
Keyword(s):  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Evaluation Studies ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Comprehensive Overview ◽  
Severe Injuries ◽  
Widespread Application ◽  
Pavement Markings ◽  
Safety Countermeasures

Wrong-way driving (WWD) crashes are rare but tend to cause severe injuries and fatalities. When they occur, WWD crashes are mostly head-on and tend to be more severe than any other crash type. Currently, most efforts to mitigate WWD crashes focus on the application of intelligent transportation systems (ITS) technologies. Since the mid-1960s, many agencies have proposed and tested a variety of countermeasures ranging from the conventional, including improvements in signage and pavement markings, to the more advanced, based mainly on ITS. The application of ITS in detecting and deterring WWD crashes involves a combination of several components, such as detection, warning, and action. The main objective of this paper is to provide a comprehensive overview of ITS technologies implemented by different transportation agencies in the mitigation and prevention of WWD crashes. This study proves the importance of ITS technologies that have seen widespread application in recent years. Moreover, according to the evaluation studies of different ITS-related countermeasures, it shows that the countermeasures deployed have been effective in detecting wrong-way drivers and reducing the rate of wrong-way incidents. The results will provide insights for policymakers, engineers, and researchers into the application of ITS for reducing the severity and frequency of WWD crashes and other incidents on highway facilities.

scholarly journals Towards Personal Virtual Traffic Lights

Information ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 32 ◽  
Author(s):  
Vanessa Martins ◽  
João Rufino ◽  
Luis Silva ◽  
João Almeida ◽  
Bruno Miguel Fernandes Silva ◽  
...  
Keyword(s):  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Communication Systems ◽  
Field Tests ◽  
Transportation Systems ◽  
Smart Devices ◽  
Vehicular Communication ◽  
Traffic Light ◽  
Correct Operation ◽  
Traffic Lights

Traffic control management at intersections, a challenging and complex field of study, aims to strike a balance between safety and efficient traffic control. Nowadays, traffic control at intersections is typically done by traffic light systems which are not optimal and exhibit several drawbacks, such as poor efficiency and real-time adaptability. With the advent of Intelligent Transportation Systems (ITS), vehicles are being equipped with state-of-the-art technology, enabling cooperative decision-making which will certainly overwhelm the available traffic control systems. This solution strongly penalizes users without such capabilities, namely pedestrians, cyclists, and other legacy vehicles. Therefore, in this work, a prototype based on an alternative technology to the standard vehicular communications, Bluetooth Low Energy (BLE), is presented. The proposed framework aims to integrate legacy and modern vehicular communication systems into a cohesive management system. In this framework, the movements of users at intersections are managed by a centralized controller which, through the use of networked retransmitters deployed at intersections, broadcasts alerts and virtual light signalization orders. Users receive the aforementioned information on their own smart devices, discarding the need for dedicated light signalization infrastructures. Field tests, carried out with a real-world implementation, validate the correct operation of the proposed framework.

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