scholarly journals Alleviating Road Traffic Congestion with Artificial Intelligence

2021 ◽  
Author(s):  
Guni Sharon
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Road Traffic ◽  
State Of The Art ◽  
Autonomous Driving ◽  
Paper Briefly ◽  
Efficient Manner ◽  
Implementation Gaps ◽  
Road Traffic Congestion ◽  
Intersection Management

This paper reviews current AI solutions towards road traffic congestion alleviation. Three specific AI technologies are discussed, (1) intersection management protocols for coordinating vehicles through a roads intersection in a safe and efficient manner, (2) road pricing protocol that induce optimized traffic flow, and (3) partial or full autonomous driving that can stabilize traffic flow and mitigate adverse traffic shock waves. The paper briefly presents the challenges affiliated with each of these applications along with an overview of state-of-the-art solutions. Finally, real-world implementation gaps and challenges are discussed.

Discussion on Urban Road Traffic Congestion Algorithm for Automatically Determining

2014 ◽  
Vol 926-930 ◽  
pp. 3790-3793
Author(s):  
Yu Bo Dong
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Road Traffic ◽  
Traffic Signal Control ◽  
Transportation Engineering ◽  
Urban Road ◽  
Traffic Incident ◽  
Road Congestion ◽  
Road Traffic Congestion

Compared with the expressway, most of the traffic flow in urban road network can be denoted as interrupted traffic flow. Based on the current employed equipment for traffic flow collection and traffic signal control in urban roads, different types of traffic flow in urban roads are analyzed with the traffic flow arrival/departure model in transportation engineering. Mathematical models complying with traffic flow changes are utilized to match the traffic flow in both entry and exit road blocks, thus, enabled the automatic detection of traffic incident. This algorithm provides a measurement for the automatic judgment of urban road congestion and the expansion utility of intelligent transportation facilities in urban areas.

scholarly journals Road Traffic Congestion Management Based on a Search-Allocation Approach

2017 ◽  
Vol 18 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Jamal Raiyn
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Smart Cities ◽  
Self Regulation ◽  
Congestion Management ◽  
Shortest Route ◽  
Road Traffic Congestion

Abstract This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA). An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT) technologies.

scholarly journals V2V-based method for the detection of road traffic congestion

2019 ◽  
Vol 13 (5) ◽  
pp. 880-885 ◽  
Author(s):  
Runmin Wang ◽  
Zhigang Xu ◽  
Xiangmo Zhao ◽  
Jinchao Hu
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Road Traffic Congestion

scholarly journals Urban Wasteful Transport and Its Estimation Methods

2018 ◽  
Vol 10 (12) ◽  
pp. 4562 ◽  
Author(s):  
Xiangyang Cao ◽  
Bingzhong Zhou ◽  
Qiang Tang ◽  
Jiaqi Li ◽  
Donghui Shi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Transport Theory ◽  
Road Traffic ◽  
Urban Traffic ◽  
Flow Density ◽  
Urban Road ◽  
Road Capacity ◽  
Density Relationship

The paper studies urban road traffic problems from the perspective of resource science. The resource composition of urban road traffic system is analysed, and the road network is proved as a scarce resource in the system resource combination. According to the role of scarce resources, the decisive role of road capacity in urban traffic is inferred. Then the new academic viewpoint of “wasteful transport” was proposed. Through in-depth research, the paper defines the definition of wasteful transport and expounds its connotation. Through the flow-density relationship analysis of urban road traffic survey data, it is found that there is a clear boundary between normal and wasteful transport in urban traffic flow. On the basis of constructing the flow-density relationship model of road traffic, combined with investigation and analysis, the quantitative estimation method of wasteful transport is established. An empirical study on the traffic conditions of the Guoding section of Shanghai shows that there is wasteful transport and confirms the correctness of the wasteful transport theory and method. The research of urban wasteful transport also reveals that: (1) urban road traffic is not always effective; (2) traffic flow exceeding road capacity is wasteful transport, and traffic demand beyond the capacity of road capacity is an unreasonable demand for customers; (3) the explanation that the traffic congestion should apply the comprehensive theory of traffic engineering and resource economics; and (4) the wasteful transport theory and method may be one of the methods that can be applied to alleviate traffic congestion.

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