scholarly journals Application of Macroscopic Fundamental Diagram under Flooding Situation to Traffic Management Measures

2021 ◽  
Vol 13 (20) ◽  
pp. 11227
Author(s):  
Piyapong Suwanno ◽  
Rattanaporn Kasemsri ◽  
Kaifeng Duan ◽  
Atsushi Fukuda
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Road Network ◽  
Road Traffic ◽  
Control Measures ◽  
Flow Density ◽  
Fundamental Diagram ◽  
Urban Flood ◽  
Traffic Conditions ◽  
Macroscopic Fundamental Diagram

Bangkok, Thailand is prone to flooding after heavy rain. Many road sections become impassable, causing severe traffic congestion and greatly impacting activities. Optimal vehicle management requires the knowledge of flooding impact on road traffic conditions in specific areas. A method is proposed to quantify urban flood situations by expressing traffic conditions in specific ranges using the concept of macroscopic fundamental diagram (MFD). MFD-based judgement allows for a road manager to understand the current traffic situation and take appropriate traffic control measures. MFD analysis identified traffic flow–density and density–velocity relationships by using the shape of the estimated MFD travel time-series plots. Then, results were applied to develop a traffic model with vehicle-flow parameters as a measuring method for road-network performance. The developed model improved road-network traffic-flow performance under different flood conditions. A method is also presented for traffic management evaluation on the assumption that flooding occurs.

An Improved Regional Traffic Volume Dynamic Feedback Control

2016 ◽  
Vol 26 (09n10) ◽  
pp. 1539-1554
Author(s):  
Yiman Du ◽  
Jianping Wu ◽  
Yuhan Jia ◽  
Ming Xu
Keyword(s):  
Feedback Control ◽  
Traffic Congestion ◽  
Road Network ◽  
Control Method ◽  
Road Traffic ◽  
Dynamic Control ◽  
Traffic Volume ◽  
Dynamic Feedback ◽  
Fundamental Diagram ◽  
Traffic Conditions

The connection between traffic congestion and regional demand has become a consensus. A reasonable road network inflow control is essential to prevent the occurrence of congestion. With a consideration of deployment of detectors, an improved macroscopic fundamental diagram-based traffic volume dynamic control method via the feedback control is proposed in this study. Based on the origin–destination distribution of trips and connectivity of nodes, a novel method is adopted to identify the key nodes, on which the detectors are laid. An artificial neural network is adopted to predict traffic volume of those sections without detectors. As a case study, the proposed methodology is applied and estimated via simulation study to the regional road network which is located in the downtown area of Nanning, China. Adequate survey and analysis are carried out under the current road traffic conditions. It is proved that the regional traffic volume dynamic control can ensure steady and orderly regional traffic flow, and enhance the mobility during saturated traffic conditions.

Space–time correlation analysis of traffic flow on road network

2017 ◽  
Vol 31 (05) ◽  
pp. 1750027 ◽  
Author(s):  
Fei Su ◽  
Honghui Dong ◽  
Limin Jia ◽  
Zhao Tian ◽  
Xuan Sun
Keyword(s):  
Correlation Analysis ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Network ◽  
Road Traffic ◽  
Seasonal Pattern ◽  
Time Correlation ◽  
Space Time ◽  
Theoretical Assumption

Space–time correlation analysis has become a basic and critical work in the research on road traffic congestion. It plays an important role in improving traffic management quality. The aim of this research is to examine the space–time correlation of road networks to determine likely requirements for building a suitable space–time traffic model. In this paper, it is carried out using traffic flow data collected on Beijing’s road network. In the framework, the space–time autocorrelation function (ST-ACF) is introduced as global measure, and cross-correlation function (CCF) as local measure to reveal the change mechanism of space–time correlation. Through the use of both measures, the correlation is found to be dynamic and heterogeneous in space and time. The finding of seasonal pattern present in space–time correlation provides a theoretical assumption for traffic forecasting. Besides, combined with Simpson’s rule, the CCF is also applied to finding the critical sections in the road network, and the experiments prove that it is feasible in computability, rationality and practicality.

scholarly journals FORMATION OF ROAD TRAFFIC MANAGEMENT PRINCIPLES IN THE SYSTEM "PEREHIN"

World Science ◽  
2021 ◽  
Author(s):  
Polishchuk V. ◽  
Nahrebelna L.
Keyword(s):  
Traffic Flow ◽  
Transport System ◽  
Traffic Management ◽  
Road Network ◽  
Road Traffic ◽  
Road Transport ◽  
Economic Losses ◽  
Traffic Flows ◽  
The Road ◽  
Main Indicator

The development of road transport, both economically and socially, is of great importance for humanity. But along with the tremendous benefits andunlimited potential of road transport, there are many problems, particularly with its operation in human settlements, particularly in cities. Theseproblems are related to the oversaturation of the road network of cities with road transport, which leads to a decrease in speed, congestion, increased traveltime. Ensuring the required capacity of the site is the main indicator of creating conditions for the efficient functioning of the transport system of cities.Each section has its own planning features that allow the car to move at an acceptable speed and at the same time not create any situations that could lead to the formation of congestion.It is known that the lower the speed, the greater the time spent. Speed is one of the most important indicators of traffic flow. Any reduction in the speed of traffic flows compared to the permitted leads to economic losses. And if we consider the reduction of speed, taking into account the stop in motion (delay), it leads to much greater economic losses.

scholarly journals Road Traffic Analysis Using Computer Vision

2021 ◽  
Vol 9 (8) ◽  
pp. 2002-2006
Author(s):  
Needhi U. Gaonkar
Keyword(s):  
Computer Vision ◽  
Traffic Flow ◽  
Traffic Management ◽  
Road Traffic ◽  
Vehicle Detection ◽  
Traffic Analysis ◽  
Transportation Systems ◽  
Visual Object ◽  
Highway Traffic ◽  
Analysis System

Abstract: Traffic analysis plays an important role in a transportation system for traffic management. Traffic analysis system using computer vision project paper proposes the video based data for vehicle detection and counting systems based on the computer vision. In most Transportation Systems cameras are installed in fixed locations. Vehicle detection is the most important requirement in traffic analysis part. Vehicle detection, tracking, classification and counting is very useful for people and government for traffic flow, highway monitoring, traffic planning. Vehicle analysis will supply with information about traffic flow, traffic summit times on road. The motivation of visual object detection is to track the vehicle position and then tracking in successive frames is to detect and connect target vehicles for frames. Recognising vehicles in an ongoing video is useful for traffic analysis. Recognizing what kind of vehicle in an ongoing video is helpful for traffic analysing. this system can classify the vehicle into bicycle, bus, truck, car and motorcycle. In this system I have used a video-based vehicle counting method in a highway traffic video capture using cctv camera. Project presents the analysis of tracking-by-detection approach which includes detection by YOLO(You Only Look Once) and tracking by SORT(simple online and realtime tracking) algorithm. Keywords: Vehicle detection, Vehicle tracking, Vehicle counting, YOLO, SORT, Analysis, Kalman filter, Hungarian algorithm.

scholarly journals Macroscopic Fundamental Diagram based Road Network Characteristics Identification and Simulation

2020 ◽  
Vol 165 ◽  
pp. 04051
Author(s):  
Yi Yu ◽  
Liang Wang ◽  
Xianglun Mo ◽  
Yao Yu ◽  
Mei liu
Keyword(s):  
Road Network ◽  
Key Factors ◽  
Link Length ◽  
Fundamental Diagram ◽  
Road Density ◽  
Network Characteristics ◽  
The Road ◽  
Macroscopic Fundamental Diagram ◽  
Flow Equilibrium ◽  
The Relationship

As an inherent property of the road network, macroscopic fundamental diagram (MFD) method can effectively describe the traffic status of the urban roads and identify the relationship among key factors, such as traffic flow and occupancy. Currently, using MFD is easily affected by various network inner factors including topology and road density, so in this paper we propose a method to identify inner characteristic of road network and do a series of comparisons under different scenarios with fixed traffic input circumstance. The differential impact of data collector setting locations are discussed with a aim to reveal the respective location setting suitable for various networks conditions in initial; then road topology and density are designed in road network and simulated MFD performances with flow equilibrium affections. It is shown as the dispersion decreasing of link length or road density of network, the network exhibits better operation efficiency so as to increase the output of link flow and the dissipative ability of the road network. Meanwhile, the equivalent of entrances and exits is proved as another important factor has same impact on MFD.

Recent developments in traffic flow modeling using macroscopic fundamental diagram

2020 ◽  
Vol 40 (4) ◽  
pp. 529-550
Author(s):  
Lele Zhang ◽  
Zhongqi Yuan ◽  
Li Yang ◽  
Zhiyuan Liu
Keyword(s):  
Traffic Flow ◽  
Flow Modeling ◽  
Fundamental Diagram ◽  
Macroscopic Fundamental Diagram ◽  
Recent Developments

scholarly journals Evaluating Impacts of Overloaded Heavy Vehicles on Freeway Traffic Condition by a Novel Multi-Class Traffic Flow Model

2018 ◽  
Vol 10 (12) ◽  
pp. 4694 ◽  
Author(s):  
Xiang Wang ◽  
Po Zhao ◽  
Yanyun Tao
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Management Strategies ◽  
Maximum Speed ◽  
Heavy Vehicles ◽  
Fundamental Diagram ◽  
Traffic Condition ◽  
Traffic Flow Model ◽  
Traffic Conditions ◽  
The Impact

Overloaded heavy vehicles (HVs) have significant negative impacts on traffic conditions due to their inferior driving performance. Highway authorities need to understand the impact of overloaded HVs to assess traffic conditions and set management strategies. We propose a multi-class traffic flow model based on Smulders fundamental diagram to analyze the influence of overloaded HVs on traffic conditions. The relationship between the overloading ratio and maximum speed is established by freeway toll collection data for different types of HVs. Dynamic passenger car equivalent factors are introduced to represent the various impacts of overloaded HVs in different traffic flow patterns. The model is solved analytically and discussed in detail in the appendices. The model validation results show that the proposed model can represent traffic conditions more accurately with consideration for overloaded HVs. The scenario tests indicate that the increase of overloaded HVs leads to both a higher congestion level and longer duration.

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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