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.

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.

Research on Evaluation of Urban Road Congestion

2014 ◽  
Vol 536-537 ◽  
pp. 815-819
Author(s):  
Yi Dan Gao
Keyword(s):  
Traffic Congestion ◽  
Evaluation System ◽  
Road Traffic ◽  
Urban Traffic ◽  
Evaluation Index System ◽  
Analytic Hierarchy ◽  
Urban Road ◽  
Research On Evaluation ◽  
Four Levels ◽  
The Government

This paper presents an urban road traffic evaluation system from traffic behavior, transport, traffic supply and traffic concept using the analytic hierarchy process techniques. We collect data by distributing questionnaires in Qingdao and determine the congestion evaluation index system after processing the data by factor analysis. The system is designed to emulate human's expertise on specifying four levels of traffic congestion within the urban area. Case analysis shows that our evaluation system is provided for the government to manage urban traffic networks.

scholarly journals Adaptive Correction Forecasting Approach for Urban Traffic Flow Based on Fuzzyc-Mean Clustering and Advanced Neural Network

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
He Huang ◽  
Qifeng Tang ◽  
Zhen Liu
Keyword(s):  
Neural Network ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Prediction Accuracy ◽  
Intelligent Transportation System ◽  
Prediction Models ◽  
Road Traffic ◽  
Urban Traffic ◽  
Traffic Flow Prediction ◽  
Adaptive Correction

Forecasting of urban traffic flow is important to intelligent transportation system (ITS) developments and implementations. The precise forecasting of traffic flow will be pretty helpful to relax road traffic congestion. The accuracy of traditional single model without correction mechanism is poor. Summarizing the existing prediction models and considering the characteristics of the traffic itself, a traffic flow prediction model based on fuzzyc-mean clustering method (FCM) and advanced neural network (NN) was proposed. FCM can improve the prediction accuracy and robustness of the model, while advanced NN can optimize the generalization ability of the model. Besides these, the output value of the model is calibrated by the correction mechanism. The experimental results show that the proposed method has better prediction accuracy and robustness than the other models.

scholarly journals Theoretical Comparison of the Effects of Different Traffic Conditions on Urban Road Traffic Noise

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammad Maghrour Zefreh ◽  
Adam Torok
Keyword(s):  
Traffic Flow ◽  
Noise Level ◽  
Urban Areas ◽  
Road Traffic ◽  
Traffic Noise ◽  
Urban Traffic ◽  
Road Traffic Noise ◽  
Traffic Lights ◽  
Urban Road ◽  
Traffic Conditions

Road traffic noise is one of the most relevant sources in the environmental noise pollution of the urban areas where dynamics of the traffic flow are much more complicated than uninterrupted traffic flows. It is evident that different traffic conditions would play the role in the urban traffic flow considering the dynamic nature of the traffic flow on one hand and presence of traffic lights, roundabouts, etc. on the other hand. The main aim of the current paper is to investigate the effect of different traffic conditions on urban road traffic noise. To do so, different traffic conditions have been theoretically generated by the Monte Carlo Simulation technique following the distribution of traffic speed in the urban roads. The “ASJ RTN-Model” has been considered as a base road traffic noise prediction model which would deal with different traffic conditions including steady and nonsteady traffic flow that would cover the urban traffic flow conditions properly. Having generated the vehicles speeds in different traffic conditions, the emitted noise (LWA) and subsequently the noise level at receiver (LA) were estimated by “ASJ RTN-Model.” Having estimated LWA and LA for each and every vehicle in each traffic condition and taking the concept of transient noise into account, the single event sound exposure levels (SEL) in different traffic conditions are calculated and compared to each other. The results showed that decelerated traffic flow had the lowest contribution, compared to congestion, accelerated flow, free flow, oversaturated congestion, and undersaturated flow by 16%, 14%, 12%, 12%, and 10%, respectively. Moreover, the distribution of emitted noise and noise level at receiver were compared in different traffic conditions. The results showed that traffic congestion had considerably the maximum peak compared to other traffic conditions which would highlight the importance of the range of generated noise in different traffic conditions.

scholarly journals Urban road traffic flow control under incidental congestion as a function of accident duration

Open Physics ◽  
2018 ◽  
Vol 16 (1) ◽  
pp. 1085-1093
Author(s):  
Yang Xu ◽  
Duojia Zhang ◽  
Ahmad Jalal Khan Chowdhury
Keyword(s):  
Flow Control ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Abrupt Increase ◽  
Urban Road ◽  
Catastrophe Model ◽  
Traffic Capacity ◽  
Control Scheme

Abstract An abrupt increase in urban road traffic flow caused by incidental congestion is considered. The residual traffic capacity varies in different lanes after an accident, and the influence of accident duration on traffic flow is taken into account. The swallowtail catastrophe model was built based on catastrophe theory. The critical state of traffic congestion under incidental congestion was analyzed using this model, and a traffic flow control scheme is proposed with the goal of maximizing the traffic capacity. Finally, the operational state of traffic flow under different scenarios is analyzed through case study and the feasibility of the model is validated.

scholarly journals Cooperative U-Turn Merging Behaviors and Their Impacts on Road Traffic in CVIS Environment

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Wenjing Wu ◽  
Renchao Sun ◽  
Yongxing Li ◽  
Runchao Chen
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Cooperative Control ◽  
Control Algorithm ◽  
Road Traffic ◽  
Control Strategies ◽  
Arrival Rate ◽  
Urban Traffic ◽  
Delay Minimization ◽  
Infrastructure System

U-turn behavior of vehicle is one of the main causes of urban traffic congestion and accidents. A collaborative U-turn merging control algorithm is studied with collision avoidance and delay minimization for vehicles under Cooperative Vehicle Infrastructure System (CVIS) environment. Two control strategies, zip merging and platoon merging control, are proposed. The applicability of these two strategies is compared from the perspective of efficiency and driving comfort. The cellular automaton simulation system composed of a two-way four-lane traffic flow with a U-turn facility in middle of road is established with cooperative control algorithm imbedded. The influence of cooperative U-turn merging behaviors on traffic performance is evaluated by analyzing the arrival rates of main lane and U-turn vehicles and their relationship between one another. The simulation results show that the arrival rate of vehicles on target lane has a great impact on traffic delay. The cooperative control can improve the traffic flow only in the condition that the arrival rate of vehicles on target lane is less than 0.7. It provides some practical references for transportation agencies to meet efficiency requirements of the U-turn section when they apply cooperative control strategy.

The Urban Road Short-Term Traffic Flow Prediction Research

2013 ◽  
Vol 423-426 ◽  
pp. 2954-2956 ◽  
Author(s):  
Zhen Hai Qin
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Evaluation Model ◽  
Social Resources ◽  
Urban Traffic ◽  
Short Term ◽  
Urban Road ◽  
Traffic Flow Prediction ◽  
Flow Prediction ◽  
Short Period

To predict the future traffic flow status more accurately is of great significance to alleviate urban traffic congestion for a short period of time and avoid the waste of social resources. At first, this paper summarizes the characteristics of urban expressway traffic flow. Then establishes BP neural network short-term traffic flow evaluation model based on MATLAB, and finally through the instance, verify the validity of the model.

scholarly journals Large-scale traffic flow simulation based on intelligent PSO

2022 ◽  
Vol 355 ◽  
pp. 02010
Author(s):  
Zeyu Liu ◽  
Gongping Yang
Keyword(s):  
Traffic Flow ◽  
Waiting Time ◽  
Large Scale ◽  
Road Traffic ◽  
Rapid Development ◽  
Flow Simulation ◽  
Urban Traffic ◽  
The Real ◽  
Urban Road ◽  
Grid Model

With the rapid development of urban traffic, a large number of vehicles in cities not only bring convenience to people, but also bring a series of traffic problems, including traffic congestion and high traffic accident rates. Driving speed and waiting time of vehicles are two important factors of traffic problems. To simulate the real urban road traffic flow, a one-dimensional traffic flow grid model was proposed, which considered the nearest and next neighbour car at the same time, and connected the front and rear neighbour cars to optimize the traffic flow. The experiment results showed that our traffic flow grid model can simulate the real urban road traffic flow. In addition, we tried to optimize the urban traffic network model and improved the traffic speed of vehicles and reduced the waiting time.

Fuzzy peak hour for urban road traffic network

2015 ◽  
Vol 29 (15) ◽  
pp. 1550074 ◽  
Author(s):  
Zhao Tian ◽  
Li-Min Jia ◽  
Hong-Hui Dong ◽  
Zun-Dong Zhang ◽  
Yang-Dong Ye
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Road Traffic ◽  
Flow Speed ◽  
Urban Traffic ◽  
Traffic Network ◽  
Traffic Condition ◽  
Time Pattern ◽  
Urban Road ◽  
Optimal Separation

Traffic congestion is now nearly ubiquitous in many urban areas and frequently occurs during rush hour periods. Rush hour avoidance is an effective way to ease traffic congestion. It is significant to calculate the rush hour for alleviating traffic congestion. This paper provides a method to calculate the fuzzy peak hour of the urban traffic network considering the flow, speed and occupancy. The process of calculation is based on betweenness centrality of network theory, optimal separation method, time period weighting, probability–possibility transformations and trapezoidal approximations of fuzzy numbers. The fuzzy peak hour of the urban road traffic network (URTN) is a trapezoidal fuzzy number [m1, m2, m3, m4]. It helps us (i) to confirm a more detailed traffic condition at each moment, (ii) to distinguish the five traffic states of the traffic network in one day, (iii) to analyze the characteristic of appearance and disappearance processes of the each traffic state and (iv) to find out the time pattern of residents travel in one city.

scholarly journals Intelligent Planning and Research on Urban Traffic Congestion

2021 ◽  
Vol 13 (11) ◽  
pp. 284
Author(s):  
Qigang Zhu ◽  
Yifan Liu ◽  
Ming Liu ◽  
Shuaishuai Zhang ◽  
Guangyang Chen ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Intelligent Transportation System ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Urban Traffic ◽  
Traffic Planning ◽  
City Development ◽  
Urban Road

For large and medium-sized cities, the planning and development of urban road networks may not keep pace with the growth of urban vehicles, resulting in traffic congestion on urban roads during peak hours. Take Jinan, a mid-sized city in China’s Shandong Province, for example. In view of the daily traffic jam of the city’s road traffic, through investigation and analysis, the existing problems of the road traffic are found out. Based on real-time, daily road traffic data, combined with the existing road network and the planned road network, the application of a road intelligent transportation system is proposed. Combined with the application of a road intelligent transportation system, this paper discusses the future development of urban road traffic and puts forward improvement suggestions for road traffic planning. This paper has reference value for city development, road network construction, the application of intelligent transportation systems, and road traffic planning.

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