scholarly journals Predicting traffic flow during peak commuting hours

2021 ◽  
Author(s):  
Z. Shen
Keyword(s):  
Traffic Flow ◽  
Public Transportation ◽  
Traffic Congestion ◽  
High Efficiency ◽  
Road Traffic ◽  
Low Cost ◽  
Survey Method ◽  
Rail Transit ◽  
Validity And Reliability ◽  
Peak Period

Abstract Traffic congestion during the peak commuting period is becoming more and more serious in many cities in China. Accurate prediction of traffic flow on urban roads during the peak commuting period is one of the key fundamental problems to reduce traffic congestion and build intelligent transportation. This paper proposes a low-cost and high-efficiency method to address the challenges of the existing ORIGIN-DESTINATION survey method, which is costly, inefficient and has limited accuracy of results. By using the city-wide traffic, social security, insurance, population and other digital city data, we group the residents' travel modes into four types: walking, public transportation, rail transit and self-driving based on the service radius and travel distance of transportation, and analyze and count the number of private car trips and rail transit passenger flow by using the rail transit priority principle and the shortest path algorithm, and predict the commuting peak period based on this method. The road traffic flow during the peak commuting period is also predicted. The validity and reliability of the method are demonstrated by using typical data of Wuhan city as an example.

scholarly journals A Multi-Loop Vehicle-Counting Method under Gray Mode and RGB Mode

2021 ◽  
Vol 11 (15) ◽  
pp. 6831
Author(s):  
Yue Chen ◽  
Jian Lu
Keyword(s):  
Intelligent Transportation Systems ◽  
High Efficiency ◽  
Road Traffic ◽  
Low Cost ◽  
Rapid Development ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Counting Method ◽  
Moving Vehicle ◽  
Available Information

With the rapid development of road traffic, real-time vehicle counting is very important in the construction of intelligent transportation systems (ITSs). Compared with traditional technologies, the video-based method for vehicle counting shows great importance and huge advantages in its low cost, high efficiency, and flexibility. However, many methods find difficulty in balancing the accuracy and complexity of the algorithm. For example, compared with traditional and simple methods, deep learning methods may achieve higher precision, but they also greatly increase the complexity of the algorithm. In addition to that, most of the methods only work under one mode of color, which is a waste of available information. Considering the above, a multi-loop vehicle-counting method under gray mode and RGB mode was proposed in this paper. Under gray and RGB modes, the moving vehicle can be detected more completely; with the help of multiple loops, vehicle counting could better deal with different influencing factors, such as driving behavior, traffic environment, shooting angle, etc. The experimental results show that the proposed method is able to count vehicles with more than 98.5% accuracy while dealing with different road scenes.

scholarly journals Research on Decision Evaluation Model of HOV Lane Setting

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Ding Lv ◽  
Qunqi Wu ◽  
Bo Chen ◽  
Yahong Jiang
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Evaluation Model ◽  
Path Selection ◽  
Urban Traffic ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Travel Efficiency ◽  
Hov Lanes ◽  
The City

In order to achieve the purpose of improving the travel efficiency of commuters in the periphery of the city, expanding the beneficiary groups of urban rail transit, and alleviating urban road traffic congestion, when planning and setting up HOV in the periphery of the city, it is necessary to analyze the feasibility of HOV lane setting from both the demand conditions and the setting conditions. This paper combines machine learning to construct a decision-making evaluation model for HOV lane setting and studies the optimal layout model and algorithm of HOV lanes in service rail transit commuter chain. The setting, planning, and layout of HOV lanes are a two-way interactive process of traveler's path selection and designer's road planning. Finally, after the model is constructed, the performance of the system model is verified. The results show that the system studied in this paper can be used for traffic data and lane planning analysis. Therefore, in the process of urban operation, the HOV model constructed in this paper is mainly used to alleviate urban traffic and improve urban operation efficiency.

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.

scholarly journals Improved Spatio-Temporal Residual Networks for Bus Traffic Flow Prediction

2019 ◽  
Vol 9 (4) ◽  
pp. 615 ◽  
Author(s):  
Panbiao Liu ◽  
Yong Zhang ◽  
Dehui Kong ◽  
Baocai Yin
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Transportation Network ◽  
Temporal Correlation ◽  
Traffic Flow Prediction ◽  
Temporal Correlations ◽  
Building Models ◽  
Spatio Temporal ◽  
Specific Scenario

Buses, as the most commonly used public transport, play a significant role in cities. Predicting bus traffic flow cannot only build an efficient and safe transportation network but also improve the current situation of road traffic congestion, which is very important for urban development. However, bus traffic flow has complex spatial and temporal correlations, as well as specific scenario patterns compared with other modes of transportation, which is one of the biggest challenges when building models to predict bus traffic flow. In this study, we explore bus traffic flow and its specific scenario patterns, then we build improved spatio-temporal residual networks to predict bus traffic flow, which uses fully connected neural networks to capture the bus scenario patterns and improved residual networks to capture the bus traffic flow spatio-temporal correlation. Experiments on Beijing transportation smart card data demonstrate that our method achieves better results than the four baseline methods.

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 INTELLIGENT TRAFFIC CONTROL DEVICE MODEL USING AD HOC NETWORK

2019 ◽  
Vol 01 (02) ◽  
pp. 68-76
Author(s):  
Robert Bestak
Keyword(s):  
Traffic Flow ◽  
Automobile Industry ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Communication Systems ◽  
Ad Hoc ◽  
Road Traffic ◽  
Control Device ◽  
Device Model

The advancements in the technologies related to the wireless communication systems has made the vehicular adhoc networks prominent area of research in the automobile industry. The absolute volume of road traffic affects the safety, convenience and the efficiency of the traffic flow in the urban areas. So the paper scopes in developing an intelligent traffic control device model using the adhoc network to ameliorate the traffic flow. The proposed system enhances the convenience in travel by gathering the information of the vehicles along with the density of the vehicles and the movement of the vehicles on road. The device is modelled using the MATLAB and examined over the traffic flow on the peak hours as well as the normal hours and the holidays to understand its intelligent traffic control. The results obtained shows that the performance improvement in optimizing the traffic congestion through the proposed method is better compared to the existing methodologies used in traffic controlling.

Microscopic Road Traffic Scene Analysis Using Computer Vision and Traffic Flow Modelling

2018 ◽  
Vol 22 (5) ◽  
pp. 704-710 ◽  
Author(s):  
Robert Kerwin C. Billones ◽  
◽  
Argel A. Bandala ◽  
Laurence A. Gan Lim ◽  
Edwin Sybingco ◽  
...  
Keyword(s):  
Computer Vision ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Volume Estimation ◽  
Public Utility ◽  
Scene Analysis ◽  
Volume Distribution ◽  
Distribution Analysis ◽  
Traffic Scene Analysis

This paper presents the development of a vision-based system for microscopic road traffic scene analysis and understanding using computer vision and computational intelligence techniques. The traffic flow model is calibrated using the information obtained from the road-side cameras. It aims to demonstrate an understanding of different levels of traffic scene analysis from simple detection, tracking, and classification of traffic agents to a higher level of vehicular and pedestrian dynamics, traffic congestion build-up, and multi-agent interactions. The study used a video dataset suitable for analysis of a T-intersection. Vehicle detection and tracking have 88.84% accuracy and 88.20% precision. The system can classify private cars, public utility vehicles, buses, and motorcycles. Vehicular flow of every detected vehicles from origin to destination are also monitored for traffic volume estimation, and volume distribution analysis. Lastly, a microscopic traffic model for a T-intersection was developed to simulate a traffic response based on actual road scenarios.

Experience and Reference of Implementing Public Transport Priority Strategy Dominated by Urban Rail Transit in Tokyo

2014 ◽  
Vol 505-506 ◽  
pp. 813-819
Author(s):  
Bin Ya Zhang ◽  
Hao Yue ◽  
Shuai Wang
Keyword(s):  
Public Transport ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Paper Analysis ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
High Population Density ◽  
Large Cities ◽  
The Public ◽  
Urban Rail

Urban public transportation is the main effective way to solve the problem of increasingly congested city ground traffic, and public transport priority is the important guarantee to realize the way. Due to the short domestic history, there are problems to be solved in the respects of on the implementation of "public transport priority" in specific operation method, implementation measures and matters needing attention etc. Some oversea cities with high population density and serious traffic congestion have made some exploration in public transport priority development whose experiences are worthy of reference. Tokyo, the typical oversea city, has been selected out by this paper. Analysis has been down on the issue of the experiences and achievement of Tokyo in implementing the public transport priority strategy which is donated by urban rail transit, and experiences are summed up. On the basis of it, some suggestions have been proposed for the implementation of China's large cities public transport priority strategy.

scholarly journals Exploiting witness for traffic simulation

2014 ◽  
Vol 1 (1) ◽  
pp. 12-24
Author(s):  
Azhar Ismail ◽  
Muhammad Latif ◽  
Mian Awai
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Waiting Times ◽  
Simulation Software ◽  
Peak Time ◽  
Traffic Lights ◽  
Traffic Intersection ◽  
Flow Through ◽  
Alternative Scenarios

Traffic congestion in urban cities is an increasing problem. Not only does it lead to an increase in pollution, but the time spent waiting in traffic queues wastes valuable time in addition to causing frustration. A system that can control and manage traffic efficiently is one way that this issue can be reduced.A specific road traffic intersection in South Manchester, UK, was selected for investigation as it experiences high levels of traffic flow through it during the evening peak time. This has led to large queues and long waiting times due to the fixed timings of the traffic lights. This paper explores strategies to better control the traffic flow through it. A model of the selected traffic junction has been built using Witness simulation software. Data for this junction has been obtained partially from observations and mostly from traffic surveys enabling a simulation of the traffic flow. Analysing the results allowed two alternative scenarios to be developed and simulated. Results from one of the scenarios showed noticeable reductions in the average queue waiting times at the traffic junction.

scholarly journals Do Rail Transits Improve Local Air Quality? Take Chengdu-Nanchang for Example

2021 ◽  
Author(s):  
Xueyuan Wang ◽  
Yuping Wang ◽  
Zhijian Zhang ◽  
Jingwei Li
Keyword(s):  
Air Pollution ◽  
Carbon Monoxide ◽  
Air Quality ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Urban Air Pollution ◽  
Point Estimate ◽  
Urban Air ◽  
Rail Transit ◽  
Transit System

Abstract Many cities in China have invested the city’s rail transit system to reduce urban air pollution and traffic congestion. Earlier studies rarely compare the effects of rail transit on urban air quality in different cities, providing little guidance to urban planners in solving traffic congestion and air quality. By using the rail transit lines in Chengdu and Nanchang as case studies, this paper attempts to examine the effect of rail transit on air pollution. Data were collected from 18 monitoring stations distributed along the chosen rail transit lines in both cities during the period 2014 to 2016 and analyzed using the regression discontinuity design to address the potential endogenous location of subway stations. The results show that subway opening in Nanchang has a better reductions from automobile exhaust than that in Chengdu, specifically, carbon monoxide pollution, one key tailpipe pollutant, experienced a 10.23% greater reduction after Nanchang Metro Line 1 opened. On the contrary, the point estimate for carbon monoxide in Chengdu is 22.42% and statistically significant at the 1% level. Nanchang Metro Line 1 does play an important role in road traffic externalities, but the benefit was not huge enough to change the overall air quality. On the contrary, the opening of the Chengdu Metro Line 4 is unlikely to yield improvements in air quality.

Sign in / Sign up

Export Citation Format

Share Document