scholarly journals A Novel Approach to Calculate the Spatial–Temporal Correlation for Traffic Flow Based on the Structure of Urban Road Networks and Traffic Dynamic Theory

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4725
Author(s):  
Mao Du ◽  
Lin Yang ◽  
Jiayu Tu
Keyword(s):  
Road Traffic ◽  
Temporal Correlation ◽  
Calculation Model ◽  
Urban Traffic ◽  
Research Fields ◽  
Novel Approach ◽  
Correlation Information ◽  
Two Parameters ◽  
Traffic Operation ◽  
Operation Characteristics

Determining the spatial–temporal correlation (STC) between roads can help clarify the operation characteristics of road traffic. Moreover, this correlation affects the utilization quality of traffic data in related research fields. Therefore, it is of significance to provide more reasonable correlation information for other research, such as in traffic speed prediction. Most of the traditional correlation calculation methods for traffic are based on only statistical theory. These methods are simple, but their ability to explain the actual phenomenon is limited due to the lack of consideration of the actual traffic operation characteristics. Therefore, to provide more reasonable correlation information between roads, this paper analysed the influence mechanism of urban traffic based on the traffic dynamic model, and two parameters, traffic complete influence time and traffic correlation strength, were proposed to bring physical meaning to the calculation of STC. Then, an improved calculation model of the STC between different roads considering the adjacency between roads was proposed in this paper. Finally, this paper verified this method against two common traditional methods through different experiments. The verification results show that the calculation method proposed in this paper has better interpretability for the STC between different roads and can better reveal the internal traffic operation characteristics of the road network.

Research on Calculation Model of Minimum Net Distance between Interchanges on Eight-Lane Expressway

2011 ◽  
Vol 97-98 ◽  
pp. 121-129 ◽  
Author(s):  
Bing Hong Pan ◽  
Ling Chen Kong
Keyword(s):  
Probability Theory ◽  
Calculation Model ◽  
Operating Speed ◽  
Lane Change ◽  
Gap Acceptance ◽  
Lane Changing ◽  
Change Operation ◽  
Traffic Operation ◽  
Gap Acceptance Theory ◽  
Operation Characteristics

According to traffic operation characteristics and lane changing maneuvers, combining with the export notice signs and considering the worst driving conditions, the gap acceptance theory and kinematics are employed to establish the length of lane change operation between interchanges with probability theory. To operating speed as the premise, the necessary length that drivers change to the inside lane from the nearside lane is analyzed in terms of waiting for the gap acceptance, and the necessary length that drivers change to the nearside lane from the inside lane is also analyzed in terms of running for the gap acceptance, then calculation model of minimum net distance between interchanges on eight-lane expressway is constructed. The recommended value is then put forward.

scholarly journals Analysis of Traffic Operation Characteristics and Calculation Model of the Length of the Connecting Section between Ramp and Intersection

2022 ◽  
Vol 14 (2) ◽  
pp. 629
Author(s):  
Fu Wang ◽  
Dengjun Gu ◽  
Anqi Chen
Keyword(s):  
Traffic Congestion ◽  
Calculation Model ◽  
Combined Model ◽  
Average Delay ◽  
Factors Affecting ◽  
Calculated Length ◽  
Comparison Results ◽  
Main Factors ◽  
Traffic Operation ◽  
Operation Characteristics

Many cities have built expressways to alleviate traffic congestion, among which elevated expressways are the most common form. However, traffic congestion still occurs frequently in the connecting section between the ramp of expressway and the ground intersection. Based on the field traffic survey data, the traffic operation characteristics of vehicles in the connecting section and the main factors affecting the length of the connecting section are analyzed. A combined model for calculating the length of the connecting section between ramp of urban expressway and intersection is proposed. VISSIM is used to simulate the traffic flow under the current and calculated length of the connecting section. The comparison results show that under the calculation length, the travel time, average delay, parking time and queue length are reduced to varying degrees, which verifies the rationality of the calculation model.

Travel mode recognition of urban residents using mobile phone data and MapAPI

2021 ◽  
pp. 239980832098300
Author(s):  
Zhenghong Peng ◽  
Guikai Bai ◽  
Hao Wu ◽  
Lingbo Liu ◽  
Yang Yu
Keyword(s):  
Urban Planning ◽  
Mobile Phone ◽  
Traffic Flow ◽  
Road Traffic ◽  
Urban Traffic ◽  
Phone Call ◽  
Traffic Information ◽  
Mobile Phone Data ◽  
Urban Residents ◽  
Travel Mode

Obtaining the time and space features of the travel of urban residents can facilitate urban traffic optimization and urban planning. As traditional methods often have limited sample coverage and lack timeliness, the application of big data such as mobile phone data in urban studies makes it possible to rapidly acquire the features of residents’ travel. However, few studies have attempted to use them to recognize the travel modes of residents. Based on mobile phone call detail records and the Web MapAPI, the present study proposes a method to recognize the travel mode of urban residents. The main processes include: (a) using DBSCAN clustering to analyze each user’s important location points and identify their main travel trajectories; (b) using an online map API to analyze user’s means of travel; (c) comparing the two to recognize the travel mode of residents. Applying this method in a GIS platform can further help obtain the traffic flow of various means, such as walking, driving, and public transit, on different roads during peak hours on weekdays. Results are cross-checked with other data sources and are proven effective. Besides recognizing travel modes of residents, the proposed method can also be applied for studies such as travel costs, housing–job balance, and road traffic pressure. The study acquires about 6 million residents’ travel modes, working place and residence information, and analyzes the means of travel and traffic flow in the commuting of 3 million residents using the proposed method. The findings not only provide new ideas for the collection and application of urban traffic information, but also provide data support for urban planning and traffic management.

Relative consumption, relative wealth, and long-run growth: when and why is the standard analysis prone to incorrect conclusions?

2021 ◽  
pp. 1-25
Author(s):  
Franz X. Hof ◽  
Klaus Prettner
Keyword(s):  
Growth Rate ◽  
Traditional Approach ◽  
Total Change ◽  
Relative Consumption ◽  
Fundamental Factor ◽  
Elasticity Of Intertemporal Substitution ◽  
Relative Wealth ◽  
Novel Approach ◽  
Long Run ◽  
Two Parameters

Abstract We employ a novel approach for analyzing the effects of relative consumption and relative wealth preferences on economic growth. In the pertinent literature, these effects are usually assessed by examining the dependence of the growth rate on the two parameters of the utility function that seem to measure the strength of the relative consumption and the relative wealth motives. Applying our fundamental factor approach, we identify specifications in which the traditional approach yields incorrect qualitative conclusions. The problematic specifications have the common unpleasant property that the parameter that seems to determine the strength of the relative consumption motive actually also affects the elasticity of intertemporal substitution of absolute consumption (and the strength of the relative wealth motive). Since the standard approach is unaware of the additional effect(s), it attributes the total change in the growth rate incorrectly to the change in the strength of the relative consumption motive.

scholarly journals PATTERN RECOGNITION BASED SPEED FORECASTING METHODOLOGY FOR URBAN TRAFFIC NETWORK

Transport ◽  
2018 ◽  
Vol 33 (4) ◽  
pp. 959-970 ◽  
Author(s):  
Tamás Tettamanti ◽  
Alfréd Csikós ◽  
Krisztián Balázs Kis ◽  
Zsolt János Viharos ◽  
István Varga
Keyword(s):  
Neural Network ◽  
Input Data ◽  
Road Traffic ◽  
Urban Traffic ◽  
Traffic Network ◽  
Data Handling ◽  
Urban Road ◽  
Traffic Sensors ◽  
Network Training ◽  
Artificial Neural Network Ann

A full methodology of short-term traffic prediction is proposed for urban road traffic network via Artificial Neural Network (ANN). The goal of the forecasting is to provide speed estimation forward by 5, 15 and 30 min. Unlike similar research results in this field, the investigated method aims to predict traffic speed for signalized urban road links and not for highway or arterial roads. The methodology contains an efficient feature selection algorithm in order to determine the appropriate input parameters required for neural network training. As another contribution of the paper, a built-in incomplete data handling is provided as input data (originating from traffic sensors or Floating Car Data (FCD)) might be absent or biased in practice. Therefore, input data handling can assure a robust operation of speed forecasting also in case of missing data. The proposed algorithm is trained, tested and analysed in a test network built-up in a microscopic traffic simulator by using daily course of real-world traffic.

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 A NOVEL APPROACH TO OPTIMIZE THE RIDESHARING PROBLEM USING GENETIC ALGORITHM

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 875-878
Author(s):  
S. Rangriz ◽  
M. Davoodi ◽  
J. Saberian
Keyword(s):  
Genetic Algorithm ◽  
Air Pollution ◽  
Public Transportation ◽  
Noise Pollution ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Traffic Jam ◽  
Novel Approach ◽  
Proposed Model ◽  
Public Transportation Systems

Abstract. The enormous increase in the number of vehicles in the cities makes plenty of problems including air pollution, noise pollution, and traffic jam. Overcoming these annoying issues needs a significant plan in urban management such as using modern techniques in public transportation systems. Sharing either cars or taxies is one of the most interesting ways that has been used in some countries recently. In this phenomenon, 2 or 3 people use other’s car or taxi. In this article, an innovative approach to share taxies is proposed, and it uses a Genetic Algorithm to determine the placement of travelers in taxies. Therefore, some taxis will be switched off, and this helps to decrease urban traffic jam in cities. The results present that the proposed model turns off 69.8 % of taxies, and also 27.8 % of them carry more than one passenger; hence, this confirms the performance of the proposed model.

scholarly journals EFFECTS OF THE RAINSTORM ON URBAN ROAD TRAFFIC SPEED — A CASE STUDY OF SHENZHEN, CHINA

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 71-75 ◽  
Author(s):  
Q. Li ◽  
X. Hao ◽  
W. Wang ◽  
A. Wu ◽  
Z. Xie
Keyword(s):  
Traffic Management ◽  
Road Traffic ◽  
Urban Traffic ◽  
Gps Tracking ◽  
Shenzhen City ◽  
Adverse Weather ◽  
Stormy Weather ◽  
Wide Scale ◽  
Traffic Speed ◽  
The Impact

The adverse weather may significantly impact urban traffic speed and travel time. Understanding the influence of the rainstorm to urban traffic speed is of great importance for traffic management under stormy weather. This study aims to investigate the impact of rainfall intensity on traffic speed in the Shenzhen (China) during the period 1 July 2015–31 August 2016. The analysis was carried out for five 1-h periods on weekdays during the morning periods (6:00 AM–11:00 AM). Taxi-enabled GPS tracking data obtained from Shenzhen city are used in the analysis. There are several findings in this study. Firstly, nearly half of the roads are significantly affected by the rainstorm. Secondly, the proportion of positive correlated roads is about 35 %, but there still are some roads with uncorrelated traffic speed variation rates (SVR) and rainfall intensities. Thirdly, the impact of the rainstorm on traffic speed is not homogeneous but with obvious spatial difference. This research provides useful information that can be used in traffic management on a city-wide scale under stormy weather.

scholarly journals Combining VR Visualization and Sonification for Immersive Exploration of Urban Noise Standards

2019 ◽  
Vol 3 (2) ◽  
pp. 34 ◽  
Author(s):  
Markus Berger ◽  
Ralf Bill
Keyword(s):  
Real Time ◽  
Sound Propagation ◽  
Road Traffic ◽  
Expert Knowledge ◽  
Low Cost ◽  
Traffic Noise ◽  
Urban Traffic ◽  
Road Traffic Noise ◽  
Common Noise ◽  
Noise Assessment

Urban traffic noise situations are usually visualized as conventional 2D maps or 3D scenes. These representations are indispensable tools to inform decision makers and citizens about issues of health, safety, and quality of life but require expert knowledge in order to be properly understood and put into context. The subjectivity of how we perceive noise as well as the inaccuracies in common noise calculation standards are rarely represented. We present a virtual reality application that seeks to offer an audiovisual glimpse into the background workings of one of these standards, by employing a multisensory, immersive analytics approach that allows users to interactively explore and listen to an approximate rendering of the data in the same environment that the noise simulation occurs in. In order for this approach to be useful, it should manage complicated noise level calculations in a real time environment and run on commodity low-cost VR hardware. In a prototypical implementation, we utilized simple VR interactions common to current mobile VR headsets and combined them with techniques from data visualization and sonification to allow users to explore road traffic noise in an immersive real-time urban environment. The noise levels were calculated over CityGML LoD2 building geometries, in accordance with Common Noise Assessment Methods in Europe (CNOSSOS-EU) sound propagation methods.

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