scholarly journals Computing Spatiotemporal Accessibility to Urban Opportunities: A Reliable Space-Time Prism Approach in Uncertain Urban Networks

Computation ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 51
Author(s):  
Alireza Sahebgharani ◽  
Mahmoud Mohammadi ◽  
Hossein Haghshenas
Keyword(s):  
Travel Time ◽  
Traffic Congestion ◽  
Probability Distributions ◽  
Space Time ◽  
Unified Framework ◽  
Urban Networks ◽  
Street Networks ◽  
Normal Probability ◽  
Significant Difference ◽  
Temporal Dimensions

Space-time prism (STP) is a comprehensive and powerful model for computing accessibility to urban opportunities. Despite other types of accessibility measures, STP models capture spatial and temporal dimensions in a unified framework. Classical STPs assume that travel time in street networks is a deterministic and fixed variable. However, this assumption is in contradiction with the uncertain nature of travel time taking place due to fluctuations and traffic congestion. In addition, travel time in street networks mostly follows non-normal probability distributions which are not modeled in the structure of classical STPs. Neglecting travel time uncertainty and disregarding different types of probability distributions cause unrealistic accessibility values in STP-based metrics. In this way, this paper proposes a spatiotemporal accessibility model by extending classical STPs to non-normal stochastic urban networks and blending this modified STP with the attractiveness of urban opportunities. The elaborated model was applied on the city of Isfahan to assess the accessibility of its traffic analysis zones (TAZs) to Kowsar discount retail markets. A significant difference was found between the results of accessibility values in normally and non-normally distributed networks. In addition, the results show that the northern TAZs had larger accessibility level compared to the southern ones.

scholarly journals MODELING TRANSPORT FLOWS UNDER CONDITIONS OF A LOADED STREET-ROAD NETWORK

2020 ◽  
Vol 2020 (1) ◽  
pp. 165-165
Author(s):  
Ol'ga Lebedeva
Keyword(s):  
Travel Time ◽  
Experimental Research ◽  
Traffic Congestion ◽  
Road Network ◽  
Supply And Demand ◽  
Route Selection ◽  
Traffic Flows ◽  
Urban Networks ◽  
The Road ◽  
Modeling Transport

Managing urban networks during traffic congestion requires the use of a dynamic model that allows you to simulate real situations with traffic flows with long queues and responses. To conduct experimental research in this area, it is possible to use a mesoscopic system for simulating traffic with calibration and taking into account the characteristics of the road. All supply and demand parameters (use of detectors, travel time) must be calibrated at the same time. In this study, calibration was performed using the route selection model, given overlapping routes

scholarly journals Values of Travel Time for Recreational Trips under Different Behavioural Rules

2021 ◽  
Vol 13 (12) ◽  
pp. 6831
Author(s):  
Rosa Marina González ◽  
Concepción Román ◽  
Ángel Simón Marrero
Keyword(s):  
Travel Time ◽  
National Parks ◽  
Traffic Congestion ◽  
National Park ◽  
Revealed Preference ◽  
Discrete Choice Models ◽  
Model Specification ◽  
Regret Minimization ◽  
Random Regret Minimization

In this study, discrete choice models that combine different behavioural rules are estimated to study the visitors’ preferences in relation to their travel mode choices to access a national park. Using a revealed preference survey conducted on visitors of Teide National Park (Tenerife, Spain), we present a hybrid model specification—with random parameters—in which we assume that some attributes are evaluated by the individuals under conventional random utility maximization (RUM) rules, whereas others are evaluated under random regret minimization (RRM) rules. We then compare the results obtained using exclusively a conventional RUM approach to those obtained using both RUM and RRM approaches, derive monetary valuations of the different components of travel time and calculate direct elasticity measures. Our results provide useful instruments to evaluate policies that promote the use of more sustainable modes of transport in natural sites. Such policies should be considered as priorities in many national parks, where negative transport externalities such as traffic congestion, pollution, noise and accidents are causing problems that jeopardize not only the sustainability of the sites, but also the quality of the visit.

scholarly journals Measuring Recurrent and Nonrecurrent Traffic Congestion

2003 ◽  
Vol 1856 (1) ◽  
pp. 118-124 ◽  
Author(s):  
Alexander Skabardonis ◽  
Pravin Varaiya ◽  
Karl F. Petty
Keyword(s):  
Los Angeles ◽  
Travel Time ◽  
San Francisco ◽  
Traffic Congestion ◽  
Real Life ◽  
Time Variability ◽  
Loop Detectors ◽  
Bay Area ◽  
Freeway Corridors ◽  
Travel Time Variability

A methodology and its application to measure total, recurrent, and nonrecurrent (incident related) delay on urban freeways are described. The methodology used data from loop detectors and calculated the average and the probability distribution of delays. Application of the methodology to two real-life freeway corridors in Los Angeles, California, and one in the San Francisco, California, Bay Area, indicated that reliable measurement of congestion also should provide measures of uncertainty in congestion. In the three applications, incident-related delay was found to be 13% to 30% of the total congestion delay during peak periods. The methodology also quantified the congestion impacts on travel time and travel time variability.

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.

Spatiotemporal pattern mining of drought in the last 40 years in China based on the SPEI index and space-time cube

2021 ◽  
Author(s):  
Dehe Xu ◽  
Qi Zhang ◽  
Yan Ding ◽  
De Zhang
Keyword(s):  
North China ◽  
Pattern Mining ◽  
Space Time ◽  
Central China ◽  
Spatiotemporal Pattern ◽  
Severe Drought ◽  
Monthly Precipitation ◽  
Hotspot Analysis ◽  
The Past ◽  
Significant Difference

AbstractDrought is a common natural disaster that greatly affects the crop yield and water supply in China. However, the spatiotemporal characteristics of drought in China are not well understood. This paper explores the spatial and temporal distributions of droughts in China over the past 40 years using multiscale standardized precipitation evapotranspiration index (SPEI) values calculated by monthly precipitation and temperature data from 612 meteorological stations in China from 1980 to 2019 and combines the space-time cube (STC), Mann-Kendall (M-K) test, emerging spatiotemporal hotspot analysis, spatiotemporal clustering and local outliers for the analysis. The results were as follows: 1) the drought frequency and STC show that there is a significant difference in the spatiotemporal distribution of drought in China, with the most severe drought in Northwest China, followed by the western part of Southwest China and the northern part of North China. 2) The emerging spatiotemporal hotspot analysis of SPEI6 over the past 40 years reveals two cold spots in subregion 4, indicating that future droughts in the region will be more severe. 3) A local outlier analysis of the multiscale SPEI yields a low-low outlier in western North China, indicating relatively more severe year-round drought in this area than in other areas. The low-high outlier in central China indicates that this region was not dry in the past and that drought will become more severe in this region in the future.

scholarly journals Minimizing Traffic Congestion Through Continuous-Time Route Reservations With Travel Time Predictions

2019 ◽  
Vol 4 (1) ◽  
pp. 141-153 ◽  
Author(s):  
Charalambos Menelaou ◽  
Stelios Timotheou ◽  
Panayiotis Kolios ◽  
Christos G. Panayiotou ◽  
Marios M. Polycarpou
Keyword(s):  
Travel Time ◽  
Continuous Time ◽  
Traffic Congestion

scholarly journals Estimates of Economic Cost of Congestion Travel Time Delay Between Onne-Seaport and Eleme-Junction Traffic Corridor

2020 ◽  
Vol 11 (2) ◽  
pp. 33-43
Author(s):  
Theophilus C. Nwokedi ◽  
Lazarus I. Okoroji ◽  
Ifiok Okonko ◽  
Obed C. Ndikom
Keyword(s):  
Time Delay ◽  
Travel Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Oil And Gas ◽  
Economic Cost ◽  
Oil And Gas Industry ◽  
Research Approach ◽  
Traffic Corridor ◽  
Output Losses

AbstractTravelers along the Onne-seaport to Eleme-junction road corridor in the hub of the oil and gas industry in Port-Harcourt, Nigeria, have continued to experience very serious traffic congestion travel time delays, culminating into loss of man-hours and declining productivity. This study estimated the economic cost of traffic congestion travel time delay along the corridor, with a view to providing economic justification for developing traffic management policies and road infrastructure, to remedy it. A mixed research approach was adopted in which data was sourced through field survey and from secondary sources. The gross output model was used to estimate the output losses occasioned by productive time losses related to traffic congestion. The study established that the average daily traffic congestion travel time delay along the traffic corridor by travelers in trucks, car, bus and taxi modes are 104.17 minutes, 46.60 minutes, 58.5 minutes and 56.4 minutes respectively. The estimated daily aggregate economic cost of output losses associated with traffic congestion time delay on the corridor is 46049809.8 naira (210923.5USD) for all modes. This justifies any investment in traffic congestion remedial strategies along the route.

scholarly journals ANALISIS TINGKAT KESESUAIAN DARI KLASIFIKASI KEPADATAN LALU LINTAS DAN WAKTU TEMPUH GOOGLE MAPS

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Laksita Amelia Paramesti ◽  
Dedi Atunggal
Keyword(s):  
Travel Time ◽  
Statistical Tests ◽  
Statistical Test ◽  
Traffic Information ◽  
Actual Condition ◽  
Traffic Density ◽  
Traffic Classification ◽  
Google Maps ◽  
Traffic Condition ◽  
Significant Difference

 Traffic congestion is one of problem that occur in big cities, therefore people need traffic information to determine traffic condition. One of many applications that provides traffic information is Google Maps. From the information generated, there are insuitability between google maps’s traffic update and travel time with the actual condition. So the aim of this study is to analyze the suitability level of traffic density classification and google maps travel time. Based on the speed range by Google, the level of suitability can be determined, while the google maps travel time is done by statistical tests. The statistical test used is a statistical test of two parameters using table t with 95% confidence level. The results of this study indicate that the level of suitability of the traffic classification only reaches 35%. The low level of suitability is caused by network latency. While information on google maps travel time does not have a significant difference in actual time.

Freight Vehicle Travel Time Analysis: A Case Study of Birgunj Nagdhunga Corridor

2021 ◽  
Vol 08 (02) ◽  
pp. 1-13
Author(s):  
Abhishek Jha ◽  
Keyword(s):  
Travel Time ◽  
Traffic Congestion ◽  
License Plate ◽  
Monitoring Method ◽  
Factors Affecting ◽  
Average Travel Time ◽  
Major Factors ◽  
Vehicle Travel Time ◽  
Freight Vehicles

This study covers the freight vehicle, which clears the custom clearance process for Kathmandu and transports the same goods to Kathmandu from Birgunj. In this study average travel time for freight vehicles from Birgunj to Nagdhunga has been studied, along with the factors affecting the travel time from Birgunj to Nagdhunga. License plate monitoring method of the freight vehicles was done to find the average travel time and a questionnaire survey was done to identify the factors affecting travel time of the freight vehicle. The travel time from Birgunj to Nagdhunga is different for different types of, vehicle and good. The fastest average travel time is of fixed container of 40 feet size with 23.2 hours and longest average time is for fixed container of 20 feet size with 28.95 hours. The average travel time for non-degradable goods is 26.5 hours and for degradable goods is 22.38 hours. Major factors affecting the travel time are traffic congestion along the route, bad road condition along the route and hilly road with sharp bends, turns and grade.

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