Impact of Major Road Supply on Individual Travel Time Expenditure: An Exploration with a 30-Year Variation of Infrastructure and Travel

2018 ◽  
Vol 2672 (3) ◽  
pp. 56-68
Author(s):  
Ryosuke Abe ◽  
Kay W. Axhausen
Keyword(s):  
Travel Time ◽  
Large Scale ◽  
Travel Demand ◽  
Road Traffic ◽  
Land Development ◽  
Transportation Infrastructure ◽  
Major Road ◽  
Birth Cohorts ◽  
Data Set ◽  
The Impact

This study estimates the impact of major road supply on individual travel time expenditures (TTEs) using data that cover 30-year variations in transportation infrastructure and travel behavior. The impacts of the supply of road and rail infrastructure are estimated with a data set that combines records of large-scale household travel surveys in the Tokyo metropolitan area conducted in 1978, 1988, 1998, and 2008. Linear and Tobit models of individual TTEs are estimated by following the behavior of birth cohorts over the 30-year period. The models incorporate the changes in transportation infrastructure, measured as lane kilometers of two levels of major road stock and vehicle kilometers of urban rail service. The results show significant negative effects of lane kilometers for higher-level and lower-level major roads on the TTEs for all travel purposes and for commuting, after controlling for socioeconomic backgrounds and generations of individuals. This study discusses that, in Tokyo, the estimated effect is more likely to reflect the effect of a major road network per se on individual TTEs than the (indirect) effect of major road supply on individual TTEs working through land development activities (i.e., induced car travel demand). For example, the caveat is that actual road investment decisions still need to consider the induced component of road traffic in addition to the (direct) effect that is estimated in this study.

scholarly journals Understanding vehicular routing behavior with location-based service data

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Yanyan Xu ◽  
Riccardo Di Clemente ◽  
Marta C. González
Keyword(s):  
Travel Time ◽  
Large Scale ◽  
Census Data ◽  
The United States ◽  
Location Based Services ◽  
Smartphone Applications ◽  
United States Census ◽  
Data Set ◽  
High Resolution Data ◽  
The Impact

AbstractProperly extracting patterns of individual mobility with high resolution data sources such as the one extracted from smartphone applications offers important opportunities. Potential opportunities not offered by call detailed records (CDRs), which offer resolutions triangulated from antennas, are route choices, travel modes detection and close encounters. Nowadays, there is not a standard and large scale data set collected over long periods that allows us to characterize these. In this work we thoroughly examine the use of data from smartphone applications, also referred to as location-based services (LBS) data, to extract and understand the vehicular route choice behavior. Taking the Dallas-Fort Worth metroplex as an example, we first extract the vehicular trips with simple rules and reconstruct the origin-destination matrix by coupling the extracted vehicular trips of the active LBS users and the United States census data. We then present a method to derive the commonly used routes by individuals from the LBS traces with varying sample rate intervals. We further inspect the relation between the number of routes and the trip characteristics, including the departure time, trip length and travel time. Specifically, we consider the travel time index and buffer index for the LBS users taking different number of routes. Empirical results demonstrate that during the peak hours, travelers tend to reduce the impact of traffic congestion by taking alternative routes. Overall, the proposed data analysis framework is cost-effective to treat sparse data generated from the use of smartphones to inform routing behavior. The potential in practice is to inform demand management strategies, by targeting individual users while generating large scale estimates of congestion mitigation.

Demographic Characterization of Anonymous Trace Travel Data

2015 ◽  
Vol 2526 (1) ◽  
pp. 19-28 ◽  
Author(s):  
Joshua Auld ◽  
Abolfazl (Kouros) Mohammadian ◽  
Marcelo Simas Oliveira ◽  
Jean Wolf ◽  
William Bachman
Keyword(s):  
Test Data ◽  
Large Scale ◽  
Travel Demand ◽  
Null Model ◽  
Demographic Characteristics ◽  
Travel Pattern ◽  
Data Set ◽  
Trace Data ◽  
Demographic Models ◽  
Pattern Information

Research was undertaken to determine whether demographic characteristics of individual travelers could be derived from travel pattern information when no information about the individual was available. This question is relevant in the context of anonymously collected travel information, such as cell phone traces, when used for travel demand modeling. Determining the demographics of a traveler from such data could partially obviate the need for large-scale collection of travel survey data, depending on the purpose for which the data were to be used. This research complements methodologies used to identify activity stops, purposes, and mode types from raw trace data and presumes that such methods exist and are available. The paper documents the development of procedures for taking raw activity streams estimated from GPS trace data and converting these into activity travel pattern characteristics that are then combined with basic land use information and used to estimate various models of demographic characteristics. The work status, education level, age, and license possession of individuals and the presence of children in their households were all estimated successfully with substantial increases in performance versus null model expectations for both training and test data sets. The gender, household size, and number of vehicles proved more difficult to estimate, and performance was lower on the test data set; these aspects indicate overfitting in these models. Overall, the demographic models appear to have potential for characterizing anonymous data streams, which could extend the usability and applicability of such data sources to the travel demand context.

scholarly journals The Midlatitude Continental Convective Clouds Experiment (MC3E) sounding network: operations, processing and analysis

2015 ◽  
Vol 8 (1) ◽  
pp. 421-434 ◽  
Author(s):  
M. P. Jensen ◽  
T. Toto ◽  
D. Troyan ◽  
P. E. Ciesielski ◽  
D. Holdridge ◽  
...  
Keyword(s):  
Large Scale ◽  
Scale Model ◽  
Data Sets ◽  
Central Plains ◽  
Data Set ◽  
Convective Systems ◽  
Convective Clouds ◽  
Quality Checks ◽  
Network Operations ◽  
The Impact

Abstract. The Midlatitude Continental Convective Clouds Experiment (MC3E) took place during the spring of 2011 centered in north-central Oklahoma, USA. The main goal of this field campaign was to capture the dynamical and microphysical characteristics of precipitating convective systems in the US Central Plains. A major component of the campaign was a six-site radiosonde array designed to capture the large-scale variability of the atmospheric state with the intent of deriving model forcing data sets. Over the course of the 46-day MC3E campaign, a total of 1362 radiosondes were launched from the enhanced sonde network. This manuscript provides details on the instrumentation used as part of the sounding array, the data processing activities including quality checks and humidity bias corrections and an analysis of the impacts of bias correction and algorithm assumptions on the determination of convective levels and indices. It is found that corrections for known radiosonde humidity biases and assumptions regarding the characteristics of the surface convective parcel result in significant differences in the derived values of convective levels and indices in many soundings. In addition, the impact of including the humidity corrections and quality controls on the thermodynamic profiles that are used in the derivation of a large-scale model forcing data set are investigated. The results show a significant impact on the derived large-scale vertical velocity field illustrating the importance of addressing these humidity biases.

scholarly journals Continuous high-resolution midlatitude-belt simulations for July–August 2013 with WRF

2017 ◽  
Vol 10 (5) ◽  
pp. 2031-2055 ◽  
Author(s):  
Thomas Schwitalla ◽  
Hans-Stefan Bauer ◽  
Volker Wulfmeyer ◽  
Kirsten Warrach-Sagi
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Temperature Fields ◽  
Surface Model ◽  
Limited Area ◽  
Data Set ◽  
Latitude Belt ◽  
Simulated Precipitation ◽  
The Impact

Abstract. Increasing computational resources and the demands of impact modelers, stake holders, and society envision seasonal and climate simulations with the convection-permitting resolution. So far such a resolution is only achieved with a limited-area model whose results are impacted by zonal and meridional boundaries. Here, we present the setup of a latitude-belt domain that reduces disturbances originating from the western and eastern boundaries and therefore allows for studying the impact of model resolution and physical parameterization. The Weather Research and Forecasting (WRF) model coupled to the NOAH land–surface model was operated during July and August 2013 at two different horizontal resolutions, namely 0.03 (HIRES) and 0.12° (LOWRES). Both simulations were forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis data at the northern and southern domain boundaries, and the high-resolution Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data at the sea surface.The simulations are compared to the operational ECMWF analysis for the representation of large-scale features. To analyze the simulated precipitation, the operational ECMWF forecast, the CPC MORPHing (CMORPH), and the ENSEMBLES gridded observation precipitation data set (E-OBS) were used as references.Analyzing pressure, geopotential height, wind, and temperature fields as well as precipitation revealed (1) a benefit from the higher resolution concerning the reduction of monthly biases, root mean square error, and an improved Pearson skill score, and (2) deficiencies in the physical parameterizations leading to notable biases in distinct regions like the polar Atlantic for the LOWRES simulation, the North Pacific, and Inner Mongolia for both resolutions.In summary, the application of a latitude belt on a convection-permitting resolution shows promising results that are beneficial for future seasonal forecasting.

scholarly journals Personal Exposure to BC, PM and NO2 in the Paris Region Measured by Portable Sensors Worn by Volunteers

Toxics ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 33
Author(s):  
Baptiste Languille ◽  
Valérie Gros ◽  
Bonnaire Nicolas ◽  
Cécile Honoré ◽  
Anne Kaufmann ◽  
...  
Keyword(s):  
Large Scale ◽  
Road Traffic ◽  
Personal Exposure ◽  
Portable Sensors ◽  
Promising Solution ◽  
Field Campaigns ◽  
Paris Region ◽  
The Impact ◽  
First Time ◽  
Indoor And Outdoor

Portable sensors have emerged as a promising solution for personal exposure (PE) measurement. For the first time in Île-de-France, PE to black carbon (BC), particulate matter (PM), and nitrogen dioxide (NO2) was quantified based on three field campaigns involving 37 volunteers from the general public wearing the sensors all day long for a week. This successful deployment demonstrated its ability to quantify PE on a large scale, in various environments (from dense urban to suburban, indoor and outdoor) and in all seasons. The impact of the visited environments was investigated. The proximity to road traffic (for BC and NO2), as well as cooking activities and tobacco smoke (for PM), made significant contributions to total exposure (up to 34%, 26%, and 44%, respectively), even though the time spent in these environments was short. Finally, even if ambient outdoor levels played a role in PE, the prominent impact of the different environments suggests that traditional ambient monitoring stations is not a proper surrogate for PE quantification.

scholarly journals EVALUATING THE EFFECT OF HEAVY VEHICLES ON TRAFFIC PARAMETERS BY USING HEAVY VEHICLE FACTOR

2018 ◽  
Vol 6 (4) ◽  
pp. 95-104
Author(s):  
Parthkumar Patel ◽  
H.R. Varia
Keyword(s):  
Travel Time ◽  
Traffic Flow ◽  
Road Traffic ◽  
Freight Transport ◽  
Heavy Vehicle ◽  
Mixed Traffic ◽  
Heavy Vehicles ◽  
Highway Traffic ◽  
Ideal Situation ◽  
The Impact

Safe, convenient and timely transportation of goods and passengers is necessary for development of nation. After independence road traffic is increased manifold in India. Modal share of freight transport is shifted from Railway to roadways in India. Road infrastructures continuously increased from past few decades but there is still need for new roads to be build and more than three forth of the roads having mixed traffic plying on it. The impact of freight vehicles on highway traffic is enormous as they are moving with slow speeds. Nature of traffic flow is dependent on various traffic parameters such as speed, density, volume and travel time etc. As per ideal situation these traffic parameters should remain intact, but it is greatly affected by presence of heavy vehicle in mixed traffic due to Svehicles plying on two lane roads. Heavy vehicles affect the traffic flow because of their length and size and acceleration/deceleration characteristics.  This study is aimed to analyse the impact of heavy vehicles on traffic parameters.

scholarly journals Six years of total ozone column measurements from SCIAMACHY nadir observations

2009 ◽  
Vol 2 (1) ◽  
pp. 87-98 ◽  
Author(s):  
C. Lerot ◽  
M. Van Roozendael ◽  
J. van Geffen ◽  
J. van Gent ◽  
C. Fayt ◽  
...  
Keyword(s):  
Cross Sections ◽  
Total Ozone ◽  
Large Scale ◽  
European Space Agency ◽  
Data Sets ◽  
Data Set ◽  
Ozone Data ◽  
Space Agency ◽  
German Aerospace ◽  
The Impact

Abstract. Total O3 columns have been retrieved from six years of SCIAMACHY nadir UV radiance measurements using SDOAS, an adaptation of the GDOAS algorithm previously developed at BIRA-IASB for the GOME instrument. GDOAS and SDOAS have been implemented by the German Aerospace Center (DLR) in the version 4 of the GOME Data Processor (GDP) and in version 3 of the SCIAMACHY Ground Processor (SGP), respectively. The processors are being run at the DLR processing centre on behalf of the European Space Agency (ESA). We first focus on the description of the SDOAS algorithm with particular attention to the impact of uncertainties on the reference O3 absorption cross-sections. Second, the resulting SCIAMACHY total ozone data set is globally evaluated through large-scale comparisons with results from GOME and OMI as well as with ground-based correlative measurements. The various total ozone data sets are found to agree within 2% on average. However, a negative trend of 0.2–0.4%/year has been identified in the SCIAMACHY O3 columns; this probably originates from instrumental degradation effects that have not yet been fully characterized.

scholarly journals Tropical troposphere to stratosphere transport of carbon monoxide and long-lived trace species in the Chemical Lagrangian Model of the Stratosphere (CLaMS)

2014 ◽  
Vol 7 (4) ◽  
pp. 5087-5139 ◽  
Author(s):  
R. Pommrich ◽  
R. Müller ◽  
J.-U. Grooß ◽  
P. Konopka ◽  
F. Ploeger ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Large Scale ◽  
Lower Stratosphere ◽  
Lagrangian Model ◽  
Quasi Biennial Oscillation ◽  
Data Set ◽  
Model Version ◽  
The Tropics ◽  
The Impact ◽  
Good Agreement

Abstract. Variations in the mixing ratio of trace gases of tropospheric origin entering the stratosphere in the tropics are of interest for assessing both troposphere to stratosphere transport fluxes in the tropics and the impact of these transport fluxes on the composition of the tropical lower stratosphere. Anomaly patterns of carbon monoxide (CO) and long-lived tracers in the lower tropical stratosphere allow conclusions about the rate and the variability of tropical upwelling to be drawn. Here, we present a simplified chemistry scheme for the Chemical Lagrangian Model of the Stratosphere (CLaMS) for the simulation, at comparatively low numerical cost, of CO, ozone, and long-lived trace substances (CH4, N2O, CCl3F (CFC-11), CCl2F2 (CFC-12), and CO2) in the lower tropical stratosphere. For the long-lived trace substances, the boundary conditions at the surface are prescribed based on ground-based measurements in the lowest model level. The boundary condition for CO in the free troposphere is deduced from MOPITT measurements (at ≈ 700–200 hPa). Due to the lack of a specific representation of mixing and convective uplift in the troposphere in this model version, enhanced CO values, in particular those resulting from convective outflow are underestimated. However, in the tropical tropopause layer and the lower tropical stratosphere, there is relatively good agreement of simulated CO with in-situ measurements (with the exception of the TROCCINOX campaign, where CO in the simulation is biased low ≈ 10–20 ppbv). Further, the model results are of sufficient quality to describe large scale anomaly patterns of CO in the lower stratosphere. In particular, the zonally averaged tropical CO anomaly patterns (the so called "tape recorder" patterns) simulated by this model version of CLaMS are in good agreement with observations. The simulations show a too rapid upwelling compared to observations as a consequence of the overestimated vertical velocities in the ERA-interim reanalysis data set. Moreover, the simulated tropical anomaly patterns of N2O are in good agreement with observations. In the simulations, anomaly patterns for CH4 and CFC-11 were found to be consistent with those of N2O; for all long-lived tracers, positive anomalies are simulated because of the enhanced tropical upwelling in the easterly phase of the quasi-biennial oscillation.

Does China’s transportation infrastructure have an impact on employment in the service sector?

Kybernetes ◽  
2020 ◽  
Vol 49 (11) ◽  
pp. 2737-2753
Author(s):  
Hui Wang ◽  
Meiqing Zhang
Keyword(s):  
Large Scale ◽  
Service Industry ◽  
Spillover Effect ◽  
Transportation Infrastructure ◽  
Content Type ◽  
Inland Waterways ◽  
Spatial Spillover ◽  
Positive Effects ◽  
The Impact ◽  
Spatial Spillover Effect

Purpose The large-scale construction of China’s transportation infrastructure has driven the flow of elements between regions, which has provided convenient conditions for the accumulation of advantageous resources. Design/methodology/approach Based on the panel data of 31 provinces in China in the past 2003-2017 years, this paper applies the spatial econometric model and partial differential method and empirically analyzes the spatial spillover effect of transportation infrastructure on employment in the service industry under four spatial weighting matrices. Findings The results show that for every 1 per cent increase in the level of transportation infrastructure, the employment density of the service industry in the region can be increased by 0.1274 per cent. It is worth noting that roads promote the employment of the service industry more than railways and inland waterways. However, inland waterways have not shown positive effects. The results on spatial spillover of transportation infrastructure indicate that railway has obvious promotion effect on the employment level of service industry in the surrounding area, while the highway has hindered the effect. The spatial spillover effect of inland waterway is not obvious. Originality/value The value of this paper is to consider the impact of China’s transportation infrastructure on employment in a particular industry, especially in the service industry. The research will help to provide empirical evidence for policymakers. The government needs to invest and build transportation infrastructure based on the stage and development potential of the employment development of the regional service industry.

scholarly journals Traffic Simulation Analysis on Running Speed in a Connected Vehicles Environment

2019 ◽  
Vol 16 (22) ◽  
pp. 4373 ◽  
Author(s):  
Bin Yu ◽  
Miyi Wu ◽  
Shuyi Wang ◽  
Wen Zhou
Keyword(s):  
Travel Time ◽  
Delay Time ◽  
Traffic Simulation ◽  
Road Traffic ◽  
Simulation Analysis ◽  
Simulation Software ◽  
Connected Vehicles ◽  
Running Speed ◽  
Traffic Characteristics ◽  
The Impact

Connected vehicles (CVs) exchange a variety of information instantly with surrounding vehicles and traffic facilities, which could smooth traffic flow significantly. The objective of this paper is to analyze the effect of CVs on running speed. This study compared the delay time, travel time, and running speed in the normal and the connected states, respectively, through VISSIM (a traffic simulation software developed by PTV company in German). The optimization speed model was established to simulate the decision-makings of CVs in MATLAB, considering the parameters of vehicle distance, average speed, and acceleration, etc. After the simulation, the vehicle information including speed, travel time, and delay time under the normal and the connected states were compared and evaluated, and the influence of different CV rates on the results was analyzed. In a two-lane arterial road, running speed in the connected state increase by 4 km/h, and the total travel time and delay time decrease by 5.34% and 16.76%, respectively, compared to those in the normal state. The optimal CV market penetration rate related to running speed and delay time is 60%. This simulation-based study applies user-defined lane change and lateral behavior rules, and takes different CV rates into consideration, which is more reliable and practical to estimate the impact of CV on road traffic characteristics.

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