Two Minutes per Person per Day Each Year

2005 ◽  
Vol 1917 (1) ◽  
pp. 45-53 ◽  
Author(s):  
Lavenia Toole-Holt ◽  
Steven E. Polzin ◽  
Ram M. Pendyala
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
The United States ◽  
Household Composition ◽  
Significant Implication ◽  
Data Set ◽  
Personal Transportation ◽  
Household Travel ◽  
Time Expenditures ◽  
Daily Travel

During the past several decades significant changes in travel behavior in the United States have occurred. Evidence from the Nationwide Personal Transportation Survey series and the 2001 National Household Travel Survey (NHTS) indicates that the average daily travel time per person has increased by 1.9 min per year between 1983 and 2001. The objective of this paper is to explore the growth of daily travel time expenditures. Changes in society, technology, incomes, attitudes, and sociodemographic and household structure have been hypothesized as having contributed to the travel time growth. This analysis explores those variables and their relationship to increases in travel time. Aggregate values are used to investigate the relationships between daily travel time expenditures and sociodemographic characteristics. This paper comments on the share of travel time growth that can be explained by the available variables and speculates on the implications of other factors on travel time expenditure growth. A review of the NHTS data set and an analysis of the relationships between the data set and travel time expenditures make clear that travel budget changes that appear to be related to the set of available variables do not explain the full reason for the significant increase in travel time spending. The increases are across all market segments: age, income, gender, ethnicity, household composition, and so on. Thus, shifts in demographic or other traveler conditions do not fully explain the increases in trip making. That has a significant implication for transportation planning–-traditional sociodemographic predictors for trip making do not appear to be sufficiently causal to be useful for understanding current and future factors influencing trip making and travel expenditure changes.

Interstate Speed Profiles

2018 ◽  
Vol 2672 (42) ◽  
pp. 57-70 ◽  
Author(s):  
Wenjing Pu
Keyword(s):  
United States ◽  
Performance Management ◽  
Travel Time ◽  
The United States ◽  
Time Of Day ◽  
National Average ◽  
Time Data ◽  
Data Set ◽  
Average Speed ◽  
High Level

This paper draws the first set of high-level, national speed profiles for the entire Dwight D. Eisenhower National System of Interstate and Defense Highways (Interstate system) in the United States based on the 2016 year-long National Performance Management Research Data Set (NPMRDS) and a conflated NPMRDS-HPMS (Highway Performance Monitoring System) geospatial network. This set of quantitative profiles include: ( a) national average speeds of 2016, ( b) national average speed time of day variations, ( c) national average speed day of week variations, ( d) national average speed seasonal variations, and ( e) state average speed and travel time distributions in peak hours. This work demonstrates that the integration of the private sector’s emerging big travel-time data and the public sector’s HPMS has provided a powerful resource to monitor travel-time-related performance of the nation’s highways. As the United States is transforming the Federal-aid Highway Program into a performance-based program with enhanced accountability and transparency, this integrated resource will help states and metropolitan planning organizations (MPOs) to monitor their performance and progress towards achieving targets, and enable the Federal Highway Administration (FHWA) not only to draw high-level national highway performance profiles but also to pinpoint the exact where, when, and how much the challenges are.

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.

scholarly journals Testing for the Significance of Induced Highway Travel Demand in Metropolitan Areas

2000 ◽  
Vol 1706 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Lawrence C. Barr
Keyword(s):  
Population Density ◽  
Travel Time ◽  
Public Transportation ◽  
Regression Models ◽  
Research Study ◽  
Travel Demand ◽  
Highway Capacity ◽  
Time Savings ◽  
Personal Transportation ◽  
Household Travel

A research study was conducted to evaluate and quantify the effect of highway capacity improvements on travel demand. Statistical models using Nationwide Personal Transportation Survey data were designed to estimate relationships between average household travel time and vehicle-miles of travel. Several regression models were estimated, and the results were stratified by urbanized area, public transportation availability, metropolitan area size, family life cycle, day-of-week of travel, and population density. Travel-time elasticities of -0.3 to -0.5 were generally found, after taking into account the effects of household size, income, population density, and household employment. These results suggest that travelers will spend 30 to 50 percent of the time savings afforded by highway improvements in additional travel. Overall, the results of this study provide evidence that highway capacity improvements can create additional travel, although the magnitude of the induced traffic effect was found to be smaller than that reported by some previous researchers.

Unrevealed Preferences: Unexpected Traveler Response to Pricing on Managed Lanes

2018 ◽  
Vol 2672 (5) ◽  
pp. 23-32 ◽  
Author(s):  
Mark W. Burris ◽  
John F. Brady
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
Preliminary Investigation ◽  
The United States ◽  
General Purpose ◽  
Managed Lanes ◽  
Travel Time Savings ◽  
Time Savings ◽  
The Cost ◽  
Transportation Agencies

This paper addresses priced managed lane corridors, on which travelers may choose to pay a toll to travel on the managed lanes (MLs) to realize generally faster, more reliable travel than on the adjacent, toll-free general purpose lanes (GPLs). These lanes exist in many cities across the United States and are becoming more common as transportation agencies look for innovative ways to increase capacity and regulate demand for their roadways. Commonly, demand for these lanes is modeled assuming travelers choose between the MLs and GPLs primarily based on the cost and time savings of the MLs. Although the traffic and revenue forecasts generated by these models have generally succeeded in estimating revenue, newly available empirical data from Katy Freeway and North Tarrant Express shows these models fail to capture how individual drivers make decisions. Most travelers on those freeways were not choosing—they always used the same lane regardless of travel time and toll. Travelers that used both sets of lanes often made choices that appeared counter-intuitive based on travel time savings and toll rate. This research provides a preliminary investigation into this issue, which calls into question all prior ML travel-behavior research.

State Medical Boards' Perceptions of a Minimum Data Set and Current Practices for Collecting Physician Information

2013 ◽  
Vol 99 (4) ◽  
pp. 40-45 ◽  
Author(s):  
Aaron Young ◽  
Philip Davignon ◽  
Margaret B. Hansen ◽  
Mark A. Eggen
Keyword(s):  
Media Coverage ◽  
The United States ◽  
Minimum Data Set ◽  
Direct Patient Care ◽  
Physician Workforce ◽  
Data Set ◽  
Minimum Data ◽  
State Medical Boards ◽  
The Impact ◽  
Current Practices

ABSTRACT Recent media coverage has focused on the supply of physicians in the United States, especially with the impact of a growing physician shortage and the Affordable Care Act. State medical boards and other entities maintain data on physician licensure and discipline, as well as some biographical data describing their physician populations. However, there are gaps of workforce information in these sources. The Federation of State Medical Boards' (FSMB) Census of Licensed Physicians and the AMA Masterfile, for example, offer valuable information, but they provide a limited picture of the physician workforce. Furthermore, they are unable to shed light on some of the nuances in physician availability, such as how much time physicians spend providing direct patient care. In response to these gaps, policymakers and regulators have in recent years discussed the creation of a physician minimum data set (MDS), which would be gathered periodically and would provide key physician workforce information. While proponents of an MDS believe it would provide benefits to a variety of stakeholders, an effort has not been attempted to determine whether state medical boards think it is important to collect physician workforce data and if they currently collect workforce information from licensed physicians. To learn more, the FSMB sent surveys to the executive directors at state medical boards to determine their perceptions of collecting workforce data and current practices regarding their collection of such data. The purpose of this article is to convey results from this effort. Survey findings indicate that the vast majority of boards view physician workforce information as valuable in the determination of health care needs within their state, and that various boards are already collecting some data elements. Analysis of the data confirms the potential benefits of a physician minimum data set (MDS) and why state medical boards are in a unique position to collect MDS information from physicians.

Legislative Diversity and the Rise of Women Lobbyists

2021 ◽  
pp. 106591292110093
Author(s):  
James M. Strickland ◽  
Katelyn E. Stauffer
Keyword(s):  
Gender Diversity ◽  
Personal Characteristics ◽  
The United States ◽  
Revolving Door ◽  
Women And Politics ◽  
Political Equality ◽  
Data Set ◽  
Women Legislators ◽  
Organized Interests ◽  
American States

Despite a growing body of literature examining the consequences of women’s inclusion among lobbyists, our understanding of the factors that lead to women’s initial emergence in the profession is limited. In this study, we propose that gender diversity among legislative targets incentivizes organized interests to hire women lobbyists, and thus helps to explain when and how women emerge as lobbyists. Using a comprehensive data set of registered lobbyist–client pairings from all American states in 1989 and 2011, we find that legislative diversity influences not only the number of lobby contracts held by women but also the number of former women legislators who become revolving-door lobbyists. This second finding further supports the argument that interests capitalize on the personal characteristics of lobbyists, specifically by hiring women to work in more diverse legislatures. Our findings have implications for women and politics, lobbying, and voice and political equality in the United States.

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