Household Travel Surveys and Utilization of Travel Behavior Data in Abroad

2007 ◽  
Vol 42 (0) ◽  
pp. 94-94
Author(s):  
KIYOSHI SAKAI
Keyword(s):  
Travel Behavior ◽  
Household Travel ◽  
Household Travel Surveys

Air Quality Effects of Travel Changes

1998 ◽  
Vol 1641 (1) ◽  
pp. 89-96 ◽  
Author(s):  
David A. Zavattero ◽  
Janice A. Ward ◽  
Christopher K. Strong
Keyword(s):  
Air Quality ◽  
Travel Behavior ◽  
Traffic Congestion ◽  
Management Strategies ◽  
Transit Ridership ◽  
Environmental Objectives ◽  
Reduction Strategies ◽  
Home Interview ◽  
Household Travel ◽  
Household Travel Surveys

Travel behavior in northeastern Illinois was examined for the 20-year period between 1970 and 1990 by conducting a comparative analysis of data from the Chicago Area Transportation Study 1970 Home Interview and the 1990 Household Travel Surveys. This study identified regional travel conditions and needs and provided an overview of the changes that have occurred because of population and employment growth and behavioral shifts. By understanding travel behavior and patterns in the region and resulting congestion and air quality effects, travel reduction strategies could be developed to promote mobility and meet environmental objectives. The analysis offers insight into travel purpose, mode, location, and length while identifying characteristics of the population making those trips. Changes in travel during the 1970 to 1990 period include increased total daily trips, person miles, and private automobile use, primarily single-occupant vehicle trips; substantial growth in suburban travel; increased work trips, transit and automobile trip lengths, and trip-chaining; reduced passenger trips and automobile occupancy rates; and increased suburban transit ridership. These travel changes have increased traffic congestion and affected air quality. Advances in technology have increased vehicle efficiency. The relative contributions to emissions changes that can be attributed to technology and to underlying behavioral changes are examined. Transportation management strategies can be applied to increase the efficiency of transportation facilities and further improve regional air quality.

Measuring Changes in Multimodal Travel Behavior Resulting from Transport Supply Improvement

2021 ◽  
pp. 036119812110031
Author(s):  
Elodie Deschaintres ◽  
Catherine Morency ◽  
Martin Trépanier
Keyword(s):  
Travel Behavior ◽  
Positive Impact ◽  
Good News ◽  
Sensitivity Analyses ◽  
Cross Sectional ◽  
Transport Services ◽  
Spatial Attributes ◽  
Household Travel ◽  
Household Travel Surveys ◽  
Transport Supply

Despite the desired transition toward sustainable and multimodal mobility, few tools have been developed either to quantify mode use diversity or to assess the effects of transportation system enhancements on multimodal travel behaviors. This paper attempts to fill this gap by proposing a methodology to appraise the causal impact of transport supply improvement on the evolution of multimodality levels between 2013 and 2018 in Montreal (Quebec, Canada). First, the participants of two household travel surveys were clustered into types of people (PeTys) to overcome the cross-sectional nature of the data. This allowed changes in travel behavior per type over a five-year period to be evaluated. A variant of the Dalton index was then applied on a series of aggregated (weighted) intensities of use of several modes to measure multimodality. Various sensitivity analyses were carried out to determine the parameters of this indicator (sensitivity to the least used modes, intensity metric, and mode independency). Finally, a difference-in-differences causal inference approach was explored to model the influence of the improvement of three alternative transport services (transit, bikesharing, and station-based carsharing) on the evolution of modal variability by type of people. The results revealed that, after controlling for different socio-demographic and spatial attributes, increasing transport supply had a significant and positive impact on multimodality. This outcome is therefore good news for the mobility of the future as alternative modes of transport emerge.

Who’s on Board? Examining the Changing Characteristics of Transit Riders using Latent Profile Analysis

2021 ◽  
pp. 036119812098722
Author(s):  
Andrew Schouten ◽  
Brian D. Taylor ◽  
Evelyn Blumenberg
Keyword(s):  
Travel Behavior ◽  
Latent Profile Analysis ◽  
Metropolitan Areas ◽  
Profile Analysis ◽  
Transit Systems ◽  
Poor Households ◽  
Household Travel ◽  
Household Travel Surveys ◽  
Over Time ◽  
Latent Profile

Subsidies of public transit have more than doubled since the late 1980s, with a disproportionate share of funds going to rail services. These investments have important implications, including how they affect both the composition of transit users and their travel behavior. To investigate how transit users and use are changing, we use Latent Profile Analysis and data from the 2009 and 2017 National Household Travel Surveys to examine changes in transit users in the U.S. and in five major metropolitan areas. Nationwide, we find that the share of Transit Dependents grew by 17% to account for two-thirds of all transit users in 2017. These least advantaged riders were more likely over time to reside in very poor households and to be carless. There was a corresponding decline in Occasional Transit Users, for whom transit is part of a multi-modal travel profile. Higher-income, mostly car-owning Choice Transit Riders increased slightly over time but accounted for less than one in ten transit riders in 2017. Their growth was concentrated in a few large metropolitan areas where densities and land use are most transit-supportive. While increased rail transit service has shifted riders away from buses, transit’s role as a redistributive social service that provides mobility to disadvantaged travelers has grown over time. Efforts to draw more multi-modal and car-owning travelers onto transit have been less successful. As transit systems struggle to recover riders following the pandemic, transit’s waxing role of providing mobility for those without will likely become even more prominent.

Accessibility and Intraurban Travel

1987 ◽  
Vol 19 (6) ◽  
pp. 735-748 ◽  
Author(s):  
S Hanson ◽  
M Schwab
Keyword(s):  
Travel Behavior ◽  
Activity Spaces ◽  
Household Travel Survey ◽  
Trip Frequency ◽  
Potential Activity ◽  
Using Data ◽  
Household Travel ◽  
Automobile Use ◽  
The Relationship ◽  
Travel Distances

This paper contains an examination of the fundamental assumption underlying the use of accessibility indicators: that an individual's travel behavior is related to his or her location vis-à-vis the distribution of potential activity sites. First, the conceptual and measurement issues surrounding accessibility and its relationship to travel are reviewed; then, an access measure for individuals is formulated. Using data from the Uppsala (Sweden) Household Travel Survey and controlling for sex, automobile availability, and employment status, the authors explore the relationship between both home- and work-based accessibility and five aspects of an individual's travel: mode use, trip frequencies and travel distances for discretionary purposes, trip complexity, travel in conjunction with the journey to work, and size of the activity space. From the results it can be seen that although all of these travel characteristics are related to accessibility to some degree, the travel–accessibility relationship is not as strong as deductive formulations have implied. High accessibility levels are associated with higher proportions of travel by nonmotorized means, lower levels of automobile use, reduced travel distances for certain discretionary trip purposes, and smaller individual activity spaces. Furthermore, the density of activity sites around the workplace affects the distances travelled by employed people for discretionary purposes. Overall, accessibility level has a greater impact on mode use and travel distance than it does on discretionary trip frequency. This result was unexpected in light of the strong trip frequency–accessibility relationship posited frequently in the literature.

Enriching Activity-Based Models using Smartphone-Based Travel Surveys

2018 ◽  
Vol 2672 (42) ◽  
pp. 280-291 ◽  
Author(s):  
Bat-hen Nahmias-Biran ◽  
Yafei Han ◽  
Shlomo Bekhor ◽  
Fang Zhao ◽  
Christopher Zegras ◽  
...  
Keyword(s):  
Travel Behavior ◽  
Large Scale ◽  
Leisure Activities ◽  
Behavior Modeling ◽  
Machine Learning Techniques ◽  
Initial Field ◽  
Activity Data ◽  
Large Variability ◽  
Tel Aviv ◽  
Household Travel Surveys

Smartphone-based travel surveys have attracted much attention recently, for their potential to improve data quality and response rate. One of the first such survey systems, Future Mobility Sensing (FMS), leverages sensors on smartphones, and machine learning techniques to collect detailed personal travel data. The main purpose of this research is to compare data collected by FMS and traditional methods, and study the implications of using FMS data for travel behavior modeling. Since its initial field test in Singapore, FMS has been used in several large-scale household travel surveys, including one in Tel Aviv, Israel. We present comparative analyses that make use of the rich datasets from Singapore and Tel Aviv, focusing on three main aspects: (1) richness in activity behaviors observed, (2) completeness of travel and activity data, and (3) data accuracy. Results show that FMS has clear advantages over traditional travel surveys: it has higher resolution and better accuracy of times, locations, and paths; FMS represents out-of-work and leisure activities well; and reveals large variability in day-to-day activity pattern, which is inadequately captured in a one-day snapshot in typical traditional surveys. FMS also captures travel and activities that tend to be under-reported in traditional surveys such as multiple stops in a tour and work-based sub-tours. These richer and more complete and accurate data can improve future activity-based modeling.

Investigation of Safety-in-Numbers for Pedestrians and Bicyclists at a Macroscopic Level with Various Exposure Variables

2020 ◽  
Vol 2674 (12) ◽  
pp. 568-580
Author(s):  
Jaeyoung Lee ◽  
Mohamed Abdel-Aty ◽  
Qing Cai
Keyword(s):  
Travel Behavior ◽  
Large Scale ◽  
Road User ◽  
Metropolitan Statistical Area ◽  
Macroscopic Level ◽  
Road Users ◽  
Vulnerable Road User ◽  
Safety In Numbers ◽  
Household Travel ◽  
National Household Travel Survey

Safety-in-numbers is a phenomenon whereby the crash risks of road users decrease when their numbers increase. Although several previous studies have confirmed safety-in-numbers at a microscopic level (e.g., intersection), few studies have investigated safety-in-numbers at a macroscopic level (or zonal level). In this study, safety-in-numbers is investigated at a larger scale unit, the metropolitan statistical area (MSA), which is usually composed of multiple counties in the U.S.A. Various pedestrian and bicyclist exposure data were obtained from the U.S. National Household Travel Survey (i.e., trips, miles, and hours). A series of Bayesian Poisson lognormal models confirm safety-in-numbers with the different exposure variables at a large-scale geographic level (i.e., MSA). The findings imply that regional travel behavior and cultures of respect for vulnerable road users play a key role in determining the level of pedestrian and bicyclist safety. In addition, the results reveal other factors important to vulnerable road user involved crashes, including but not limited to the climate, demographic, socioeconomic, and travel characteristics of the study regions.

Investigating the capacity of continuous household travel surveys in capturing the temporal rhythms of travel demand

2019 ◽  
Vol 47 (4) ◽  
pp. 1787-1808
Author(s):  
Wafic El-Assi ◽  
Catherine Morency ◽  
Eric J. Miller ◽  
Khandker Nurul Habib
Keyword(s):  
Travel Demand ◽  
Household Travel ◽  
Household Travel Surveys
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