Glimpse of the Future: Simulating Life with Personally Owned Autonomous Vehicles and Their Implications on Travel Behaviors

2021 ◽  
pp. 036119812110525
Author(s):  
Mustapha Harb ◽  
Jai Malik ◽  
Giovanni Circella ◽  
Joan Walker
Keyword(s):  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Vehicle Miles Traveled ◽  
Household Travel Survey ◽  
Mobility Barriers ◽  
Travel Diaries ◽  
Survey Sample ◽  
Household Travel ◽  
Families With Children ◽  
Made In

To explore potential travel behavior shifts induced by personally owned, fully autonomous vehicles (AVs), we ran an experiment that provided personal chauffeurs to 43 households in the Sacramento region to simulate life with an AV. Like an advanced AV, the chauffeurs took over driving duties. Households were recruited from the 2018 Sacramento household travel survey sample. Sampling was stratified by weekly vehicle miles traveled (VMT), and households were selected to be diverse by demographics, modal preferences, mobility barriers, and residential location. Thirty-four households received 60 h of chauffeur service for 1 week, and nine households received 60 h per week for 2 weeks. Smartphone-based travel diaries were recorded for the chauffeur week(s), 1 week before, and 1 week after. During the chauffeur week, the overall systemwide VMT (summing across all sampled households) increased by 60%, over half of which came from “zero-occupancy vehicle” (ZOV) trips (when the chauffeur was the only occupant). The number of trips made in the system increased by 25%, with ZOV trips accounting for 85% of these additional trips. There was a shift away from transit, ridehailing, biking, and walking trips, which dropped by 70%, 55%, 38%, and 10%, respectively. Households with mobility barriers and those with less auto dependency had the greatest percent increase in VMT, whereas higher VMT households and families with children had the lowest. The results highlight how AVs can enhance mobility, but also caution against the potential detrimental effects on the transportation system and the need to regulate AVs and ZOVs.

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.

Use of a Smartphone GPS Application for Recurrent Travel Behavior Data Collection

2019 ◽  
Vol 2673 (7) ◽  
pp. 89-98 ◽  
Author(s):  
Joann Lynch ◽  
Jeffrey Dumont ◽  
Elizabeth Greene ◽  
Jonathan Ehrlich
Keyword(s):  
Travel Behavior ◽  
Large Scale ◽  
Survey Design ◽  
Demographic Data ◽  
Smartphone Application ◽  
Completion Rate ◽  
Computer Assisted ◽  
Household Travel Survey ◽  
Continuous Survey ◽  
Household Travel

Smartphone-based household travel survey (HTS) studies to date have typically followed the two-part survey process that has historically been used for paper, computer-assisted telephone interviewing, and online HTS. In this two-part survey process, households provide demographic data in a recruit survey (part one) and record trips in a travel diary (part two) often at a later date. The Metropolitan Council, the planning organization serving the Twin Cities metropolitan area in Minnesota, has conducted a pilot study for their cyclical HTS, the Travel Behavior Inventory (TBI), that is one of the first large-scale fields of an all-in-one smartphone HTS design. For the 2018 TBI pilot, the traditional two-part survey was merged into a continuous survey experience within a smartphone app. The TBI pilot used a split sample to test this all-in-one design against a traditional two-part smartphone survey design. For the all-in-one design, households were invited to sign in directly to the smartphone application instead of first recruiting online or by phone. The pilot results provide a direct comparison of the two-part and all-in-one designs at the household-, person-, and trip-levels. The results showed a lower overall recruit and completion rate for the all-in-one design but showed clear promise for increasing representation of younger and lower-income populations—traditionally hard-to-reach groups who completed at a higher rate with all-in-one. The authors discuss several factors which may have contributed to the lower overall completion rate and describe planned updates for future waves of the TBI aimed at improving overall response while maintaining the developments that have improved representation from hard-to-reach groups.

scholarly journals The Role of Destination’s Built Environment on Nonmotorized Travel Behavior: A Case of Long Beach, California

2017 ◽  
Vol 38 (2) ◽  
pp. 152-166 ◽  
Author(s):  
Dohyung Kim ◽  
Jiyoung Park ◽  
Andy Hong
Keyword(s):  
Built Environment ◽  
Travel Behavior ◽  
Mode Choice ◽  
Long Beach ◽  
Environment Factors ◽  
Household Travel Survey ◽  
Future Policy ◽  
Household Travel ◽  
National Household Travel Survey

This study examines how built environment factors at trip destinations influence nonmotorized travel behavior in the City of Long Beach, California. Using 2008–2009 National Household Travel Survey with California Add-Ons, we found that nonmotorized users tend to choose more clustered destinations than motorized users, and that density, diversity, and design at destinations significantly affect mode choice decisions. Transportation networks and nonmotorized facilities at trip destinations are especially important factors for nonmotorized mode choice. Future policy and research need to consider built environment factors at trip destinations to effectively accommodate nonmotorized travel within a city.

scholarly journals Determinants of Per Capita Vehicle Miles Traveled (VMT): The Case of California

2014 ◽  
Author(s):  
Mintesnot Woldeamanuel ◽  
Andrew Kent
Keyword(s):  
Multivariate Regression ◽  
Data Sets ◽  
Vehicle Miles Traveled ◽  
Household Travel Survey ◽  
Reduction Strategies ◽  
Per Capita ◽  
Household Travel ◽  
National Household Travel Survey ◽  
Over Time

This study uses multivariate regression to isolate determinants of per capita VMT in California from the National Household Travel Survey (NHTS), as well as a Chow Test to identify structural change between the 2001 and 2009 NHTS. Results across the 2001 and 2009 NHTS data sets indicate certain determinant variables have emerged over time and others have changed in strength of impact. Our findings support mixed methods VMT reduction strategies to achieve near- and long- term GHG targets.

Fragmentation in Daily Schedule of Activities using Activity Sequences

2019 ◽  
Vol 2673 (4) ◽  
pp. 844-854 ◽  
Author(s):  
Elizabeth Callahan McBride ◽  
Adam Wilkinson Davis ◽  
Konstadinos G. Goulias
Keyword(s):  
Statistical Analysis ◽  
Travel Behavior ◽  
Daily Activity ◽  
Age Groups ◽  
Activity Participation ◽  
Household Travel Survey ◽  
Daily Schedule ◽  
Household Travel ◽  
Entire Trajectory ◽  
The Life Course

A new method of sequence analysis to measure fragmentation in activity participation is presented in this paper. We applied this method to a sample of residents in the Central Coast of California that participated in the California Household Travel Survey in 2012–2013. This method explores sequences of daily activity and travel employing techniques from the sequencing of events in the life course of individuals. Studying sequences of daily episodes (each activity and each trip) is preferable to other techniques of studying activity-travel behavior because sequences include the entire trajectory of a person’s activity during a day while at the same time considering the number of activities, order of activities in a day, and their durations jointly. We found substantial fragmentation in activity participation among persons with children and in specific age groups (25–65) amplified by the presence of children in the household. We also found poverty plays an important inhibiting role. Examinations of the days of the week showed significant and substantial differences among the days with both Sundays and Saturdays being distinct, but also substantial differences among the weekdays. The paper provides details about this new technique and the statistical analysis of fragmentation. It also provides a discussion about future steps.

Temporal Variability of Car Use as an Input to Design of Before and After Surveys

2003 ◽  
Vol 1855 (1) ◽  
pp. 112-120 ◽  
Author(s):  
A. J. Richardson
Keyword(s):  
Travel Behavior ◽  
Design Parameters ◽  
Panel Survey ◽  
Sample Sizes ◽  
Cross Sectional ◽  
Travel Diary ◽  
Before And After ◽  
Travel Diaries ◽  
Household Travel ◽  
Larger Sample

Before and after surveys are a common method for measuring the effect of specific policies and projects designed to cause changes in travel behavior. Design issues of before and after surveys used to evaluate projects designed to change travel behavior are addressed. A quantitative understanding of the underlying variability of the parameters to be measured was needed—in particular, the variation over time in car travel by individuals and households. Since no data were available locally, a detailed analysis was made of the 6-week travel diaries from the MobiDrive survey conducted in Germany to estimate the coefficients of variation in key travel parameters. These results were then adapted for use in the presented project. Several features emerged from this analysis. First, in general, larger sample sizes are needed to detect changes in either distance traveled or travel time than for trips undertaken. Second, larger sample sizes are needed to detect changes from repeated cross-sectional surveys than from a panel survey. Third, larger sample sizes are needed to detect changes when using a daily travel diary, compared with use of a weekly travel diary (although this difference can be substantially reduced in a panel survey by maintaining the same day of the week for each household in later waves of the panel). Finally, larger sample sizes are needed to detect changes from person travel data than from household travel data. However, some of the design parameters that allow smaller sample sizes also make the survey more difficult to conduct.

Exploring Factors Regarding Transit-related Walking and Walking Duration

2016 ◽  
Vol 13 (11) ◽  
pp. 1220-1229 ◽  
Author(s):  
Chia-Yuan Yu ◽  
Hsien-Chang Lin
Keyword(s):  
Low Income ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Walking Behavior ◽  
Household Travel Survey ◽  
The Mean ◽  
Household Travel ◽  
National Household Travel Survey ◽  
Step Selection ◽  
Made In

Background:Transit-related walking provides a potential opportunity to promote general walking behavior, yet few studies have examined this issue. Since people’s decisions tend to vary as they walk between home and transit and between transit and destination, this study separated trips made in each direction.Purpose:This study identified the associations between sociodemographics and the 2-step process of transit-related walking: 1) whether transit users walked for home-transit trip or transitdestination trip, and 2) the walking duration for home-transit trip or transit-destination trip among those who walked.Methods:This cross-sectional study used the 2009 National Household Travel Survey and used the Heckman 2-step selection model by including 4042 respondents (10,105 trips) who walked all portions for home-transit trip and 3756 (8075 trips) for transitdestination trip.Results:The mean walking duration for home-transit trips (7.60 minutes) was shorter than transit-destination trips (7.87 minutes). Hispanics were more likely to walk for both directions and had higher walking durations than did whites. Respondents living in low-income households were more likely to walk for home-transit trip, but not for transit-destination trips.Conclusions:This study illustrated several implications regarding to transit-related walking, such as creating short home-transit distances and targeting whites in promoting transit-related walking.

Incorporating Land Use into Methods of Synthetic Population Generation and of Transfer of Behavioral Data

2017 ◽  
Vol 2668 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Elizabeth C. McBride ◽  
Adam W. Davis ◽  
Jae Hyun Lee ◽  
Konstadinos G. Goulias
Keyword(s):  
Land Use ◽  
Travel Behavior ◽  
Travel Demand ◽  
Behavioral Data ◽  
Synthesis Methods ◽  
Population Synthesis ◽  
Household Travel Survey ◽  
Synthetic Populations ◽  
Synthetic Population ◽  
Household Travel

This paper describes a new method of population synthesis that includes land use information. The method is based on an initial identification of suitable land use summaries to build a spatial taxonomy at any spatial scale. This same taxonomy is then used to classify household travel survey records (persons and households) and in parallel geographic subdivisions for the state of California. This land use information is the added dimension in the population synthesis methods for travel demand analysis. Synthetic population generation proceeds by expanding (re-creating) the records of the households responding to the survey and the entire array of travel behavior data reproduced for the synthetic population. The basis for selecting the variables to use in the synthetic population is first testing their significance in simplified specification in models of travel behavior that include land use as an explanatory variable and account for the shape of behavioral data (e.g., observations with no travel). The paper shows differences between synthetic populations with and without land use data to demonstrate the behavioral realism added by this approach.

Impact of Crime Statistics on Travel Mode Choice

2015 ◽  
Vol 2537 (1) ◽  
pp. 81-87 ◽  
Author(s):  
Hooram Halat ◽  
Meead Saberi ◽  
Charlotte Anne Frei ◽  
Andreas Rolf Frei ◽  
Hani S. Mahmassani
Keyword(s):  
Travel Behavior ◽  
Mode Choice ◽  
Discrete Choice Models ◽  
Influential Factors ◽  
Household Travel Survey ◽  
Home Based ◽  
Walk Score ◽  
Crime Types ◽  
Household Travel ◽  
Crime Index

Whether crime or the perception of it has any direct and significant influence on travelers’ mode choice is a topic for which the evidence remains inconclusive. Studies have revealed various, and in some cases counterintuitive, roles that safety concerns can play in individuals’ travel behavior. In addition, characteristics of the physical environment such as land use and walkability are also influential factors in travelers’ decisions. This study explored these questions through the study of individual travel behavior by using discrete choice models applied to the reported home-based work trips in the Chicago household travel survey. Mode choice was modeled as functions of variables such as sociodemographics, neighborhood crime density (as a safety measure), and walk score (as a measure of walkability). Different crime types were examined, and a crime index was introduced. Results suggest that both walk score and the crime index at the destination can be considered meaningful predictors of individuals’ mode usage. The crime index at origin, however, does not show a significant and meaningful effect.

The role of peer effects and the built environment on individual travel behavior

2017 ◽  
Vol 45 (3) ◽  
pp. 452-469 ◽  
Author(s):  
Changjoo Kim ◽  
Olivier Parent ◽  
Rainer vom Hofe
Keyword(s):  
Built Environment ◽  
Travel Behavior ◽  
Social Influences ◽  
Strong Impact ◽  
Behavioral Models ◽  
Model Framework ◽  
Household Travel Survey ◽  
Transport Modes ◽  
Household Travel

While urban planners and transportation geographers have long emphasized the importance of social influences on individual travel behavior, many challenges remain to bridge the gap between complex conceptual frameworks and operational behavioral models. Improving the ability of models to forecast activity-travel behavior can provide greater insights into urban planning issues. This paper proposes a new model framework by evaluating how individual travel behavior is influenced by inter- and intra-household interactions. The built environment, land-use mix, and social interactions influence household member choices among different transport modes. We propose a spatial multivariate Tobit specification that allows each individual to face a set of potential destinations and transport modes and takes into consideration the travel behavior of other household members and nearby neighbors. Using the Greater Cincinnati Household Travel Survey, we analyzed more than 37,000 trips made by 1968 individuals located in Hamilton County in Cincinnati, Ohio. Results reveal that social influences and the built environment have a strong impact on the willingness to walk and to cycle.

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