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.

On Usage Context of Hybrid Electric Vehicles in Choice Studies

2011 ◽  
Author(s):  
Lin He ◽  
Wei Chen ◽  
Guenter Conzelmann
Keyword(s):  
Hybrid Electric Vehicle ◽  
Choice Model ◽  
Principal Component ◽  
Choice Modeling ◽  
Multiple Sources ◽  
Hybrid Electric ◽  
Using Data ◽  
Household Travel ◽  
Usage Context ◽  
The Relationship

Considering usage context attributes in choice modeling has been shown to be important when product performance highly depends on the usage context. To build a reliable choice model, it is critical to first understand the relationship between usage context attributes and customer profile attributes, then to identify the market segmentation characterized by both sets of attributes, and finally to construct a choice model by integrating data from multiple sources. This is a complex procedure especially when a large number of customer attributes are potentially influential to the product choice. Using the hybrid electric vehicle (HEV) as an example, this paper presents a systematic procedure and the associated data analysis techniques for implementing each of the above steps. Usage context and customer profile attributes extracted from both National Household Travel Survey (NHTS) and Vehicle Quality Survey (VQS) data are first analyzed to understand the relationship between usage context attributes and customer profile attributes. Next the principal component analysis is utilized to identify the key characteristics of hybrid vehicle drivers, and to determine the market segmentations of HEV and the critical attributes to include in choice models. Before the two sets of data are combined for choice modeling, statistical analysis is used to test the compatibility of the two datasets. A pooled choice model created by incorporating usage context attributes illustrates the benefits of context-based choice modeling using data from multiple sources. Even though NHTS and VQS have been used in the literature to study transportation patterns and vehicle quality ratings, respectively, this work is the first to explore how they may be used together to benefit the study of customer preference for HEVs.

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.

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.

Unraveling the Effects of Residence in an Ethnic Enclave on Immigrants’ Travel Mode Choices

2016 ◽  
Vol 37 (4) ◽  
pp. 425-443 ◽  
Author(s):  
Eun Jin Shin
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Ethnic Enclave ◽  
Network Effect ◽  
Ethnic Enclaves ◽  
Household Travel Survey ◽  
The Social ◽  
Household Travel ◽  
Transit Use ◽  
The Relationship

This article examines the relationship between immigrants’ residence in an ethnic enclave and use of alternative modes of transportation. Ethnic enclaves may offer stronger social networks, which may affect mode choice. Using the 2012–2013 California Household Travel Survey, I find that immigrants residing in ethnic enclaves have higher rates of household-external carpooling for nonwork trip purposes than immigrants residing outside ethnic enclaves. I find no difference in the rate of transit use, once built environment characteristics are taken into account. External carpools require arrangements between people in different households, and thus may reflect the social network effect of ethnic enclaves.

Obtaining Travel Intensity Profiles from Household Travel Survey Data

1998 ◽  
Vol 1625 (1) ◽  
pp. 95-101 ◽  
Author(s):  
S.M. Roddis ◽  
A.J. Richardson ◽  
C.D. Mcpherson
Keyword(s):  
Road Traffic ◽  
Demographic Data ◽  
Driver Behavior ◽  
Spatiotemporal Variations ◽  
Comprehensive Understanding ◽  
Travel Survey ◽  
Household Travel Survey ◽  
Using Data ◽  
Household Travel ◽  
Household Travel Surveys

Innovative ways to examine the spatiotemporal variations in road traffic, by using data from the Victorian Activity and Travel Survey (VATS), are presented. The approach is shown to offer significant advantages over traditional methods of analysis, such as observational surveys or roadside traffic counts. By linking the complete vehicle travel paths reported in VATS with the detailed demographic data of the respondents, a comprehensive understanding of travel and driver behavior is developed. The general methodology described is shown to be applicable to any travel data obtained from household travel surveys, especially where the origins and destinations of the recorded trips have been geocoded and stored in a geographic information system.

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.

Automobile Ownership and Use in Neotraditional and Conventional Neighborhoods

2005 ◽  
Vol 1902 (1) ◽  
pp. 18-25 ◽  
Author(s):  
Elizabeth Shay ◽  
Asad J. Khattak
Keyword(s):  
Urban Design ◽  
Travel Behavior ◽  
Household Size ◽  
Matched Pair ◽  
Neighborhood Design ◽  
Automobile Ownership ◽  
Planning Strategies ◽  
Automobile Use ◽  
The Relationship

Although the commonly accepted link between automobile ownership and automobile use has inspired some municipalities to experiment with neighborhood design in an attempt to influence both automobile ownership and travel behavior, the underlying relationship between neighborhood design and automobile ownership is still unclear. Evidence suggests that automobile ownership is tightly linked to income and household size and is less responsive to urban design. This research uses data from a matched pair of neighborhoods–-one conventional and one neotraditional–-to consider the relationship between neighborhood design and automobile ownership and the relationship between these factors and automobile use. Statistically significant differences were found for automobile ownership in the two neighborhoods. In addition, there were clear differences in automobile use–-residents of neotraditional developments made fewer automobile trips, traveled fewer miles in their vehicles, and spent less time driving. This has implications for planning strategies that may help reduce automobile trips and miles separately from changes in automobile ownership.

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