A GPS-aided survey for assessing trip reporting accuracy and travel of students without telephone land lines

A geo-positioning satellite (GPS)-based survey, using a web-based prompted recall tool, was conducted on a sample of 94 students at the University of Toronto from November 2008 to April 2009. The sample included students with and without telephone land lines, allowing for a statistical comparison of demographic and travel behaviour attributes. The same subjects simultaneously completed a traditional trip reporting survey, modelled on the household travel survey in Toronto, allowing for a comparison between the travel behaviour information obtained from the GPS and that reported by the participants in the traditional survey. Students with a land line are more likely to live in houses, with parents, and to live in suburban areas than students without a land line. They also make fewer trips in total, fewer discretionary trips, more transit and auto trips and fewer active trips than students without a land line. By comparing questionnaire-based data and GPS data, we found that most participants reported in the questionnaire either the same number of GPS-based trips or fewer. On average, the GPS survey captured 1.29 more daily trips per participant than the corresponding trips reported in the questionnaire.     

Inferring proxy response in household travel surveys with unknown completer using a group-based choice model

Transportation - A proxy response is often accepted for household travel surveys to reduce the survey cost and increase the sample size, but proxy-response biases may be introduced into the sample...     

Impact of family in-home quality time on person travel demand

This paper introduces the concept of Primary Family Priority Time (PFPT), which represents a high priority household decision to spend time together for in-home activities. PFPT is incorporated into a fully specified and operational activity based discrete choice model system for Copenhagen, called COMPAS, using the DaySim software platform. Structural tests and estimation results identify two important findings. First, PFPT has a place high in the model hierarchy, and second, strong interactions exist between PFPT and the other day level activity components of the model system. Forecasts are generated for a road pricing and congestion scenario by COMPAS and a comparison version of the model system that excludes PFPT. COMPAS with PFPT exhibits less mode changing and time-of-day shifting in response to pricing and congestion than the comparison version.     

Understanding individual travel decisions: results from a commuters survey in Geneva

In this paper, we present the results of an extended traveler behavior survey conducted in Geneva (Switzerland) in March 1994. In this survey, commuters were asked about the impact of various factors, related to individual or household characteristics and situational, contextual and environmental constraints on their basic travel decisions. In particular, the issues of mode, route and departure time choice were investigated, together with the diversion from normal patterns in response to adverse weather conditions. Some cross cultural comparisons are discussed with respect to the results of a similar survey conducted in Brussels (Belgium) in 1992 (Khattak & de Palma 1995, 1997).     

Assessing the effects of a mixed-mode design in a longitudinal household travel survey

The German Mobility Panel (MOP) is a national household travel survey, which has been collecting data on travel behavior in Germany since 1994. One of the MOP’s central assets is its ability to provide time-series data on travel behavior. Thus, the comparability of survey results from different years is a major objective of the survey method used. Declining survey participation rates in the last decade in various socio-demographic groups resulted in the implementation of a mixed-mode design for the MOP in 2013, both for the sampling stage (landline and mobile phone recruitment) and the data collection stage (paper and web). In this study, we analyze whether the adaptations in the survey mode do indeed improve the results and, if so, why and to what degree. Ideally, the survey mode adaptions have increased the representativeness of the MOP. However, measurement biases due to the mixed-mode design are also conceivable. To decompose survey mode effects, we applied the propensity score weighting method. This method imputes the hypothetical responses participants would have given in different survey modes; disparities between actual responses and hypothetical responses under another mode are then traced back to the mixed-mode design. Our analysis indicates that trip-rate biases on shopping, leisure, and short trips are partly caused by the mixed-mode design; in contrast, quantities of time spent in the transportation system, trips made by car and public transportation, and commuting trips are hardly biased.

     

Impact of telecommuting on spatial and temporal patterns of household travel

A spatial and temporal analysis of travel diary data collected during the State of California Telecommuting Pilot Project is performed to determine the impacts of telecommuting on household travel behavior. The analysis is based on geocoded trip data where missing trips and trip attributes have been augmented to the extent possible. The results confirm the earlier finding that the Pilot Project telecommuters substantially reduced travel; on telecommuting days, the telecommuters made virtually no commute trips, reduced peak-period trips by 60%, total distance traveled by 75%, and freeway miles by 90%. The spatial analysis of the trip records has shown that the telecommuters chose non-work destinations that are closer to home; they exhibited contracted action spaces after the introduction of telecommuting. Importantly, this contraction took place on both telecommuting days and commuting days. The telecommuters distributed their trips, over the day and avoided peak-period travel on telecommuting days. Non-work trips, however, show similar patterns of temporal distribution on telecommuting days and commuting days. Non-work trips continued to be made during the lunch period and late afternoon and evening hours.     

Trip misreporting forecast using count data model in a GPS enhanced travel survey

As Global Positioning System (GPS) technology advances, it has been increasingly used to supplement traditional self-reported travel surveys due to its promising features in capturing travel data with better accuracy and reliability. Realizing the limitations of diary-based surveys, this paper presents a study that directly accounts for trip misreporting behavior in trip generation models. Travel data were obtained from prompted-recall assisted GPS survey along with a diary-based survey. Negative Binomial models for count data were developed to accommodate misreporting behavior by introducing interaction effects of the sample-indicator variable with various personal and household variables. The interaction effects indicate how the impacts of the socioeconomic and demographic variables on trip-making vary across the two samples. Assuming that the GPS sample represents the ground truth, the interaction effects actually capture the likelihood and the extent of trip misreporting by detailed personal and household characteristics. The model results reveal significant interaction effects of several personal and household variables, indicating misreporting behavior associated with these attributes. The addition of interaction coefficients to the main effect model represents the real impacts of the independent variables, after compensating for trip misreporting behavior, if any.     

Post-Car World: data collection methods and response behavior in a multi-stage travel survey

Transportation - The main research question addressed by this study is to what degree individuals would change travel modes, time allocation and activity patterns after experiencing large changes...     

Assessing the representativeness of a smartphone-based household travel survey in Dar es Salaam,Tanzania

The household travel survey (HTS) finds itself in the midst of rapid technological change. Traditional methods are increasingly being sidelined by digital devices and computational power—for tracking movements, automatically detecting modes and activities, facilitating data collection, etc.. Smartphones have recently emerged as the latest technological enhancement. FMS is a smartphone-based prompted-recall HTS platform, consisting of an app for sensor data collection, a backend for data processing and inference, and a user interface for verification of inferences (e.g., modes, activities, times, etc.). FMS, has been deployed in several cities of the global north, including Singapore. This paper assesses the first use of FMS in a city of the global south, Dar es Salaam. FMS in Dar was implemented over a 1-month period, among 581 adults chosen from 300 randomly selected households. Individuals were provided phones with data plans and the FMS app preloaded. Verification of the collected data occurred every 3 days, via a phone interview. The experiment reveals various social and technical challenges. Models of individual likelihood to participate suggest little bias. Several socioeconomic and demographic characteristics apparently do influence, however, the number of days fully verified per individual. Similar apparent biases emerge when predicting the likelihood of a given day being verified. Some risk of non-random, non-response is, thus, evident.     

The value of travel time and reliability-evidence from a stated preference survey and actual usage

This research examined travel behavior of Managed Lane (ML) users to better understand the value travelers place on travel time savings and travel time reliability. We also highlight the importance of survey design techniques. These objectives were accomplished through a stated preference survey of Houston’s Katy Freeway travelers. Three stated choice experiment survey design techniques were tested in this study: Bayesian (D_b) efficient, random level attribute generation, and an adaptive random approach. Mixed logit models were developed from responses using each of those designs. The value of travel time savings (VTTSs) estimates do vary across the design strategies, with the VTTS estimates based on the D_b-efficient design being approximately half the estimates from the other two designs. However, among the three design strategies, the value of travel time reliability (VOR) was only significant in the D_b-efficient design.The estimated VTTS from actual Katy Freeway usage (as measured using actual tolls paid and travel time saved on the managed lanes) is $51/h. This likely also includes any value that travelers place on travel time reliability. In comparison, our combined estimate of VTTS and VOR based on the SP survey (D_b-efficient design) was $50/h, which is remarkably close to the estimate from the actual usage data. Based on our dataset, the D_b-efficient design technique proved superior to the other two techniques. Finally, this research also supports the importance of including both travel time and travel time reliability parameters when estimating the willingness to pay for, and therefore benefits derived from, ML travel.     

The use of travel time by rail passengers in Great Britain

In the face of a society that exhibits an increasing dependence on motorised mobility, the response of transport policy is one that remains grounded in the pursuit of quicker journey times. Less time spent travelling is assumed to convert ‘unproductive’ time into economically valuable time. This paper explores an alternative perspective on travel time. It seeks to examine the notion that travel time, rather than being wasted, can and does possess a positive utility. This brings into question the extent of assumed economic benefits derived from schemes and policies intended to reduce journey times. Specifically the paper reports on a national mail-back questionnaire survey of 26,221 rail passengers in Great Britain conducted in autumn 2004. The survey examined how passengers used their time on the train, how worthwhile that time use was considered to be and the role of mobile technologies. The results paint a picture of travel time use in which the behaviour and opinions of commuters, business travellers and leisure travellers are compared and contrasted. A substantial if not overwhelming incidence of positive utility of travel time use is revealed, especially for business travel but also for commuting and leisure travel. In light of the survey evidence the paper points to the challenge of understanding the notion of productivity and offers some critical comments concerning the current approach to economic appraisal in Britain.     

Use of an activity diary survey to examine travel and activity reporting in a home interview survey: An example using data from Adelaide,Australia

Research presented in this paper uses results from an acitivity diary survey to comment on the quality of data collected in a home interview travel survey. The two surveys were conducted in Adelaide, Australia. Evidence is presented to suggest that although a period of slightly more than three years separated the two surveys, the samples were reasonably similar with respect to their socio-demographic composition and real mobility levels. There was, however, a much higher level of travel and out-of-home activity reporting in the activity diary when compared to the home interview survey. Differences in reporting rates are examined in detail and areas of deficiency with the home interview survey are identified. The paper concludes with a short discussion of the possible implications of these deficiencies when home interview survey data is used to investigate a range of urban transport issues.     

Inter-temporal variation in the travel time and travel cost parameters of transport models

The parameters for travel time and travel cost are central in travel demand forecasting models. Since valuation of infrastructure investments requires prediction of travel demand for future evaluation years, inter-temporal variation of the travel time and travel cost parameters is a key issue in forecasting. Using two identical stated choice experiments conducted among Swedish drivers with an interval of 13 years, 1994 and 2007, this paper estimates the inter-temporal variation in travel time and cost parameters (under the assumption that the variance of the error components of the indirect utility function is equal across the two datasets). It is found that the travel time parameter has remained constant over time but that the travel cost parameter has declined in real terms. The trend decline in the cost parameter can be entirely explained by higher average income level in the 2007 sample compared to the 1994 sample. The results support the recommendation to keep the travel time parameter constant over time in forecast models, but to deflate the travel cost parameter with the forecasted income increase among travellers and the relevant income elasticity of the cost parameter. Evidence from this study further suggests that the inter-temporal and the cross-sectional income elasticities of the cost parameter are equal. The average elasticity is found to be ?0.8 to ?0.9 in the present sample of drivers, and the elasticity is found to increase with the real income level, both in the cross-section and over time.     

Intra-destination travel behavior of alpine tourists: a literature review on choice determinants and the survey work

Transportation - In the face of a continuous increase in the number of tourists in the Alps, the associated traffic volumes, and the resulting negative externalities, there is an urgent need to...     

Impact of different shopping stages on shopping-related travel behaviour: analyses of the Netherlands Mobility Panel data

From the moment e-shopping emerged, there have been speculations about its impact on personal mobility. A fair amount of research has already been carried out on Internet shopping itself as well as on its consequences for mobility. Most studies focus on the overall impact of online shopping on personal mobility. However, little is known about how personal shopping mobility can be characterised when differentiating its constituent stages, being browsing/orienting, comparing, selecting and purchasing products, and how this is affected by e-shopping. This will be the main topic of this paper. We will investigate this using recently collected data from the Netherlands Mobility Panel [in Dutch: MobiliteitsPanel Nederland (MPN)]. It is the unique combination of reported shopping trips in the three-day travel diary, the large amount of personal and household characteristics combined with the detailed information from the e-shopping questionnaire that enables us to perform this research. Using factor analysis, we explore the underlying factors related to the browsing and selection behaviour prior to the purchase of a product. Using these factors as a starting point, we apply cluster analysis resulting in three homogeneous groups of shoppers with different pre-purchase shopping behaviour. The groups differ clearly with respect to personal and household characteristics, in the frequency with which they buy and sell products online and in their perception of (dis-)advantages of online shopping. Once relevant groups have been distinguished and characterised, differences in shopping-related mobility between them are studied in two different ways. Firstly, we analyse statements from shoppers on how their shopping-related mobility has changed. Secondly, we analyse shopping trips reported in the three-day travel diary. Only one group, which consists of shoppers that rely on the Internet to search for product information, compare prices and get new product ideas, states that their shopping-related travel behaviour has changed since they started shopping online. Approximately 50% of all shoppers experienced no difference in their shopping mobility. The analysis of actual shopping mobility using the travel diary data showed only minor differences in shopping-related travel behaviour between the identified groups. Finally, we fit a multi-variate linear regression model of shopping trip distance to determine if (e)-shopping characteristics influence trip distances. The frequency with which people shop online as well as some stated changes in shopping-related travel behaviour (shopping in a similar manner and shopping longer) turn out to influence non-grocery shopping trip distance. No significant influence could be found of shopping cluster membership on shopping trip distances.

     

Heterogeneity in marginal value of urban mobility: evidence from a large-scale household travel survey in the Greater Toronto and Hamilton Area

Transportation - The value of mobility is an unresolved question in transportation economics literature. The advent of ride-hailing services and the emergence of mobility as a service (MaaS) place...     

Direct analysis of the perceived importance of attributes of reliability of travel modes in urban travel

Reliability of travel modes was found to be the most important characteristic of transportation systems in several attitudinal investigations of individual travel behavior. This paper represents the first part of a research effort aimed at gaining a better understanding of the characteristics of reliability of transportation modes in urban travel. In this research, reliability characteristics are identified; their importance relative to each other is assessed, and an insight into possible structure of an objective reliability index is discussed. The research is based on perceived values of reliability, which were identified through a large attitudinal survey conducted in the Chicago metropolitan area.     

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

Transportation - Continuous household travel surveys have been identified as a potential replacement for traditional one-off cross-sectional surveys. Many regions around the world have either...