Understanding variability,habit and the effect of long period activity plan in modal choices: a day to day,week to week analysis on panel data

Understanding variability in individual behaviour is crucial for the comprehension of travel patterns and for the development and evaluation of planning policies. But, with only one notable exception, there are no studies on the intrinsic variability in the individual preferences for mode choices in absence of external changes in the transport infrastructures. This requires using continuous panel data. Few papers have studied mode choice with continuous panel data but mainly focused on the panel correlation. In this work we use a six-week travel diary survey to study the intrinsic variability in the individual preferences for mode choices, the effect of long period plans and habitual behaviour in the daily mode choices. Mixed logit models are estimated that account for the above effects as well as for systematic and random heterogeneity over individual preferences and responses. We also account for correlation over several time periods. Our results suggest that individual tastes for time and cost are fairly stable but there is a significant systematic and random heterogeneity around these mean values and in the preferences for the different alternatives. We found that there is a strong inertia effect in mode choice that increases with (or is reinforced by) the number of time the same tour is repeated. The sequence of mode choice made is influenced by the duration of the activity and the weekly structure of the activities     

Passenger experience with quality-enhanced bus service: the tyne and wear ‘superoute’ services

This paper investigates the role that enhanced service quality introduced into a deregulated market has in improving the experience of bus travel by a sample of passengers in the Tyne and Wear area of England. A generalised ordered choice (GOC) model that accounts for preference heterogeneity through random parameters, as well as heteroscedasticity in unobserved variance, and random parameterisation of thresholds, is implemented to identify sources of influence on the overall experience of bus travel in the presence and absence of the quality-enhanced treatment of service. The GOC model is contrasted with a standard ordered logit model, and the marginal effects associated with the preferred GOC model are derived for each influencing attribute, taking into account the various ways in which each influence contributes to the utility associated with each level of bus experience. The paper supports a view that the introduction of quality improvements, via a Quality Bus Partnership, does contribute non-marginally to an increase in a positive bus experience, and signals a way forward through cooperative intervention, to grow patronage. Knowing which attributes successfully deliver a more positive experience (and those that do not) means that resources are effectively targeted at the aspect of service provision which will increase patronage and therefore revenues, satisfying the objectives of both the bus operator and the local authority partner.     

Understanding repetitive travel mode choices in a stable context: A panel study approach

It is argued that most travel mode choices are repetitive and made in a stable context. As an example, the everyday use of public transport is analyzed based on a panel survey with a random sample of about 1300 Danish residents interviewed up to three times in the period 1998–2000. The use of public transport is traced back to attitudes towards doing so, beliefs about whether or not public transportation can cover one’s transport needs, and car ownership. The influence of these variables is greatly attenuated when past behavior is accounted for, however. For subjects without a car, behavior changes are in the direction of greater consistency with current attitudes and perceptions. For car owners, current attitudes are inconsequential. The temporal stability of transport behavior is also higher for car-owners than for non-owners.     

Modeling the choice continuum: an integrated model of residential location,auto ownership,bicycle ownership,and commute tour mode choice decisions

The integrated modeling of land use and transportation choices involves analyzing a continuum of choices that characterize people’s lifestyles across temporal scales. This includes long-term choices such as residential and work location choices that affect land-use, medium-term choices such as vehicle ownership, and short-term choices such as travel mode choice that affect travel demand. Prior research in this area has been limited by the complexities associated with the development of integrated model systems that combine the long-, medium- and short-term choices into a unified analytical framework. This paper presents an integrated simultaneous multi-dimensional choice model of residential location, auto ownership, bicycle ownership, and commute tour mode choices using a mixed multidimensional choice modeling methodology. Model estimation results using the San Francisco Bay Area highlight a series of interdependencies among the multi-dimensional choice processes. The interdependencies include: (1) self-selection effects due to observed and unobserved factors, where households locate based on lifestyle and mobility preferences, (2) endogeneity effects, where any one choice dimension is not exogenous to another, but is endogenous to the system as a whole, (3) correlated error structures, where common unobserved factors significantly and simultaneously impact multiple choice dimensions, and (4) unobserved heterogeneity, where decision-makers show significant variation in sensitivity to explanatory variables due to unobserved factors. From a policy standpoint, to be able to forecast the “true” causal influence of activity-travel environment changes on residential location, auto/bicycle ownership, and commute mode choices, it is necessary to capture the above-identified interdependencies by jointly modeling the multiple choice dimensions in an integrated framework.     

A methodology for planning bus service

A methodology to assist transportation planners in designing bus services is developed. The methodology is most relevant for use in locations where bus service of the type being studied does not currently exist and therefore no information is available on past choice behavior, or in instances when transferability of travel models estimated in another location is difficult. The methodology assesses the sensitivity of bus service characteristics upon intended bus usage using survey data collected in Orange County, California, by the Orange County Transit District (OCTD). The methodology is based on a nonparametric statistical test developed by Kolmogorov and Smirnov.Scenarios describing hypothetical operations of bus service are presented to survey respondents who indicate their intended levels of bus usage under each situation. Significant differences between the response distributions associated with pairs of scenarios are identified and potential ridership levels, as bus operations become more favorable, are assessed. Various user segments are then identified on the basis of their levels of intended bus usage and the corresponding marketing implications associated with each segment are discussed.     

Time taken for residents to adopt a new public transport service: examining heterogeneity through duration modelling

When a new public transport service is introduced it would be valuable for public authorities, financing organisations and transport operators to know how long it will take for people to start to use the service and what factors influence this. This paper presents results from research analysing the time taken for residents living close to a new guided bus service to start to use (or adopt) the service. Data was obtained from a sample of residents on whether they used the new service and the number of weeks after the service was introduced before they first used it. Duration modelling has been used to analyse how the likelihood of starting to use the new service changes over time (after the introduction of the service) and to examine what factors influence this. It is found that residents who have not used the new service are increasingly unlikely to use it as time passes. Those residents gaining greater accessibility benefits from the new service are found to be quicker to use the service, although the size of this effect is modest compared to that of other between-resident differences. Allowance for the possibility that there existed a proportion of the sample that would never use the new service was tested using a split population model (SPD) model. The SPD model indicates that 36% of residents will never use the new service and is informative in differentiating factors that influence whether Route 20 is used and when it is used.

A comparison of accuracy and cost of attribute data in analysis of transit service areas using GIS

User oriented transit service is designed to meet the particular needs of a selected group of travelers. Transit Routes are located to provide convenient linkages between user's origin and destination in such a way that out-of-vehicle time, such as access and transfer time, is minimized. Planning transit routes requires understanding demographics, land use and travel patterns in an area. The dynamic nature of these systems necessitates regular review and analysis to insure that the transit system continues to meet the needs of the area it serves. Geographic Information Systems (GIS) provide a flexible framework for planning and analyzing transit routes and stops. Socioeconomic, demographic, housing, land use, and traffic data may be modeled in a GIS to identify efficient and effective corridors to locate routes. Part of the route location and analysis problem requires estimating population within the service area of a route. A route's service area is defined using walking distance or travel time. The problem of identifying service areas for park and ride or auto/bus users is not considered here, but assumed analogous to walk/bus trips. This paper investigates the accuracy and costs associated with the use of different attribute data bases to perform service area analysis for transit routes using GIS. A case study is performed for Logan, Utah, where a new fixed route service is operated. The case study illustrates the use of census data, postal data, data collected from aerial photographs, and data collected during a field survey using the network area analysis technique for transit service area analysis. This comparison allows us to describe the amount of error introduced by various spatial modeling techniques of data bases representing a variety of aggregation levels.     

Understanding Travel Time Expenditures Around the World: Exploring the Notion of a Travel Time Frontier

Travel behavior researchers have been intrigued by the amount of time that people allocate to travel in a day, i.e., the daily travel time expenditure, commonly referred to as a “travel time budget”. Explorations into the notion of a travel time budget have once again resurfaced in the context of activity-based and time use research in travel behavior modeling. This paper revisits the issue by developing the notion of a travel time frontier (TTF) that is distinct from the actual travel time expenditure or budget of an individual. The TTF is defined in this paper as an intrinsic maximum amount of time that people are willing to allocate for travel. It is treated as an unobserved frontier that influences the actual travel time expenditure measured in travel surveys. Using travel survey datasets from around the world (i.e., US, Switzerland and India), this paper sheds new light on daily travel time expenditures by modeling the unobserved TTF and comparing these frontiers across international contexts. The stochastic frontier modeling methodology is employed to model the unobserved TTF as a production frontier. Separate models are estimated for commuter and non-commuter samples to recognize the differing constraints between these market segments. Comparisons across the international contexts show considerable differences in average unobserved TTF values.     

Analysing Demand for Suburban Trips: A Mixed RP/SP Model with Latent Variables and Interaction Effects

We analyse mode choice behaviour for suburban trips in the Grand Canary island using mixed revealed preference (RP)/stated preference (SP) information. The SP choice experiment allowed for interactions among the main policy variables: travel cost, travel time and frequency, and also to test the influence of latent variables such as comfort. It also led to discuss additional requirements on the size and sign of the estimated model parameters, to assess model quality when interactions are present. The RP survey produced data on actual trip behaviour and was used to adapt the SP choice experiment. During the specification searches we detected the presence of income effect and were able to derive willingness-to-pay measures, such as the subjective value of time, which varied among individuals. We also studied the systematic heterogeneity in individual tastes through the specification of models allowing for interactions between level-of-service and socio-economic variables. We concluded examining the sensitivity of travellers’ behaviour to various policy scenarios. In particular, it seems that contrary to political opinion, in a crowded island policies penalising the use of the private car seem to have a far greater impact in terms of bus patronage than policies implying direct improvements to the public transport service.     

A dichotomous choice survey for quantifying option and non-use values of bus services in Korea

The total economic value for a transportation service consists of use, option, and non-use value. The use benefit is based on a traveler’s willingness to pay for usual consumption of the service. The optional value, on the other hand, is related to the possible use of the service for trips not yet anticipated or currently accommodated by other travel modes. The non-use value, however, is derived from the intrinsic merit of the service, even though a trip-maker never actually or potentially depends on the mode. A closed-ended contingent valuation method is considered for the quantification of the option and non-use values. A survey of single- and double-bounded dichotomous choices is conducted with a case study of South Korean bus operations. A logistic regression model and a survival analysis for the single- and double-bounded approaches, respectively, are applied. The estimation result is examined according to the statistical property required and the behavioral validity expected. In particular, three issues from the output are discussed. First, the results help to show the preferable framework between single- and double-bounded surveys for addressing an individual’s option and non-use values. Second, the differences in the absolute values of option and non-use values are compared. Thirdly, the relationship between trip-makers’ willingness to pay and the level of service of their primary travel modes are investigated. In conclusion, the summary of research and the possibilities for future studies are given.     

An analysis of weekly out-of-home discretionary activity participation and time-use behavior

Activity-travel behavior research has hitherto focused on the modeling and understanding of daily time use and activity patterns and resulting travel demand. In this particular paper, an analysis and modeling of weekly activity-travel behavior is presented using a unique multi-week activity-travel behavior data set collected in and around Zurich, Switzerland. The paper focuses on six categories of discretionary activity participation to understand the determinants of, and the inter-personal and intra-personal variability in, weekly activity engagement at a detailed level. A panel version of the Mixed Multiple Discrete Continuous Extreme Value model (MMDCEV) that explicitly accounts for the panel (or repeated-observations) nature of the multi-week activity-travel behavior data set is developed and estimated on the data set. The model also controls for individual-level unobserved factors that lead to correlations in activity engagement preferences across different activity types. To our knowledge, this is the first formulation and application of a panel MMDCEV structure in the econometric literature. The analysis suggests the high prevalence of intra-personal variability in discretionary activity engagement over a multi-week period along with inter-personal variability that is typically considered in activity-travel modeling. In addition, the panel MMDCEV model helped identify the observed socio-economic factors and unobserved individual specific factors that contribute to variability in multi-week discretionary activity participation.

Evaluation of a public transportation level of service concept

The level of service of a bus line is evaluated by its operational characteristics, particularly by the ratio between average bus travel time on a given route and the average passenger car travel time on the shortest distance between the origin and the destination of the bus in question. It is shown that the level-of-service measure may be predicted by such independent variables as route length, average distance between bus stations, number of signalized and unsignalized intersections, and the ratio between such intersections. It is hypothesized that use of other independent variables such as boarding and alighting passengers, or volume to capacity ratio on the route concerned, could improve the predictive power of the suggested models. Further research is recommended on the effect of these latter variables and other operational variables which might influence bus level of service, and also on the comparison between direct bus lines and lines which use transfer points.     

Household travel surveys: Where are we going?

In this paper, we commence by reviewing the recent history of household travel surveys. We note some of the problems that contemporary surveys are encountering throughout the world. We also review the data demands of current and emerging travel demand models, concluding that there are many new demands being placed on data, both in terms of the extent of the data required and the accuracy and completeness of the data. Noting that the standard method for conducting most household travel surveys is, and has been for some years, a diary, we briefly explore the evolution of the diary survey from the late 1970s to the present. In the next section of the paper, we explore a number of facets of potential future data collection. We include in this the use of GPS devices to measure travel, the potential of panel designs and some of the alternatives within panel designs, the development of continuous household travel surveys, especially in Australia, and the emerging capabilities in data fusion. Using some of these emerging methods for data collection and data simulation, we then propose a new paradigm for data collection that places the emphasis on a paid, national panel that is designed as a rotating, split panel, with the cross-sectional component conducted as a continuing survey. The basis of the panel data collection is proposed as GPS with demographic data, and the continuing national sample would also use GPS at its core. The potential to add in such specialised surveys as stated choice and process surveys is also noted as an advantage of the panel approach. We also explore briefly the notion that a special access panel or panels could be included as part of the design.     

Importance of user perception in evaluating level of service for bus transit for a developing country like India: a review

Assessment of service quality in bus transit planning has received due attention in recent years from the viewpoint of optimal service allocation. The concept of level of service (LOS) has emerged as an effective tool to measure quality of services. Service-quality assessment provides operators with knowledge on users' satisfaction with existing services and their expected LOSs. The importance of user perception towards assessment of LOS has been acknowledged by researchers. While LOS standards for public transportation have been established by the Transportation Research Board in the USA, researchers have questioned the applicability of these standards in the context of different geographic regions. Since the service delivery environment differs between developed and developing nations, the user perception of service quality varies between these economic regions. Substantial research has been carried out in the context of both developed and developing nations, to identify the bus transit service parameters that affect users' perceived service quality; however, little research exists that establishes LOS thresholds for bus transit, based on user perception. This paper reviews the concept of LOS, describes the importance of user perception in assessment of service quality and identifies the need to establish LOS thresholds for bus transit from user perception for developing countries.     

Spatiotemporal influence of land use and household properties on automobile travel demand

Understanding the patterns of automobile travel demand can help formulate policies to alleviate congestion and pollution. This study focuses on the influence of land use and household properties on automobile travel demand. Car license plate recognition (CLPR) data, point-of-interest (POI) data, and housing information data were utilized to obtain automobile travel demand along with the land use and household properties. A geographically and temporally weighted regression (GTWR) model was adopted to deal with both the spatial and temporal heterogeneity of travel demand. The spatial-temporal patterns of GTWR coefficients were analyzed. Also, comparative analyses were carried out between automobile and total person travel demand, and among travel demand of taxis, heavily-used private cars, and total automobiles. The results show that: (I) The GTWR model has significantly higher accuracy compared with the Ordinary Least Square (OLS) model and the Geographically Weighted Regression (GWR) model, which means the GTWR model can measure both the spatial and temporal heterogeneity with high precision; (II) The influence of built environment and household properties on automobile travel demand varies with space and time. In particular, the temporal distribution of regression coefficients shows significant peak phenomenon; and (III) Comparative analyses indicate that residents’ preference for automobiles over other travel modes varies with their travel purpose and destination. The above findings indicate that the proposed method can not only model spatial-temporal heterogeneous travel demand, but also provide a way to analyze the patterns of automobile travel demand.     

Temporal transferability of updated alternative-specific constants in disaggregate mode choice models

Methods of updating disaggregate discrete choice models have been proposed as a means of obtaining better transferability. However, the temporal transferability of models updated for better spatial transferability has rarely been analysed, and the factors affecting temporal transferability have not been determined. This paper deals with one updating method—the use of disaggregate data to update alternative-specific constants—and investigates the factors affecting the temporal transferability of the updated constants. In the analysis, repeated cross-section data collected in the Chukyo metropolitan area are divided, efficiently generating many application areas. The analysis showed that the factors can depend on regional characteristics and past travel behaviours (inertia), and are anti-symmetric and path-dependent of changes in the level of service.     

Estimating bus run times for new limited-stop service using archived AVL and APC data

In recent years, several transit agencies have been trying to be more competitive with the automobile to attract choice riders. Transit agencies can only be competitive if they can provide services that are reliable, have a short access and egress time, and have run times that are comparable to automobiles. Several transit agencies try to be competitive through offering faster service, such as limited-stop (express) bus service. This study uses AVL and APC data, in addition to a disaggregate data obtained from a travel behavior survey, to select stops and estimate run times for a new limited-stop service that will run parallel to a heavily used bus route (67 Saint-Michel) in Montréal, Canada. Three different scenarios are developed based on theory and practice to select stops to be incorporated in the new limited service. The time savings for each scenario are then evaluated as a range and a fourth scenario is developed. A limited-stop service is recommended based on selecting stops serving both directions of the route, major activity points and stop spacing. This study shows that implementing a limited-stop service would yield substantial time savings for both, the new limited service and the existing regular service running in parallel.     

基于时间指标的P＆R换乘需求预测研究

城市外围停车换乘需求预测是停车换乘系统规划设计的重要组成部分,也是规划设计的基础和依据。以距离为指标划定P＆R设施吸引范围在山区城市有一定的局限性,文章基于山区地形、居民分布、路网等因素考虑,提出了基于时间指标划分吸引范围的方法,并且通过依据交通方式选择影响因素的相关研究,建立了换乘轻轨、公共汽车、继续使用小汽车的多项logit选择模型。     

Preference heterogeneity in mode choice based on a nationwide survey with a focus on urban rail

The provision of efficient and effective urban public transport and transport policy requires a deep understanding of the factors influencing urban travellers’ choice of travel mode. The majority of existing literature reports on the results from single cities. This study presents the results of a nationwide travel survey implemented to examine multiple modes of urban passenger transport across five mainland state capitals in Australia, with a focus of urban rail. The study aims to explore differences in mode choices among surveyed travellers sampled from the five cities by accounting for two types of factors: service quality and features of public transport, and socio demographic characteristics. A stated preference approach is adopted to elicit people’s valuation of specified mode-choice related factors and their willingness to pay. In particular, the availabilities of wireless and laptop stations – two factors rarely examined in the literature, were also considered in the SP survey. The survey data were analysed using mixed logit models. To test for preference heterogeneity, socio-demographic factors were interacted with random parameters, and their influences on marginal utilities simulated. The analysis reveals that intercity differences, user group status, gender, income, and trip purposes partially explain observed preference heterogeneity.