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Incorporating the Influence of Latent Modal Preferences in Travel Demand Models

  • Author(s): Vij, Akshay
  • Advisor(s): Walker, Joan L.
  • et al.
Abstract

Latent modal preferences, or modality styles, are defined as behavioral predispositions towards a certain travel mode or set of travel modes that an individual habitually uses. They are reflective of higher-level orientations, or lifestyles, that are hypothesized to influence all dimensions of an individual's travel and activity behavior. For example, in the context of travel mode choice different modality styles may be characterized by the set of travel modes that an individual might consider when deciding how to travel, her sensitivity, or lack thereof, to different level-of-service attributes of the transportation (and land use) system when making that decision, and the socioeconomic characteristics that predispose her one way or another. Travel demand models currently in practice assume that individuals are aware of the full range of alternatives at their disposal, and that a conscious choice is made based on a tradeoff between perceived costs and benefits associated with alternative attributes. Heterogeneity in the choice process is typically represented as systematic taste variation or random taste variation to incorporate both observable and unobservable differences in sensitivity to alternative attributes. Though such a representation is convenient from the standpoint of model estimation, it overlooks the effects of inertia, incomplete information and indifference that are reflective of more profound individual variations in lifestyles built around the use of different travel modes and their concurrent influence on all dimensions of individual and household travel and activity behavior.

The objectives of this dissertation are three-fold: (1) to develop a travel demand model framework that captures the influence of modality styles on multiple dimensions of individual and household travel and activity behavior; (2) to test that the framework is both methodologically flexible and empirically robust; and (3) to demonstrate the value of the framework to transportation policy and practice.

In developing an appropriate framework, the dissertation builds on Latent Class Choice Models (LCCMs) used previously in the literature, synthesizing recent advances in the sub-domains of taste heterogeneity and choice set generation, and contributing methodologically to the sub-domains of preference endogeneity and simultaneous choice models. With regards to preference endogeneity, discrete choice models in the past have usually subscribed to the neoclassical assumption that preferences, as denoted by taste parameters and choice sets, are characteristics of the decision-maker that are exogenous to the choice situation and stable over time. Such a representation would be adequate if an individual's modality style were expected to be invariant across time. However, modality styles are subject to external influences, such as changes to the transportation system. For example, one would expect the introduction of transportation policies such as the London Congestion Charge or the implementation of infrastructural initiatives such as Bogota's Transmilenio bus rapid transit system to lead to changes in modality styles, and an apposite framework should be able to model and predict these changes. With regards to simultaneous choice models, discrete choice models in the past have introduced correlation across multiple dimensions through the covariance structure of the utility specification corresponding to each of the dimensions. Though such an approach has been shown to result in a significant improvement in fit, the covariance structure is a black box that it does not offer any insight to the underlying source of correlation. We introduce correlation through the modality styles construct, conditioning multiple dimensions of individual and household travel and activity behavior on a single overarching modality style, and thereby offering a behavioral rationale to the underlying source of correlation.

The proposed framework has the following structure: modality styles are specified as latent classes. Heterogeneity across modality styles is captured by allowing taste parameters and choice sets corresponding to the class-specific choice models to vary across classes. Preferences are endogenized by defining class membership as a function not only of the characteristics of the decision-maker, as is standard practice, but also of the consumer surplus offered by each class, which in turn is a function of alternative attributes, taste parameters and choice sets. Choices across multiple dimensions are correlated by conditioning the class-specific choice models for all dimensions of interest on the class membership model.

We apply the framework to study the relationship between individual modality styles and travel mode choice behavior using two very distinct travel diary datasets from two very culturally and geographically distinct regions. The first dataset was collected in Karlsruhe, Germany and comprises a relatively small sample of 119 individuals surveyed over a fairly long observation period of six weeks. Estimation results indicate the presence of habitual drivers who display a strong bias for using the automobile and multimodal individuals who exhibit variation in their modal preferences. Multimodal behavior is further distinguished by those who appear to be sensitive to travel times and those who appear to be insensitive. The second dataset was collected in the San Francisco Bay Area in the United States and consists of a relatively large sample of 26,350 individuals surveyed over a fairly short observation period of two days. Estimation results uncover six modality styles that are distinguishable from one another by the kinds of individuals that belong to each of the six modality styles, their latent preferences for different travel modes and the relative importance that they attach to different level-of-service attributes of each of the travel modes. For example, two of the six modality styles comprising 30% of the sample population only consider the car when deciding how to travel. These two modality styles, labeled inveterate drivers and car commuters, can further be distinguished from one another by their value of travel time. Inveterate drivers have a very low value of in-vehicle travel time of 0.55 $/hr for mandatory tours and are insensitive to in-vehicle travel times for non-mandatory tours. Car commuters have a value of in-vehicle travel time of 6.95 $/hr for mandatory tours and are insensitive to travel costs for non-mandatory tours, indicating a very high value of in-vehicle travel time for the same. Consistent with findings in the social sciences and multiple streams within economics that have shown preferences to be endogenous, the case study shows that a decision-maker's value of time is sensitive to the level-of-service of the transportation system, and an increase in overall travel times can induce decision-makers to lower their value of time.

The framework is subsequently adapted to study the evolution and persistence of modality styles and travel mode choice behavior in a dynamic context. Individual modality styles are still represented as latent classes, but an individual is allowed to have different modality styles at different time periods. The evolutionary path is hypothesized to be a Markov process such that an individual's modality style in the current time period is dependent only on her modality style in the previous time period. As before, travel mode choices for a particular time period are conditioned on the individual's modality style for that time period. The framework is empirically tested using travel diary data collected in Santiago, Chile. The dataset comprises a sample of 220 individuals surveyed over four one-week periods that span a time period of twenty-two months that includes the introduction of Transantiago, a complete redesign of the city's public transit system. Estimation results identify three modality styles: unimodal auto users who only consider the automobile, unimodal transit users who only consider the public transit system and have a low value of time, and multimodal users who consider all travel modes and have a high value of time. The case study further finds that the distribution of individuals across modality styles is highly sensitive to a shock to the transportation system such as that represented by the introduction of Transantiago. Results from a sample enumeration show that nearly a quarter of the sample population changed its modality style post-Transantiago.

For all three datasets, estimation results find that modality styles are strongly correlated with more long-term travel and activity decisions, such as level of vehicle ownership and residential location. In examining the influence of individual modality styles on travel mode choice behavior, the model framework for both the static and the dynamic context took one or more of these decisions as exogenous inputs. However, such a causal representation risks endogeneity, leading us to reverse the representation and include these dimensions explicitly as dependent variables. In doing so, we recognize that dimensions such as level of vehicle ownership represent decisions that are not made by individuals in isolation from other members of the household. An individual's preferences and choices are strongly shaped by the opinions and behaviors of the people around her, particularly when a choice is made collectively by a group of individuals, as in the case of a household. Therefore, interaction between household members must be understood to influence, among other things, individual modality styles. To reflect this influence, we introduce the household modality styles construct, characterized by the modality styles of the respective individuals that make up the household. We build upon the LCCM framework described previously, replacing the individual modality styles construct with the household modality styles construct and conditioning both individual and household level dimensions on the household's modality style, therefore introducing correlation between preferences of the individuals that constitute the household.

The framework is used to examine the relationship between household modality styles, level of vehicle ownership, transit season pass possession and travel mode choice behavior using travel diary data from Karlsruhe, Germany. The dataset comprises a sample of 96 male and female household heads belonging to 48 households surveyed over a six-week observation period. Estimation results identify four distinct household modality styles. The model uncovers both significant correlation between modal preferences of heads of the same household and notable differences as well. In general, female household heads are found to be less reliant on the automobile for their mobility requirements than their male counterparts. Short-term individual decisions, such as mode choice, are found to be inextricably linked with more long-term individual and household decisions, namely level of vehicle ownership and transit season pass possession, both of which vary considerably across different modality styles.

Modality styles have important implications for transportation policies and infrastructural initiatives seeking to change existing patterns of travel mode choice behavior. Travel demand models constitute an important component of the planning and policy-making process, being widely used to make forecasts, which in turn are driven by the assumptions that these models make about how individuals arrive at decisions. We use estimation results from the BATS 2000 dataset to compare forecasts from different model specifications for scenarios evaluating the impact of increased auto congestion and improvements to the public transit system on travel mode choice behavior. Findings reveal that models of travel mode choice behavior that ignore the influence of modality styles can overestimate expected gains from transport policies and infrastructural initiatives seeking to reduce automobile use by factors of between one-and-a-half and three. The dissertation further demonstrates how incremental improvements in the transportation system, unless accompanied by corresponding shifts in the distribution of individuals across different modality styles, will result in far smaller changes in travel behavior than would be predicted by a traditional model of travel mode choice. This dissertation makes the case that what is needed is a dramatic change to the transportation system that forces individuals to reconsider how they travel.

Though the applications presented in the dissertation restrict their attention to the influence of modality styles on four specific dimensions of individual and household travel and activity behavior - travel mode choice for work/mandatory tours, travel mode choice non-work/non-mandatory tours, transit season pass possession and level of vehicle ownership, our results serve as a good starting point for a more comprehensive framework that recognizes the influence of modality styles on all dimensions of individual and household travel and activity behavior. The model framework developed by this dissertation is shown to be both methodologically flexible and empirically robust. Using a model of individual modality styles and travel mode choices in a static context as the foundation, we were able to expand the framework in multiple directions, extending it to a dynamic context, including additional dimensions of decision-making such as transit season pass possession and level of vehicle ownership, and incorporating the influence of intra-household interactions on individual preferences. Despite differences in observation period, sample size, local topography and cultural context across the three datasets, the framework was consistently found to outperform traditional models of travel behavior in terms of both statistical measures of fit and behavioral interpretation. The dissertation concludes with a discussion on how the framework might be extended further to include dimensions such as destination choice, vehicle miles traveled and residential location. We identify some of the major hurdles to their inclusion and suggest possible solutions, laying out an extensive road map for future research in the area. When complete, the line of work initiated by this dissertation is expected to result in a comprehensive model of individual and household travel and activity behavior that integrates travel demand and land use analysis through the modality styles construct with the objective of offering a deeper understanding of decision-making and greater predictive power than current models in practice.

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