A latent class joint mode and departure time choice model for the Greater Toronto and Hamilton Area

This paper presents a closed-form Latent Class Model (LCM) of joint mode and departure time choices. The proposed LCM offers compound substitution patterns between the two choices. The class-specific choice models are of two opposing nesting structures, each of which provides expected maximum utility feedback to the corresponding class membership model. Such feedback allows switching class membership in response to the changes in choice contexts. The model is used for an empirical investigation of commuting mode and departure time choices in the Greater Toronto and Hamilton Area (GTHA) by using a large sample household travel survey dataset. The empirical model reveals that overall 38% of the commuters in the GTHA are more likely to switch modes than departure times and 62% of them are more likely to do the reverse. The empirical model also reveals that the average Subjective Value of Travel Time Savings (SVTTS) of the commuters in the GTHA can be as low as 3 dollars if a single choice pattern of departure time choices nested within mode choices is considered. It can also be as high as 67 dollars if the opposite nesting structure is assumed. However, the LCM estimates the average SVTTS to be around 27 dollars in the GTHA. An empirical scenario analysis by using the estimated model indicates that a 50% increase in morning peak period car travel time does not sway more than 4% of commuters from the morning peak period.

     

An investigation of prediction errors in work trip mode choice models

This paper reports some analyses of predictive accuracy of disaggregate work trip mode choice models. The prediction error is separated into three components: model specification error, aggregation error, and transfer error. The main results are (1) the total forecasting errors can be very large, especially if the model transfers poorly; (2) poor transfer-ability was found between cities where the transit or shared ride markets are much different; (3) prediction from models having statistically different coefficients need not be much different and (4) the type of level-of-service data, i.e. manually coded or network based, used in model estimation has little influence on forecasting accuracy. These and other results are provisional for reasons discussed in the main text.     

Route choice and the value of commuting time: An economic model of dichotomous choice

This paper presents an economic model of generalized travel cost and provides an empirical study of the parameters of the cost function. The route-choice model that is estimated combines McFadden's theory of qualitative choice behavior with a function for the value of travel time in which total trip time and the income level are assumed to influence the marginal value of time. The empirical results indicate that, for a sample of commuters in the Chicago metropolitan area in 1972, the value of time is a positive function of total trip time, but is not a function of income.     

Accommodating preference heterogeneity in commuting mode choice: an empirical investigation in Shaoxing,China

A latent class model is developed to accommodate preference heterogeneity across commuters with respect to their mode choice between electric bike, private car, and public bus within the context of China. A three-segment solution – ‘electric bike individuals’, ‘private car addicts’, and ‘public bus enthusiasts’ – is identified, each characterized by heterogeneous preferences regarding specific mode attributes and unique socio-demographic profile. The choice model confirms the determinative effects of perceived alternative attributes on commuting mode choice, while the traditionally used objective attributes – travel time and cost – are found to have relatively small influences. The membership model provides solid explanations for these segment-specific preferences. This study provides a better understanding of the nature of mode choice behavior, which can be useful for strategies tailored to a specific segment in order to promote the use of sustainable transport modes.     

An analysis of trip length and land use patterns in the Greater Athens Area

The research described in this paper is an attempt to quantify the impact of a certain distribution of land uses upon trip characteristics — notably trip lengths. The idea is to relate trip lengths classified by mode and purpose to the distance of one trip end from the conurbation centre. The latter is defined as the point which represents a reasonable estimate of the place where the economic, administrative, and cultural life of the urban area is centered.By relating trip lengths to the distance of one trip end from the centre, one could obtain a relation which in effect would be a quantitative expression of the relation between transport and land use. The first application of this idea was in London using the 1966 journey to work data, and it gave quite satisfactory results.The area examined in this research is the Greater Athens Area. The method of analysis is similar to that followed in London so the results of the two studies can be compared. Only work trips are considered for four modes: car, bus, train and all modes (total). It is found that in the case of Athens too, when distance of the workplace from the centre is considered, trip lengths change in smoothly varying ways and a series of mathematical curves can be fitted to the data with an acceptable degree of accuracy. These curves are of the Gamma family having a constant spread factor and varying scale factors for each mode considered. When the distance of the residence end of the trip from the centre is considered, the trip length distributions are not very smooth, a clear mathematical curve cannot be fitted, but again a considerable degree of order can be detected. In addition to the above results a discussion is given on their meaning and the possibilities for future research. In fact the results so far are considered to be the first stage of a more extended research programme which will eventually connect trip length distributions to income and other economic or social parameters in an urban area.The author wishes to express his thanks and appreciation for the comments and constructive criticism made on the various drafts of this paper by M.J.M.     

Hierarchical ordering of nests in a joint mode and destination choice model

This paper seeks to explore the relationship between mode and destination choice in an integrated nested choice model. A fundamental argument can be made that in certain circumstances, the ordering of choices should be reversed from the usual sequence of destination choice preceding mode choice. This results in a travel demand model where travelers are more likely to change destinations than to change transportation modes. For small and medium size urban areas, particularly in the United States, with less well developed public transit systems that draw few choice riders, this assumption makes much more sense than the traditional modeling assumptions. The models used in the new travel modeling system developed for Knoxville, Tennessee utilize this reversed ordering, with generally good results, which required no external tinkering in the logsum parameters.     

A joint trip timing store-type choice model for grocery shopping,including inventory effects and nonparametric control for omitted variables

In principle, stochastic modelling methods are ideally suited to the analysis and forecasting of discretionary travel; they formalise both the capriciousness and continuity which are empirically typical of recurrent choice. In practice, the development of theoretically justifiable but tractable stochastic models has appeared to be an illusive goal in transportation research and stochastic models have found little favour. Recent statistical results on the nonparametric characterisation of mixing distributions now enable stochastic models to simultaneously represent a much greater variety of behaviour while, at the same time, actually reducing problems over tractability. The consequent case for reappraisal is illustrated by the development and calibration of a new joint timing/choice model for shopping travel. This model has sound theoretical underpinnings, permits complex variation in the frequency and regularity of shopping due to both observed and unobserved characteristics and constraints, and yet is readily calibrated from diary data.     

Understanding transport mode choice for commuting: the role of affect

This study examines the relationship between positive and negative user valence and transport mode choice behaviour. We integrate latent attitudes ‘affect’ and ‘salience’ into transport mode choice models using the framework of integrated choice and latent variable modelling and simultaneous maximum likelihood estimation methods. The results are consistent with findings in similar travel behaviour and behavioural economics literature. The study extends the findings of previous research and has demonstrated that user sentiments about public transport mode and salient public transport experiences have a significant impact on travel mode choice behaviour. It was found that private motorised users are more sensitive to overcrowding and anti-social behaviours on PT than active and PT travellers. Key attitudinal indicators influencing individual transport choice behaviour are established to guide public policy. The key indicators of Affect and Salience must be analysed and addressed through public policy to enhance PT user experience and develop services and facilities to increase the utility of PT in-vehicle travel time.     

Modelling commuting mode choice with explicit consideration of carpool in the choice set formation

This article investigates the carpool mode choice option in the context of overall commuting mode choice preferences. The article uses a hybrid discrete choice modelling technique to jointly model the consideration of carpooling in the choice set formation as well as commuting mode choice together with the response bias corrections through the accommodation of measurement equations. A cross-nested error structure for the econometric formulation is used to capture correlations among various commuting modes and carpool consideration in the choice set. Empirical models are estimated using a data set collected through a week-long commuter survey in Edmonton, Alberta. The empirical model reveals many behavioural details of commuting mode choice and carpooling. Interestingly, it reveals that interactions between various Travel Demand Management (TDM) tools with the carpooling option can be different at different level of decision making (choice set formation level and final choice making level).     

Longitudinal analysis of activity generation in the Greater Toronto and Hamilton Area

Transportation - This paper presents a longitudinal analysis of activity generation behaviour in the Greater Toronto and Hamilton Area (GTHA) between 1996 and 2016 for various activity types: work,...     

Modelling the joint choice of activity timing and duration

This paper develops a model of activity and trip scheduling that combines three elements that have to date mostly been investigated in isolation: the duration of activities, the time-of-day preference for activity participation and the effect of schedule delays on the valuation of activities. The model is an error component discrete choice model, describing individuals’ choice between alternative workday activity patterns. The utility function is formulated in a flexible way, applying a bell-shaped component to represent time-of-day preferences for activities. The model was tested using a 2001 data set from the Netherlands. The estimation results suggest that time-of-day preferences and schedule delays associated with the work activity are the most important factors influencing the scheduling of the work tour. Error components included in the model suggest that there is considerable unobserved heterogeneity with respect to mode preferences and schedule delay.     

Unraveling the relationship between trip chaining and mode choice: evidence from a multi-week travel diary

Abstract

Trip chaining (or tours) and mode choice are two critical factors influencing a variety of patterns of urban travel demand. This paper investigates the hierarchical relationship between these two sets of decisions including the influences of socio-demographic characteristics on them. It uses a 6-week travel diary collected in Thurgau, Switzerland, in 2003. The structural equation modeling technique is applied to identify the hierarchical relationship. Hierarchy and temporal consistency of the relationship is investigated separately for work versus non-work tours. It becomes clear that for work tours in weekdays, trip-chaining and mode choice decisions are simultaneous and remain consistent across the weeks. For non-work tours in weekdays, mode choice decisions precede trip-chaining decisions. However, for non-work tours in weekends, trip-chaining decisions precede mode choice decisions. A number of socioeconomic characteristics also play major roles in influencing the relationships. Results of the investigation challenge the traditional approach of modeling mode choice separately from activity-scheduling decisions.     

Modeling co-dependent choice of workplace,residence and commuting mode using an error component mixed logit model

Transportation - This paper develops an error component mixed logit model to analyze the multi-dimensional residential, work and transportation mode choice. It expanse previous studies based on...     

A study on possibility of commuting trip using private motorized modes in cities around the world: Application of multilevel model

The focus of the current research was to evaluate how the individual’s social characteristics and urban infrastructure impacts the usage of Private Motorized Modes (PMM). Based on individual and urban characteristics a multilevel analysis was conducted on the possibility of commuting trip by private motorized modes on the rush time of 78 cities around the world. Also the selected cities were classified through a principal component analysis, and based on the classification the impact of and urban variables on the possibility of commuting trips made by private motorized modes (PCTP) was verified. Results showed a diverse range of variables related to the usage of PMM, as well as the urban structure and railway lengths being an important variable in travel behavior.     

Steering short-term demand for car-sharing: a mode choice and policy impact analysis by trip distance

Transportation - Car-sharing could have substantial benefits. However, there is not enough evidence about if more people choosing car-sharing would reduce private car usage or public transport...     

Time-dependent congestion pricing system for large networks: Integrating departure time choice,dynamic traffic assignment and regional travel surveys in the Greater Toronto Area

Congestion pricing is one of the widely contemplated methods to manage traffic congestion. The purpose of congestion pricing is to manage traffic demand generation and supply allocation by charging fees (i.e., tolling) for the use of certain roads in order to distribute traffic demand more evenly over time and space. This study presents a framework for large-scale variable congestion pricing policy determination and evaluation. The proposed framework integrates departure time choice and route choice models within a regional dynamic traffic assignment (DTA) simulation environment. The framework addresses the impact of tolling on: (1) road traffic congestion (supply side), and (2) travelers’ choice dimensions including departure time and route choices (demand side). The framework is applied to a simulation-based case study of tolling a major freeway in Toronto while capturing the regional effects across the Greater Toronto Area (GTA). The models are developed and calibrated using regional household travel survey data that reflect the heterogeneity of travelers’ attributes. The DTA model is calibrated using actual traffic counts from the Ontario Ministry of Transportation and the City of Toronto. The case study examined two tolling scenarios: flat and variable tolling. The results indicate that: (1) more benefits are attained from variable pricing, that mirrors temporal congestion patterns, due to departure time rescheduling as opposed to predominantly re-routing only in the case of flat tolling, (2) widespread spatial and temporal re-distributions of traffic demand are observed across the regional network in response to tolling a significant, yet relatively short, expressway serving Downtown Toronto, and (3) flat tolling causes major and counterproductive rerouting patterns during peak hours, which was observed to block access to the tolled facility itself.     

Development and validation of a direct mode choice model

A direct discrete mode choice model is introduced using relative attributes of competing modes as well as socioeconomic characteristics of travelers. The model is calibrated and validated for two available historic databases in the Dallas–Fort Worth region. The validation is conducted against the outputs of a current nested logit model used by the regional planning organization as well as the observed values based on transit ridership surveys for a newly inaugurated commuter rail service. The calibrated model is applied after the introduction of this new transit mode. The results show that the estimated mode shares by the proposed model have a statistically better consistency with the observed values than the estimates of the conventional nested logit model. Unlike the logit model, the structure of the direct model based on relative attributes also has the advantage of not needing recalibration each time a new travel mode is introduced. The model is found to be easier to calibrate and produces more accurate results than the nested logit model, commonly used by many metropolitan planning organizations.     

A comparison of the sustainability of public and private transportation systems: Study of the Greater Toronto Area

A macroscopic assessment of the impacts of private and public transportation systems on the sustainability of the Greater Toronto Area (GTA) is undertaken from economic, environmental and social perspectives. The methodology draws upon the urban metabolism and sustainability indicators approaches to assessing urban sustainability, but compares modes in terms of passenger-kms. In assessing the economic sustainability of a city, transportation should be recognized as a product, a driver and a cost. In 1993, the traded costs of automobile use in the GTA were approximately balanced by the value of the automobile parts and assembly industry. But local transit costs 1/3 to 1/6 of the auto costs per person-km, in traded dollars, mainly because local labour is the primary cost.Public transportation is more sustainable from an environmental perspective. Automobile emissions are a major contributor to air pollution, which is a serious contemporary environmental health problem in Toronto. Public transportation modes are less energy intensive (including indirect energy consumption) and produce CO₂ at an order of magnitude lower, although these benefits are partially undermined by under-utilization of transit capacity and the source of electricity generation.The social benefits of automobile use are likely more significant than costs in determining GTA residents' preferential mode choice. The speed and access of auto use provide important economic benefits, e.g. relating to employment and product choice. Nevertheless, offsetting the service attributes of private transportation are large social costs in terms of accidents. The costs of automobile insurance provide one tangible measure of such negative impacts.In order to improve the sustainability of the GTA, innovative approaches are required for improving the performance level of public transportation or substantially reducing the need for the service level provided by automobiles. Efforts such as greater integration of bicycles with public transit, or construction of light-rail systems in wide roadways, might be considered. But to be sustainable overall, a transportation system has to be flexible and adaptable and so must combine a mixture of modes.     

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...