Are we there yet? Assessing smartphone apps as full-fledged tools for activity-travel surveys

Transportation - Given the limitations of traditional methods of data collection and the increased use of smartphones, there is growing attention given to using smartphone apps for activity-travel...     

Modelling daily activity program generation considering within-day and day-to-day dynamics in activity-travel behaviour

This paper presents a comprehensive econometric modelling framework for daily activity program generation. It is for day-specific activity program generations of a week-long time span. Activity types considered are 15 generic categories of non-skeletal and flexible activities. Under the daily time budget and non-negativity of participation rate constraints, the models predict optimal sets of frequencies of the activities under consideration (given the average duration of each activity type). The daily time budget considers at-home basic needs and night sleep activities together as a composite activity. The concept of composite activity ensures the dynamics and continuity of time allocation and activity/travel behaviour by encapsulating altogether the activity types that are not of our direct interest in travel demand modelling. Workers’ total working hours (skeletal activity and not a part of the non-skeletal activity time budget) are considered as a variable in the models to accommodate the scheduling effects inside the generation model of non-skeletal activities. Incorporation of previous day’s total executed activities as variables introduces day-to-day dynamics into the activity program generation models. The possibility of zero frequency of any specific activity under consideration is ensured by the Kuhn-Tucker optimality conditions used for formulating the model structure. Models use the concept of random utility maximization approach to derive activity program set. Estimations of the empirical models are done using the 2002–2003 CHASE survey data set collected in Toronto.

Modelling the dynamics between tour-based mode choices and tour-timing choices in daily activity scheduling

Transportation - The paper presents a dynamic discrete–continuous modelling approach to capture individuals’ tour-based mode choices and continuous time expenditure choices tradeoffs in...     

Modelling users’ behaviour of a carsharing program: Application of a joint hazard and zero inflated dynamic ordered probability model

This paper presents an econometric model for the behaviour of carsharing users. The econometric model is developed to jointly forecast membership duration, the decision to become an active member in a particular month, and the frequency of monthly usage of active members. The model is estimated using the membership directory and monthly transaction data of a carsharing program, ‘Communauto Inc.’, based in Montréal, Canada. The model shows a high degree of fit to the observed dataset and provides many behavioural details of carsharing users. The results are instructive to carsharing planners in devising efficient policies.     

An investigation of commuting trip timing and mode choice in the Greater Toronto Area: Application of a joint discrete-continuous model

The trip timing and mode choice are two critical decisions of individual commuters mostly define peak period traffic congestion in urban areas. Due to the increasing evidence in many North American cities that the duration of the congested peak travelling periods is expanding (peak spreading), it becomes necessary and natural to investigate these two commuting decisions jointly. In addition to being considered jointly with mode choice decisions, trip timing must also be modelled as a continuous variable in order to precisely capture peak spreading trends in a policy sensitive transportation demand model. However, in the literature to date, these two fundamental decisions have largely been treated separately or in some cases as integrated discrete decisions for joint investigation. In this paper, a discrete-continuous econometric model is used to investigate the joint decisions of trip timing and mode choice for commuting trips in the Greater Toronto Area (GTA). The joint model, with a multinomial logit model for mode choice and a continuous time hazard model for trip timing, allows for unrestricted correlation between the unobserved factors influencing these two decisions. Models are estimated by occupation groups using 2001 travel survey data for the GTA. Across all occupation groups, strong correlations between unobserved factors influencing mode choice and trip timing are found. Furthermore, the estimated model proves that it sufficiently captures the peak spreading phenomenon and is capable of being applied within the activity-based travel demand model framework.     

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).     

Exploring the correlation between ride-hailing and multimodal transit ridership in toronto

Transportation - Ride-hailing (RH) services have been growing rapidly and gaining popularity worldwide. However, many transit agencies are experiencing ridership stagnation or even decline....     

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...     

Use of repeated cross-sectional travel surveys for developing meta models of activity-travel scheduling processes

Transportation - The paper presents an investigation of the temporal transferability of activity scheduling process models and a Meta model of activity scheduling processed by using repeated...     

Modeling commuting mode choice jointly with work start time and work duration

This paper presents a joint trivariate discrete-continuous-continuous model for commuters’ mode choice, work start time and work duration. The model is designed to capture correlations among random components influencing these decisions. For empirical investigation, the model is estimated using a data set collected in the Greater Toronto Area (GTA) in 2001. Considering the fact that work duration involves medium- to long-term decision making compared to short-term activity scheduling decisions, work duration is considered endogenous to work start time decisions. The empirical model reveals many behavioral details of commuters’ mode choice, work start time and duration decisions. The primary objective of the model is to predict workers’ work schedules according to mode choice, which is considered a skeletal activity schedule in activity-based travel demand models. However, the empirical model reveals many behavioral details of workers’ mode choices and work scheduling. Independent application of the model for travel demand management policy evaluations is also promising, as it provides better value in terms of travel time estimates.