Microsimulating Residential Mobility and Location Choice Processes within an Integrated Land Use and Transportation Modelling System

This research investigates motivational and procedural aspects of households’ long-term decisions of residential locations. The main goal of the research is to develop microbehavioural models of location processes in order to implement this critical land use component within a microsimulation-based model of Integrated Land Use, Transportation and Environment (ILUTE). The research takes a disaggregate and longitudinal approach to develop the models, which is consistent with the real-world decision-making process of households concerning their movements from one residence to another over time. It identifies two sequential model components to represent households’ relocation behaviour: (1) a model of household residential mobility that determines whether a household decides to become active in the housing market, and (2) a (re) location choice model. Both components are empirically investigated using retrospective surveys of housing careers. For the residential mobility decision, the research tests continuous-time hazard duration models and discrete-time panel logit models, and attempts to capture heterogeneity effects due to repeated choices within both modelling techniques. A discrete-time random parameter model is selected for implementation within ILUTE since it incorporates time-varying covariates. Assuming a sequential decision process, this mobility decision model is linked to the (re) location choice model that establishes preference orderings for each active household for a given set of dwelling units that it considers to relocate within the housing market. A unique feature of the (re) location model developed in this research is that it incorporates reference dependence that explicitly recognizes the role of the status quo and captures asymmetric responses towards gains and losses in making location choice decisions. The research then estimates an asking price model, which is used to generate base prices for active dwellings to interact with active households through a market clearing process within a microsimulation environment. A multilevel model that simultaneously accounts for both temporal and spatial heterogeneity is developed in this research using multi-period property transaction data. Finally, this research simulates evolution of households’ location choices for a twenty-year period (1986-2006) and compares the results against observed location patterns.Ph

Investigation of the use of smartphone applications for trip planning and travel outcomes

This paper explores the use of smartphone applications for trip planning and travel outcomes using data derived from a survey conducted in Halifax, Nova Scotia, in 2015. The study provides empirical evidence of relationships of smartphone use for trip planning (e.g. departure time, destination, mode choice, coordinating trips and performing tasks online) and resulting travel outcomes (e.g. vehicle kilometers traveled, social gathering, new place visits, and group trips) and associated factors. Several sets of factors such as socio-economic characteristics and travel characteristics are tested and interpreted. Results suggest that smartphone applications mostly influence younger individuals’ trip planning decisions. Transit pass owners are the frequent users of smartphone applications for trip planning. Findings suggest that transit pass owners commonly use smartphone applications for deciding departure times and mode choices. The study also identifies the limited impact of smartphone application use on reducing travel outcomes, such as vehicle kilometers traveled. The highest impact is in visiting new places (a 48.8% increase). The study essentially offers an original in-depth understanding of how smartphone applications are affecting everyday travel

Evaluation of Preferences for Alternative Transportation Services and Loyalty towards Active Transportation during a Major Transportation Infrastructure Disruption

This paper investigates active transportation mode users’ preferences for alternative services during the temporary closure event of a bridge and its active transportation (AT) lanes. It also evaluates the loyalty of AT users during the event. The study uses data from a travel survey distributed to cyclists and pedestrians, who are the regular AT lane users of the Macdonald Bridge in Halifax, Canada. Random parameter logit models are developed in this study that examine the effects of socio-demographic, travel and neighborhood characteristics on active transportation users’ preferences. Four alternative transportation services are considered in this study: free shuttle services, frequent ferry services, frequent bus services and other services. Results suggest that higher-income individuals are more likely to prefer frequent ferry services during the AT lane closure event. Transit commuters are found to prefer frequent bus services. Probability of preferring free shuttle services increases if individuals use AT lanes for cost savings. Loyalty towards AT is explored in this study by means of anticipated modal shift. For instance, higher mixed land use area dwellers tend to be loyal towards AT during the disruption event, as demonstrated by their lower probability to shift from current AT mode. This study offers critical behavioral insights, which would assist transportation planning and policies that aim to adopt sustainable transportation planning measures to retain current users’ loyalty towards active transportation and prevent a long-term behavioral shift

Life-Oriented Approach of Modeling Commute Mode Loyalty and Transition Behavior

This study developed a dynamic model for individuals’ commute mode choice over their lifetime by using retrospective survey data. The study conceptualized that individuals reassessed their choice of commute mode when they relocated to a new residential location. Following the re-appraisal, people either continued using the same mode, which was considered mode loyalty, or made a transition to a new mode, which was considered mode transition in this study. The study developed a panel-based random-parameters logit model. One key feature of this study is a life-oriented approach to accommodate the effects of life-cycle events, longer-term changes, life-oriented sociodemographic transitions, and accessibility transitions. The model results suggest that the high-income group tends to be car loyal. No car ownership over the lifetime and the addition of a job increase the probability of transit loyalty. Individuals with no children in the household and residing in an area with high walk and bike usage have a higher probability to be loyal to active transportation. A decrease in household income and tenure transition from owned to rental are likely to trigger a transition from car to transit. However, the presence of children and the addition of a car increase the transition propensity from transit to car. The model results suggest that the use of life-oriented characteristics to explain longer-term commute mode loyalty and transition behavior provides important behavioral insights into the dynamics of individuals’ travel behavior over their lifetime

Impacts of COVID-19 on Transport Modes and Mobility Behavior: Analysis of Public Discourse in Twitter

This study proposes a framework to analyze public discourse in Twitter to understand the impacts of COVID-19 on transport modes and mobility behavior. It also identifies reopening challenges and potential reopening strategies that are discussed by the public. First, the study collects 15,776 tweets that relate to personal opinions on transportation services posted between May 15 and June 15, 2020. Next, it applies text mining and topic modeling techniques to the tweets to determine the prominent themes, terms, and topics in those discussions to understand public feelings, behavior, and broader sentiments about the changes brought about by COVID-19 on transportation systems. Results reveal that people are avoiding public transport and shifting to using private car, bicycle, or walking. Bicycle sales have increased remarkably but car sales have declined. Cycling and walking, telecommuting, and online schools are identified as possible solutions to COVID-19 mobility problems and to reduce car usage with an aim to tackle traffic congestion in the post-pandemic world. People appreciated government decisions for funding allocation to public transport, and asked for the reshaping, restoring, and safe reopening of transit systems. Protecting transit workers, riders, shop customers and staff, and office employees is identified as a crucial reopening challenge, whereas mask wearing, phased reopening, and social distancing are proposed as effective reopening strategies. This framework can be used as a tool by decision makers to enable a holistic understanding of public opinions on transportation services during COVID-19 and formulate policies for a safe reopening