Activity planning processes in the Agent-based Dynamic Activity Planning and Travel Scheduling (ADAPTS) model

This paper describes the representation of the activity planning process utilized in a new activity-based microsimulation model called the ADAPTS (Agent-based Dynamic Activity Planning and Travel Scheduling) model, which dynamically simulates activity and travel planning and scheduling. The model utilizes a dynamic activity planning framework within the larger overall microsimulation system, which is a computational process model that attempts to replicate the decisions which comprise time-dependent activity scheduling. The model presents a step forward in which the usual concepts of activity generation and activity scheduling are significantly enhanced by adding an additional component referred to as activity planning in which the various attributes which describe the activity are determined. The model framework, therefore, separates activity planning from activity generation and treats all three components, generation, planning and scheduling, as separate discrete but dynamic events within the overall microsimulation. The development of the planning order model, which determines when and in what order each activity planning decision is made is the specific focus of this paper. The models comprising the planning order framework are developed using recent survey data from a GPS-based prompted recall survey. The model development, estimation, validation, and its use within the overall ADAPTS system are discussed. A significant finding of the study is the verification of the apparent transferability of the activity planning order model.     

Modeling activity conflict resolution strategies using scheduling process data

Developments in activity scheduling process data have recently allowed for much improvement and validation of rule-based activity scheduling models. The use of actual scheduling process data allows for a potentially more realistic model in terms of how the travel episodes are actually derived. Since these types of models are simulations of the scheduling process, scheduling conflicts naturally arise in the creation of the final schedule. The handling of these scheduling conflicts is a critical component of all rule-based activity models. Many of these models rely on the concept of priority of the activities to resolve conflicts. However, recent research has shown that this is often not how conflicts are actually resolved. In order to more accurately model actual conflict resolution behavior, scheduling process data was used to estimate conflict resolution rules using decision trees. The use of a conflict resolution model allows the strategy chosen to depend on the attributes of the individual and the conflicting activities, rather than assuming a prior definition of precedence based on the activity types. The conflict resolution decision showed reasonable ability to predict the resolution strategy chosen in actual scheduling process survey data, and represents an important advance in developing a functional computational process model of activity scheduling.     

Roadmap for free-floating bikeshare research and practice in North America

ABSTRACT

The deployment of smartphone-operated, non-station-based bicycle fleets (“dockless” or “free-floating” bikeshare) represents a new generation of bikesharing. Users locate bikes in these free-floating systems using Global Positioning Systems (GPS) and lock bikes in place at their destinations. In this paper, we review current free-floating bikesharing systems in North America and discuss priorities for future research and practice. Since launching in 2017, free-floating bikeshare has expanded rapidly to encompass 200+ systems operating 40,000+ bikes within 150+ cities. In contrast with previous systems, free-floating systems operate almost exclusively using commercial “for-profit” models, amidst concerns of financial sustainability. Governance for these systems is in early stages and can include operating fees, fleet size caps, safety requirements, parking restrictions, data sharing, and equity obligations. We identify research and practice gaps within the themes of usage, equity, sharing resources, business model, and context. While some existing bikesharing literature translates to free-floating systems, novel topics arise due to the ubiquity, fluidity, and business models of these new systems. Systems have numerous obstacles to overcome for long-term sustainability, including barriers common to station-based systems: limited supportive infrastructure, equity, theft or vandalism, and funding. Other unique obstacles arise in free-floating bikeshare around parking, sidewalk right of ways, varied bicycle types, and data sharing. This review offers background in and critical reflection on the rapidly evolving free-floating bikeshare landscape, including priorities for future research and practice. If concerns can be overcome, free-floating bikeshare may provide unprecedented opportunities to bypass congested streets, encourage physical activity, and support urban sustainability.     

A behavioral housing search model: Two-stage hazard-based and multinomial logit approach to choice-set formation and location selection

Residential location search has become an important topic to both practitioners and researchers as more detailed and disaggregate land-use and transportation demand models are developed which require information on individual household location decisions. The housing search process starts with an alternative formation and screening stage. At this level households evaluate all potential alternatives based on their lifestyle, preferences, and utilities to form a manageable choice set with a limited number of plausible alternatives. Then the final residential location is selected among these alternatives. This two-stage decision making process can be used for both aggregate zone-level selection as well as searching disaggregate parcel or building-based housing markets for potential dwellings. In this paper a zonal level household housing search model is developed. Initially, a household specific choice set is drawn from the entire possible alternatives in the area based on the average household work distance to each alternative. Following the choice set formation step, a discrete choice model is utilized for modeling the final residential zone selection of the household. A hazard-based model is used for the choice set formation module while the final choice selection is modeled using a multinomial logit formulation with a deterministic sample correction factor. The approach presented in the paper provides a remedy for the large choice set problem typically faced in housing search models.     

Integrating Climate and Ocean Change Vulnerability into Conservation Planning

Tropical coastal and marine ecosystems are particularly vulnerable to ocean warming, ocean acidification, and sea-level rise. Yet these projected climate and ocean change impacts are rarely considered in conservation planning due to the lack of guidance on how existing climate and ocean change models, tools, and data can be applied. Here, we address this gap by describing how conservation planning can use available tools and data for assessing the vulnerability of tropical marine ecosystems to key climate threats. Additionally, we identify limitations of existing tools and provide recommendations for future research to improve integration of climate and ocean change information and conservation planning. Such information is critical for developing a conservation response that adequately protects these ecosystems and dependent coastal communities in the face of climate and ocean change.