MOBILITY AND ACTIVITY SPACE: UNDERSTANDING HUMAN DYNAMICS FROM MOBILE PHONE LOCATION DATA

Studying human mobility patterns and people’s use of space has been a major focus in geographic research for ages. Recent advancements of location-aware technologies have produced large collections of individual tracking datasets. Mobile phone location data, as one of the many emerging data sources, provide new opportunities to understand how people move around at a relatively low cost and unprecedented scale. However, the increasing data volume, issue of data sparsity, and lack of supplementary information introduce additional challenges when such data are used for human behavioral research. Effective analytical methods are needed to meet the challenges to gain an improved understanding of individual mobility and collective behavioral patterns. This dissertation proposes several approaches for analyzing two types of mobile phone location data (Call Detail Records and Actively Tracked Mobile Phone Location Data) to uncover important characteristics of human mobility patterns and activity spaces. First, it introduces a home-based approach to understanding the spatial extent of individual activity space and the geographic patterns of aggregate activity space characteristics. Second, this study proposes an analytical framework which is capable of examining multiple determinants of individual activity space simultaneously. Third, the study introduces an anchor-point based trajectory segmentation method to uncover potential demand of bicycle trips in a city. The major contributions of this dissertation include: (1) introducing an activity space measure that can be used to evaluate how individuals use urban space around where they live; (2) proposing an analytical framework with three individual mobility indicators that can be used to summarize and compare human activity spaces systematically across different population groups or geographic regions; (3) developing analytical methods for uncovering the spatiotemporal dynamics of travel demand that can be potentially served by bicycles in a city, and providing suggestions for the locations and daily operation of bike sharing stations

Smart Work Centres: An Analysis of Demand in Western Sydney

This study sets out to explore the potential for smart work centres in the local government areas of Liverpool, Blacktown and Penrith in Western Sydney. Smart work centres are differentiated from other work environments like main workplace, serviced offices, coworking spaces, third spaces and home offices by location, operations and atmosphere. Targeted to serve teleworkers, they are located close to where people live, provide a fully serviced formal workplace but operate with a community atmosphere that engenders creativity and innovation. This report investigates the circumstances that support teleworking, examines the commuting patterns and demographics of the 3 LGAs, and then analyses census data to predict a demand for a centre in any one of the 3 locations. The report goes on to propose a scenario for a successful centre based on the findings from the research

Passengers’ choices in multimodal public transport systems : A study of revealed behaviour and measurement methods

The concept of individual choice is a fundamental aspect when explaining and anticipating behavioural interactions with, and responses to, static and dynamic travel conditions in public transport (PT) systems. However, the empirical rounding of existing models used for forecasting travel demand, which itself is a result of a multitude of individual choices, is often insufficient in terms of detail and accuracy. This thesis explores three aspects, or themes, of PT trips – waiting times, general door-to-door path preferences, with a special emphasis on access and egress trip legs, and service reliability – in order to increase knowledge about how PT passengers interact with PT systems. Using detailed spatiotemporal empirical data from a dedicated survey app and PT fare card transactions, possible cross-sectional relationships between travel conditions and waiting times are analysed, where degrees of mental effort are gauged by an information acquisition proxy. Preferences for complete door-todoorpaths are examined by estimation of full path choice models. Finally, longitudinal effects of changing service reliability are analysed using a biennial panel data approach. The constituent studies conclude that there are otherexplanatory factors than headway that explain waiting times on first boarding stops of PT trips and that possession of knowledge of exact departure times reduces mean waiting times. However, this information factor is not evidentin full path choice, where time and effort-related preferences dominate with a consistent individual preference factor. Finally, a statistically significant on-average adaption to changing service reliability is individual-specific andnon-symmetrical depending on the direction of reliability change, where a relatively large portion of the affected individuals do not appear to respond to small-scale perturbations of reliability while others do, all other thingsbeing equal

Cell Towers as Urban Sensors: Understanding the Strengths and Limitations of Mobile Phone Location Data

Understanding urban dynamics and human mobility patterns not only benefits a wide range of real-world applications (e.g., business site selection, public transit planning), but also helps address many urgent issues caused by the rapid urbanization processes (e.g., population explosion, congestion, pollution). In the past few years, given the pervasive usage of mobile devices, call detail records collected by mobile network operators has been widely used in urban dynamics and human mobility studies. However, the derived knowledge might be strongly biased due to the uneven distribution of people’s phone communication activities in space and time. This dissertation research applies different analytical methods to better understand human activity and urban environment, as well as their interactions, mainly based on a new type of data source: actively tracked mobile phone location data. In particular, this dissertation research achieves three main research objectives. First, this research develops visualization and analysis approaches to uncover hidden urban dynamics patterns from actively tracked mobile phone location data. Second, this research designs quantitative methods to evaluate the representativeness issue of call detail record data. Third, this research develops an appropriate approach to evaluate the performance of different types of tracking data in urban dynamics research. The major contributions of this dissertation research include: 1) uncovering the dynamics of stay/move activities and distance decay effects, and the changing human mobility patterns based on several mobility indicators derived from actively tracked mobile phone location data; 2) taking the first step to evaluate the representativeness and effectiveness of call detail record and revealing its bias in human mobility research; and 3) extracting and comparing urban-level population movement patterns derived from three different types of tracking data as well as their pros and cons in urban population movement analysis

Using Volunteer Tracking Information for Activity-Based Travel Demand Modeling and Finding Dynamic Interaction-Based Joint-Activity Opportunities

Technology used for real-time locating is being used to identify and track the movements of individuals in real time. With the increased use of mobile technology by individuals, we are now able to explore more potential interactions between people and their living environment using real-time tracking and communication technologies. One of the potentials that has hardly been taken advantage of is to use cell phone tracking information for activity-based transportation study. Using GPS-embedded smart phones, it is convenient to continuously record our trajectories in a day with little information loss. As smart phones get cheaper and hence attract more users, the potential information source for self-tracking data is pervasive. This study provides a cell phone plus web method that collects volunteer cell phone tracking data and uses an algorithm to identify the allocation of activities and traveling in space and time. It also provides a step that incorporates user-participated prompted recall attribute identification (travel modes and activity types) which supplements the data preparation for activity-based travel demand modeling. Besides volunteered geospatial information collection, cell phone users’ real-time locations are often collected by service providers such as Apple, AT&T and many other third-party companies. This location data has been used in turn to boost new location-based services. However, few applications have been seen to address dynamic human interactions and spatio-temporal constraints of activities. This study sets up a framework for a new kind of location-based service that finds joint-activity opportunities for multiple individuals, and demonstrates its feasibility using a spatio-temporal GIS approach

Modellierung der Zugänglichkeit zu öffentlichen Verkehrsmitteln auf der Grundlage von Raumbewegungsdaten

The thesis serves three objectives: 1) exploration of biking distances at individual transit stations from trajectory and smart card data, 2) investigation of transit catchment area to raise the public awareness of the transit accessibility at a general level, and 3) inspection of accessibility constrained by crowdedness at a fine-grained level.Die Dissertation hat drei Ziele: 1) Untersuchung der Fahrraddistanzen an den einzelnen Transitstationen anhand von Trajektorien- und Smartcard-Daten, 2) Untersuchung des Transit-Einzugsgebietes zur Sensibilisierung der Öffentlichkeit für die Zugänglichkeit des Transits auf allgemeiner Ebene und 3) Untersuchung der durch Überfüllung eingeschränkten Zugänglichkeit auf Detailebene

Exploring Travel and Activity Behavior in Transit-Oriented Developments: Insights Into Transportation Benefits and Travel Demand Modelling

As a sustainable urban development and transportation planning strategy, researchers and planners are increasingly interested in transit-oriented development (TOD). By integrating transit system and neighborhood design, TOD aims to provide a livable environment that is alternative mode friendly, higher density, and mixed-use to residents and workers in the vicinity of transit stations. Despite the recent growing interest in TOE), however, transportation benefits of TOD are not well quantified and characteristics of TOD are not adequately reflected in travel demand models. This dissertation contributes to understanding of the travel and activity behavior by comprehensively exploring them in the context of TOD. Key dimensions of the behavior identified and analyzed in this study are activity location, travel mode use, activity time allocation, location choice and sequence, and commute time and schedule delay. With a strong research design of comparing TOD (0.5 mile buffer areas around transit stations) with auto-oriented development (AOD) that features relatively low density and mainly residential use, behavioral differences in each dimension were hypothesized and tested. Focusing on the Washington, D.C. metropolitan area, this study used the state of the art address-based household travel survey (N=11,436). The validity of the data was systematically checked for 1) non-coverage errors due to recently increasing mobile phone-only households and 2) trip underreporting as measurement errors. The data appropriateness was confirmed. Rigorous statistical models were estimated at the household, person, trip, and activity levels, ranging from a local neighborhood to regional space. Results suggest that the travel and activity behavior between TOD and AOD contexts is significantly different. Key findings are that TOD residents tends to 1) make fewer and shorter automobile trips, but use transit more and walk more for their daily travel, 2) participate in out-of-home activities and sequence the activity locations centered on transit stations, and 3) commute more reliably (less variant travel time and more on-time arrival by using a subway or walking), compared to AOD residents. These are largely attributed to the characteristics of the integrated built and transportation environments (e.g., mixed-use, high density, walkable design, accessibility, and/or connectivity). Implications of the findings for sustainable urban development, travel demand modeling, and geographical travel time reliability are discussed

Sustainable Mobility for Island Destinations

This open access book presents the findings of the CIVITAS DESTINATIONS project regarding the link between mobility and tourism in urban areas and the complications tourist destinations face in becoming more sustainable. It integrates the tourist mobility needs and the associated fluctuation impacts in the design of mobility solutions in order to enforce the accessibility, attractiveness, efficiency and sustainability of transport services and infrastructure for both residents and tourists in island cities such as Rethymno, Crete, and Valetta, Malta. Sustainable Mobility for Island Destinations contains contributions from highly experienced academics, engineers, and planners in the area of sustainable tourism, mobility services, and smart solutions design companies assisting: the change of the mind set in insular and tourism areas; the adoption of green mobility systems and services; and monitoring the environmental benefits to assist towards the Climate Change. It explores the challenges tourist islands face, such as the seasonal fluxes in transport usage, the pressures of tourism to provide aesthetic green spaces, and the space issues of being an island in relation to economic potential and infrastructure construction. The book suggests areas for future research, and implementation of innovative systems and policies. It will be of interest to academics, planners, decision makers, and environmentalists

Examining and optimizing the BCycle bike-sharing system – A pilot study in Colorado, US

Many cities around the world have integrated bike-sharing programs into their public transit systems to promise sustainable, affordable transportation and reduce environmental pollution in urban areas. Investigating the usage patterns of shared bikes is of key importance to understand cyclist’s behaviors and subsequently optimize bike-sharing programs. Based on the historical trip records of bike users and station empty/full status data, this paper evaluated and optimized the bike-sharing program BCycle in the city of Boulder, Colorado, the United States, using a combination of different methods including the Potential Path Area (PPA) and the Capacitated Maximal Covering Location Problem (CMCLP). Results showed significantly different usage patterns between membership groups, revealed diverse imbalance patterns of bike supply and demand across stations in the city and provided three system upgrading strategies about maximizing the service coverage. This case study is committed to future energy conservation and sustainable energy systems nationwide and ultimately worldwide, by holding immerse potential to adapt the resulting optimization strategies to the cities with a similar urban context across the United States, as well as more emerging bike-sharing programs in other countries, such as China