The potential use of smart cards in vehicle management with particular reference to the situation in Western Australia

Vehicle management may be considered to consist of traffic management, usage control, maintenance, and security. Various regulatory authorities undertake the first aspect, fleet managers will be concerned with all aspects, and owner-drivers will be interested mainly in maintenance and security. Car theft poses a universal security problem. Personalisation, including navigational assistance, might be achieved as a by-product of an improved management system. Authorities and fleet managers may find smartcards to be key components of an improved system, but owners may feel that the need for improved security does not justify its cost. This thesis seeks to determine whether smartcards may be used to personalise vehicles in order to improve vehicle management within a forseeable time and suggest when it might happen. In the process four broad questions are addressed. • First, what improvements in technology are needed to make any improved scheme using smartcards practicable, and what can be expected in the near future? • Second, what problems and difficulties may impede the development of improved management? • Third, what non-vehicle applications might create an environment in which a viable scheme could emerge? • Finally, is there a perceived need for improved vehicle management? The method involved a literature search, the issue of questionnaires to owner drivers and fleet managers, discussions with fleet managers, the preparation of data-flow and state diagrams, and the construction of a simulation of a possible security approach. The study concludes that although vehicle personalisation is possible- and desirable it is unlikely to occur within the next decade because the environment needed to make it practicable will not emerge until a number of commercial and standardisation problems that obstruct all smartcard applications have been solved

Exploring the relationship between intelligent transport system capability and business agility within the Bus Rapid Transit in South Africa

Abstract: More than 65% of South Africans use public transportation to access educational, business, and financial activity. Mobility of individuals and products, particularly in metropolitan areas, suffers from delays, unreliability, absence of safety and air pollution. On the other hand, mobility demand is increasing quicker than South Africa's accessible infrastructure. Public transport services are poor in general, but this picture is transforming a high-quality mass transit system using high-capacity buses along dedicated bus lanes by implementing the Bus Rapid Transit (BRT) system. The BRT system appeared as the leading mode of urban passenger transit in the first decade of the twenty-first century after a few pioneering applications in the later portion of the twentieth century. In addition, Intelligent Transport System’s (ITS) advantages motivate both advanced and developing nations, such as South Africa, to invest in these techniques rather than spending enormous quantities on expanding the transportation network. Various stakeholders in government, academia and industry are in the process of presenting a shared vision of this new strategy and first practical steps should be taken towards this objective. Intelligent transport system capacity can provide better and more inclusive public transportation facilities to commuters through enhanced reliability and accessibility; to operators through efficiency gains; and to customers and operators in terms of cost-effectiveness and service provision affordability. International experience shows that capacities of the ITS can boost transportation profits by as much as 10-15%...D.Phil. (Engineering Management

Formal Savings & Informal Insurance in Villages: A Field Experiment on Indirect Effects of Financial Deepening on Safety Nets of the Ultra-Poor

This thesis exploits a unique micro dataset that uses a natural field experiment to identify indirect effects of formal savings access on de facto ineligibles residing in the same community. Despite widespread interest in microfinance as a poverty-reduction tool, the indirect effects on the very poor of expanding formal financial services remain largely unexplored. This study examines evidence from a large field experiment which helps fill this gap. It also contributes to an important emerging literature on the indirect impacts of policy interventions in developing countries, often (incompletely) evaluated solely on the basis of how they impact participants and beneficiaries. In developing regions, households vulnerable to extreme poverty often benefit from long-standing local safety nets based on cash gifts and other transfers from relatives and friends, which help them smooth consumption across food-deficits and household shocks. To date, little is known about how these pre-existing practices are affected as community members begin adopting newly available formal financial services, and there remains much unexplored in the interaction of formal financial markets with informal safety nets. This paper addresses that gap by examining how formal savings expansion affects inter-household wealth transfers, with a particular emphasis on receipts by the most vulnerable. Using a rich panel dataset from Central Malawi that includes over 2,000 households, I find that experimentally boosting local savings uptake in rural areas leads to a strong positive effect on assistance receipts by non service-users during peak periods of hunger. The difference is strongest among the most vulnerable households. That is, the entrance of formal savings appears to complement local informal support systems for the highly vulnerable through an indirect mechanism, channeling greater wealth to such households during periods of food-deficits. The positive impacts of formal savings expansion on non service-users suggests that formal savings may have substantially greater benefits than would be suggested by focusing exclusively on the impacts experienced by the service-users themselves

Leveraging Geotagged Social Media to Monitor Spatial Behavior During Population Movements Triggered by Hurricanes

In a world of increased mobility and interconnectedness, the study of spatial behavior becomes more relevant than ever. However, multiple researchers have highlighted that the understanding of these dynamic processes has reached a bottleneck derived from the rigidity of traditional spatial behavior inquiry methods and the unavailability of trustworthy and relevant information. These difficulties are even more prominent during emergencies and disasters as these events often create scenarios where spatial behavior does not follow regular and logical patterns and where conventional mobility datasets are often skewed or not existent. Thus, many scholars working within the spatial behavior sub-discipline are pursuing innovative data collection methods to deepen the understanding of human spatial behavior. Researchers see digital geospatial trace data, also known as passive citizen sensor data, as one of the most promising opportunities to develop and test new hypotheses on spatial behavior. Nevertheless, the application of these new methods has not been fully explored within the hazard/disaster discipline for spatial behavior purposes under stressed situations. This dissertation investigates the suitability of geotagged social media (Twitter) as an innovative approach for the study of spatial behavior of people in stressed contexts and responds to three main research questions: 1) How well do geotagged social media estimate hurricane evacuation compliance? 2) To what extent is geotagged social media amenable for determining hurricane evacuation behavior? 3) How suitable is geotagged social media to evaluate post-disaster displacement and tourist flows? The dissertation therefore not only attempts to develop a new method to estimate the number of movements associated with the different stages of an emergency but also tries to answer long-standing questions about the response of different population sub-groups (residential status, gender, age, race/ethnicity) before, during, and after hurricanes. Results confirm the potential of geotagged social media to tackle some of the deficiencies of traditional approaches, particularly offering more timely, dynamic, and affordable information about the evacuation and post-disaster population movements. In addition, results demonstrate that the Twitter-based approach complements survey-based methods as it permits accessing underrepresented groups in traditional approaches such as the young, short-term residents, and racial/ethnic minorities. Although the representativeness of Twitter samples is still debatable and needs further research, this method to investigate emergency-triggered population movements can ultimately improve our understanding of the response and recovery phases of a disaster

A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions

Why should you read another book about transport and land use? This book differs in that we won’t focus on empirical arguments – we present political arguments. We argue the political aspects of transport policy shouldn’t be assumed away or treated as a nuisance. Political choices are the core reasons our cities look and function the way they do. There is no original sin that we can undo that will lead to utopian visions of urban life. The book begins by introducing and expanding on the idea of Accessibility. Then we proceed through several major parts: Infrastructure Preservation, Network Expansion, Cities, and Institutions. Infrastructure preservation concerns the relatively short-run issues of how to maintain and operate the existing surface transport system (roads and transit). Network expansion in contrast is a long-run problem, how to enlarge the network, or rather, why enlarging the network is now so difficult. Cities examines how we organize, regulate, and expand our cities to address the failures of transport policy, and falls into the time-frame of the very long-run, as property rights and land uses are often stickier than the concrete of the network is durable. In the part on Institutions we consider things that might at first blush appear to be short-run and malleable, are in fact very long-run. Institutions seem to outlast the infrastructure they manage. Many of the transport and land use problems we want to solve already have technical solutions. What these problems don’t have, and what we hope to contribute, are political solutions. We expect the audience for this book to be practitioners, planners, engineers, advocates, urbanists, students of transport, and fellow academics

CROWDSOURCED DATA FOR MOBILITY ANALYSIS

The importance of data in transportation research has been widely recognized since it plays a crucial role in understanding and analyzing the movement of people, identifying inefficiencies in transportation systems, and developing strategies to improve mobility services. This use of data, known as mobility analysis, involves collecting and analyzing data on transport infrastructure and services, traffic flows, demand, and travel behavior. However, traditional data sources have limitations. The widespread use of mobile devices, such as smartphones, has enabled the use of Information and Communications Technology (ICT) to improve data sources for mobility analysis. Mobile crowdsensing (MCS) is a paradigm that uses data from smart devices to provide researchers with more detailed and real-time insights into mobility patterns and behaviors. However, this new data also poses challenges, such as the need to fuse it with other types of information to obtain mobility insights. In this thesis, the primary source of data that is being examined and leveraged is the popularity index of local businesses and points of interest from Google Popular Times (GPT) data. This data has significant potential for mobility analysis as it overcomes limitations of traditional mobility data, such as data availability and lack of reflection of demand for secondary activities. The main objective of this thesis is to investigate how crowdsourced data can contribute to reduce the limitations of traditional mobility datasets. This is achieved by developing new tools and methodologies to utilize crowdsourced data in mobility analysis. The thesis first examines the potential of GPT as a source to provide information on the attractiveness of secondary activities. A data-driven approach is used to identify features that impact the popularity of local businesses and classify their attractiveness based on these features. Secondly, the thesis evaluates the possible use of GPT as a source to estimate mobility patterns. A tool is created to use the crowdness of a station to estimate transit demand information and map the precise volume and temporal dynamics of entrances and exits at the station level. Thirdly, the thesis investigates the possibility of leveraging the popularity of activities around stations to estimate flows in and out of stations. A method is proposed to profile stations based on the dynamic information of activities in catchment areas. Through this data, machine learning techniques are used to estimate transit flows at the station level. Finally, this study concludes by exploring the possibility of exploiting crowdsourced data not only for extracting mobility insights under normal conditions but also to extract mobility trends during anomalous events. To this end, we focused on analyzing the recovery of mobility during the first outbreak of COVID-19 for different cities in Europe

The Multi-Agent Transport Simulation MATSim

"The MATSim (Multi-Agent Transport Simulation) software project was started around 2006 with the goal of generating traffic and congestion patterns by following individual synthetic travelers through their daily or weekly activity programme. It has since then evolved from a collection of stand-alone C++ programs to an integrated Java-based framework which is publicly hosted, open-source available, automatically regression tested. It is currently used by about 40 groups throughout the world. This book takes stock of the current status. The first part of the book gives an introduction to the most important concepts, with the intention of enabling a potential user to set up and run basic simulations.The second part of the book describes how the basic functionality can be extended, for example by adding schedule-based public transit, electric or autonomous cars, paratransit, or within-day replanning. For each extension, the text provides pointers to the additional documentation and to the code base. It is also discussed how people with appropriate Java programming skills can write their own extensions, and plug them into the MATSim core. The project has started from the basic idea that traffic is a consequence of human behavior, and thus humans and their behavior should be the starting point of all modelling, and with the intuition that when simulations with 100 million particles are possible in computational physics, then behavior-oriented simulations with 10 million travelers should be possible in travel behavior research. The initial implementations thus combined concepts from computational physics and complex adaptive systems with concepts from travel behavior research. The third part of the book looks at theoretical concepts that are able to describe important aspects of the simulation system; for example, under certain conditions the code becomes a Monte Carlo engine sampling from a discrete choice model. Another important aspect is the interpretation of the MATSim score as utility in the microeconomic sense, opening up a connection to benefit cost analysis. Finally, the book collects use cases as they have been undertaken with MATSim. All current users of MATSim were invited to submit their work, and many followed with sometimes crisp and short and sometimes longer contributions, always with pointers to additional references. We hope that the book will become an invitation to explore, to build and to extend agent-based modeling of travel behavior from the stable and well tested core of MATSim documented here.