Incorporation of micro-level analysis in strategic urban transport modelling: with a case study of the Greater Beijing

Many developing countries and regions are suffering from severe urban transport problems arising from accidents, congestion, air pollution, rising carbon intensity, and chronic under-funding of infrastructure and services. The problems make those cities the most polluted and often the least liveable. Strategic transport modelling has been recognised as an effective approach for developing and testing policy options, especially where it is integrated with land use planning and urban design. However, in most developing-country cities strategic transport modelling has been out of reach for practical policy use because of its sophisticated data and skill requirements, which currently imply unaffordable high costs and long durations for model development. This means that strategic urban transport modelling is the least available where it is needed most urgently. Meanwhile, the spread of smart data in mapping and urban activity monitoring has often been just as rapid in developing countries as in the developed. This has triggered new approaches in micro-level analyses of transport networks, personal movements and vehicles. In the most advanced cases, the new analyses have started to influence strategic modelling. The main hypothesis of this dissertation is that an incorporation of the micro-level smart data and analyses in strategic urban transport modelling will make it feasible to establish a sufficiently robust strategic transport model for evidence-based policy analysis with cost, time and skill thresholds that are close to being affordable in developing country cities. In order to test this main hypothesis, a number of novel model development tasks have been carried out which contribute to the field of applied urban modelling. This new approach aims to contribute to the transformation of the prevailing modus operandi where model development could not start in earnest until extensive data collection and skills training have been completed to a situation where a sufficiently robust model can be established cheaply and quickly to support on-going and incremental refinements. More specifically, new modelling tools have been developed as part of this dissertation using sparse GPS taxi traces to identify slow-moving and stopping traffic hotspots using an extended density-based spatial clustering algorithm that is tolerant of significant data noise, and to estimate congested road speeds (which used to be very costly and time-consuming to obtain if at all). The micro-level network, congested speeds and insights into the nature of the congested traffic have been incorporated into a MEPLAN-based strategic transport model interacting with a MEPLAN-based land use and travel demand model. This means that the strategic economic, social and environmental impacts of transport interventions can be tested in a robust way through accounting for the interactions among transport, land-use and background social-technical trends. A new approach to establish the medium to long term visions for alternative travel demand management and transport investment scenarios has been tested using this model. The methods and algorithms have been tested in a case study of the Greater Beijing region, which consists of the municipalities of Beijing and Tianjin together with the surrounding areas in the province of Hebei. The government’s data regulations of restricting overseas studies to using only publicly available data sources have made the case study ideal for testing the new approach. The potential of the new strategic urban transport model has been tested through a wide range of policy scenarios. The results suggest that the new approach developed in this dissertation has made it not only cheaper and faster to develop a robust model, but could also potentially fill a gap in the lack of medium to long term perspectives regarding major road and metro investments over the next two decades. Such analyses could be of critical importance in improving the performance of the transport system in terms of safety, economic efficiency, air quality and carbon reduction given the long lead times to plan and deliver transport infrastructure investments

Quantifying the Effects of Sustainable Urban Mobility Plans

This technical note uses the expert scoring information available in current scientific literature in order to explore the impacts and effects that different urban measures may have in planning for sustainability on a European wide level.JRC.J.1-Economics of Climate Change, Energy and Transpor

Inferring transportation mode from smartphone sensors:Evaluating the potential of Wi-Fi and Bluetooth

Understanding which transportation modes people use is critical for smart cities and planners to better serve their citizens. We show that using information from pervasive Wi-Fi access points and Bluetooth devices can enhance GPS and geographic information to improve transportation detection on smartphones. Wi-Fi information also improves the identification of transportation mode and helps conserve battery since it is already collected by most mobile phones. Our approach uses a machine learning approach to determine the mode from pre-prepocessed data. This approach yields an overall accuracy of 89% and average F1 score of 83% for inferring the three grouped modes of self-powered, car-based, and public transportation. When broken out by individual modes, Wi-Fi features improve detection accuracy of bus trips, train travel, and driving compared to GPS features alone and can substitute for GIS features without decreasing performance. Our results suggest that Wi-Fi and Bluetooth can be useful in urban transportation research, for example by improving mobile travel surveys and urban sensing applications

Transport systems analysis : models and data

Funding: This research project has been funded by Spanish R+D Programs, specifcally under Grant PID2020-112967GB-C31.Rapid advancements in new technologies, especially information and communication technologies (ICT), have significantly increased the number of sensors that capture data, namely those embedded in mobile devices. This wealth of data has garnered particular interest in analyzing transport systems, with some researchers arguing that the data alone are sufficient enough to render transport models unnecessary. However, this paper takes a contrary position and holds that models and data are not mutually exclusive but rather depend upon each other. Transport models are built upon established families of optimization and simulation approaches, and their development aligns with the scientific principles of operations research, which involves acquiring knowledge to derive modeling hypotheses. We provide an overview of these modeling principles and their application to transport systems, presenting numerous models that vary according to study objectives and corresponding modeling hypotheses. The data required for building, calibrating, and validating selected models are discussed, along with examples of using data analytics techniques to collect and handle the data supplied by ICT applications. The paper concludes with some comments on current and future trends

THE IMPACT OF TELECOMMUNICATION AND TRANSPORT ON SPATIAL BEHAVIOUR

Telecommunication has not only for the sender but as well for the addressee both mobile and immobile elements. Regarding telecommunication in the interpersonal context with the related traffic behaviour, it becomes clear that telecommunication has so far an unknown influence on our spatial behaviour. Based on these considerations a concept is being developed to demonstrate the influence, the use and the increasing penetration of communication and information media on spatial behaviour of humans. The question, which effects are to be considered from this for the future and in which way it affects planning of interventions in the traffic sector, follows directly. On the basis of empirical results from Germany, Sweden and Korea it is shown that additional communication and information possibilities have no decreasing affect on the physical mobility of humans. Based on this result the advantages of novel communication and information services are being systematised to analyse the impacts on spatial behaviour in detail. For this it is possible to fall back on data-sets ranging from the mega-city Seoul over cities and rural regions in Germany to remote areas in Sweden. So it is to be expected that certain time-consuming, standardise and according to their nature suitable activities/ trips (e. g. telebanking) might be substituted in the every day live. At the same time, however, it is to be expected that far distant destinations can be more easily investigated by better information and communication possibilities, in order to lead afterwards to additional physical mobility - thus an induction of physical transport appears this way. The increases are to be expected fewer in everyday life transport, since the financial and temporal budget restrictions are effective here due to capacity limitations of the traffic system. Rather increases in the weekend and holiday traffic are to be expected, where either by the generated interest via simplified information access or by the decrease of initial trave) thresholds (reduction of uncertainties concerning the selected destination by telecommunications) additional journeys can be performed. Within the leisure area and the global business and service area activities and appropriate journeys are thus generated, which would not have been possible without existence of the electronic media. Finally, it is stated, which (feedback-) effects result on the structure of demand, if more spontaneous acts caused by information and communication technologies provoke critical and on a long-term basis not calculable effects

Econometric Modeling for the Analysis of the Influence of Safety Perceptions on Travelers’ Behavior

The objective of this research is to study the influence that safety perceptions have on travelers’ behavior in a broad array of choice contexts and investigate issues that have not been sufficiently addressed by the transportation literature, such as the influence of tangible attributes on perceptions and the influence of indicators’ complexity on the model estimates. Using three existing databases, we study the influence of risk perception on drivers' behavior, the influence of safety and comfort perceptions on individuals’ preferences for inland waterway passenger transportation, and the influence of these latent variables in the competition between BRT and motorcycle taxis. We design two ad-hoc surveys, the first one to study the influence of safety perceptions and some individual attitudes toward cycling, on the intention to use the public transportation integration on a bike and ride strategy. The second survey study safety and comfort perceptions of riding conventional feeder buses and auto-rickshaws as part of a BRT system. We demonstrate that tangible attributes have a significant effect on both the utility and the safety perception of individuals, which allows for the evaluation of policies related to latent variables and studying how a certain policy modifies safety perception. We also prove that the number of indicators per latent variable, the type of the scale and the granularity in which indicators are measured do affect the error variance of the measurement component. We show that the use of odd-numbered Likert scales contributes to a lower error variance of the measurement component

Feasibility Study of a Campus-Based Bikesharing Program at UNLV

Bikesharing systems have been deployed worldwide as a transportation demand management strategy to encourage active modes and reduce single-occupant vehicle travel. These systems have been deployed at universities, both as part of a city program or as a stand-alone system, to serve for trips to work, as well as trips on campus. The Regional Transportation Commission of Southern Nevada (RTCSNV) has built a public bikesharing system in downtown Las Vegas, approximately five miles from the University of Nevada, Las Vegas (UNLV). This study analyzes the feasibility of a campus-based bikesharing program at UNLV. Through a review of the literature, survey of UNLV students and staff, and field observations and analysis of potential bikeshare station locations, the authors determined that a bikesharing program is feasible at UNLV