Quantifying and Mapping Streetspace: a Geocomputational Method for the Citywide Analysis of Pedestrian and Vehicular Streetspace

The purpose of this paper is to present a methodology for quantifying streetspace designation across entire cities. The new street level data is generated using a geocomputational approach that both allows for a quantitative citywide description of streetspace at a micro-scale and that can be replicated across multiple cities. The high spatial resolution description of streetspace covering large urban areas can be valuable to city designers and urban planners in the context of current challenges of street congestion, promoting active travel and rapidly evolving mobility technologies. It is observed that London streetspace is assigned mainly to vehicles and wider streets relate to the street network hierarchy and concentrate in the inner city. The new street level data introduced here can yield important insights for street research, planning and design

On alleviating cell overload in vehicular scenarios

Fifth Generation (5G) networks will support countless new applications and new business models. One of the 5G paradigms is network slicing, which enables the integration of multiple logical networks each one tailored to the requirements of the different services that can be provided by both network operators and vertical industries. One of the services where 5G is expected to have a greatest impact is vehicular-to-everything (V2X) communications, which will have their stringent latency requirements now met. However, the mobility associated to vehicles can lead to cell overload compromising the required quality of service (QoS). To address this problem, in this paper we propose and evaluate the performance of three network overload alleviation techniques to control network congestion provoked by traffic jams using realistic vehicular traces in a network slicing environment. Firstly, we describe the architecture supporting V2X communications. Secondly, the network congestion control approaches are explained. Finally, after providing a complete description of the considered scenario, results will be detailed, showing that the network overload appearing during rush hour can be significantly reduced.This research was supported by the Spanish Centre for the Development of Industrial Technology (CDTI) and the Ministry of Economy, Industry and Competitiveness under grant/project CER-20191015 / Open, Virtualized Technology Demonstrators for Smart Networks (Open-VERSO).Peer ReviewedPostprint (author's final draft

Understanding the costs of urban transportation using causal inference methods

With urbanisation on the rise, the need to transport the population within cities in an efficient, safe and sustainable manner has increased tremendously. In serving the growing demand for urban travel, one of the key policy question for decision makers is whether to invest more in road infrastructure or in public transportation. As both of these solutions require substantial spending of public money, understanding their costs continues to be a major area of research. This thesis aims to improve our understanding of the technology underlying costs of operation of public and private modes of urban travel and provide new empirical insights using large-scale datasets and application of causal econometric modelling techniques. The thesis provides empirical and theoretical contributions to three different strands in the transportation literature. Firstly, by assessing the relative costs of a group of twenty-four metro systems across the world over the period 2004 to 2016, this thesis models the cost structure of these metros and quantifies the important external sources of cost-efficiency. The main methodological development is to control for confounding from observed and unobserved characteristics of metro operations by application of dynamic panel data methods. Secondly, the thesis provides a quantification of the travel efficiency arising from increasing the provision of road-based urban travel. A crucial pre-condition of this analysis is a reliable characterisation of the technology describing congestion in a road network. In pursuit of this goal, this study develops novel causal econometric models describing vehicular flow-density relationship, both for a highway section and for an urban network, using large-scale traffic detector data and application of non-parametric instrumental variables estimation. Our model is unique as we control for bias from unobserved confounding, for instance, differences in driving behaviour. As an important intermediate research outcome, this thesis also provides a detailed association of the economic theory underlying the link between the flow-density relationship and the corresponding production function for travel in a highway section and in an urban road network. Finally, the influence of density economies in metros is investigated further using large-scale smart card and train location data from the Mass Transit Railway network in Hong Kong. This thesis delivers novel station-based causal econometric models to understand how passenger congestion delays arise in metro networks at higher passenger densities. The model is aimed at providing metro operators with a tool to predict the likely occurrences of a problem in the network well in advance and materialise appropriate control measures to minimise the impact of delays and improve the overall system reliability. The empirical results from this thesis have important implications for appraisal of transportation investment projects.Open Acces

Rethinking Streets: a study of streetspace allocation metrics and street networks in London

This research investigates streetspace allocation metrics for all streets in London providing quantitative evidence about a key parameter of street design citywide. A new methodology to quantify streetspace allocation is introduced using a geocomputational approach that allows both the processing of high-resolution topographic data over a large geographic extent and enables replicability for other cities. The correlation between streetspace allocation metrics and street network centrality at distinct scales is investigated across different geographic areas. These variables are then examined using cluster analysis to identify a typology of streets based on streetspace allocation and centrality. The results provide the framework for a design scenario study of inner London applying shortest-path analysis under an active travel prioritisation perspective. Streetspace statistics for London confirm the predominance of space allocated for vehicular transport over pedestrian uses. Most streets display standard "residential" street metrics, coinciding with traditional street classification schemes. Also, this serves to demonstrate quantitatively the spatially efficient organisation of the London street system with few wider distributors and many narrower local streets. In addition, through the combined examination of the streets' allocation and configurational metrics, it is possible to identify a new sub-type of local streets. The spatial arrangement of the streets segments types follows a centre-periphery pattern: wider and higher centrality streets are clustered at the city centre and show relative larger streetspace designated to pedestrians, corresponding with higher levels of estimated activity. On a prescriptive streetspace model of Inner London, the streetspace allocation of critical pathways is modified to illustrate how strategic scale street properties affect and are affected by design scale street parameters. The fine-grain physical metrics analysed here, not only can be useful to tackle a wide range of contemporary street related questions from urban environmental quality to the adoption of new technologies but also offer alternative analytical methods for street research, planning and design

Business cases, potential new functions and technology implementation plan

D5.3.1: Business cases, and potential new functions has been renamed within D5.3.1 as follows: ‘Business cases, and potential new functions and Technology Implementation Plan’ - to include also the Technology Implementation Plan, planned in the DoW as the main outcome from T5.3.1 Exploitable Result Cases. This Deliverable includes references to the main activities to be performed in WP 5.3 Facilitation of Exploitation and has strong links to other Work packages and Sub Projects activities

A GIS-based methodology for evaluating the increase in multimodal transport between bicycle and rail transport systems. A case study in Palermo

Background: In a world where every municipality is pursuing the goals of more sustainable mobility, bicycle plays a fundamental role in getting rid of private cars and travelling by an eco-friendly mode of transport. Also, private and shared bikes can be used as a feeder transit system, solving the problem of the first and last-mile trips. Thanks to GIS (Geographic Information System) software, it is possible to evaluate the effectiveness of such a sustainable mean of transport in the future users’ modal choice. Methods: Running an accessibility analysis of cycling and rail transport services, the potential mobility demand attracted by these services and the possible multimodality between bicycle and rail transport systems can be assessed. Moreover, thanks to a modal choice model calibrated for high school students, it could be verified if students will be really motivated to adopt this solution for their home-to-school trips. Results: The GIS-based analysis showed that almost half of the active population in the study area might potentially abandon the use of their private car in favour of bike and its combination with public transport systems; furthermore, the percentage of the students of one high school of Palermo, the Einstein High School, sharply increases from 1.5% up to 10.1%, thanks also to the combination with the rail transport service. Conclusions: The GIS-based methodology shows that multimodal transport can be an effective way to pursue a more sustainable mobility in cities and efficiently connect suburbs with low-frequent public transport services to the main public transport nodes

Identifying and Characterising Active Travel Corridors for London in Response to COVID-19 Using Shortest Path and Streetspace Analysis

Covid-19 related restrictions are forcing public transport services to operate with less capacity. In response, trips are being channelled to walking and cycling. We use shortest-path analysis to identify all street-level connections between all rail and underground stations in inner London. We are able to identify the critical pathways which show a long tail distribution and a radial/cellular spatial pattern. We visually compare this network with the existing cycling network, and explore two scenarios of street interventions in 8 critical pathways using streetspace cross-section analysis. The methods presented here can offer valuable analytical capacity for developing new cycling and walking schemes and designing place-based streets that are more appropriate to control virus propagation

The pathway to sustainable passenger transport: a life cycle perspective of decarbonisation strategies

212 p.This thesis confronts the pressing challenge of mitigating transportation emissions in the face of escalating global mobility demands. It leverages Life Cycle Assessment (LCA) to explore strategies for curbing the Global Warming Potential (GWP) of both private and public vehicles in urban environments. Comparative studies underscore a striking 23% increase in emissions within urban settings compared to rural ones. Simulated scenarios within a medium-sized city reveal the potential for substantial emissions reductions, reaching up to 64.28%, through interventions like limiting daily trips and expanding public transportation options.Furthermore, the research evaluates optimal replacement times for petrol cars, showcasing the importance of running electric vehicles with renewable energy in order to make them efficient alternatives. This work underscores the significance of tailored policies that account for social behaviour, commuting patterns, and specific environmental concerns, essential for achieving successful low-carbon urban transportation solutions.Life Cycle Thinking Grou