TY - CONF

T1 - Spatiotemporal Analysis of the e-Mobility System in Newcastle-Gateshead Area

AU - El-Banhawy, Eiman

AU - Dalton, Ruth

PY - 2015/7/13

Y1 - 2015/7/13

N2 - The world is witnessing an accelerating expansion of urban areas and intensive urbanization. The robust relation between transport infrastructure and urban planning is reflected in how integrated and reliable any system is within the urban spatial system. Designing an integrated infrastructure to support full electric vehicle (EV) use is a crucial matter, which concerns planning authorities, policy makers, as well as current and potential users. Reducing range anxiety by facilitating access to public refuelling stations (RSs) is designed to overcome one of the main barriers that stops potential users to utilise EVs. The uncertainty of having a reliable and integrated charging infrastructure presents hurdles to, and slows down, the growing trend of smart ecosystems and sustainable urban communities as whole. Strategically locating non-domestic (public) EV charging points will help to pave the way for a better market penetration of EVs and, in space syntax terms, this involves establishing the spatial configurational correlates to successful charging locations. This paper analyses real information about EV usage of the year 2012, in one of these metropolitan areas. A case study of 38 charging points (CPs) with 120 EV users located in the inner urban core (NE1, NE4, and NE8 postcode districts) of a metropolitan area in the North-East England, the city of Newcastle upon Tyne, incorporating space-time analysis of the EV population, is presented. Information about usage and charging patterns has been collected from the main local service provider in the North East of England, Charge Your Car (CYC) Ltd. The primary methodology employed is a clustering analysis. It is conducted as a dimensional analysis technique for data mining and for significant analysis of quantitative datasets. A spatial (consisting of space syntax measures) and temporal analysis of charging patterns is conducted using SPSS and predictive analytics software. The study outcomes provide recommendations and an explorative design theory for the implementation of non-domestic EV charging infrastructure. This paper presents a methodological approach useful for planning authorities, policy makers and commercial agents in evaluating and measuring the degree of usability of the public electric mobility (e-mobility) system.

AB - The world is witnessing an accelerating expansion of urban areas and intensive urbanization. The robust relation between transport infrastructure and urban planning is reflected in how integrated and reliable any system is within the urban spatial system. Designing an integrated infrastructure to support full electric vehicle (EV) use is a crucial matter, which concerns planning authorities, policy makers, as well as current and potential users. Reducing range anxiety by facilitating access to public refuelling stations (RSs) is designed to overcome one of the main barriers that stops potential users to utilise EVs. The uncertainty of having a reliable and integrated charging infrastructure presents hurdles to, and slows down, the growing trend of smart ecosystems and sustainable urban communities as whole. Strategically locating non-domestic (public) EV charging points will help to pave the way for a better market penetration of EVs and, in space syntax terms, this involves establishing the spatial configurational correlates to successful charging locations. This paper analyses real information about EV usage of the year 2012, in one of these metropolitan areas. A case study of 38 charging points (CPs) with 120 EV users located in the inner urban core (NE1, NE4, and NE8 postcode districts) of a metropolitan area in the North-East England, the city of Newcastle upon Tyne, incorporating space-time analysis of the EV population, is presented. Information about usage and charging patterns has been collected from the main local service provider in the North East of England, Charge Your Car (CYC) Ltd. The primary methodology employed is a clustering analysis. It is conducted as a dimensional analysis technique for data mining and for significant analysis of quantitative datasets. A spatial (consisting of space syntax measures) and temporal analysis of charging patterns is conducted using SPSS and predictive analytics software. The study outcomes provide recommendations and an explorative design theory for the implementation of non-domestic EV charging infrastructure. This paper presents a methodological approach useful for planning authorities, policy makers and commercial agents in evaluating and measuring the degree of usability of the public electric mobility (e-mobility) system.

KW - Charging behaviour

KW - clustering analysis

KW - Design configuration

KW - Electric vehicles

KW - Spatial analysis

KW - Refuelling stations

M3 - Conference paper

T2 - The 10th Space Syntax Symposium (SSS10)

Y2 - 13 July 2015 through 17 July 2015

ER -