Imperial College London

Dr Nicolò Daina

Faculty of EngineeringDepartment of Civil and Environmental Engineering

Research Fellow
 
 
 
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Contact

 

+44 (0)20 7594 6086n.daina

 
 
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Location

 

602Skempton BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

20 results found

Hardman S, Jenn A, Tal G, Axsen J, Beard G, Daina N, Figenbaum E, Jakobsson N, Jochem P, Kinnear N, Plötz P, Pontes J, Refa N, Sprei F, Turrentine T, Witkamp Bet al., 2018, A review of consumer preferences of and interactions with electric vehicle charging infrastructure, Transportation Research Part D: Transport and Environment, Vol: 62, Pages: 508-523, ISSN: 1361-9209

Abstract This paper presents a literature review of studies that investigate infrastructure needs to support the market introduction of plug-in electric vehicles (PEVs). It focuses on literature relating to consumer preferences for charging infrastructure, and how consumers interact with and use this infrastructure. This includes studies that use questionnaire surveys, interviews, modelling, GPS data from vehicles, and data from electric vehicle charging equipment. These studies indicate that the most important location for PEV charging is at home, followed by work, and then public locations. Studies have found that more effort is needed to ensure consumers have easy access to PEV charging and that charging at home, work, or public locations should not be free of cost. Research indicates that PEV charging will not impact electricity grids on the short term, however charging may need to be managed when the vehicles are deployed in greater numbers. In some areas of study the literature is not sufficiently mature to draw any conclusions from. More research is especially needed to determine how much infrastructure is needed to support the roll out of PEVs. This paper ends with policy implications and suggests avenues of future research.

Journal article

Latinopoulos C, Daina N, Polak J, Trust in IoT-enabled mobility services: predictive analytics and the impact of prediction errors on the quality of service in bike sharing, Living in the Internet of Things: Cybersecurity of the IoT

Conference paper

Daina N, Latinopoulos C, Manca F, Zavitsas K, Sivakumar A, Polak JWet al., 2018, An analysis of the joint dynamics of attitudes, intentions and behaviour in e-cycling, hEART 2018 - 7th Symposium of the European Association for Research in Transportation

Conference paper

Daina N, Modelling the user variable, Nature Energy, ISSN: 2058-7546

Journal article

Suel E, Daina N, Polak JW, 2017, A hazard-based approach to modelling the effects of online shopping on intershopping duration, Transportation, ISSN: 1572-9435

Despite growing prevalence of online shopping, its impacts on mobility are poorlyunderstood. This partially results from the lack of sufficiently detailed data. In thispaper we address this gap using consumer panel data, a new dataset for this context.We analyse one year long longitudinal grocery shopping purchase data from Londonshoppers to investigate the effects of online shopping on overall shopping activity pat-terns and personal trips. We characterise the temporal structure of shopping demandby means of the duration between shopping episodes using hazard-based durationmodels. These models have been used to study inter-shopping spells for traditionalshopping in the literature, however effects of online shopping were not considered.Here, we differentiate between shopping events and shopping trips. The former refersto all types of shopping activity including both online and in-store, while the latteris restricted to physical shopping trips. Separate models were estimated for each andresults suggest potential substitution effects between online and in-store in the contextof grocery shopping. We find that having shopped online since the last shopping tripsignificantly reduces the likelihood of a physical shopping trip. We do not observethe same effect for inter-event durations. Hence, shopping online does not have a sig-nificant effect on overall shopping activity frequency, yet affects shopping trip rates.This is a key finding and suggests potential substitution between online shopping andphysical trips to the store. Additional insights on which factors, including basket sizeand demographics, affect inter-shopping durations are also drawn.

Journal article

Manca F, Sivakumar A, Daina N, Axsen J, Polak Jet al., 2017, Exploring the inclusion of social influence in a hybrid choice model of electric vehicle (EV) purchase preferences, 6th Symposium of the European Association for Research in Transportation

Conference paper

Daina N, Sivakumar A, Polak JW, 2017, Electric vehicle charging choices: modelling and implications for smart charging services, Transportation Research Part C: Emerging Technologies, Vol: 81, Pages: 36-56, ISSN: 1879-2359

The rollout of electric vehicles (EV) occurring in parallel with the decarbonisation of the power sector can bring uncontested environmental benefits, in terms of CO2 emission reduction and air quality. This roll out, however, poses challenges to power systems, as additional power demand is injected in context of increasingly volatile supply from renewable energy sources. Smart EV charging services can provide a solution to such challenges. The development of effective smart charging services requires evaluating pre-emptively EV drivers’ response. The current practice in the appraisal of smart charging strategies largely relies on simplistic or theoretical representation of drivers’ charging and travel behaviour. We propose a random utility model for joint EV drivers’ activity-travel scheduling and charging choices. Our model easily integrates in activity-based demand modelling systems for the analyses of integrated transport and energy systems. However, unlike previous charging behaviour models used in integrated transport and energy system analyses, our model empirically captures the behavioural nuances of tactical charging choices in smart grid context, using empirically estimated charging preferences. We present model estimation results that provide insights into the value placed by individuals on the main attributes of the charging choice and draw implications charging service providers.

Journal article

Manca F, Sivakumar A, Daina N, Axsen J, Polak JWet al., 2017, Including social influence in choice models: comparison of different formulations, 5th International Choice Modelling Conference

Conference paper

Daina N, Sivakumar A, Polak JW, 2016, Modelling electric vehicles use: a survey on the methods, Renewable and Sustainable Energy Reviews, Vol: 68, Pages: 447-460, ISSN: 1879-0690

In the literature electric vehicle use is modelled using of a variety of approaches in power systems, energy and environmental analyses as well as in travel demand analysis. This paper provides a systematic review of these diverse approaches using a twofold classification of electric vehicle use representation, based on the time scale and on substantive differences in the modelling techniques. For time of day analysis of demand we identify activity-based modelling (ABM) as the most attractive because it provides a framework amenable for integrated cross-sector analyses, required for the emerging integration of the transport and electricity network. However, we find that the current examples of implementation of AMB simulation tools for EV-grid interaction analyses have substantial limitations. Amongst the most critical there is the lack of realism how charging behaviour is represented.

Journal article

N Daina, J W Polak, 2016, Hazard based modelling of electric vehicles charging patterns, 2016 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific), Publisher: IEEE, Pages: 479-484

Conference paper

Daina, Polak, Sivakumar, 2015, Capturing the Effect Range of Anxiety on Electric Vehicle Charging Behaviour: An Integrated Choice and Latent Variable Approach, 4th symposium of the European Association for Research in Transportation (hEART)

Conference paper

Daina, Polak, Sivakumar, 2015, Patent and Latent Predictors of Electric Vehicle Charging Behavior, Transport Research Board 94th Annual Meeting

Conference paper

Daina N, Polak JW, Sivakumar A, 2015, Patent and Latent Predictors of Electric Vehicle Charging Behavior, TRANSPORTATION RESEARCH RECORD, Pages: 116-123, ISSN: 0361-1981

Journal article

Daina, 2014, Modelling electric vehicle use and charging behaviour

Thesis dissertation

Daina, 2014, Empirically grounded electromobility microsimulations in smart grid contexts, 46th Universities' Transport Study Group Conference

Conference paper

Daina, Sivakumar, Polak, 2013, Modelling the Effects of Driving Range Uncertainty on Electric Vehicle Users’ Charging Behaviour, International Choice Modelling Conference 2013

Conference paper

Daina, Sivakumar, Polak, 2013, Electric Vehicle Market: Stated Valuation Of The Charging Operation, 45th Universities'Transport Study Group Conference

Conference paper

Daina, Sivakumar, Polak, 2012, A Framework for Joint Analyses of Electric Vehicle Use and Charging, 13th International Conference on Travel Behaviour Research

Conference paper

Daina, Sivakumar, Polak, 2012, Development of a Stated Response Survey for Electric Vehicle’s Users Charging and Mobility Behaviour, 44th Universities' Transport Study Group Conference

Conference paper

Corradi M, Daina N, Di Sciuva M, Gherlone M, Mattone Met al., 2010, Sensitivity Analysis and Optimization of Sandwich Plates with Metallic Foam Cores in the presence of Uncertain Parameters, 10th International Conference on Computational Structures Technology, Publisher: CIVIL COMP PRESS, ISSN: 1759-3433

Conference paper

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