Publications
101 results found
Pawlak J, Circalla G, Polak J, et al., 2015, Is There Anything Exceptional about ICT Use while Travelling as Compared to Other Contexts, and is it Good or Bad? Empirical Insights into Multitasking Patterns and their Well-being Implications, International Association for Travel Behaviour Research (IATBR)
Pawlak J, Le Vine S, Polak J, et al., 2015, ICT and Physical Mobility – State of Knowledge and Future Outlook, ICT and Physical Mobility – State of Knowledge and Future Outlook, Munich, Publisher: Institute for Mobility Research ifmo: A Research Facility of the BMW Group
Pawlak J, Polak J, Sivakumar A, et al., 2015, Investigating Diffusion of Relationships between ICT and Travel Behaviour by Pooling Independent Cross-sectional Data across Time, 94th Annual Meeting of Transportation Research Board
Daina, Polak, Sivakumar, 2015, Patent and Latent Predictors of Electric Vehicle Charging Behavior, Transport Research Board 94th Annual Meeting
Anvari B, Bell MGH, Sivakumar A, et al., 2015, Modelling shared space users via rule-based social force model, Transportation Research Part C: Emerging Technologies, Vol: 51, Pages: 83-103
Pawlak J, Zolfaghari A, Polak J, 2015, Imputing Socioeconomic Attributes for Movement Data by Analysing Patterns of Visited Places and Google Places Database: Bridging between Big Data and Behavioural Analysis, 4th International Choice Modelling Conference
Pawlak J, Polak J, Sivakumar A, 2015, Investigating Conditions for Robust Fusion of ICT and Travel Behaviour Datasets, International Association for Travel Behaviour Research (IATBR) Conference
Latinopoulos C, Sivakumar A, Polak JW, 2015, Modeling Joint Charging and Parking Choices of Electric Vehicle Drivers Decentralized Control Approach for Charging Service Providers, TRANSPORTATION RESEARCH RECORD, Pages: 124-133, ISSN: 0361-1981
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- Citations: 1
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
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- Citations: 16
Pawlak J, Polak JW, Sivakumar A, 2014, Towards a microeconomic framework for modelling the joint choice of activity–travel behaviour and ICT use, Transportation Research Part A - Policy and Practice, Vol: 76, Pages: 92-112, ISSN: 0965-8564
The rapid development of information and communication technologies (ICT) has been argued to affect time use patterns in a variety of ways, with consequent impacts on travel behaviour. While there exists a significant body of empirical studies documenting these effects, theoretical developments have lagged this empirical work and in particular, microeconomic time allocation models have not to date been fully extended to accommodate the implications of an increasingly digitised society. To address this gap, we present a modelling framework, grounded in time allocation theories and the goods–leisure framework, for joint modelling of the choice of mode of activity (physical versus tele-activity), travel mode and route, and ICT bundle. By providing the expression for a conditional indirect utility function, we use hypothetical scenarios to demonstrate how our framework can conceptualise various activity–travel decision situations. In our scenarios we assume a variety of situations such as the implications of severe weather, the introduction of autonomous vehicles, and the interaction between multiple decision makers. Moreover, our approach lays the microeconomic foundations for deriving subjective values of ICT qualities such as broadband speed or connection reliability. Finally, we also demonstrate the means by which our framework could be linked to various data collection protocols (stated preference exercises, diaries of social interactions, laboratory experiments) and modelling approaches (discrete choice modelling, hazard-based duration models).
Maldonado-Hinarejos R, Sivakumar A, Polak JW, 2014, Exploring the role of individual attitudes and perceptions in predicting the demand for cycling: a hybrid choice modelling approach, TRANSPORTATION, Vol: 41, Pages: 1287-1304, ISSN: 0049-4488
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- Citations: 61
Le Vine SE, Lee-Gosselin MEH, Sivakumar A, et al., 2014, A new approach to predict the market and impacts of round-trip and point-to-point carsharing systems: case study of London, Transportation Research Part D: Transport and Environment, Vol: 32, Pages: 218-229, ISSN: 1361-9209
There are nearly two million subscribers to carsharing services worldwide. These services can provide large benefits both to users and the general public (e.g. through emissions reductions). There has not however previously existed a general framework for forecasting their market potential and impacts that is sensitive to the way that they re-structure the costs associated with personal car ownership. Techniques for predicting market scope and impacts ahead of field implementation are urgently required, both by entrepreneurs and the public sector, whose support, or at least acquiescence, is generally required.This paper draws on the Perceived Activity Set conceptual framework that was recently developed to address the methodological challenges posed by carsharing, and presents the first set of empirical findings from employing it to model carsharing. The empirical analysis makes uses of pooled data from the British National Travel Survey and a purpose-designed stated-choice survey. We investigate both the ‘round-trip’ and ‘point-to-point’ carsharing service models.The results suggest that the number of prospective subscribers to a point-to-point carsharing service in London is between three and four times as large as the comparable number for round-trip carsharing. The greatest reduction in overall vehicle-miles of travel – including both carsharing cars and private cars – was found from introducing round-trip carsharing across all of London. Survey respondents indicated they would use point-to-point carsharing for commuting journeys much more frequently than round-trip carsharing. Finally, point-to-point carsharing was found to be a substitute for public transport, whilst round-trip carsharing was found to be a complement.
Daina, 2014, Modelling electric vehicle use and charging behaviour
Pawlak J, Polak JW, Sivakumar A, 2014, Microsimulation-Based Estimation of Value of Employer's Business Traveler's Value of Time: Comparison with Current Estimation Practices and Implications for Investment Appraisal, 93rd Annual Meeting of Transportation Research Board
Zolfaghari A, Sivakumar A, Polak JW, 2014, Simplified probabilistic choice set formation models in a residential location choice context
The implementation of a theoretically sound, two-stage discrete-choice modelling paradigm incorporating probabilistic choice sets is impractical when the number of alternatives is large, which is a typical case in most spatial choice contexts. In the context of residential location choice, Kaplan et al., 2009, Kaplan et al., 2011 and Kaplan et al., 2012 (KBS) developed a semi-compensatory choice model incorporating data of individuals searching for dwellings observed using a customised real estate agency website. This secondary data is used to compute the probability of considering a choice set that takes the form of an ordered probit model. In this paper, we illustrate that the simplicity of the KBS model arises because of an unrealistic assumption that individuals' choice sets only contain alternatives that derive from their observed combination of thresholds. Relaxing this assumption, we introduce a new probabilistic choice set formation model that allows the power set to include all potential choice sets derived from variations in thresholds' combinations. In addition to extending the KBS model, our proposed model asymptotically approaches the classical Manski model, if a suitable structure is used to categorise alternatives. In order to illustrate the biases inherent in the original KBS approach, we compare it with our proposed model and the MNL model using a Monte Carlo experiment. The results of this experiment show that the KBS model causes biases in predicted market share if individuals are free to choose from any potential choice sets derived from combinations of thresholds.
Anvari B, Bell MGH, Sivakumar A, et al., 2013, Modelling of Shared Space Users Using Rule-based Social Forces to Verify New Design Approaches, IEEE Transactions on Intelligent Transportation Systems
Daina, Sivakumar, Polak, 2013, Modelling the Effects of Driving Range Uncertainty on Electric Vehicle Users’ Charging Behaviour, International Choice Modelling Conference 2013
Le Vine S, Lee-Gosselin M, Sivakumar A, et al., 2013, A new concept of accessibility to personal activities: development of theory and application to an empirical study of mobility resource holdings, JOURNAL OF TRANSPORT GEOGRAPHY, Vol: 31, Pages: 1-10, ISSN: 0966-6923
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- Citations: 20
Pawlak J, Sivakumar A, Polak JW, 2013, An Imputation Approach to the Fusion of Travel Diary and Lifestyle Data: Application to the Analysis of the Interaction of ICT and Physical Mobility, New Technologies and Techniques for Statistics (NTTS) 2013 conference
, 2013, Activity-based modelling for urban energy systems, Urban Energy Systems, Publisher: Routledge, Pages: 226-239
, 2013, Urban transport technologies, Urban Energy Systems, Publisher: Routledge, Pages: 140-158
Daina, Sivakumar, Polak, 2013, Electric Vehicle Market: Stated Valuation Of The Charging Operation, 45th Universities'Transport Study Group Conference
Sivakumar A, 2013, Activity-based modelling for urban energy systems, Urban Energy Systems: An Integrated Approach, Pages: 204-217, ISBN: 9780415529013
In this chapter, we present activity-based modelling techniques as a means of enhancing the behavioural modelling of demand within integrated urban energy model systems. The activity-based modelling paradigm is commonly used in state-of-the-art land usetransport model systems to develop bottom-up and policy-sensitive predictions of the demand for travel. This chapter describes the activity-based modelling paradigm and explores the role of activity-based models within urban energy systems.
Sivakumar A, Acha S, Keirstead J, 2013, Urban transport technologies, Urban Energy Systems: An Integrated Approach, Pages: 118-135, ISBN: 9780415529013
Urban areas offer significant opportunities for innovations in efficient transport technologies and services (Banister 2008). Emerging trends include the alternative fuel vehicles market (e.g. electric vehicles, hybrids, biofuels), co-operative vehicle infrastructure systems (e.g. automatic crash avoidance, fleet logistics management), realtime information and intelligent transport systems, and smart mobility services such as car and bike-sharing. This chapter will present an overview of the major trends and technologies that have the potential to create a significant impact on the urban transport system. In this chapter, we focus exclusively on technologies and services that are directly related to transport; there are a number of land use policies and developments influencing the design of the urban area that also have a significant impact on the transport system.
Le Vine S, Sivakumar A, Lee-Gosselin M, et al., 2013, Empirically Constrained Efficiency in a Strategic-Tactical Stated Choice Survey of the Usage Patterns of Emerging Carsharing Services, TRANSPORT SURVEY METHODS: BEST PRACTICE FOR DECISION MAKING, Editors: Zmud, LeeGosselin, Munizaga, Carrasco, Publisher: EMERALD GROUP PUBLISHING LTD, Pages: 453-470, ISBN: 978-1-78190-287-5
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- Citations: 1
Keirstead JE, Sivakumar A, 2012, Using Activity-Based Modeling to Simulate Urban Resource Demands at High Spatial and Temporal Resolutions, Journal of Industrial Ecology, Vol: 2012
Cities are increasingly recognized as major contributors to global resourceconsumption and other environmental problems. To date, urban industrialecology literature has focused largely on assessments of urban performance atannual whole-city scales, for example in descriptive urban metabolism studiesor strategic assessments of future policy directions. However implementingthese strategies and constructing e cient urban infrastructures in particularrequires greater spatial and temporal resolution in the underlying demanddata. As this information is rarely available, we demonstrate how activity-based modelling can be used to simulate these demand pro les. The methodis rst described in general before demonstrating its use in the simulationof electricity and gas demands in London. A simple regression model isused to convert activity pro les into resource demands and we discuss thestrengths and weaknesses of this approach, as well as evaluate future researchdirections.
Daina, Sivakumar, Polak, 2012, A Framework for Joint Analyses of Electric Vehicle Use and Charging, 13th International Conference on Travel Behaviour Research
Sivakumar A, Pinjari A, 2012, Recent advances in activity and travel pattern modelling, TRANSPORTATION, Vol: 39, Pages: 749-754, ISSN: 0049-4488
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- Citations: 1
Sivakumar A, Batley R, Polak JW, 2012, Toward the future of travel behaviour and demand modelling, TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH, Vol: 4, Pages: 75-77, ISSN: 1942-7867
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- Citations: 2
Keirstead J, Jennings M, Sivakumar A, 2012, A review of urban energy system models: approaches, challenges and opportunities, Renewable and Sustainable Energy Reviews, Vol: 6, Pages: 3847-3866
Energy use in cities has attracted signi cant research in recent years. However such a broad topic inevitably results in number of alternative interpretations of the problem domain and the modelling tools used in its study. This paper seeks to pull together these strands by proposing a theoretical de nition of an urban energy system model and then evaluating the state of current practice. Drawing on a review of 219 papers, ve key areas of practice were identi ed { technology design, building design, urban climate, systems design, and policy assessment - each with distinct and incomplete interpretations of the problem domain. We also highlight a sixth fi eld, land use and transportation modelling, which has direct relevance to the use of energy in cities but has been somewhat overlooked by the literature to date. Despite their diversity, these approaches to urban energy system modellingshare four common challenges in understanding model complexity, data quality and uncertainty, model integration, and policy relevance. We then examine the opportunities for improving current practice in urban energy systems modelling, focusing on the potential of sensitivity analysis and cloud computing,data collection and integration techniques and standards, and theuse of activity-based modelling as an integrating framework. The results indicate that there is signi cant potential for urban energy systems modelling to move beyond single disciplinary approaches towards a sophisticated integratedperspective that more fully captures the theoretical complexity of urban energy systems.
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