Response of electric vehicle drivers to dynamic pricing of parking and charging services: Risky choice in early reservations

Abstract When clusters of electric vehicles charge simultaneously in urban areas, the capacity of the power network might not be adequate to accommodate the additional electricity demand. Recent studies suggest that real-time control strategies, like dynamic pricing of electricity, can spread the demand and help operators to avoid costly infrastructure investments. To assess the effectiveness of dynamic pricing, it is necessary to understand how electric vehicle drivers respond to uncertain future prices when they charge their vehicle away from home. Even when data is available from electric vehicle trials, the lack of variability in electricity prices renders them insufficient for this analysis. We resolve this problem by designing a survey where we observe the stated preferences of the respondents for hypothetical charging services. A novel feature of this survey is its interface, which resembles an online or smartphone application for parking-and-charging reservations. The time-of-booking choices are evaluated within a risky-choice modelling framework, where expected utility and non-expected utility specifications are compared to understand how people perceive price probabilities. In the progress, we bring together theoretical frameworks of forward-looking behaviour in contexts where individuals were subject to equivalent price uncertainties. The results suggest that (a) the majority of the electric vehicle drivers are risk averse by choosing a certain price to an uncertain one and (b) there is a non-linearity in their choices, with a disproportional influence by the upper end of the price distribution. This approach gives new perspectives in the way people plan their travel activities in advance and highlights the impact of uncertainty when managing limited resources in dense urban centres. Similar surveys and analyses could provide valuable insights in a wide range of innovative mobility applications, including car-sharing, ride-sharing and on-demand services.

[1]  Garrett J. van Ryzin,et al.  Revenue Management Under a General Discrete Choice Model of Consumer Behavior , 2004, Manag. Sci..

[2]  D. Shoup,et al.  Getting the Prices Right , 2013 .

[3]  Robin Lindsey,et al.  State-dependent congestion pricing with reference-dependent preferences , 2011 .

[4]  Yanfeng Ouyang,et al.  Dynamic pricing and reservation for intelligent urban parking management , 2017 .

[5]  J. Neumann,et al.  Theory of games and economic behavior , 1945, 100 Years of Math Milestones.

[6]  John W. Polak,et al.  Modeling Joint Charging and Parking Choices of Electric Vehicle Drivers , 2015 .

[7]  John G. Wilson,et al.  Wait or buy? The strategic consumer: Pricing and profit implications , 2003, J. Oper. Res. Soc..

[8]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .

[9]  J. Driesen,et al.  The Impact of Charging Plug-In Hybrid Electric Vehicles on a Residential Distribution Grid , 2010, IEEE Transactions on Power Systems.

[10]  Flavien Balbo,et al.  Generic model for resource allocation in transportation. Application to urban parking management , 2016 .

[11]  John M. Rose,et al.  Interactive stated choice surveys: a study of air travel behaviour , 2012 .

[12]  D. Hensher,et al.  Stated Choice Methods: Analysis and Applications , 2000 .

[13]  A. Tversky,et al.  Prospect Theory : An Analysis of Decision under Risk Author ( s ) : , 2007 .

[14]  Ryuichi Kitamura,et al.  Reference Points in Commuter Departure Time Choice: A Prospect Theoretic Test of Alternative Decision Frames , 2004, J. Intell. Transp. Syst..

[15]  Piet H. L. Bovy,et al.  Identification of Parameters for a Prospect Theory Model for Travel Choice Analysis , 2008 .

[16]  Yanfeng Ouyang,et al.  Parking Space Management via Dynamic Performance-Based Pricing , 2015, ArXiv.

[17]  Jun Li,et al.  Are Consumers Strategic? Structural Estimation from the Air-Travel Industry , 2014, Manag. Sci..

[18]  J. R. DeShazo,et al.  Pricing Workplace Charging , 2014 .

[19]  Aruna Sivakumar,et al.  Design of a Strategic-Tactical Stated-Choice Survey Methodology Using a Constructed Avatar , 2011 .

[20]  Harikesh S. Nair,et al.  Intertemporal price discrimination with forward-looking consumers: Application to the US market for console video-games , 2006 .

[21]  Elliot Bendoly,et al.  Are Consumers Really Strategic? Implications from an Experimental Study , 2015 .

[22]  Charilaos Latinopoulos Efficient operation of recharging infrastructure for the accommodation of electric vehicles : a demand driven approach , 2015 .

[23]  J. Maule,et al.  Responses to complex pricing signals: Theory, evidence and implications for road pricing , 2007 .

[24]  Jordan J. Louviere,et al.  Quick and easy choice sets: Constructing optimal and nearly optimal stated choice experiments , 2005 .

[25]  Pinar Keskinocak,et al.  Analysis of a price markdown mechanism , 2001, Proceedings Third International Workshop on Advanced Issues of E-Commerce and Web-Based Information Systems. WECWIS 2001.

[26]  Yinghong Li,et al.  Predicting customer purchase behavior in the e-commerce context , 2015, Electron. Commer. Res..

[27]  S. Bekhor,et al.  An airline itinerary choice model that includes the option to delay the decision , 2017 .

[28]  Nicolò Daina,et al.  Modelling electric vehicle use and charging behaviour , 2014 .

[29]  Andrew Daly,et al.  New analysis issues in stated preference research , 1993 .

[30]  Xuanming Su,et al.  Intertemporal Pricing with Strategic Customer Behavior , 2007, Manag. Sci..

[31]  J. Bates,et al.  The valuation of reliability for personal travel , 2001 .

[32]  John M. Rose,et al.  Asymmetric preference formation in willingness to pay estimates in discrete choice models , 2008 .

[33]  Michel Bierlaire,et al.  BIOGEME: a free package for the estimation of discrete choice models , 2003 .

[34]  J. Polak,et al.  Nonlinearity and Specification of Attitudes toward Risk in Discrete Choice Models , 2007 .

[35]  Carl Binding,et al.  Charging service elements for an electric vehicle charging service provider , 2011, 2011 IEEE Power and Energy Society General Meeting.

[36]  J. Quiggin A theory of anticipated utility , 1982 .

[37]  Hamed Mohsenian Rad,et al.  Optimal Residential Load Control With Price Prediction in Real-Time Electricity Pricing Environments , 2010, IEEE Transactions on Smart Grid.

[38]  Henry X. Liu,et al.  Boundedly rational route choice behavior: A review of models and methodologies , 2016 .

[39]  K. Talluri,et al.  The Theory and Practice of Revenue Management , 2004 .

[40]  Manel Baucells,et al.  Behavioral Anomalies in Consumer Wait-or-Buy Decisions and Their Implications for Markdown Management , 2017 .

[41]  G. Fulli,et al.  A business case for Smart Grid technologies: A systemic perspective , 2011 .