Data

Economic Assessment of Electric-Drive Vehicle Operation in California and Other U.S. Regions

Jeffrey Lidicker
Tim Lipman
Susan Shaheen
2010

This study examines the relative economics of electric vehicle operation in the context of current electricity rates in specific utility service territories. Fourteen utility territories offering electric vehicle (EV) rates were examined, with a focus on California but including other regions of the United States. The consumer costs of EV charging were examined in comparison with gasoline price data, geographic location, and three highly variable gasoline price periods: July 2008, January 2009, and July 2009. In a switch from a conventional 23 mpg (10.2-L/100 km) vehicle to a 300 Wh/mi...

Challenges and Opportunities for Electric Vehicle Charging Detection Using Utility Energy Consumption Data

Elpiniki Apostolaki-Iosifidou
Soomin Woo
Tim Lipman
2019

Partly in response to ongoing environmental and energy security concerns, and with supportive government policies, the total number of electric vehicles (EVs) has been rapidly increasing in the last years worldwide. The growing EV penetration into the electric power system changes the electricity consumption profiles and leads to challenges for different stakeholders such as transmission system operators and electric utilities. Electric utilities benefit from having information of EV charging to forecast any additional load and peaks, to understand temporal and spatial aspects, and to...

Electric Vehicle Charge Management for Lowering Costs and Environmental Impact

Elpiniki Apostolaki-Iosifidou
Marco Pruckner
Soomin Woo
Tim Lipman
2020

As the number of electric vehicles is increasing, there is a pervasive call for research and new strategies in the field of vehicle grid integration. Using electric vehicle real-time data, drivers' spatial behavior and patterns can be derived for their morning and evening commute. These patterns combined with dynamic electricity costs, wholesale and retail, and variable greenhouse gas (GHG) emissions, lead to significant outcomes on savings and environmental impact. In this study, electric vehicle charging management is analyzed for the case of north California, using real world data. The...

Optimal Sampling Strategies for Statistical Models with Discrete Dependent Variables

Carlos Daganzo
1980

The object of this paper is to improve the cost-effectiveness of data gathering procedures for models with discrete dependent variables. It is assumed throughout the paper that the true value of the parameter vector is approximately known and that, with that information, one must select a statistically optimal number of observations from different population subgroups to refine the accuracy of the estimate. It is shown that the problem can be reduced to a small mathematical program whose objective function can be written after a few preliminary algebraic manipulations. For binary choice...

Multinomial Probit with Time-Series Data: Unifying State Dependence and Serial Correlation Models

Carlos Daganzo
Sheffi, Y.
1982

This paper develops a general method for treating discrete data sets containing individuals that have made more than one choice under varying stimuli. The multinomial probit model is shown to possess properties that make it very attractive for this application, as with it, it is possible to develop an estimation process that uses all the information in the data, and is both relatively inexpensive and consistent with utility maximization. The method, which is a generalization of Heckman's binary model, can include taste variations and more than two alternatives.

Extrapolating Automobile Usage Data to Long Time Periods

Horowitz, Abraham D.
Carlos Daganzo
1986

This study illustrates a statistical procedure that can be used to estimate the fraction of a given population experiencing a “rare” event during a long time period, given a few days of observation. In an automobile usage context, the rare event could be the occurrence of an automobile occupancy of four or more persons and/or a travel distance of 100 miles or more on any given day. The technique, which can be important for the design of durable goods, is illustrated with four numerical examples.

Bounding the VRP Distance Before Knowing the Location of Points

Carlos Daganzo
1991

This note presents upper bounds for the minimum distance needed to visit n points in a unit circle, with a vehicle fleet based at its center and allowed to visit a maximum of q points per vehicle tour. The paper shows that the minimum distance can never exceed: [2n/q]+ + pi q. If points are randomly and uniformly distributed, and travel can only take place on a ring-radial network, the paper also proves that for q = 0(n**beta), 0 less than beta less than 1/2, the average minimum distance does not exceed: [4n/3q] + 0.82(pi n)**1/2 + 0(q). For the Euclidean metric, it is claimed that a...

Predictability of Time-Dependent Traffic Backups and Other Reproducible Traits in Experimental Highway Data

Smilowitz, Karen
Carlos Daganzo
1999

Traffic data from a 4-mile long congested rural road in Orinda, California, are used to show that traffic delays and vehicle accumulations between any two generic observers located inside a road section can be predicted from the traffic counts measured at the extremes of the section. The traffic model does not require "recalibration" on the day of the experiment, and works well despite what appears to be location-specific driver behavior.

Asymptotic Approximations for the Transportation LP and Other Scalable Network Problems

Carlos Daganzo
Smilowitz, Karen R.
2000

Network optimization problems with a "scalable" structure are examined in this report. Scalable networks are embedded in a normed space and must belong to a closed family under certain transformations of size (number of nodes) and scale (dimension of the norm). The transportation problem of linear programming (TLP) with randomly distributed points and random demands, the earthwork minimization problem of highway design, and the distribution of currents in an electric grid are examples of scalable network problems. Asymptotic formulas for the optimum cost are developed for the case where...

In Traffic Flow, Cellular Automata = Kinematic Waves

Carlos Daganzo
2004

This paper proves that the vehicle trajectories predicted by (i) a simple linear carfollowing model, CF(L), (ii) the kinematic wave model with a triangular fundamental diagram, KW(T), and (iii) two cellular automata models CA(L) and CA(M) match everywhere to within a tolerance comparable with a single "jam spacing". Thus, CF(L) = KW(T) = CA(L,M).