Phd Dissertation

A dynamic household alternative-fuel vehicle demand model using stated and revealed transaction information.

Publication Date

June 30, 1999

Author(s)

Hongyan Sheng

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment Zero-Emission Vehicles & Low-Carbon Fuels

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Abstract

Forecasting the demand for alternative-fuel vehicles (AFVs) is quite important for manufacturers, fuel suppliers and environmental planners. AFVs have attributes such as reduced range and limited refueling options that are very different from existing vehicles. Therefore stated preference (SP) data is necessary for demand models. Previous work by Brownstone, Bunch, and Train (1998) shows that there are serious biases in these stated preference data. Another source of households’ vehicle preference, is households’ actual observed transaction behavior (Revealed preference (RP) data). I develop a dynamic stated and revealed preference vehicle transaction model which uses the RP data to control for the biases of using pure SP data in order to better forecast households’ demand for AFVs for California. I implement a “scale factor” to specify the relationship of the different variances of the RP and SP data. Moreover, I examine the nested structure over different fuel-type vehicle choices and estimate both the multinomial logit (MNL) and nested logit (NL) models. In addition, I conduct forecast using the pure SP and joint SP-RP MNL models under the scenario consisting of new vehicle technologies for year 1998. Compared to the new vehicle sales statistics, it is obvious that the joint SP-RP model provides more reasonable forecasts. I also examine the different substitution patterns implied by the pure SP MNL and NL models when new vehicle choices are introduced. The NL model predicts more realistic substitution pattern. I also add the used vehicle choices to the forecast scenario to make the forecast more realistic because the used vehicle market is taken into consideration. Large panel data sets have been collected by the California Alternative-Fuel Vehicle Demand Forecast Project since May 1993. These data contain extensive information on households’ stated and revealed preference vehicle transactions, vehicle utilization and households’ socioeconomic characteristics. This study serves as an example of how to forecast new products or technologies that mark considerable departures from existing products or technologies.

Suggested Citation

Hongyan Sheng (1999) A dynamic household alternative-fuel vehicle demand model using stated and revealed transaction information.. PhD Dissertation. UC Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/17uq3m8/alma991035093101304701.

research report

Using UMTA Section 15 data for triennial reviews

Publication Date

June 1, 1987

Associated Project

Using UMTA Section 15 data for triennial reviews

Author(s)

Gordon (Pete) Fielding, Mark. Yamarone, Marcy Jaffe

Final Report

CA-06-0213-3

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

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Abstract

Illustrates the application of the Irvine Performance Evaluation Method (IPEM) to triennial reviews of transit performance conducted by the Urban Mass Transportation Administration under provisions of the Surface Transportation Assistance Act of 1982

Suggested Citation

Gordon J. Fielding, Mark. Yamarone and Marcy Jaffe (1987) Using UMTA Section 15 data for triennial reviews. Final Report CA-06-0213-3. Washington, D.C. : Springfield, Va.: U.S. Dept. of Transportation, Urban Mass Transportation Administration, Office of Grants Management ; Available through the National Technical Information Service. Available at: https://catalog.hathitrust.org/Record/102497535.

conference paper

An analysis of train emissions and their health impacts in California's alameda corridor

Proceedings of INFORMS, san diego, CA

Publication Date

October 1, 2009

Author(s)

Jean-Daniel Saphores, Mana Sangkapichai, Stephen Ritchie, Gunwoo Lee, Ghangshin Lee, I. You, Roberto Ayala

Suggested Citation

J. Saphores, M. Sangkapichai, S. Ritchie, G. Lee, I. You and R. Ayala (2009) “An analysis of train emissions and their health impacts in California's alameda corridor”, in Proceedings of INFORMS, san diego, CA.

published journal article

Modeling the dynamics of passenger travel demand by using structural equations

Environment & planning A

Publication Date

September 1, 1988

Author(s)

Thomas Golob, H Meurs

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Suggested Citation

T F Golob and H Meurs (1988) “Modeling the dynamics of passenger travel demand by using structural equations”, Environment & planning A, 20(9), pp. 1197–1218. Available at: 10.1068/a201197.

published journal article

Analysing non-linearities and threshold effects between street-level built environments and local crime patterns: An interpretable machine learning approach

Urban Studies

Publication Date

May 1, 2025

Author(s)

Sugie Lee, Donghwan Ki, John R Hipp, Jae Hong Kim

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

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Abstract

Despite the substantial number of studies on the relationships between crime patterns and built environments, the impacts of street-level built environments on crime patterns have not been definitively determined due to the limitations of obtaining detailed streetscape data and conventional analysis models. To fill these gaps, this study focuses on the non-linear relationships and threshold effects between built environments and local crime patterns at the level of a street segment in the City of Santa Ana, California. Using Google Street View (GSV) and semantic segmentation techniques, we quantify the features of the built environment in GSV images. Then, we examine the non-linear relationships and threshold effects between built environment factors and crime by applying interpretable machine learning (IML) methods. While the machine learning models, especially Deep Neural Network (DNN), outperformed negative binomial regression in predicting future crime events, particularly advantageous was that they allowed us to obtain a deeper understanding of the complex relationship between crime patterns and environmental factors. The results of interpreting the DNN model through IML indicate that most streetscape elements showed non-linear relationships and threshold effects with crime patterns that cannot be easily captured by conventional regression model specifications. The non-linearities and threshold effects revealed in this study can shed light on the factors associated with crime patterns and contribute to policy development for public safety from crime.

Suggested Citation

Sugie Lee, Donghwan Ki, John R Hipp and Jae Hong Kim (2025) “Analysing non-linearities and threshold effects between street-level built environments and local crime patterns: An interpretable machine learning approach”, Urban Studies, 62(6), pp. 1186–1208. Available at: 10.1177/00420980241270948.

published journal article

Building insights on true positives vs. false positives: Bayes’ rule

Decision Sciences Journal of Innovative Education

Publication Date

October 1, 2022

Author(s)

Alexander Robinson, Robin Keller, Cristina Del Campo

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Abstract

Abstract COVID‐19 pandemic policies requiring disease testing provide a rich context to build insights on true positives versus false positives. Our main contribution to the pedagogy of data analytics and statistics is to propose a method for teaching updating of probabilities using Bayes’ rule reasoning to build understanding that true positives and false positives depend on the prior probability. Our instructional approach has three parts. First, we show how to construct and interpret raw frequency data tables, instead of using probabilities. Second, we use dynamic visual displays to develop insights and help overcome calculation avoidance or errors. Third, we look at graphs of positive predictive values and negative predictive values for different priors. The learning activities we use include lectures, in‐class discussions and exercises, breakout group problem solving sessions, and homework. Our research offers teaching methods to help students understand that the veracity of test results depends on the prior probability as well as helps students develop fundamental skills in understanding probabilistic uncertainty alongside higher‐level analytical and evaluative skills. Beyond learning to update the probability of having the disease given a positive test result, our material covers naïve estimates of the positive predictive value, the common mistake of ignoring the disease’s base rate, debating the relative harm from a false positive versus a false negative, and creating a new disease test.

Suggested Citation

Alexander Robinson, L. Robin Keller and Cristina Del Campo (2022) “Building insights on true positives vs. false positives: Bayes’ rule”, Decision Sciences Journal of Innovative Education, 20(4), pp. 224–234. Available at: 10.1111/dsji.12265.

published journal article

Is the Journey to Work Explained by Urban Structure?

Urban Studies

Publication Date

November 1, 1993

Author(s)

Genevieve (Gen) Giuliano, Kenneth Small

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Abstract

Basic to several key issues in current urban economic theory and public policy is a presumption that local imbalances between employment and residential sites strongly influence people’s commuting patterns. We examine this presumption by finding the commuting pattern for the Los Angeles region in 1980 which would minimise average commuting time or distance, given the actual spatial distributions of job and housing locations. We find that the amount of commuting required by these distributions is far less than actual commuting, and that variations in required commuting across job locations only weakly explain variations in actual commuting. We conclude that other factors must be more important to location decisions than commuting cost, and that policies aimed at changing the jobs-housing balance will have only a minor effect on commuting.

Suggested Citation

Genevieve Giuliano and Kenneth A. Small (1993) “Is the Journey to Work Explained by Urban Structure?”, Urban Studies, 30(9), pp. 1485–1500. Available at: 10.1080/00420989320081461.

published journal article

The traffic statics problem in a road network

Transportation Research Part B: Methodological

Publication Date

December 1, 2012

Author(s)

Wenlong Jin

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Suggested Citation

Wen-Long Jin (2012) “The traffic statics problem in a road network”, Transportation Research Part B: Methodological, 46(10), pp. 1360–1373. Available at: 10.1016/j.trb.2012.06.003.

conference paper

Effect of route choice models on estimation of travel time reliability under demand and supply variations

Proceedings, First International Symposium on Transportation Network Reliability

Publication Date

January 1, 2002

Author(s)

Qi Alfred Chen, Z. Ji, Will Recker

Suggested Citation

A. Chen, Z. Ji and W. W. Recker (2002) “Effect of route choice models on estimation of travel time reliability under demand and supply variations”, in Proceedings, First International Symposium on Transportation Network Reliability. Kyoto.

published journal article

Uncertainty and the timing of an urban congestion relief investment.

Journal of Urban Economics

Publication Date

March 1, 2006

Author(s)

Jean-Daniel Saphores, Marlon Boarnet

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Abstract

We analyze the impact of population uncertainty on the socially optimum timing of a congestion-relief project in a linear monocentric city with fixed boundaries, where congestion pricing cannot be implemented. This project requires time to bear fruit but no urban land. Under certainty, we show that utility maximization is roughly equivalent to a standard benefit-cost analysis (BCA). Under Uncertainty, we derive an explicit optimal threshold for relieving congestion when the urban population follows a geometric Brownian motion. If the time to implement the project is short, we show analytically that deciding on the timing of congestion relief based on a BCA could lead to acting prematurely; the reverse holds if project implementation is long and uncertainty is large enough. (c) 2005 Elsevier Inc. All rights reserved.

Suggested Citation

Jean-Daniel M. Saphores and Marlon G. Boarnet (2006) “Uncertainty and the timing of an urban congestion relief investment.”, Journal of Urban Economics, 59(2), pp. 189–208. Available at: 10.1016/j.jue.2005.04.003.