published journal article

Network structure and airline scheduling

J Industrial Economics

Publication Date

June 1, 2004

Author(s)

Abstract

This paper provides a simple analysis of the effects of network structure on the scheduling, traffic, and aircraft size choices of a monopoly airline. The analysis shows that switching to a hub-and-spoke network leads to increases in both flight frequency and aircraft size, while stimulating local traffic in and out of the hub. In addition, HS networks are shown to be preferred by the airline when travel demand is low, when flights are expensive to operate, and when passengers place a high value on flight frequency but are not excessively inconvenienced by the extra travel time required for a connecting trip. The welfare analysis shows that the flight frequency, traffic volumes, and aircraft size chosen by the monopolist are all inefficiently low under both network types. Moreover, in the most plausible case, the monopolist’s network choice exhibits an inefficient bias toward the HS network, apparently reflecting an excessive desire to economize on the number of flights.

Suggested Citation
Jan K. Brueckner (2004) “Network structure and airline scheduling”, J Industrial Economics, 52(2), pp. 291–312. Available at: 10.1111/j.0022-1821.2004.00227.x.

working paper

A Structural Model of Vehicle Use in Two-Vehicle Households

Publication Date

June 1, 1994

Associated Project

Working Paper

UCI-ITS-WP-94-12, UCTC 224

Areas of Expertise

Abstract

This research is part of the project aimed at developing a model system to forecast demand for clean fuel vehicles in California, conducted by researchers at the University of California, Irvine and University of California, Davis. The objective of the research reported here is to explain annual vehicle miles of travel for each of the two vehicles in two-vehicle households as a function only of household characteristics that can be forecasted using the household sociodemographic updating model being developed as part of the personal vehicle submodel (brownstone, Bunch and Golob, 1994). The household’s choice of the number of vehicles to own and the types of these vehicles, in terms of the class and vintage of each vehicle, are taken as given in this model.

Suggested Citation
Thomas F. Golob, Seyoung Kim and Weiping Ren (1994) A Structural Model of Vehicle Use in Two-Vehicle Households. Working Paper UCI-ITS-WP-94-12, UCTC 224. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/9wp6c79q.

published journal article

Effects of property taxation on development timing and density: Policy perspective

Brookings-Wharton Papers on Urban Affairs

Publication Date

January 1, 2006

Author(s)

Richard Arnott
Suggested Citation
Richard Arnott (2006) “Effects of property taxation on development timing and density: Policy perspective”, Brookings-Wharton Papers on Urban Affairs, 2006(1), pp. 189–230. Available at: 10.1353/urb.2006.0015.

published journal article

Modeling determinants of ridesourcing usage: A census tract-level analysis of Chicago

Transportation Research Part C: Emerging Technologies

Publication Date

October 1, 2020

Abstract

Ridesourcing services provided by companies like Uber, Lyft, and Didi have grown rapidly over the past decade and now serve a sizable portion of trips in many metropolitan areas. An understanding of these services (e.g. to whom, where, when, and for what purposes do they provide service?) is critical for regulating, planning, and managing urban multi-modal transportation systems effectively. Unfortunately, little is known about ridesourcing travel because private companies providing ridesourcing services were not previously subject to data sharing requirements. Fortunately, the city of Chicago recently collected and released spatially (census tract) and temporally (15-minute interval) aggregated data on ridesourcing trips collected from private companies. This study analyzes the Chicago ridesourcing data to examine factors influencing ridesourcing usage. The study employs a random-effects negative binomial (RENB) regression approach to model ridesourcing usage. Determinants considered in the model include weekend vs. weekday and weather variables as well as census tract socio-demographics and commute characteristics, land-use variables, places of interest, transit supply, parking features, and crime. The model results indicate ridesourcing demand is higher on days when temperatures are lower, there is less precipitation, and on the weekend, as well as in census tracts with (i) higher household incomes, (ii) a higher percentage of workers who carpool or take transit to work, (iii) a higher percentage of households with zero vehicles, (iv) higher population and employment density, (v) higher land-use diversity, (vi) fewer parking spots and higher parking rates, (vii) more restaurants, and (viii) more homicides. The results also demonstrate a non-linear (and insightful) relationship between ridesourcing demand and transit supply variables. The paper discusses the implications of these model results to inform transportation planning and policymaking as well as future research.

Suggested Citation
Arash Ghaffar, Suman Mitra and Michael Hyland (2020) “Modeling determinants of ridesourcing usage: A census tract-level analysis of Chicago”, Transportation Research Part C: Emerging Technologies, 119, p. 102769. Available at: 10.1016/j.trc.2020.102769.

published journal article

Does Britain or the United States Have the Right Gasoline Tax?

American Economic Review

Publication Date

August 1, 2005

Author(s)

Ian W. H Parry, Kenneth Small
Suggested Citation
Ian W. H Parry and Kenneth A Small (2005) “Does Britain or the United States Have the Right Gasoline Tax?”, American Economic Review, 95(4), pp. 1276–1289. Available at: 10.1257/0002828054825510.

working paper

Road Pricing for Congestion Management: The Transition from Theory to Policy

Publication Date

September 5, 1998

Associated Project

Author(s)

Kenneth Small, Jose A. Gomez-Ilbanez

Working Paper

UCI-ITS-WP-98-1, UCTC 391

Areas of Expertise

Abstract

Traffic congestion is a classic externality, especially pervasive in urban areas. The theoretical and empirical relationships governing it have been thoroughly studied. As a result, most urban economists and a growing number of other policy analysts agree that the best policy to deal with it would be some form of congestion pricing. Such a policy involves charging a substantial fee for operating a motor vehicle at times and places where there is insufficient road capacity to easily accommodate demand. The intention is to alter people’s travel behavior enough to reduce congestion.

Suggested Citation
Kenneth A. Small and Jose A. Gomez-Ilbanez (1998) Road Pricing for Congestion Management: The Transition from Theory to Policy. Working Paper UCI-ITS-WP-98-1, UCTC 391. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/8kk909p1.

MS Thesis

Analysis of High-Occupancy-Toll Lane Operation / by Xuting Wang.

Publication Date

January 1, 2016

Author(s)

Abstract

In this thesis, we propose one approach to determine the real-time tolling strategy for high occupancy toll (HOT) lane, and calibrate driver’s value of time(VOT) as well. There are two goals of operating HOT lane, one is to maximize the freeway’s, and another one is to maintain the free flow speed. We use queue length to track the trac dynamics, and the point queue model is used. And with the application of a proportional-integral-derivative(PID) controller, we can calculate the pricing rate for HOT lane and calibrate driver’s (VOT). Simulation results and comparison with previous studies are provided.

Suggested Citation
Xuting Wang (2016) Analysis of High-Occupancy-Toll Lane Operation / by Xuting Wang.. MS Thesis. University of California, Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/17uq3m8/alma991023240719704701.

Phd Dissertation

A mathematical programming model of activity scheduling/rescheduling in an uncertain environment

Publication Date

January 1, 2007

Author(s)

Abstract

The so-called activity-based approach to analysis of human interaction within social and physical environments dates back to the original time-space geography works of Hägerstrand and his colleagues at the Lund School in 1970, with a unique kernel problem termed “household activity scheduling”. The problem attempts to derive estimates of activity decisions taking into account the time, duration, mode, location and route of the given activity sets performed by individuals. This dissertation research studies the activity scheduling/rescheduling problem under an uncertain environment. Theories and models for predicting activity-travel behavior are developed within the context of an activity-based approach built on the general consensus that the demand for travel is derived from a need or desire to participate in activities. Computationally-tractable systems are developed that inherently incorporate factors of uncertainty that can potentially increase the ability to address the household activity scheduling problem and the related dynamics of human movement required for social interaction and household sustenance. A stochastic mixed integer linear program is formulated to model travel behavior in which each activity of the prescribed household agenda has a known probability of being completed (or cancelled). Further, a chance-constrained program is proposed to determine the optimal activity/travel pattern when travel time and activity duration are assumed to be stochastically distributed, while the remaining inputs are precisely known. Finally, under the assumption that the activity/travel pattern involves a dynamic decision-making process of rescheduling/adaptations to initial plans subject to unexpected events, a predictive model of activity rescheduling behavior is developed in the form of a mixed integer linear program. The dissertation presents solution methodologies to the proposed models. Data drawn from a comprehensive on-line survey are utilized to verify the proposed activity schedule/reschedule models. Numerical results are presented to demonstrate the performance of the proposed models. Finally, conclusions and directions for future research are summarized.

Suggested Citation
Liping Gan (2007) A mathematical programming model of activity scheduling/rescheduling in an uncertain environment. Ph.D.. University of California, Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/17uq3m8/alma991035092996504701 (Accessed: October 14, 2023).

published journal article

The optimization of DC fast charging deployment in California

Applied Energy

Publication Date

November 1, 2015

Abstract

Battery electric vehicles (BEVs) are important for reducing fuel consumption and vehicle operating cost, and have the potential to reduce GHG and pollutant emissions. However, the range limits and long recharging times serve as obstacles to mass deployment. Well planned Level 3 DC fast charging stations are a potential solution to satisfy long distance travel demand instead of an expansive Level 2 non-home charging infrastructure. This paper identifies candidate charging routes and uses freeway exits and highway intersections as approximate candidate charging locations, and consequently solves a set covering problem to minimize the number of charging stations. Results show that 290 Level 3 charging locations are required for the State of California based on the 2000 California Travel Survey and BEVs with 60 mile range. With this optimized station network, electric light duty vehicle miles travelled (VMT) can reach 92% and BEVs can be used by 98% of drivers. If BEVs with 100 or 200 mile range are used, 126 or 31 Level 3 charging locations are required, respectively. This study also assesses the temporal utilization of charging stations. Congestion at several stations suggests extra chargers are required. A reservation system can benefit both the BEV drivers and station operators by reducing the wait times, decreasing the extra chargers needed, and more evenly utilizing all the stations. Related policies are also discussed to better deploy fast charging stations. (C) 2015 Elsevier Ltd. All rights reserved.

Suggested Citation
Li Zhang, Brendan Shaffer, Tim Brown and G. Scott Samuelsen (2015) “The optimization of DC fast charging deployment in California”, Applied Energy, 157, pp. 111–122. Available at: 10.1016/j.apenergy.2015.07.057.

conference paper

Real option pricing of continuous network design investments

Proceedings of the 88th annual meeting of the transportation research board

Publication Date

January 1, 2009

Abstract

A real option analytical framework for investments made in a network is considered as a method for addressing managerial flexibility in transportation planning. The core of the framework is a hierarchical Bellman equation with continuous network design investment allocation and user-optimal route choice in each recursion. A continuous network investment deferment framework is formulated with stochastic OD flows evolving as discretized geometric Brownian motions. A numerical approach based on Least Squares Monte Carlo simulation and an Iterative Optimization Assignment heuristic is considered. The option premium is shown to decompose into a basic deferment premium and a flexible network design premium. Additionally, the basic deferment premium for a network setting can be further broken down into a set of link deferment premiums plus a non-positive synergy effect premium. The proposed framework is tested on the classic Sioux Falls, SD network.

Suggested Citation
Joseph Y.J. Chow and Amelia Regan (2009) “Real option pricing of continuous network design investments”, in Proceedings of the 88th annual meeting of the transportation research board, p. 18p.