published journal article

Dueling emergencies: Flood evacuation ridesharing during the COVID-19 pandemic

Transportation Research Interdisciplinary Perspectives

Publication Date

June 1, 2021

Author(s)

Elisa Borowski, Victor Limontitla Cedillo, Amanda Stathopoulos

Abstract

Volunteered sharing of resources is often observed in response to disaster events. During evacuations the sharing of resources and vehicles is a crucial mechanism for expanding critical capacity and enabling inclusive disaster response. This paper examines the complexity of rideshare decision-making in the wake of simultaneous emergencies. Specifically, the need for physical distancing measures during the coronavirus (COVID-19) pandemic complicates face-to-face resource sharing between strangers. The ability of on-demand ridesharing to provide emergency transportation to individuals without access to alternatives calls for an understanding of how evacuees weigh risks of contagion against benefits of spontaneous resource sharing. In this research, we examine both sociodemographic and situational factors that contribute to a willingness to share flood evacuation rides with strangers during the COVID-19 pandemic. We hypothesize that the willingness to share is significantly correlated with traditional emergency resource sharing motivations and current COVID-19 risk factors. To test these hypotheses, we distributed an online survey during the pandemic surge in July 2020 to 600 individuals in three midwestern and three southern states in the United States with high risk of flooding. We estimate a random parameter multinomial logit model to determine the willingness to share a ride as a driver or passenger. Our findings show that willingness to share evacuation rides is associated with individual sociodemographics (such as being female, under 36 years old, Black, or republican-identifying) and the social environment (such as households with children, social network proximity, and neighborly sharing attitudes). Moreover, our findings suggest higher levels of income, COVID-19 threat perception, evacuation fear, and household preparedness all correspond with a lower willingness to share rides. We discuss the broader implications of emergency on-demand mobility during concurrent disasters to formulate strategies for transportation agencies and on-demand ridehailing providers.

Suggested Citation
Elisa Borowski, Victor Limontitla Cedillo and Amanda Stathopoulos (2021) “Dueling emergencies: Flood evacuation ridesharing during the COVID-19 pandemic”, Transportation Research Interdisciplinary Perspectives, 10, p. 100352. Available at: 10.1016/j.trip.2021.100352.

conference paper

A demand forecasting system for clean-fuel vehicles

Towards clean transport: Fuel-efficient and clean motor vehicles

Publication Date

January 1, 1996

Author(s)

Abstract

This paper describes an ongoing project to develop a demand forecasting model for clean-fuel vehicles in California. Large-scale surveys of both households and commercial fleet operators have been carried out These data are being used to calibrate a new micro-simulation based vehicle demand forecasting system. Based on pre-specified attributes of future vehicles (including specified clean-fueled vehicle incentives), the system will produce annual forecasts of new and used vehicle demand by type of vehicle and geographic region. The system will also forecast annual vehicle miles traveled for all vehicles and recharging demand by time of day for electric vehicles. These results are potentially useful to utility companies in their demand-side management planning, to public agencies in their evaluation incentive schemes, and to manufacturers faced with designing and marketing clean-fuel vehicles.

Suggested Citation
D Brownstone, DS Bunch and TF Golob (1996) “A demand forecasting system for clean-fuel vehicles”, in Towards clean transport: Fuel-efficient and clean motor vehicles. ORGANIZATION ECONOMIC COOPERATION & DEVELOPMENT / Org Econ Cooperat & Dev; Int Energy Agcy, pp. 609–623.

Phd Dissertation

Dynamic and stochastic routing optimization: Algorithm development and analysis

Abstract

The last several years has witnessed a sharp increase in interest in stochastic and dynamic routing and scheduling. Because many systems contain inherently stochastic factors, decisions must often be made before all necessary information is available. To a certain degree, algorithm development has lagged behind implementation. In order to fully leverage advances in information technologies, algorithms which explicitly consider dynamic and stochastic factors should be examined. Or, if static algorithms are to be applied in these dynamic environments, proper attention should be given to examining the conditions under which these perform well. This is the primary theme of this research. This dissertation examines several key dynamic and stochastic routing and scheduling problems: the probabilistic traveling salesman problem, the dynamic traveling salesman problem and the dynamic traveling repair problem. In addition, as part of our research on the dynamic traveling salesman problem, we examine a related M/G/1 queueing problem with switching costs. These problems arise in pickup and delivery operations, repair fleet operations, and emergency vehicle and police operations in addition to many computing, telecommunications and manufacturing applications. As part of our research, we demonstrate that heuristics which rely on partitioning the service region into smaller regions can be very effective for dynamic routing problems. Using a partitioning scheme we show that if a constant guarantee algorithm exists for the k-capacitated median problem, then a constant guarantee algorithm exists for the probabilistic traveling salesman problem. For the DTRP, we show that a partitioning algorithm is asymptotically optimal when the traffic intensity is high. We show that robust a priori algorithms can be developed for dynamic routing problems. For the M/G/1 with switchover cost, we show that an a priori cyclic polling algorithm works very well using both theoretical and simulation analysis. Cyclic polling algorithm also works well for dynamic traveling salesman problem. For these both problems, we identify certain conditions under which the a priori (cyclic polling) solution is close to optimal. We demonstrate that the existence of the connection between the static and dynamic vehicle routing and scheduling problem that have been observed by earlier researchers.

Suggested Citation
Xiangwen Lu (2001) Dynamic and stochastic routing optimization: Algorithm development and analysis. PhD Dissertation. UC Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/17uq3m8/alma991035093172804701.

conference paper

The impacts of allowing hybrid vehicles and solo toll-paying vehicles in existing high-occupancy vehicle lanes

Proceedings, 11th International Conference on Travel Behaviour Research

Publication Date

August 1, 2006
Suggested Citation
David Brownstone, Will Recker and C. Breiland (2006) “The impacts of allowing hybrid vehicles and solo toll-paying vehicles in existing high-occupancy vehicle lanes”, in Proceedings, 11th International Conference on Travel Behaviour Research. Kyoto, Japan.

working paper

Structural Equation Modeling of Travel Choice Dynamics

Publication Date

June 1, 1988

Associated Project

Author(s)

Working Paper

UCI-ITS-WP-88-13, UCI-ITS-AS-WP-88-1

Areas of Expertise

Abstract

This research has two objectives. The first objective is to explore the use of the modeling tool called “latent structural equations” (structural equations with latent variables) in the general field of travel behavior analysis and the more specific field of dynamic analysis of travel behavior. The second objective is to apply a latent structural equation model in order to determine the causal relationships between income, car ownership, and mobility. Many transportation researchers might be unfamiliar with latent structural equation modeling, which is also known as “latent structural analysis,” “causal analysis,” and “soft modeling.” However, most researchers will be quite familiar with techniques that are special cases of latent structural equations: e.g., conventional multiple regression and simultaneous equations, path analysis, and (confirmatory) factor analysis. Furthermore, recent advances in estimation techniques have made it possible to incorporate discrete choice variables and other non-normal variables in structural equations models. Thus, probit choice models (binomial, ordered, and multinomial) can be incorporated within the general model framework. The empirical analysis reported here involves dynamic travel demand data from the Dutch National Mobility Panel for the three years 1984 through 1986. All variables in the model, with the exception of income level in the first year, are endogenous: income is treated as an ordinal (four category) variable; car ownership is treated as either an ordinal (ordered probit) or a categorical (multinomial probit) choice variable; and mobility, in terms of car trips and public transport trips, is treated as two censored (tobit) continuous variables. The model fits the data well, but only scratches the surface of the potential of latent structural equation modeling with panel data. Some possible extensions are outlined.

Suggested Citation
Thomas F. Golob (1988) Structural Equation Modeling of Travel Choice Dynamics. Working Paper UCI-ITS-WP-88-13, UCI-ITS-AS-WP-88-1. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/8kg9s6zb.

presentation

Streamlining the Permitting Process for Transit-Oriented Development: The Case of California's Senate Bill 375

Publication Date

April 25, 2024

Author(s)

Bailey Affolter, Jamey Volker, Susie Pike, Nicholas Marantz, Graham DeLeon

published journal article

Airline emission charges: Effects on airfares, service quality, and aircraft design

Transportation Research Part B: Methodological

Publication Date

September 1, 2010

Author(s)

Jan Brueckner, Anming Zhang
Suggested Citation
Jan K. Brueckner and Anming Zhang (2010) “Airline emission charges: Effects on airfares, service quality, and aircraft design”, Transportation Research Part B: Methodological, 44(8-9), pp. 960–971. Available at: 10.1016/j.trb.2010.02.006.

published journal article

Joint models of attitudes and behavior in evaluation of the San Diego I-15 congestion pricing project

Transportation Research Part A: Policy and Practice

Publication Date

July 1, 2001

Author(s)

Abstract

Understanding attitudes held by the public about the acceptability, fairness, and effectiveness of congestion pricing systems is crucial to the planning and evaluation of such systems. In this study, joint models of attitude and behavior are developed to explain how both mode choice and attitudes regarding the San Diego I-15 Congestion Pricing Project differ across the population. Results show that some personal and situational explanations of opinions and perceptions are attributable to mode choices, but other explanations are independent of behavior. With respect to linkages between attitudes and behavior, none of the models tested found any significant effects of attitude on choice; all causal links were from behavior to attitudes. (C) 2001 Elsevier Science Ltd. All rights reserved.

Suggested Citation
Thomas F. Golob (2001) “Joint models of attitudes and behavior in evaluation of the San Diego I-15 congestion pricing project”, Transportation Research Part A: Policy and Practice, 35(6), pp. 495–514. Available at: 10.1016/s0965-8564(00)00004-5.

conference paper

Environmental and health impacts of shifting drayage truck operations to off-peak hours: An analysis of the PierPASS program in southern California

Proceedings of the 94th annual meeting of the transportation research board

Publication Date

January 1, 2015

Abstract

This paper analyses some environmental and health impacts from the PierPASS program, which shifted drayage trucks operations from daytime/peak hours to evening/night hours to reduce congestion and air pollution at the San Pedro Bay Ports (i.e. the Ports of Los Angeles and Long Beach in Southern California). The authors focus on emissions of nitrogen dioxide (NO2) and particulate matter (PM2.5), and some related health impacts, using a framework that integrates microscopic traffic simulation with emission estimation, air dispersion, and a health impact assessment. The authors find that PierPASS had little impact on traffic congestion and slightly decreased overall emissions of NO2 and PM2.5. However, PierPASS substantially changed their day-night distributions: at night, total port truck emissions increased by 19.4% for NO2 and by 19.5% for PM2.5, while daytime emissions decreased respectively by 5.0% and 4.9%. As a result, PierPASS increased air pollutant concentrations during both daytime and nighttime because of atmospheric boundary layer effects. Finally, health impact analyses using the Environmental Protection Agency’s (EPAâ??s) BenMAP model show that the implementation of PierPASS increased annual health costs in the study area (which does not include the ports themselves) by over $430 million.

Suggested Citation
Ankoor Bhagat, Jean-Daniel Saphores and R. Jayakrishnan (2015) “Environmental and health impacts of shifting drayage truck operations to off-peak hours: An analysis of the PierPASS program in southern California”, in Proceedings of the 94th annual meeting of the transportation research board, p. 18p. Available at: https://trid.trb.org/view/1339096.

conference paper

Peeking into your app without actually seeing it: Ui state inference and novel android attacks

Proceedings of the 23rd USENIX security symposium

Publication Date

January 1, 2014

Author(s)

Qi Alfred Chen, Zhen (Sean) Qian, Z.M. Mao
Suggested Citation
Q.A. Chen, Z. Qian and Z.M. Mao (2014) “Peeking into your app without actually seeing it: Ui state inference and novel android attacks”, in Proceedings of the 23rd USENIX security symposium, pp. 1037–1052.