published journal article
Impacts of plug-in electric vehicles in a balancing area
Applied Energy
Publication Date
December 1, 2016
Area of Expertise: Unspecified
published journal article
Transportation-Related Emissions Surrogates Support Modeling of Oxides of Nitrogen Exposure
ISEE Conference Abstracts
Publication Date
September 18, 2022
Author(s)
Nathan Pavlovic, Lianfa Li, Frederick Lurmann, Jun Wu, Beate Ritz, Rima Habre
Abstract
Background: Mobile sources such as traffic and airports contribute significantly to concentrations of nitrogen oxides (NOx) and nitrogen dioxide (NO2). Exposure to these pollutants in turn are associated with a range of negative health outcomes. Accurate, high resolution spatiotemporal models of NOx /NO2 are needed to support further epidemiological research. Traffic tailpipe emissions are especially elevated under high engine load (acceleration), and our earlier work shows accounting for airport emissions may decrease measurement error in our spatiotemporal NOx models. The goal of this work is to showcase improvements in accounting for these mobile sources more accurately and these features’ importance in our spatiotemporal NOx models. Methods: We calculated airport-related NOx emissions by allocating airport-related NOx emissions from CARB’s CEPAM emission inventory tool to each airport in California from 2004 through 2019. For 2020 and 2021, emissions were further scaled on a weekly basis to account for decreased flight volume during the COVID period. To account for on-road vehicle tailpipe emissions due to acceleration at intersections, we developed a dataset representing intersection density, broken into class by intersection type based on road class type and supported by GPS activity data. These variables were incorporated into spatiotemporal modeling of outdoor NOx/NO2 concentrations in California. Results: Airport emissions and intersection density were ranked highly by variable importance within the model. The transportation-related emissions surrogates improved the spatial representation of NOx/NO2 at fine scales, supporting accurate air quality exposure estimates. Conclusions: Our findings demonstrate how improved measures of mobile source emissions (beyond distance to airports or roads) that capture gradients in emission patterns across spatial features (e.g. road class) can enhance spatiotemporal prediction performance of high resolution exposure models. Keywords: Air pollution, NOx, transportation, mobile sources
Suggested Citation
Nathan Pavlovic, Lianfa Li, Frederick Lurmann, Jun Wu, Beate Ritz and Rima Habre (2022) “Transportation-Related Emissions Surrogates Support Modeling of Oxides of Nitrogen Exposure”, ISEE Conference Abstracts, 2022(1). Available at: 10.1289/isee.2022.P-0240. published journal article
Car2work: Shared mobility concept to connect commuters with workplaces
Transportation Research Record
Publication Date
January 1, 2016
Author(s)
Suggested Citation
Robert Regue, Neda Masoud and Will Recker (2016) “Car2work: Shared mobility concept to connect commuters with workplaces”, Transportation Research Record, 2542(1), pp. 102–110. Available at: 10.3141/2542-12. published journal article
Handbook of logistics and supply-chain management.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
Publication Date
January 1, 2003
Author(s)
Suggested Citation
AC Regan (2003) “Handbook of logistics and supply-chain management.”, TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 37(2), pp. 189–190. Available at: 10.1016/S0965-8564(02)00040-X.
research report
Understanding Post-Pandemic Travel Behavior Patterns and Trends in California
Publication Date
July 1, 2026
Author(s)
Abstract
The COVID-19 pandemic fundamentally reshaped global mobility, forcing a departure from previous travel norms. In California, initial declines in public transit and ride-hailing were accompanied by a surge in private vehicle interest and shifts to active travel. To assess whether spatial and temporal travel patterns shifted between 2019 and 2023, this study analyzed Performance Measurement System freeway data, regional transit boarding records, and spatial econometric modeling of Streetlight Insight data. The findings reveal a near-recovery of weekday freeway volumes and stable weekend patterns, yet an uneven transit recovery that favors buses over rail and weekends over weekdays. There was significant spatial dependence in active transportation; while the primary factors influencing walking and cycling remain consistent, their relative magnitudes have shifted. Ultimately, Californians’ choices of transportation modes are different after the pandemic than they were before it. Integrating these altered patterns into current planning frameworks is essential for developing resilient, equitable, and sustainable transportation policies.
Suggested Citation
Sabah Hossain Iqra and Jean-Daniel Saphores (2026) Understanding Post-Pandemic Travel Behavior Patterns and Trends in California. Research Report. UC ITS. Available at: https://doi.org/10.7922/g2br8qkb. conference paper
System performance and controller design of the PI-ALINEA ramp metering scheme
Proceedings of the 95th annual meeting of the transportation research board
Publication Date
January 1, 2016
Author(s)
Abstract
Ramp metering (RM) has been deployed for decades and it is considered an efficient technique to control lane-drop bottlenecks by limiting ramp demand and avoiding the so-called capacity-drop phenomena, drop in the downstream flux that occurs when queues form up- stream of bottleneck. In this study, the authors use a simple link queue model to describe traffic dynamics inside a merge zone with an ordinary differential equation, which combines a capacity drop model and a proportional-integral feedback control algorithm (PI-ALINEA). This enables us to analytically study the system performance and controller design for the ramp metering problem. First they analyze the systemâ??s equilibrium states, their stability, and transition subject to varying demand levels. They consider impacts of both fixed and dynamical metering rates on the equilibrium states of the system and examine the reachability of the system. They further analyze the closed-loop systems and design parameters of PI-ALINEA such that the system can be stabilized at the optimal state at a high demand level. With numerical examples they verify the analytical results with respect to the systemâ??s stability and robustness.
Suggested Citation
Felipe Augusto de Souza and Wenlong Jin (2016) “System performance and controller design of the PI-ALINEA ramp metering scheme”, in Proceedings of the 95th annual meeting of the transportation research board, p. 24p. conference paper
Evaluating the potential to predict activity types from GPS and GIS data
Proceedings of the 86th annual meeting of the transportation research board
Publication Date
January 1, 2007
Author(s)
Abstract
Current travel forecasting models have had limited sensitivity to policy decisions. One of the primary challenges is limitations in the primary data source, the daily travel diary (e.g., accuracy and sample size). The daily travel diary has known problems with underreporting, time inaccuracies, respondent fatigue, and other human errors. The Global Positioning System (GPS) has been recently used to supplement the daily travel diary. As GPS becomes more accurate, reliable, and cost effective, could it entirely replace the daily travel diary? GPS devices can be used to record times and locations of each activity and the trips in between. To use GPS data to replace the daily travel diary one needs to predict the activity types. The goal of this research is to test the feasibility of a model that predicts activity types based solely on: (1) GPS data from devices placed on the individualâ??s vehicle or person, (2) Land use data, such as location type, expressed as GIS data, and (3) Individual and household demographic data. This report summarizes models developed with surrogate geo-coded data using discriminant analysis and classification/ regression trees. The models predicted in which of 26 different activity types the individual participated. Accuracy for the best model was: (1) 63% for out of home activities (2) 79% when including the â??at homeâ?? activity (3) 72% considering that GPS data may miss as much as 10% of trips Since travel diaries have known underreporting problems as high as 30%, GPS data with the model developed seems competitive.
Suggested Citation
Patrick Tracy McGowen and Michael G. McNally (2007) “Evaluating the potential to predict activity types from GPS and GIS data”, in Proceedings of the 86th annual meeting of the transportation research board, p. 22p. published journal article
Schedule competition revisited
Journal of Transport Economics and Policy
Publication Date
September 1, 2010
Author(s)
Suggested Citation
Jan K. Brueckner (2010) “Schedule competition revisited”, Journal of Transport Economics and Policy, 44, pp. 261–285. Available at: 10.2307/25801401. conference paper
A conceptual statewide freight forecasting framework for California
Proceedings of the 4th METRANS national urban freight conference, Long Beach, California.
Publication Date
January 1, 2011
Suggested Citation
J.Y. Chow, S.G. Ritchie, M. Zhao, F. Ranaiefar, S. You, A. Tok and M.G. McNally (2011) “A conceptual statewide freight forecasting framework for California”, in Proceedings of the 4th METRANS national urban freight conference, Long Beach, California.. conference paper
Assessing network vulnerability of degradable transportation systems: An accessibility based approach
Proceedings of transportation and traffic theory 2007, papers selected for presentation at ISTTT17, london, england
Publication Date
January 1, 2007
Author(s)
Abstract
Transportation networks are an indispensable component of everyday life in modern society. Disruption to the networks can make peoplesâ?? daily lives extremely difficult as well as seriously cripple economic productivity. In this paper, the authors develop network-based accessibility measures for assessing vulnerability of degradable transportation networks. The accessibility-based vulnerability measures explicitly consider the interaction between the disrupted network and the multi-dimensional travel responses of the network users. To model different dimensions of travel behavioral responses, a combined travel demand model formulated as a variational inequality problem is adopted to estimate the utility-based accessibility measure that is consistent with random utility theory. Numerical examples are conducted to demonstrate the feasibility of the proposed network-based accessibility measures for assessing vulnerability of degradable transportation networks. The results indicate that the accessibility measures derived from the combined travel demand model are capable of measuring the consequences of both demand and supply changes in the network and have the flexibility to reflect the effects of different travel choice dimensions on the network vulnerability.