published journal article
Freeway ramp metering using artificial neural networks
Transportation Research Part C: Emerging Technologies
Publication Date
October 1, 1997
Archives: Research Products
Phd Dissertation
On the Formation of Household Travel/Activity Patterns: A Simulation Approach
Publication Date
January 1, 1986
Author(s)
Areas of Expertise
Abstract
This dissertation presents a policy sensitive approach to modeling travel behavior based on activity pattern analysis. A theoretical model of complex travel behavior is formulated on a recognition of a wide range of interdependencies associated with an individual’s travel decisions in a constrained environment. Travel is viewed as input to a more basic process involving activity decisions. A fundamental tenet of this approach is that travel decisions are driven by the collection of activities that form an agenda for participation; the utility of any specific travel decision can be determined only within the context of the entire agenda. Based on this theoretical model of complex travel behavior, an operational system of models, STARCHILD (Simulation of Travel/Activity Responses to Complex Household Interactive Logistic Decisions), has been developed to examine the formation of household travel/activity patterns. The system employs a simulation approach in combination with techniques of pattern recognition, multiobjective optimization, and disaggregate choice models. Initial empirical verification of the theory and the system of models is presented based on results obtained from a sample data set.
Suggested Citation
Michael Greyson McNally (1986) On the Formation of Household Travel/Activity Patterns: A Simulation Approach. Ph.D.. University of California, Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/17uq3m8/alma9956668663606533 (Accessed: August 21, 2025). published journal article
In memoriam frank a. Haight 1919-2006 - obituary
TRANSPORTATION RESEARCH PART B: METHODOLOGICAL
Publication Date
January 1, 2007
Author(s)
Thomas Golob, Molly I. Haight
Suggested Citation
Thomas F. Golob and Molly I. Haight (2007) “In memoriam frank a. Haight 1919-2006 - obituary”, TRANSPORTATION RESEARCH PART B: METHODOLOGICAL, 41(1), pp. 1–3. Available at: 10.1016/j.trb.2006.07.001. working paper
Joint Models of Attitudes and Behavior in the Evaluation of the San Diego I-15 Congestion Pricing Project
Publication Date
November 1, 1999
Author(s)
Working Paper
UCI-ITS-WP-99-3
Areas of Expertise
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 1-15 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.
Suggested Citation
Thomas F. Golob (1999) Joint Models of Attitudes and Behavior in the Evaluation of the San Diego I-15 Congestion Pricing Project. Working Paper UCI-ITS-WP-99-3. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/8x52q6p7. published journal article
Analyzing building-height restrictions: Predicted impacts and welfare costs
Regional Science and Urban Economics
Publication Date
March 1, 2005
Author(s)
Alain Bertaud, Jan Brueckner
Abstract
This paper analyzes the impacts and the welfare costs of building-height restrictions. The theoretical analysis demonstrates that a height restriction causes a city to expand spatially, a consequence of lower densities near the center. The analysis also establishes that the consumer welfare cost generated by the height restriction can be measured by the increase in commuting cost for the household living at the edge of the city. Simulation results for a stylized urban area show that this welfare cost is approximately 2% of household income. Illustrative calculations for Bangalore, India, where a height restriction is in force, suggest a similar welfare cost, which lies in the 1.5-4.5% range. (c) 2005 Elsevier B.V. All rights reserved.
Suggested Citation
Alain Bertaud and Jan K. Brueckner (2005) “Analyzing building-height restrictions: Predicted impacts and welfare costs”, Regional Science and Urban Economics, 35(2), pp. 109–125. Available at: 10.1016/j.regsciurbeco.2004.02.004. published journal article
Harnessing cross-border resources to confront climate change
Environmental Science & Policy
Publication Date
September 1, 2018
Author(s)
Octavio Aburto-Oropeza, Andrew F. Johnson, Mickey Agha, Edith B. Allen, Michael F. Allen, Jesús Arellano González, Diego M. Arenas Moreno, Rodrigo Beas-Luna, Scott Butterfield, Gabriel Caetano, Jennifer E. Caselle, Gamaliel Castañeda Gaytán, Max C.N. Castorani, Linh Anh Cat, Kyle Cavanaugh, Jeffrey Q. Chambers, Robert D. Cooper, Nur Arafeh-Dalmau, Todd Dawson, Aníbal Díaz de la Vega Pérez, Joseph Dimento, Saúl Domínguez Guerrero, Matthew Edwards, Joshua R. Ennen, Hector Estrada-Medina, Natalia Fierro-Estrada, Héctor Gadsden, Patricia Galina-Tessaro, Paul M. Gibbons, Eric V. Goode, Morgan E. Gorris, Thomas Harmon, Susanna Hecht, Marco Antonio Heredia Fragoso, Alan Hernández-Solano, Danae Hernández-Cortés, Gustavo Hernández-Carmona, Scott Hillard, Raymond B. Huey, Matthew B. Hufford, G. Darrel Jenerette, Juan Jiménez-Osornio, Karla Joana López-Nava, Rafael A. Lara Reséndiz, Heather M. Leslie, Alejandro López-Feldman, Víctor H. Luja, Norberto Martínez Méndez, William J. Mautz, Josué Medellín-Azuara, Cristina Meléndez-Torres, Fausto R. Méndez de la Cruz, Fiorenza Micheli, Donald B. Miles, Giovanna Montagner, Gabriela Montaño-Moctezuma, Johannes Muller, Paulina Oliva, José Abraham Ortinez Álvarez, J. Pablo Ortiz-Partida, Julio Palleiro-Nayar, Víctor Hugo Páramo Figueroa, P.Ed. Parnell, Peter Raimondi, Arturo Ramírez-Valdez, James T. Randerson, Daniel C. Reed, Meritxell Riquelme, Teresita Romero Torres, Philip C. Rosen, Jeffrey Ross-Ibarra, Victor Sánchez-Cordero, Samuel Sandoval-Solis, Juan Carlos Santos, Ruairidh Sawers, Barry Sinervo, Jack W. Sites, Oscar Sosa-Nishizaki, Travis Stanton, Jared R. Stapp, Joseph A.E. Stewart, Jorge Torre, Guillermo Torres-Moye, Kathleen K. Treseder, Jorge Valdez-Villavicencio, Fernando I. Valle Jiménez, Mercy Vaughn, Luke Welton, Michael F. Westphal, Guillermo Woolrich-Piña, Antonio Yunez-Naude, José A. Zertuche-González, J. Edward Taylor
Abstract
The US and Mexico share a common history in many areas, including language and culture. They face ecological changes due to the increased frequency and severity of droughts and rising energy demands; trends that entail economic costs for both nations and major implications for human wellbeing. We describe an ongoing effort by the Environment Working Group (EWG), created by The University of California’s UC-Mexico initiative in 2015, to promote binational research, teaching, and outreach collaborations on the implications of climate change for Mexico and California. We synthesize current knowledge about the most pressing issues related to climate change in the US-Mexico border region and provide examples of cross-border discoveries and research initiatives, highlighting the need to move forward in six broad rubrics. This and similar binational cooperation efforts can lead to improved living standards, generate a collaborative mindset among participating universities, and create an international network to address urgent sustainability challenges affecting both countries.
Suggested Citation
Octavio Aburto-Oropeza, Andrew F. Johnson, Mickey Agha, Edith B. Allen, Michael F. Allen, Jesús Arellano González, Diego M. Arenas Moreno, Rodrigo Beas-Luna, Scott Butterfield, Gabriel Caetano, Jennifer E. Caselle, Gamaliel Castañeda Gaytán, Max C.N. Castorani, Linh Anh Cat, Kyle Cavanaugh, Jeffrey Q. Chambers, Robert D. Cooper, Nur Arafeh-Dalmau, Todd Dawson, Aníbal Díaz de la Vega Pérez, Joseph F.C. DiMento, Saúl Domínguez Guerrero, Matthew Edwards, Joshua R. Ennen, Hector Estrada-Medina, Natalia Fierro-Estrada, Héctor Gadsden, Patricia Galina-Tessaro, Paul M. Gibbons, Eric V. Goode, Morgan E. Gorris, Thomas Harmon, Susanna Hecht, Marco Antonio Heredia Fragoso, Alan Hernández-Solano, Danae Hernández-Cortés, Gustavo Hernández-Carmona, Scott Hillard, Raymond B. Huey, Matthew B. Hufford, G. Darrel Jenerette, Juan Jiménez-Osornio, Karla Joana López-Nava, Rafael A. Lara Reséndiz, Heather M. Leslie, Alejandro López-Feldman, Víctor H. Luja, Norberto Martínez Méndez, William J. Mautz, Josué Medellín-Azuara, Cristina Meléndez-Torres, Fausto R. Méndez de la Cruz, Fiorenza Micheli, Donald B. Miles, Giovanna Montagner, Gabriela Montaño-Moctezuma, Johannes Muller, Paulina Oliva, José Abraham Ortinez Álvarez, J. Pablo Ortiz-Partida, Julio Palleiro-Nayar, Víctor Hugo Páramo Figueroa, P.Ed. Parnell, Peter Raimondi, Arturo Ramírez-Valdez, James T. Randerson, Daniel C. Reed, Meritxell Riquelme, Teresita Romero Torres, Philip C. Rosen, Jeffrey Ross-Ibarra, Victor Sánchez-Cordero, Samuel Sandoval-Solis, Juan Carlos Santos, Ruairidh Sawers, Barry Sinervo, Jack W. Sites, Oscar Sosa-Nishizaki, Travis Stanton, Jared R. Stapp, Joseph A.E. Stewart, Jorge Torre, Guillermo Torres-Moye, Kathleen K. Treseder, Jorge Valdez-Villavicencio, Fernando I. Valle Jiménez, Mercy Vaughn, Luke Welton, Michael F. Westphal, Guillermo Woolrich-Piña, Antonio Yunez-Naude, José A. Zertuche-González and J. Edward Taylor (2018) “Harnessing cross-border resources to confront climate change”, Environmental Science & Policy, 87, pp. 128–132. Available at: 10.1016/j.envsci.2018.01.001. working paper
Is the Journey to Work Explained by Urban Structure?
Publication Date
October 30, 1993
Associated Project
Author(s)
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?. Working Paper UCTC 107. Institute of Transportation Studies, UC Irvine: University of California Transportation Center. Available at: https://escholarship.org/uc/item/2ss7x5b1.Related Publications
working paper |
Jan 1999
The Determinants of Growth of Employment Subcenters
working paper |
Dec 1994
Hazard Models of Changing Household Demographics
working paper |
Sep 1994
Population and Employment Densities: Structure and Change
working paper |
Oct 1993
Ameliorating Congestion by Income Redistribution
working paper
Does Generalizing Density Functions Better Explain Urban Commuting? Some Evidence from the Los Angeles Region
Publication Date
October 30, 1994
Associated Project
Author(s)
Abstract
The assumption that urban workers economize on commuting is implicit in urban economic theory. Yet it has been challenged by some recent studies. This paper estimates commute flows implied by three urban density functions: monocentric, polycentric, and dispersive. It finds that an urban density function better predicting the actual spatial patterns also better explains the actual commuting behavior. This finding helps us to preserve the assumption that urban workers make attempts to economize on commuting in their location choices.
Suggested Citation
Shunfeng Song (1994) Does Generalizing Density Functions Better Explain Urban Commuting? Some Evidence from the Los Angeles Region. Working Paper No. 197. Institute of Transportation Studies, UC Irvine: University of California Transportation Center. Available at: https://escholarship.org/uc/item/353631r6.Related Publications
working paper |
Jan 1999
The Determinants of Growth of Employment Subcenters
working paper |
Dec 1994
Hazard Models of Changing Household Demographics
working paper |
Sep 1994
Population and Employment Densities: Structure and Change
working paper |
Oct 1993
Ameliorating Congestion by Income Redistribution
published journal article
ERUDITE: Human-in-the-Loop IoT for an Adaptive Personalized Learning System
IEEE Internet of Things Journal
Publication Date
April 1, 2024
Author(s)
Mojtaba Taherisadr, Mohammad Al Faruque, Salma Elmalaki
Abstract
Thanks to the rapid growth in wearable technologies and advancements in machine learning, monitoring complex human contexts becomes feasible, paving the way to develop human-in-the-loop IoT systems that naturally evolve to adapt to the human and environment state autonomously. Nevertheless, a central challenge in designing many of these IoT systems arises from the requirement to infer the human mental state, such as intention, stress, cognition load, or learning ability. While different human contexts can be inferred from the fusion of different sensor modalities that can correlate to a particular mental state, the human brain provides a richer sensor modality that gives us more insights into the required human context. This article proposes ERUDITE, a human-in-the-loop IoT system for the learning environment that exploits recent wearable neurotechnology to decode brain signals. Through insights from concept learning theory, ERUDITE can infer the human state of learning and understand when human learning increases or declines. By quantifying human learning as an input sensory signal, ERUDITE can provide adequate personalized feedback to humans in a learning environment to enhance their learning experience. ERUDITE is evaluated across 15 participants and showed that by using the brain signals as a sensor modality to infer the human learning state and providing personalized adaptation to the learning environment, the participants’ learning performance increased on average by 26%. Furthermore, to evaluate ERUDITE practicality and scalability, we showed that ERUDITE can be deployed on an edge-based prototype consuming 75-mW power on average with 100 MB memory footprint.
Suggested Citation
Mojtaba Taherisadr, Mohammad Abdullah Al Faruque and Salma Elmalaki (2024) “ERUDITE: Human-in-the-Loop IoT for an Adaptive Personalized Learning System”, IEEE Internet of Things Journal, 11(8), pp. 14532–14550. Available at: 10.1109/JIOT.2023.3343462. published journal article
Beyond visual inspection: capturing neighborhood dynamics with historical Google Street View and deep learning-based semantic segmentation
Journal of Geographical Systems
Publication Date
July 12, 2023
Author(s)
Jae Hong Kim, Donghwan Ki, N Osutei, Sugie Lee, John R. Hipp
Abstract
While street view imagery has accumulated over the years, its use to date has been largely limited to cross-sectional studies. This study explores ways to utilize historical Google Street View (GSV) images for the investigation of neighborhood change. Using data for Santa Ana, California, an experiment is conducted to assess to what extent deep learning-based semantic segmentation, processing historical images much more efficiently than visual inspection, enables one to capture changes in the built environment. More specifically, semantic segmentation results are compared for (1) 248 sites with construction or demolition of buildings and (2) two sets of the same number of randomly selected control cases without such activity. It is found that the deep learning-based semantic segmentation can detect nearly 75% of the construction or demolition sites examined, while screening out over 60% of the control cases. The results suggest that it is particularly effective in detecting changes in the built environment with historical GSV images in areas with more buildings, less pavement, and larger-scale construction (or demolition) projects. False-positive outcomes, however, can emerge due to the imperfection of the deep learning model and the misalignment of GSV image points over years, showing some methodological challenges to be addressed in future research.