conference paper
Area of Expertise: Unspecified
Phd Dissertation
Essays on pricing dynamics, price dispersion, and nested logit modelling
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Suggested Citation
Jeremy Alan Verlinda (2005) Essays on pricing dynamics, price dispersion, and nested logit modelling. PhD Dissertation. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/1go3t9q/alma991035093410804701.conference paper
Assessing Public Opinions of and Interest in Bidirectional EV Charging Technologies: A U.S. Perspective
Transportation Research Board 103rd Annual Meeting
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Matthew D. Dean and Kara Kockelman (2024) “Assessing Public Opinions of and Interest in Bidirectional EV Charging Technologies: A U.S. Perspective”.conference paper
Adaptive signal control system with online performance measure for a single intersection
ADVANCED TRAFFIC MANAGEMENT SYSTEMS FOR FREEWAYS AND TRAFFIC SIGNAL SYSTEMS 2002: HIGHWAY OPERATIONS, CAPACITY, AND TRAFFIC CONTROL
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Abstract
An adaptive signal control system with an online signal performance measure is introduced. Unlike conventional signal control systems, the proposed method uses real-time delay estimation and an online signal timing update algorithm. As a signal performance measure, intersection delay for each phase is measured in real-time via an advanced surveillance system that reidentifies individual vehicles at upstream and downstream stations by using vehicle waveforms obtained from advanced inductive loop detectors. In each cycle, the signal timing plan is optimized based on the delay estimated from the vehicle reidentification technology. The main thrust of the algorithm is the online control capability utilizing direct intersection delay measures. A description of the overall control system architecture and the optimization algorithm is addressed. Performance of the proposed system is evaluated with a high-performance microscopic traffic simulation program, Paramics, and the preliminary results prove the promising properties of the proposed system.
Suggested Citation
HX Liu, JS Oh and W Recker (2002) “Adaptive signal control system with online performance measure for a single intersection”, in ADVANCED TRAFFIC MANAGEMENT SYSTEMS FOR FREEWAYS AND TRAFFIC SIGNAL SYSTEMS 2002: HIGHWAY OPERATIONS, CAPACITY, AND TRAFFIC CONTROL. TRANSPORTATION RESEARCH BOARD NATL RESEARCH COUNCIL (Transportation research record), pp. 131–138. Available at: 10.3141/1811-16.working paper
The Activity-Based Approach
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Working Paper
Abstract
What is the activity-based approach (ABA) and how does it differ from the conventional trip-based model of travel behavior? From where has the activity approach evolved, what is its current status, and what are its potential applications in transportation forecasting and policy analysis. What have been the contributions of activity-based approaches to understanding travel behavior?The conventional trip-based model of travel demand forecasting (see Chapters 2 and 3) has always lacked a valid representation of underlying travel behavior. This model, commonly referred to as the four-step model (FSM), was developed to evaluate the impact of capital-intensive infrastructure investment projects during a period where rapid increases in transportation supply were arguably accommodating, if not directing, the growth in population and economic activity of the post-war boom. As long as the institutional environment and available resources supported this policy, trip-based models were sufficient to assess the relative performance of transportation alternatives. It was clear from the beginning, however, that the derived nature of the demand for transportation was understood and accepted, yet not reflected in the FSM. The 1970s, however, brought fundamental changes in urban, environmental, and energy policy, and with it the first re-consideration of travel forecasting. It was during this period that the ABA was first studied in depth.A wealth of behavioral theories, conceptual frameworks, analytical methodologies, and empirical studiesof travel behavior emerged during this same period that the policy environment was evolving. These advances shared “a common philosophical perspective, whereby the conventional approach to the study of travel behavior … is replaced by a richer, more holistic, framework in which travel is analyzed as daily or multi-day patterns of behavior, related to and derived from differences in lifestyles and activity participation among the population” (Jones et al., 1990). This common philosophy has become known as the “activity-based approach”. The motivation of the activity approach is that travel decisions are activity based, and that any understanding of travel behavior is secondary to a fundamental understanding of activity behavior. The activity approach explicitly recognizes and addresses the inability of trip-based models to reflect underlying behavior and, therefore, the inability of such models to be responsive to evolving policies oriented toward management versus expansion of transportation infrastructure and services.In the next section, a summary and critique of the convention trip-based approach is presented, followed by an overview of ABAs, focusing on how these approaches address the various limitations of the conventional model. This is followed by a review of representative examples of activity-based approaches, including several perhaps best considered as contributions to understanding travel behavior, and several oriented toward direct application in forecasting and policy analysis. Some summary comments are then provided including an assessment of the future of both trip-based and activity-based approaches.
Suggested Citation
Michael G. McNally and Craig R. Rindt (2007) The Activity-Based Approach. Working Paper UCI-ITS-WP-07-1. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/86h7f5v0.conference paper
An L.A. Story: Impacts of Land Use and Housing Costs on Commuting
101st Annual Meeting of the Transportation Research Board
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Suggested Citation
Md Rabiul Islam and Jean-Daniel Saphores (2022) “An L.A. Story: Impacts of Land Use and Housing Costs on Commuting”.conference paper
Disaggregating FAF2 data for California
Proceedings of the 2009 meeting of the Transportation Research Forum
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Suggested Citation
S. Aly and A.C. Regan (2009) “Disaggregating FAF2 data for California”, in Proceedings of the 2009 meeting of the Transportation Research Forum.published journal article
Assessing Perception of Wildfires and Related Impacts among Adult Residents of Southern California
International Journal of Environmental Research and Public Health
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Abstract
Major wildfires and their smoke pose a threat to public health and are becoming more frequent in the United States, particularly in California and other populated, fire-prone states. Therefore, it is crucial to understand how California residents view wildfires and engage in risk-reducing behaviors during wildfire events. Currently, there is a knowledge gap concerning this area of inquiry. We disseminated a 40-question cross-sectional survey to explore wildfire perception and knowledge along with related risk-reducing measures and policies among 807 adult residents in the fire-prone region of Orange County, California. Results demonstrated that nearly all (>95%) participants had (or knew someone who had) previously experienced a wildfire. Female gender, knowing a wildfire victim and reporting to have a general interest/passion for environmental issues were the three factors most strongly associated with (1) wildfires (and smoke) being reported as a threat, (2) participants’ willingness to evacuate if threatened by a nearby wildfire, and (3) participants’ willingness to support a wildfire-related tax increase (p < 0.05). The majority (57.4%) of participants agreed that the occurrence of wildfires is influenced by climate change, with the most commonly reported risk-reducing actions (by 44% of participants) being informational actions (e.g., tracking the news) rather than self-motivated physical safety actions (e.g., using an air purifier) (29%). The results of this study can help to inform decision- and policy-making regarding future wildfire events as well as allow more targeted and effective public health messaging and intervention measures, in turn helping to reduce the risk associated with future wildfire/smoke episodes.
Suggested Citation
Shahir Masri, Erica Anne Shenoi, Dana Rose Garfin and Jun Wu (2023) “Assessing Perception of Wildfires and Related Impacts among Adult Residents of Southern California”, International Journal of Environmental Research and Public Health, 20(1), p. 815. Available at: 10.3390/ijerph20010815.conference paper
Activity pattern recognition by using support vector machines with multiple classes
Proceedings of the 92nd annual meeting of the transportation research board
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Abstract
The focus of this paper is to learn the daily activity engagement patterns of travelers by using a nontraditional model called Support Vector Machines (SVM) that is widely used in Artificial intelligence and Machine Learning. It is postulated that an individualâ??s choice of activities depends not only on socio-demographic characteristics but also on previous activities of individual at the same day. In the paper, Markov Chain models are used to study the sequential choice of activities. The dependency between activity type, activity sequence and socio-demographic data are captured by employing Conditional Random Fields. In order to learn model parameters, we use sequential multinomial logit model and multiclass Support Vector Machines (K-SVM) with two different dependency structures. In the first dependency structure, it is assumed that type of activity at time t depends on the last previous activity and sociodemographic data, whereas in the second structure we assume activity selection at time t depends on all previous activity types of the individual on the same day and her sociodemographic characteristics. The models are applied to data drawn from Orange County and San Diego County households and a comparison of the accuracy of estimation indicates the superiority of K-SVM with first dependency structure over the other models tested. Additionally, we show that by using different sets of explanatory variables or tuning parameters of the kernel function in K-SVM, its accuracy in estimating activity patterns increases.
Suggested Citation
Mahdieh Allahviranloo and Will Recker (2013) “Activity pattern recognition by using support vector machines with multiple classes”, in Proceedings of the 92nd annual meeting of the transportation research board, p. 20p.book/book chapter