Navigation is a central part of daily life. For some, getting around is easy, while others struggle. Some clinical populations, such as those with Alzheimer’s Disease, display wandering behaviors and extensive disorientation. Working at the interface between immersive virtual reality and neuroimaging techniques, my research uses these complementary approaches to inform questions about how we acquire and use spatial knowledge. In this talk, I will discuss both some of my recent work and current experiments that center on three main themes: 1) how we learn new environments, 2) how the brain tracks spatial information, and 3) how individuals differ in their spatial abilities. The studies presented in this talk inform new frameworks for understanding spatial knowledge, leading to novel approaches to answering the next major questions in navigation, learning, and memory.
Dr. Elizabeth Chrastil is an Associate Professor in the Department of Neurobiology & Behavior at UC Irvine, with an appointment in the Department of Cognitive Sciences, and is a fellow of the Center for the Neurobiology of Learning & Memory. She was awarded the Early Career Award from the Psychonomic Society in 2023. Dr. Chrastil received her PhD from Brown University and did her postdoctoral work at Boston University. She also received an MS in biology from Tufts University and a BA from Washington University in St. Louis.
High school students in the US generate a lot of travel, but their travel behavior has not been widely studied. We have administered a survey to high school students in Los Angeles to measure their travel behavior and examine their response to a new program (called GoPass) that provides free transit trips to any K-14 student in the Los Angeles metropolitan area. We examine students’ choice to sign up and use GoPass. Our survey includes a Stated Preference experiment to measure students’ value of time and their demand for new services such as robotaxis. This talk provides preliminary results from the survey and transportation choice models.
David Brownstone is an emeritus Professor of Economics at UCI. He has studied the impacts of tax reform on housing demand, the impacts of measurement errors in economic surveys, the impacts of carpool lanes and road pricing, the impacts of urban form on household vehicle choice and utilization, the demand for alternative-fueled vehicles, the economic impact of California’s rail system, and the demand for public transportation. In addition to his applied work, Brownstone was one of the first econometricians to apply bootstrapping and multiple imputations to generate valid inferences in complex models. Together with Kenneth Train and David Bunch he was one of the first to apply mixed logit models in household vehicle demand and transportation mode choice models. Brownstone currently serves on the editorial boards of Transportation Research (Part B: Methodological), Economics of Transportation, and The Journal of Choice Modeling.
The planning of linear transportation infrastructures, which for decades has followed the geometric design premises of highways and railways mainly in greenfield projects, currently faces significant challenges. These challenges include the need for a strong inclusion of socio-environmental perspectives, as well as a continuous analysis of the logistical and economic feasibility of the project considering the existence of an already operating transportation system. In this sense, this presentation will argue for the need to modernize transportation planning and promote ESG (Environmental, Social, and Governance) principles in current and future projects. Results of research projects on the topic will be presented, focusing on Transport Ecology, Geographic Modeling of Corridors of Technical, Economic, and Environmental Feasibility, geographical simulations of routes and micro-logistic basins based on changes in freight costs resulting from new highways and railways, and predictive models of impacts on landscapes and distant indigenous populations.
Dr. Rodrigo A. A. Nóbrega holds a degree in Cartographic Engineering from UNESP (1996), and a Master’s and PhD in Transportation Engineering specializing in Remote Sensing and GIS from the Polytechnic School of USP (2007) in Brazil. He completed his Postdoctoral studies at the Geosystems Research Institute – Mississippi State University (2010). With 28 years of experience in GIS, Dr. Nobrega’s research focuses on geographic intelligence for transportation planning. He is currently an Associate Professor at the Department of Cartography, Institute of Geosciences at Federal University of Minas Gerais (UFMG).
Now in its 9th year, the Transportation Colloquium at the University of California, Irvine (UCI) features presentations from leading scholars and practitioners in the fields of urban planning, public policy, engineering and transportation. Guests may attend virtually or in-person.
Motor vehicle crashes have remained the leading cause of death among adolescents for decades. Today, Riding with an Impaired Driver (RWI) and Driving While Impaired (DWI) among young drivers is prevalent. The presentation will describe recent theory-driven, multistage, mixed-methods investigation focused on the development of trajectories of RWI/DWI behaviors in adolescents and will provide early insights of trajectory influence on health, education, and employment among emerging adults.
Dr. Federico Vaca was recently recruited back to UCI from the Yale School of Medicine where he was Professor and Vice Chair in the Department of Emergency Medicine. During his tenure at Yale, he established the Yale Developmental Neurocognitive Driving Simulation Research Center (DrivSim Lab).Now here at UCI he is Professor and Executive Vice Chair in the Department of Emergency Medicine at the University of California Irvine’s School of Medicine – Department of Emergency Medicine. He is a board-certified emergency medicine physician and physician-scientist. He previously served as a Medical Fellow for the U.S. Department of Transportation’s National Highway Traffic Safety Administration (NHTSA) in Washington, D.C. Over the last 20 years, his research has focused on occupant safety, adolescent development and behaviors that influence the risk of motor vehicle crash injury as well as health disparities in alcohol use disorders, impaired driving, and crash-injury. His research has been funded by the NIH’s Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NIH’s Office of Behavioral and Social Sciences Research (OBSSR), and the National Institute of Alcohol Abuse and Alcoholism (NIAAA).Dr. Vaca has chaired and served on several NIH scientific review committees, chaired national expert panels directed by the National Academies of Sciences, Medicine, and Engineering’s Transportation Research Board, and was previously appointed by the U.S. Secretary for Health and Human Services to serve on the Board of Scientific Counselors for the CDC’s National Center for Injury Prevention and Control.
Over 10% of US new vehicle sales are electric (25% in California). As the number of EVs grows and the power system moves to intermittent renewable generation, there is a natural synergy of encouraging flexible charging schedules to absorb renewables and avoid creating a new demand peak. Further, a growing share of EVs now offer bi-directional charging technology that can power small appliances up to one’s home or sell power back to the grid. Despite numerous research studies on the financial and technical requirements of smart EV charging, only a few have directly investigated consumer interest in these charging features. This presentation presents early findings from a study exploring Americans’ values of a zero-carbon energy-transportation future, willingness to accept smart charging (and at what cost), willingness to pay and expected use of bi-directional features.
Dr. Dean is an Assistant Professor of Civil and Environmental Engineering at the Institute of Transportation Studies, UC Irvine. His research focuses on sustainable transportation systems, planning and operations of electric and fully-automated vehicle fleets, integrated transportation and energy system modeling, and the link between physical activity and transportation-land use planning. His research identifies the suite of technologies and policies that can address complex urban problems, like climate change, rising energy and mobility demands with constrained infrastructure, and physical inactivity, to create sustainable and healthy communities.
He received his Ph.D. and MS in Civil Engineering from the University of Texas at Austin and his BS in Civil Engineering with a minor in Urban and Environmental Planning from the University of Virginia. Matt is a member of the ASCE T&DI Mobility on Demand and as a Service (MODaaS) and the Sustainable Transportation committees. During his graduate studies, he was an NSF Graduate Research Fellow.
This presentation will navigate the intricacies of driving tasks, whether for human-driven or automated vehicles, involves a tripartite framework: sensing, planning, and action. While the action stage demonstrates commendable precision and the sensing stage grapples with stochastic variables amid fervent development, the trajectory planning stage emerges as a linchpin in ensuring safe operations within the realm of sensor uncertainties and inaccuracies. Presently, prevailing paradigms rooted in artificial intelligence, advanced driving assistance systems, and car-following models remain bereft of a rigorous mathematical safety proof and the ability to replicate human-like acceleration and deceleration patterns.
Dr. Wenlong Jin (BS in Automatic Control, University of Science and Technology of China, 1998; PhD in Applied Mathematics, UC Davis, 2003) is a Professor of Civil and Environmental Engineering at the Institute of Transportation Studies, UC Irvine. With a profound passion for the intricate workings of transportation and mobility systems, his expertise lies in the exploration of fundamental principles, concepts, models, and methods. Throughout his career, Dr. Jin has delved deep into various facets of transportation, including the comprehensive study of network traffic flow theory, capacity drop and lane-changing models, connected vehicle systems theory, and eco-friendly driving strategies.
The Transportation Colloquium at the University of California, Irvine began seven years ago. It is an annual series that features presentations from leading scholars and practitioners in the fields of urban planning, public policy, engineering and transportation.
The Colloquium was established as a collaborative effort celebrating the close relationship between planners and engineers. It provides a forum for scholars and practitioners from these different fields to share their work and learn from each other and provides an opportunity for students to learn from experits in the field and to network with potential employers.
The Colloquium has covered a wide range of topics over the years, including transportation and technology, autonomous and connected vehicles, as well as this year’s theme of equity and social justice.
We gratefully acknowledge the support of the UC ITS Statewide Transportation Research Program (STRP), UC ITS Resilient and Innovative Mobility Initiative (RIMI), USDOT Center for Automated Vehicle Research and Multimodal AssurED Navigation (CARMEN), USDOT Pacific Southwest Region University Transportation Center (PSR).
Motivated by the need to manage a complex and evolving intelligent transportation system in a collaborative framework, we describe five components of multi-agent modeling paradigm with several implementation examples from the VT-SCORES research lab at Virginia Tech. The research components discussed range from driver behavior, car-following models, adaptive control, and connected vehicles applications. We will show examples of extracting driver behavior from large datasets, modeling evolving system behavior with intelligent agents, integration of state estimation and communication frameworks in a connected vehicles environment, and the ramifications of neglecting learning in modeling. The presented agent-based framework is intermodal, and can incorporate performance characteristics and needs of different users (cars, trucks, busses, pedestrians, and bikes). The presentation will also touch on the latest innovations at the VT-SCORES lab and how it can help address evolving and complex transportation problems.
Dr. Monty Abbas is a Professor in the Transportation Infrastructure and Systems Engineering at Virginia Tech. He holds a PhD in Civil Engineering from Purdue University (2001). Dr. Abbas developed and implemented several algorithms and systems in his areas of interest, including the Platoon Identification and Accommodation system (PIA), the Pattern Identification Logic for Offset Tuning (PILOT 05), the Supervisory Control Intelligent Adaptive Module (SCIAM), the Cabinetin-the-loop (CabITL) simulation platform, the Intelligent Multi Objective Control Algorithms (I-MOCA), the Traffic Responsive Iterative Urban-Control Model for Pattern-matching and Hypercube Optimal Parameters Setup (TRIUMPH OPS), the Multi Attribute Decision-making Optimizer for Next-generation Network-upgrade and Assessment (MADONNA), the Safety and Mobility Agent-based Reinforcement-learning Traffic Simulation Add-on Module (SMART SAM), and the Broad Area-wide and Distance-wise Agent-based Signal-optimization System (BADASS). He was also one of the key developers of the dilemma zone protection Detection Control System (D-CS) that was selected as one of the seven top
research innovations and findings in the state of Texas for the year 2002. He is a recipient of the Dean’s Award for Excellence in Service, ICAT Creativity and Innovation Day Process Award for the Traffic SONATA project, Best Paper Award, Western Decision Sciences Institute (WDSI) 2018 Conference, Oak Ridge National Lab Associated niversities (ORAU) Ralf E. Powe Junior Faculty Enhancement Award and the G. V. Loganathan Faculty Achievement Award for Excellence in Civil Engineering Education. He is also a recipient of the TTI/Trinity New Researcher Award for his significant contributions to the field of Intelligent Transportation Systems and Traffic Operations.
Logistic systems, often face big challenges when making operational decisions, mainly due to existence of unpredictable and uncontrollable variables. Obviously, the complexities are more pronounced as problems scale up, often with exponential rates. Large and various datatypes generated from different resources means more variables to calibrate and tune and more models to validate. It demands use and development of state-of-the-art optimization models and machine learning tools, that are robust but also adoptable and transferrable from one application to another. In this presentation, an overview of different distributed mathematical models will be presented, it will be followed by the use cases of these approaches in different transportation problems. Finally, we will discuss how transportation experts, can benefit from the cloud computing and the advantages that it can offer through a practical example.
Dr. Mahdieh Allahviranloo is an associate professor of civil engineering, at the City College of New York (CCNYCUNY). She is also a Visiting Academic at Amazon, working with the Amazon Last Mile Science team, and is currently spending her sabbatical from the university. After getting her civil engineering degree in Iran, she got her PhD in transportation engineering at the University of California, Irvine. In her academic research, she integrates data mining, statistical analysis, and optimization models to study how individuals move in urban areas. During her sabbatical at Amazon, she uses her academic training to solve a wide range of problems in the last mile logistic domain.