Event Type: Seminar

Advances in spatial technologies, specifically geographic information systems (GIS), are allowing new and innovative forms of transportation research. Drs. Horan and Hilton will present findings from recent research at their Advanced GIS Lab. These innovations include several undertakings in transportation safety, and more recently, spatial analysis of freight rail and community development. The transportation safety work has highlighted the extensiveness of rural safety problems and the regional freight research has linked economic cluster analysis with community development. The aim of this research is to provide policy makers and citizens with an understanding of transportation’s spatial dimension in a manner that can inform policies aimed to improve transportation’s safety and community impacts.

Dr. Horan is Professor and Director, Center for Information Systems and Technology, Claremont Graduate University. Dr. Horan has over 25 years experience in transportation research, including Intelligent Transportation Systems (ITS) and Geographic Information Systems (GIS). He has published over 140 articles and has led several national studies on rural transportation safety, emergency response systems, and transportation community impacts.
Dr. Hilton is Associate Clinical Professor and Director, Advanced GIS Lab, Center for Information Systems and Technology, Claremont Graduate University. Dr. Hilton has 15 years experience is GIS and led the creation of the founding Esri Development Center (EDC) at Claremont Graduate University.
Drs. Hilton and Horan’s work on GIS and transportation safety were recently showcased at the White House’s Open Data Initiative Conference.

The rapid expansion of the U.S. biofuel industry diverts a large amount of farm land into energy feedstock production, and in turn affects food, energy and land market equilibria, as well as agricultural economic development in local areas. In this talk, we present Stackelberg-Nash game models that incorporate farmers’ decisions on land use and market choice into the biofuel manufacturers’ supply chain design problem. The models determine the optimal number and locations of biorefineries, the required prices for these refineries to compete for feedstock resources, as well as farmers’ land acquisition and production decisions. We also introduce government farmland use regulations that aim at balancing food and energy production and marginal land use, and a cap-and-trade implementation mechanism. Spatial market equilibrium is utilized to model the relationship between crop supply and demand and the associated price variations in local food markets. We develop solution approaches that transform the original discrete mathematical program with equilibrium constraints into a mixed integer quadratic programming problem, and explore adaptive decomposition methods based on Lagrangian and linear relaxations. The proposed methodologies are illustrated with an empirical case study of the Illinois State. The computation results reveal interesting insights into optimal land use strategies, government regulations, and supply chain design for sustainable development of the emerging "biofuel economy.”
(Joint work with Yun Bai and Jong-Shi Pang)

Yanfeng Ouyang is an associate professor and the Paul F. Kent Endowed Faculty Scholar of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign (UIUC). He received his Ph.D. in civil engineering from the University of California at Berkeley in 2005. His research interest mainly focuses on the areas of transportation and logistics systems, interdependent infrastructure systems, traffic flow theory and operations, and applications to renewable energy, sensor, and agricultural systems. He currently serves as a department editor of IIE Transactions (Focused Issue on Operations Engineering and Analytics), an associate editor of Transportmetrica B, a guest editor of Transportation Research Part B (special issue), and he is on the editorial advisory board of Transportation Research Part B and the Journal of Infrastructure Systems. He received the Faculty Early Career Development (CAREER) Award from the U.S. National Science Foundation in 2008, the High Impact Project Award from the Illinois Department of Transportation in 2014, the Engineering Council Outstanding Advisor Award from UIUC in 2014, the Xerox Award for Faculty Research from UIUC in 2010, and the Gordon F. Newell Award from Berkeley in 2005.

Over the past 20 years the transportation engineering field has witnessed a data revolution—some might say that we have transitioned from a data “desert” to a data “ocean.” Join Prof. Robert Bertini as he traces aspects of his research career over this period and describes the ways in which this data “ocean” has inspired, enabled and influenced his work. We know that most transportation management, logistics, and operations systems, as well as intelligent transportation systems (ITS) applications are founded upon a data infrastructure, and sometimes these data are archived in a systematic manner. If managed properly, archived ITS data from sensors and mobile probes can provide a unique foundation for scientific discovery in the traffic and transportation field. Through careful processing and using innovative visualization techniques, transportation data can reveal fundamental traffic principles, behavior and phenomena, such as freeway merging at on-ramps and lane-drops and oscillations. Transport data may also be used to enable the optimization of the deployment of transportation resources, such as freeway sensors, traffic management applications or transit stops. Further, transport data, if analyzed carefully can provide the basis for conducting evaluations and assessments of transportation system congestion and performance, at different geographic levels, such as facility, corridor or region. Finally, the inception of a “connected” transportation environment with vehicles and infrastructure devices communicating at high frequency, we are moving to yet another level of transportation data availability. But numerous questions remain about who will own and manage these data, how will privacy be maintained and more. What does the future hold in the field of transportation enabled by an avalanche of high-resolution multimodal data? Also to be presented will be some approaches for meeting challenges and opportunities in the civil and environmental engineering field, which continues to be people-serving, relevant and critical for the future of our society. Finally some thoughts on teaching and civil and environmental engineering education will be discussed.

Robert L. Bertini is a professor of Civil and Environmental Engineering at Portland State University. He earned a B.S. in Civil Engineering from the California Polytechnic State University, San Luis Obispo; an M.S. in Civil Engineering from San Jose State University, and a Ph.D. in Civil Engineering from the University of California at Berkeley. He is a sought-after teacher, advisor, lecturer and facilitator. He received a National Science Foundation CAREER award. He is the faculty lead for the Portland Sustainable Transport Lab, chairs the TRB Committee on Traffic Flow Theory and Characteristics and will be serving as the Chair of the TRB Operations Section (covering 13 committees). He has developed an innovative Intelligent Transportation Systems Laboratory and was the founding director of the Oregon Transportation Research and Education Consortium (OTREC), a National University Transportation Center. From 2009-2011, he served as Deputy Administrator of the Research and Innovative Technology Administration at the U.S. Department of Transportation.

Against the backdrop of an ageing Japan, and as a countermeasure against the low birthrate phenomenon, the promotion of an environment that allows children, pregnant women, and parents of babies and young children to participate in out-of-home activities in a safe and comfortable manner is increasingly becoming more important. This study focuses on barriers encountered by parents with young children when conducting out-of-home daily activities. We conducted a web-based questionnaire survey on 1,000 women with young children living in the Kanto Region, including Tokyo Metropolitan Area. We found differences in their travel mode and frequency, and attitude towards barriers for out-of-home activity participation among living areas and individual/household characteristics such as working mother or not, numbers and years of children, years of raising child, household structures, etc.

Nobuaki Ohmori is associate Professor in the Department of Urban Engineering at the University of Tokyo. He received his PhD in Urban Engineering in March of 2000 from the University of Tokyo. His research interests include urban accessibility and transportation for Children and parents, and more generally urban transportation planning;travel behavior; activity-travel analysis;and Information and Communication Technologies applied to transportation.

 

Two analytical models are introduced for predicting the allocation to ports and transportation channels of containerized goods imported from Asia to North America. Assuming fixed distributions for container flow-times, the Long-Run Model heuristically solves a mixed integer non-linear program to determine the least-cost supply-chain strategies for importers. The Short-Run Model uses estimates of the flow times as a function of traffic volumes on fixed infrastructure to iteratively develop the best near-term strategies.

The models allocate imports to alternative ports and logistics channels so as to minimize total transportation and inventory costs for each importer. Alternative logistics channels include direct shipment of marine containers via truck or rail, and trans-loading cargoes in the hinterlands of the ports of entry from marine containers into domestic trailers or containers.

The models are calibrated on industrial data. Minimum volume requirements and capacities for ports and landside channels are considered. The results are analyzed, and are used to describe the mix of supply-chain strategies utilized by various types of importers and the consequent trends in import flows by port and landside channel. Policy recommendations for governments, transportation and logistics service providers, and importers are also provided. (Joint work with Rob Leachman at U.C. Berkeley)

Payman Jula is an Associate Professor at Beedie School of Business, Simon Fraser University (SFU), Vancouver, Canada, where he teaches courses related to operations management, and decision making under uncertainty. Payman has a PhD in Industrial Engineering and Operations Research from University of California at Berkeley. His research interests are in transportation and logistics, and applications of operations management in the manufacturing and service industries. Payman has studied the economics of Asia – North America supply chains, and today will present his work in this area.

Transportation involves human, infrastructure, vehicle, and environmental interactions and is therefore a very complicated system. Traditionally, transportation has been studied through classical methods, typically with ideal assumptions, limited data support, and poor computing resources. While the theories (such as traffic flow and driver behavior models) developed through these efforts provide valuable insights in understanding transportation-related issues, they are often ineffective in large-scale transportation system analysis with massive amount of data. Also, transportation activities have been found affecting public health, air quality, environmental sustainability, etc., but our understanding in these relationships has been trivial and far from complete.

With recent advances in sensing, networking, and computing technologies, more and more transportation-related data and computational resources become available. These new assets are likely to bring in new opportunities to understand transportation systems better and address those critical transportation issues in a faster, more accountable, and more cost-effective way. From big data to big discoveries and big decisions: what is the gap and what needs to be done? Clearly, a new theoretical framework is needed to integrate the quickly growing massive amount of data, typically from numerous sources of varying spatial and temporal characteristics, into the large-scale transportation problem solving and decision making processes. Efforts along this line are likely to form up a new subject area, namely e-science of transportation, in the years to come. The speaker will share his vision and pilot research in linking big data to big discoveries and big decisions through his talk.

Dr. Yinhai Wang is a professor in transportation engineering at the University of Washington (UW). He has a Ph.D. in transportation engineering from the University of Tokyo (1998), a master’s degree in computer science from the UW, and another master’s degree in construction management and a bachelor degree in civil engineering from Tsinghua University, China. Dr. Wang is the founding director of the Smart Transportation Applications and Research Laboratory (STAR Lab) at the UW. He also serves as the director for Pacific Northwest Transportation Consortium (PacTrans), USDOT University Transportation Center for Federal Region 10.

Dr. Wang’s active research fields include traffic sensing, transportation safety, e-science of transportation, traffic operations, traffic simulation, and intelligent transportation systems (ITS). He has over 170 academic publications and delivered more than 240 academic talks. He was the winner of the ASCE Journal of Transportation Engineering Best Paper Award for 2003. Dr. Wang serves as members of three Transportation Research Board committees: Transportation Information Systems and Technology Committee (ABJ50), Freeway Operations Committee (AHB20), and Highway Capacity and Quality of Services (AHB40). He is currently on the Board of Governors for the ASCE Transportation & Development Institute. He was an elected member of the Board of Governors for the IEEE ITS Society from 2010 to 2013. Additionally, Dr. Wang is associate editor for three journals: Journal of ITS, Journal of Computing in Civil Engineering, and Journal of Transportation Engineering.

Intelligent Transportation Systems (ITS) encompass a broad range of wireless and wireline communications-based information, control and electronics technologies. When integrated into the transportation system infrastructure, and in vehicles themselves, these technologies help to monitor and manage traffic flow and capacity, reduce congestion, provide alternate routes to travelers, enhance productivity, and save lives, time and money.

Mr. Quon will be providing an overview of traditional infrastructure projects to develop a framework of how ITS technologies can be used to effectively manage traffic. Case studies of ITS projects in the Los Angeles region will be introduced to show the process of identifying traffic problems and responding with the appropriate ITS strategies that bridges the gap between existing infrastructure and technology through Intermodal Integration.

This will lead into a discussion of ITS strategies including: adaptive ramp metering, Connected Corridors, Bike Detection, Bus Signal Priority, Smart Park and Ride, Express Park, Smart Arterials, Smarter Highways, Express Lanes and Traffic Signal Synchronization.

Frank Quon is currently the Executive Officer in the Highway Program with the Los Angeles County Metropolitan Transportation Authority (Metro). He holds responsibilities for the delivery of Highway Projects funded through Metro and the Countywide Signal Synchronization/Bus Speed Priority Program. He manages the delivery of $12-$15 billion highway projects throughout Los Angeles County. Previously, Frank was the Deputy District Director for Operations in District 7. He had the responsibility for the safety and operation of the state freeway and highway system in Los Angeles and Ventura Counties. Frank earned his Bachelor of Science degree in Civil Engineering from Loyola Marymount University.

Ever since the term “SCM”first emerged in 1982 by Keith Oliver, one of strategic consultants at BAH, it has been widely acknowledged that supply chain management could be used as a strategic differentiator in a global business environment. As the network of supply gets more complicated and dispersed, this trend becomes a normal phenomenon among many of the leading corporates. Under this environment, SCM is no more a simple and tactical principle that governs the operation of a corporate: rather, it has to be highlighted as somewhat novel concept which is directly related to the core value of an enterprise. Starting with a basic question about the true identity of the SCM, this presentation will redefine the meaning of SCM from corporate’s core value system. To this end, various business cases will be discussed to draw some significant implications that can be observed only when we look SCM from value perspectives.

Dr. Jung Ung Min received his Ph.D degree in Civil and Environmental Engineering from Stanford University. He is currently an Associate Professor with Asia-Pacific School of Logistics and the Graduate School of Logistics in Inha University, Korea. His current research interests include Supply Chain Management Strategy, Supply Chain Solutions, and Logistics Security. Using his past experience in Samsung SDS as a senior consultant, he is actively participating in industry consultancy and advisory boards of many leading Korean companies such as Samsung Electronics, LG Electronics, Hyundai Motors, and etc. He has authored for 14 peer-reviewed journal papers and 2 books.

Driving behavior caused by vehicle interactions, such as acceleration, deceleration, and stop-and-go, is highly associated with traffic safety and the environment. The purpose of this study is to investigate whether traffic safety can be linked to environmental conditions, more specifically crash potential and on-road vehicle emissions. Individual vehicle trajectory data obtained from the US-101 freeway, as a part of the Next Generation Simulation (NGSIM) project, was used to investigate the relationship. A probabilistic rear-end crash potential model and a motor vehicle emission simulator (MOVES) were adopted to characterize traffic safety and environmental conditions, respectively. Both the crash potential index (CPI) and the vehicle emission index (VEI) were derived, and then investigated through correlation, regression, and clustering analyses. The findings revealed that the relationship is positively correlated and statistically significant. In addition, the results showed that severely congested traffic conditions, which include frequent stop-and-go situations and the formation of shockwaves, lead to greater crash potential as well as vehicle emissions. In summary, traffic safety and environmental conditions are positively associated. The outcomes of this study are expected to be used as useful fundamentals in developing effective vehicle safety and emission control programs and policies.

Cheol Oh received the Ph.D. degree in civil engineering-transportation from the University of California, Irvine. He is currently an Associate Professor with the Department of Transportation and Logistics Engineering, Hanyang University at Ansan, Korea. His research interests include traffic operations and control, traffic safety, and intelligent transportation systems (ITS). He is primarily focused on the development and application of information technologies toward safer and more efficient transportation systems. He has authored 94 peer-reviewed journal papers (Korean:66, International:28).Network and Spatial Economics. He is also on the editorial board of Transportation Research Part B, Journal of Intelligent Transportation Systems, and IET Intelligent Transportation Systems Journal.

Understanding the traffic evolution process after an unexpected network disruption is of great significance to traffic engineers who are responsible for traffic restoration. In this talk, we will discuss our recent findings on the day-to-day traffic equilibration process following the unexpected collapse and eventual reopening of the I-35W Bridge over the Mississippi River in Minneapolis. Following the I-35W Bridge collapse, drivers were observed to drastically avoid areas near the disruption site until the perceived congestion in that area gradually diminished. After the reopening of the disrupted link, despite a complete restoration of network topology, it was found that total demand restoration on that link did not occur, implying that a different traffic equilibrium was reached. Due to the rare occurrence of the network disruption event, such behaviour has not been reported in the literature and none of the existing day-to-day traffic assignment models are capable of explaining the empirical evidences. To fill in this gap, we have developed a nonlinear dynamic system that is capable of describing the transient states of a disrupted network, answering questions related to the traffic evolution trajectory from a disequilibrium (due to a network disruption) toward an equilibrium. Our models are calibrated and validated using the data collected from the Twin Cities network after the bridge collapse and reopening. To the best of our knowledge, this is the first time that day-to-day traffic equilibration models have been constructed and compared against real world observations.

Dr. Henry Liu is currently an associate professor of Civil Engineering at the University of Minnesota – Twin Cities. Before joining the University of Minnesota, he was an assistant professor at Utah State University and a post-doctoral researcher at the California PATH Program of UC-Berkeley. He received his Ph.D. degree in Civil and Environmental Engineering from the University of Wisconsin at Madison in 2000 and his B.E. degree in Automotive Engineering from Tsinghua University (China) in 1993. Dr. Liu’s research interests are in the area of traffic network monitoring, modeling, and control, which includes traffic flow modeling and simulation, traffic signal operations, and equilibrium traffic assignment. On these topics, he has published more than 50 articles in peer-reviewed journals. Dr. Liu is currently the overview paper editor of Transportation Research Part C and an associate editor of Network and Spatial Economics. He is also on the editorial board of Transportation Research Part B, Journal of Intelligent Transportation Systems, and IET Intelligent Transportation Systems Journal.