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Updated: 30 min 13 sec ago

Transit-Oriented Development: Putting it all Together, Mar 20-29

30 min 13 sec ago
Transit-oriented development (TOD) has emerged as a powerful, effective way to integrate land use and public transit. TOD done right links smart growth and sustainability with higher capacity rail or bus transit services. This linkage takes place in the environs of the rail passenger station or the bus rapid transit stop. TOD concentrates workplaces, residences, and supporting retail services within convenient walking distance of rail or bus rapid transit service. In doing so, TOD brings customers to public transit services as well as creates vibrant, mixed-use communities. There are many challenges in creating successful TODs. These include building effective public-private partnerships, ensuring multi-modal TOD access for the "last mile" and beyond, "right-sizing parking", and balancing private and public uses to create a unique place identify.

Inside NSF, Mar 23

30 min 13 sec ago
This workshop will explain how NSF is structured, how it functions, and how it reviews proposals, with an eye towards how trends and federal policies affect its work. This session will help faculty apply an understanding of how NSF works to their funding strategies.

Writing Specific Aims, Apr 13

30 min 13 sec ago
This workshop will show you how to write succinct yet powerful specific aims for your research proposal. Your specific aims are the scaffold that holds your entire proposal together, and they can either grab a reviewer's attention or lose their interest completely. In this workshop, we will describe how to frame your specific aims to best support your research proposal.

Modeling and Analysis of Dynamic Pricing of Ride-Sourcing Services, Apr 21

30 min 13 sec ago
Abstract: Ride-sourcing companies such as Uber, Lyft and Didi Chuxing are transforming the way people travel in cities. The services these companies offer have enjoyed huge success but also created many controversies — one of them centered on dynamic (surge) pricing. In this talk, we present an aggregate, equilibrium modeling framework for ride-sourcing markets with a focus on evaluating temporal and spatial effects of dynamic pricing. Our modeling framework features the equilibration of demand and supply, while explicitly capturing the advanced matching technology that a ride-sourcing platform adopts to match customers and drivers. The framework can be tailored to addressing key modeling considerations in different dimensions such as the spatial distribution of vacant vehicles and drivers’ work scheduling behaviors. The tradeoffs in the welfare of different market players under dynamic pricing and possible management policies will be discussed based on the equilibrium outcomes.

Bio: Dr. Yafeng Yin is a Professor at Department of Civil and Environmental Engineering, University of Michigan. He works in the area of transportation systems analysis and modeling, and has published over 90 refereed papers in leading academic journals.. Dr. Yin is the Editor-in-Chief of Transportation Research Part C: Emerging Technologies and serves on the editorial boards for another four transportation journals. He is a member of Transportation Network Modeling Committee and International Cooperation Committee of Transportation Research Board. He is also the Immediate Past President of Chinese Overseas Transportation Association (COTA). Dr. Yin received his Ph.D. from the University of Tokyo, Japan in 2002, his master’s and bachelor’s degrees from Tsinghua University, Beijing, China in 1996 and 1994 respectively. Prior to his current appointment at the University of Michigan, he was a faculty member at University of Florida between 2005 and 2016. He worked as a postdoctoral researcher and then assistant research engineer at University of California at Berkeley between 2002 and 2005. Between 1996 and 1999, he was a lecturer at Tsinghua University.

Increasing Freeway Capacity by Efficiently Timing its Nearby Arterial Traffic Signals, May 5

30 min 13 sec ago
Abstract: The objective of freeway on-ramp metering is to regulate the entry of vehicles to prevent capacity drop on the freeway mainline. However, the nearby arterial traffic signals facilitating freeway access fail to recognize that the metered on-ramps can be oversaturated due to the flow restriction and limited storage. Instead, the arterial traffic signals provide long cycles in order to maximize arterial capacity during peak hours. This often leads to large platoons of arterial traffic advancing to the on-ramps and thus queue spillback on the surface street. As a result, most ramp meters employ a “queue override” feature that is intended to prevent the on-ramp queue from obstructing traffic conditions along the adjacent surface streets. The override is triggered whenever a sensor placed at the entrance of the on-ramp detects a potential queue spillover of the on-ramp vehicles on the adjacent surface streets, and releases the queue into the freeway. The queue override reduces the effectiveness of ramp metering during the time of highest traffic demand, when the ramp metering is most needed. A field test undertaken at a freeway bottleneck in San Jose, California shows that queue override may reduce the freeway capacity by 10%. Significant benefits can be realized by reducing cycle length to prevent on-ramp oversaturation and thereby queue override. A method for determining the appropriate cycle length was developed and the improved signal timing was tested through simulation. The results show that the proposed approach prevented queue override and reduced both freeway and arterial delays.
Bio: David Kan is a Ph.D. candidate in Civil and Environmental Engineering in the Transportation Engineering program. He received his M.S. in Civil and Environmental Engineering at UC Berkeley in May 2014, and his B.S. in Civil and Environmental Engineering at University of Illinois Urbana Champaign in May 2013. His research interests include traffic operations, intelligent transportation systems, and connected and automated vehicles. He will be joining PATH as a postdoctoral researcher in May 2017.

Changing Fuel Loading Behavior to Improve Airline Fuel Efficiency, Mar 24

30 min 13 sec ago
Abstract: Airlines rely on flight dispatchers to perform the duty of fuel planning. The required trip fuel is calculated by airlines’ Flight Planning Systems (FPS). However, the FPS trip fuel predictions are not always accurate. If planned trip fuel is higher than actual trip fuel, then a flight will waste fuel by carrying excess fuel weight. On the other hand, if trip fuel is under-estimated, then a flight might run into fuel emergency. In practice, dispatchers may also load contingency fuel to mitigate the risks of under-prediction. FPS also calculates recommended contingency fuel quantity for dispatchers called statistical contingency fuel (SCF). However, dispatchers will almost always load extra fuel above suggested SCF values. Therefore, airline fuel efficiency can be improved by more accurate fuel predictions, a deeper understanding of dispatchers’ fuel loading behavior, and more reliable SCF recommendations. Based on a large scale flight fuel loading dataset provided by a US major airline, an ensemble learning algorithm is proposed to improve fuel burn prediction. This method is found to reduce prediction error by over 50% compared to airline’s own predictions. By merging with a dispatcher survey, we are able to integrate dispatchers’ latent attributes into contingency fuel loading modeling. Furthermore, random quantile forests method will also be discussed in improving SCF recommendations. The benefit of improved fuel efficiency will be measured by estimating cost-to-carry reduced unnecessary fuel loading.

Bio: Lei Kang is a Ph.D. candidate of the Institute of Transportation Studies in the Department of Civil and Environmental Engineering, University of California, Berkeley. He received a Master of Arts degree in Biostatistics from the Division of Biostatistics at University of California, Berkeley. He also obtained his Master’s degree in Transportation and Infrastructure Systems Engineering from Purdue University. Lei's Bachelor’s degree is in Transportation Engineering from Tongji University in Shanghai, China. He is a member of the Committee on Airfield and Airspace Capacity and Delay, Transportation Research Board. His research interests are in the application of statistical methods and machine learning techniques to air traffic management and airline fuel loading decisions. He is also interested in causal inference in the area of traffic safety.

Traffic Signal Design: Engineering Concepts, Mar 29-30

30 min 13 sec ago
This newly updated course covers basic concepts, standards, and practices related to the design and installation of traffic signals. Within the framework of the California Vehicle Code, California Manual on Uniform Traffic Control Devices (CA MUTCD), and Chapter 9 on Highway Lighting from Caltrans Traffic Manual, this course will explore the relationship among various engineering disciplines as foundations for signal design; introduce signal phasing diagrams, signal controllers and cabinets; explain the layouts of signal heads, signal poles, conductor schedule, and associated signal conduits, pullboxes, wiring, interconnects, detection and safety lighting. The course includes lectures, sample problems, and exercise projects that will familiarize the course participant with the design process for a simple signal design plan, and to provide for a unit-price-based cost estimate. While this course will focus only on the introductory engineering aspects in signal design and introduce some local agencies' equivalent standards and specifications that vary from Caltrans, the goal is for the course participants to become familiar with standards and specifications that guide the design and lead to successful project delivery of an operational traffic signal.

Commercial Development Site Design and Traffic Impact Analysis, Apr 6-7

30 min 13 sec ago
This new online course is about examining the key components that result in effective internal circulation for commercial land development projects. The course will also focus on why earlier designs have failed to provide good circulation and the resulting impacts on the tenants of shopping centers and business parks. It will discuss the problem of designing commercial development projects for safe access and minimizing traffic impacts on the neighboring roads. It will also discuss the preparation of traffic impact studies for new development projects to make sure impacts are properly addressed and cases studies of projects where studies failed to do so.

Airport Capacity Prediction Using Machine Learning and its Applications, Apr 7

30 min 13 sec ago
Abstract: Air traffic managers and flight operators are faced with challenging decisions due to the uncertainty in capacity stemming from variability in weather, demand and human factors. Accurate airport capacity predictions are necessary to develop efficient decision-support tools for air traffic control and for planning effective traffic management initiatives. Capacity of an airport can be observed only at sufficiently large demand. However, if the throughput of an airport is limited by the demand, we can only conclude that the capacity is larger than or equal to the observed throughput. This inability to directly observe capacity makes capacity prediction a challenging and less explored problem.

This work applies machine-learning methods that incorporate observations censored by insufficient demand to develop an airport capacity prediction model. The model predicts a capacity distribution rather than a single capacity value for an hour of interest at an airport using its weather and scheduled demand data. We also discuss validation measures that account for the presence of censored observations. This work explores an important application of the estimated model: to develop capacity-based distance metric between two days using their predicted hourly capacity distributions. For a given reference day, the capacity-based distance can be used to identify similar historical days. The traffic management initiatives taken on past similar days and their resulting outcomes can augment controller experience to guide decision-making on the reference day at an airport.

Bio: Sreeta Gorripaty is a doctoral candidate in the Transportation Engineering program at UC Berkeley. Sreeta received her MS in Transportation Engineering at UC Berkeley and did her undergraduate in Civil Engineering from IIT Bombay. Her research focuses on applying machine learning and statistical methods to improve air traffic management and airport planning. Sreeta received the Graduate Research Award from Airport Cooperative Research Program in 2015 and also won Women's Transportation Seminar (WTS) Legacy Scholarship in 2015.

Funding and Programming Transportation Projects in California, Apr 12-13

30 min 13 sec ago
Funding state and local transportation projects in California is a complex process involving multiple inter-related federal, state, regional, and local planning and operating agencies, as well as an alphabet soup of documents and funding programs. Changing requirements and shifting political priorities can further complicate the process. Without a map and a strategy for developing fundable projects, public agencies and local governments risk losing funding opportunities. This course explains how the process works on the ground and provides planners, project managers, and grant managers with guidelines for thinking strategically as they develop fiscal plans, programs, and project descriptions.

Bus Rapid Transit: Planning, Design, and Operations, Apr 18-27

30 min 13 sec ago
Bus rapid transit (BRT) is an adaptable, cost-effective mode of public transportation suitable for deployment in both larger and smaller cities worldwide. The optimal BRT functions like light rail transit, but on existing streets as a premium express urban bus transit service. BRT can either supplement or replace existing bus networks, as well as either supplement or substitute for light rail transit services. BRT offers the opportunity to expand urban and regional transit networks for less cost and in less time than rail transit alternatives. Additionally, BRT can serve as a medium-term alternative to rail transit until demand for the more expensive but higher capacity mode is proven. There are many versions of BRT deployment, but best practices include: install bus rapid transit on dedicated bus lanes with traffic signal preemption capabilities at intersections, distinctive vehicles, enhanced bus stop amenities, wider stop spacing than convention urban bus transit, platform-level boarding, and unique branding. BRT corridors need to be evaluated carefully with attention to population and employment density and growth forecasts, right of way availability, ridership and cost compared to transit modal alternatives, and ease or difficulty in implementation. Successful BRT lines and networks build transit mode share by offering a time-competitive alternative to the private motor vehicle.

Traffic Signal Operations: Fundamental Concepts, Apr 19

30 min 13 sec ago
This course covers the basic concepts and practical applications and operations of traffic signal timing systems for isolated and coordinated intersections. The course engages students through hands-on exercises and real-world examples of signal timing and operations. Some class exercises and demonstrations are taught in a computer lab. A basic knowledge of EXCEL is needed to complete the exercises. NOTE: This is an introductory course in a series of courses on traffic signal operations offered by the Technology Transfer Program. It is strongly recommended that students complete this course before taking either Traffic Signal Operations: Advanced Applications (TE-10) or SYNCHRO and SimTraffic (TE-13). It is also helpful for students to complete this course before taking Type 170 Traffic Signal Controller (TE-08) or Type 2070 Traffic Signal Controller (TE-09).

VMT Metrics Application and Analysis for SB 743 Compliance, Apr 25

30 min 13 sec ago
OPR has selected vehicle-miles-of-travel (VMT) as the preferred metric to comply with Senate Bill 743 (SB 743). The recommended changes to the CEQA Guidelines include a Technical Advisory that provides recommendations about VMT screening, methodology, and thresholds. These recommendations require fundamental changes in current transportation impact analysis practices and have implications for transportation planning as part of general plans and regional transportation plans. This course will explain the technical details of how to address these changes and include detailed step-by-step flow-chart explanations of how to analyze land use projects, transportation projects, land use plans (e.g., general plans), and regional transportation plans under SB 743.

Type 2070 Traffic Signal Controller, May 1-2

30 min 13 sec ago
Many California cities have started using the Type 2070 Advanced Traffic Controller (2070 ATC), which is also used for advanced transportation system applications. This hands-on course provides working knowledge about the capabilities, uses, and operations of the Type 2070 controller, as well as how to program signal timing plans into the controller. The course covers all key topics ranging from controller hardware, module options, diagnostic tools, field applications of the 2070 ATC, implementation issues, to how to upgrade from Type 170 or NEMA controllers. The course combines lectures with classroom exercises, case-studies, and hands-on controller labs.

2017 California Transportation Planning Conference, May 3-5

30 min 13 sec ago
The California Department of Transportation (Caltrans), in partnership with the Institute of Transportation Studies (ITS) at University of California, Berkeley present the: 2017 California Transportation Planning Conference, Partnering for Sustainable Transportation: Meeting the Challenge Now and Into the Future.

This three-day conference will provide attendees the opportunity to interact with transportation practitioners and decision-makers, exchange ideas and learn about emerging technologies and advancements in transportation planning from national, state, and local experts. The conference will focus on themes around sustainability and how we can partner to meet the challenges facing us now and into the future as required by California legislation and influenced by funding constraints.

Multimodal Transportation Impact Analysis, May 9-10

30 min 13 sec ago
Recent California legislation, as well as public sentiment, has made it imperative that transportation professionals better understand how to analyze and interpret performance measures related to complete streets and sustainable transportation. This new course provides the basics and practical applications for determining level of service for pedestrians, bicyclists, bus transit users, and auto users. It also provides information on the evolving changes in CEQA (SB 743- Steinberg) that requires determining the vehicle miles of travel (VMT) generated by a project, and the determination of what constitutes a significant impact under the new law (including safety impacts).

This course emphasizes the use of the latest 2010 Highway Capacity Manual (HCM 2010), the Institute of Transportation Engineer's (ITE) new Trip Generation Handbook 3rd edition, and other methods.

This course focuses on urban/suburban streets (non-freeways), with equal emphasis on responsibilities normally under Caltrans' control or local agency control. Applications of analyses include improving transportation project design, preparation of defensible environmental impact reports and project mitigation, and prioritizing facilities for improvement. This course combines instructor presentations with eight interactive engagements to apply the techniques in the real-world, with case studies and applications of the material.