Institute of Transportation Studies Upcoming Events Type 2070 Traffic Signal Controller, May 1-2 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 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. <br /> <br /> 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. Increasing Freeway Capacity by Efficiently Timing its Nearby Arterial Traffic Signals, May 5 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.<br /> 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. Multimodal Transportation Impact Analysis, May 9-10 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). <br /> <br /> 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. <br /> <br /> 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. Traffic Signal Operations: Advanced Applications, May 10-11 This two-day course focusing on advanced signal operations topics, will enable you to develop and evaluate performance of two types of traffic signal coordination -- time of day and traffic responsive systems. This course also introduces the advanced traffic adaptive system. For time of day and traffic responsive systems, attendees learn how to determine good timing and coordinated solutions with innovative approaches for managing vehicle queues, turns, and potential gridlock situations, how to find optimal timing solutions, and how to safely accommodate non-motorists. Students will work on signal timing plans using several signals along arterials including freeway interchange signals; assess whether more complex timing solutions offer operational improvements; solve specialized problems such as offset intersections and diamond interchanges; and learn to perform analysis and evaluation of traffic volumes and field checks. The operational concept for traffic adaptive systems will be introduced and results compared with results from the time of day and traffic responsive plans. A basic knowledge of SYNCHRO is helpful. The Holy Trinity: Blending Statistics, Machine Learning, and Discrete Choice with Applications to Strategic Bicycle Planning, May 12 Abstract:<br /> Across all levels of government in the United States (U.S.), transportation and planning agencies have prioritized encouraging bicycle use. However, despite such admirable goals, actually increasing bicycle usage has been a struggle. For instance, the City of San Francisco set a goal in 2010 to increase its 3.5% bicycle mode share to 20% by 2020 (SFMTA, 2012). Unfortunately, given the 2014 bicycle mode share of 4.0% (U.S. Census Bureau, 2015), San Francisco appears unlikely to meet its mode share goals. Similarly, in 1999, Oakland set a goal of increasing it’s 1990 bicycle commute mode share of 1.1% to 4% in 2010 (City of Oakland, 2007). In 2014, Oakland’s bicycle commute share was only 3.1% (U.S. Census Bureau, 2015). While sad, this pattern is common. Many agencies are interested yet unsuccessful in raising their bicycle commute mode shares.<br /> <br /> To successfully make planning and investment decisions regarding bicycle infrastructure projects, agencies must accurately judge how much each possible project is expected to increase bicycle ridership. To support this activity, my research aims to improve bicycle demand models. In this talk, I will focus on three flaws of current mode choice models: (1) the exclusion of roadway-level variables (e.g. on-street bicycle infrastructure measures, traffic speeds, etc.), (2) the assumption of “perfectly rational” decision makers, and (3) the issue of class imbalance (i.e. the relatively small numbers of cyclists in household travel surveys). In addressing these issues, I merge traditional discrete choice with recent advances in statistics and machine learning, making use of methods such as parametric link functions, Bayesian decision trees, and Gaussian Process models. In all cases, these methods are modified and theoretically extended for use in a transportation context. Together, the developed techniques increase the policy relevance and accuracy of bicycle demand models in particular, and they advance the field of choice modeling in general.<br /> <br /> Bio:<br /> Timothy Brathwaite is a Ph.D. candidate in transportation engineering in the Civil and Environmental Engineering department from the University of California (UC) at Berkeley, working under the supervision of Professor Joan Walker. Motivated by efforts to predict the demand for bicycling under various policy scenarios, Timothy’s research makes methodological improvements to discrete choice models to account for omitted roadway variables, traveler “irrationality,” and the typically low number of cyclists in household travel surveys. He was the UCCONNECT Outstanding Graduate Student of 2017 and a UC Berkeley 2016 Outstanding Graduate Student Instructor. Previously, he received his Master of City Planning and Master of Science in Civil Engineering from UC Berkeley and his Bachelor of Science in Urban Studies and Planning from the University of New Orleans. Professionally, Timothy has worked on the data science team at Lyft, with transportation consulting firms (Fehr and Peers and Cambridge Systematics), with the bicycle facilities program at the City of Oakland, and with the non-profit "Bike Easy" in New Orleans. Traffic Signal Design: Complete Streets Application, May 16-17 This new course introduces the practical design considerations in traffic signal designs that are above and beyond the basic introductions. Within the framework of the California Vehicle Code, the California Manual on Uniform Traffic Control Devices (CA MUTCD), and other national and state references with recommended practices and real-world illustrations, this course will explore the multi-modal design expectations from today's traffic signal designers in a complete-street environment. <br /> <br /> This course will introduce complex signal phasing diagrams, typical features of controller firmware, and configuration of signal cabinets; and signal indications/heads placement and detection layout with respect to design applications for rail crossings, emergency vehicles, bus transit, bicycles, pedestrians, and cars. Additionally, this course will introduce the design concept for bus rapid transit (BRT), light rail transit (LRT) and heavy rail. <br /> <br /> The course includes lectures, sample problems, and exercise projects that will familiarize the course participant with the design process that starts with preliminary and progress design submittals, as well as formats of design review comments and resolutions expected by typical public agencies. While this course is suitable for traffic signal designers with varying experience, this course will be introduced as a sequential next-level course to Tech Transfer's TE-02 (Traffic Signal Design: Engineering Concepts), or equivalent. The goal is for the course participants to become familiar with real-world, multi-modal, signal-design applications that accommodate various street types and intersections users. HST California, May 22 This one-day symposium explores the current status and challenges ahead for High Speed Rail in California. Leaders from the California High Speed Rail Authority, academic institutions, and industry provide updates and ample opportunity for discussion and networking.<br /> <br /> The Symposium is free to student and faculty, if interested please email Multimodal Transportation Operations: Evaluation Methods and Performance Measures, May 23-Jun 8 This new online training course provides the fundamentals required to understand, perform, and interpret the results from multimodal operational analysis and performance evaluations. Several of the most commonly used evaluation and analysis methods are presented with real-world examples. The course focuses on how to develop an appropriate set of performance measures to reliably compute the gains in performance to the transportation system (and/or subsystems) attributable to a project, policy, or program of interest. It also covers the data sources and data reliability, analytic (evaluation) methods and their strengths and limitations, and the overall reliability of the analytical results.