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Smart Cities: Improving the Roadside Environment with Distributed Sensor Systems

The City of Portland is exploring how distributed “Internet of Things” (IoT) sensor systems can be used to improve the available data that is usable by city engineers, planners, and the public to help inform transportation operations, enable assessments of public health and equity, advance Portland’s Climate Action Plan goals, and...

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Data Science Course - Part 2: Intermediate Scientific Computing for Planners, Engineers, and Scientists with Tammy Lee and Joe Broach

For the third year, we're hosting our two-part data science course in Portland, OR. You can register for one part or the other– or attend both at a discount: Data Science Course, Part 1: Introduction to Scientific Computing for Planners, Engineers, and Scientists

Did you ever feel you are “drinking from a hose” with the amount of data you are attempting to analyze? Have you been frustrated with the tedious steps in your data processing and analysis process and thinking, “There’s gotta be a better way to do things”? Are you curious what the buzz of data science is about? If any of your answers are yes, then this course is for you.

Classes will all be hands-on sessions with lecture, discussions and labs. Participants can choose to sign up for one or both courses. For more information, download the syllabus (PDF). This course was developed as part of a NITC education project: Introduction to Scientific Computing for Planners, Engineers, and Scientists.

Agenda: Part Two - Intermediate Course

  1. Transforming, visualizing, and modeling data
  2. ...
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The video begins at 3:12.

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Summary: Real-world traffic trends observed in PORTAL and INRIX traffic data are used to expand the performance measures that can be obtained from Portland Metro's travel demand model to include the number of hours of congestion that can be expected during a typical weekday and travel time reliability measures for congested freeway corridors.

Bio: Michael Mauch, a senior data analyst and project manager with DKS Associates, has over 20 years of experience in transportation data analysis, applications programming, mathematical model building and transportation demand forecasting.  Over the years, Mike has been project manager and has led the technical analyses for numerous large transportation data collection and data analysis projects including BRT and rail transit studies, CIP updates, transportation corridor studies, trip and parking generation studies, corridor capacity analysis, General and Master Plan Updates, incident management cost effectiveness analysis and numerous EIRs. In addition to working with DKS, Mike currently holds a variable-time position as a Research Engineer with UC Berkeley’s Institute of Transportation Studies.  He has taught “Traffic Flow Theory”, “Transit Operations”, and “Computer Programming & Numerical...

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The proliferation of information technology in the transportation field has opened up opportunities for communication and analysis of the performance of transportation facilities. The Highway Capacity Manual relies on rules of thumb and small data samples to generate levels of service to assess performance, but modern detection technology gives us the opportunity to better capture the dynamism of these systems and examine their performance from many perspectives. Travelers, operations staff, and researchers can benefit from measurements that provide information such as travel time, effectiveness of signal coordination, and traffic density. In particular, inductive loop detectors show promise as a tool to collect the data necessary to generate such information. But while their use for this purpose on restricted‐access facilities is well understood, a great many challenges remain in using loop detectors to measure the performance of surface streets.

This thesis proposes 6 methods for estimating arterial travel time. Estimates are compared to simulated data visually, with input/output diagrams; and statistically, with travel times. Methods for estimating travel time are applied to aggregated data and to varying detector densities and evaluated as above. Conclusions are drawn about which method provides the best estimates, what levels of data aggregation can still provide useful information, and what the effects of detector density are on the quality of estimates....

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Webinar: Modeling Freeway Traffic in a Mixed Environment: Connected and Human-Driven Vehicles - Terry Yang

 

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OVERVIEW

Although connected vehicles (CVs) will soon go beyond testbeds, CVs and human-driven vehicles (HVs) will co-exist over a long period. Hence, it is critical to consider the interactions between these two types of vehicles in traffic flow modeling. In this study, we aim to develop a macroscopic model to understand how CVs would impact HVs in the traffic stream. Grounded on the second-order traffic flow model, we study the relationships among flow, density, and speed by two sets of formulations for the groups of CVs and HVs, respectively. A set of friction factors, which indicate CVs' impact to HVs, are introduced to the speed equation for accounting CV speed impacts. Then extended Kalman Filter is employed to update both model parameters and friction factors in real-time. By using CVs trajectory data as measurements, the difference between CV average speed and overall traffic mean speed will be fully accounted. The proposed model will serve as a basis for designing CV-based traffic control function,...

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Summary: Although the running of red lights is perceived by motorists as a commonplace behavior for cyclists, little research has been done on the actual rates of cyclist compliance at signalized intersections. Furthermore, little is known about the factors that influence cyclist non-compliance. This research seeks to illuminate the rates of and reasons for infringement against red lights using video footage and survey data from cyclists in Oregon. 

Bio: Sam became interested in transportation and planning while studying abroad in Freiburg im Breisgau, Germany. After benefiting from the efficient transit service and excellent walkability there, he came back to the states with a gusto for safe, efficient, and environmentally sustainable transportation. After finally figuring out what to do with his Civil Engineering degree, he enrolled in Portland State. Sam's research interests include cyclist behavior and the comprehension and safety implications of new infrastructure. Originally hailing from Kansas, he has grown weary of Wizard of Oz jokes but is otherwise happy to call Portland his home, especially with the abundance of good coffee, micro brews, and stellar pie that PDX has to offer.

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