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Events for May 07, 2014
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PhD Defense- Bei (Penny) Pan
Wed, May 07, 2014 @ 10:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Candidate: Bei (Penny) Pan
Title:
Utilizing Real-World Traffic Data to Forecast the Impact by Traffic Incidents
Committee:
Cyrus Shahabi (chair)
Craig Knoblock
Genevieve Giuliano (outside member)
Abstract:
For the first time, real-time high-fidelity spatiotemporal data on transportation networks of major cities have become available. This gold mine of data can be utilized to learn about the behavior of traffic congestion at different times and locations, potentially resulting in major savings in time and fuel, the two important commodities of the 21st century. Therefore, how to mine valuable information from this data to enable next-generation technologies for unprecedented convenience, have become key topics in spatiotemporal data mining. By utilizing real-world transportation related datasets, this thesis focuses on the address the problems related with impact of traffic incidents. Traffic incidents refer to non-recurring issues occurred on the road network, such as traffic accidents, weather hazard, special events and construction zone closures, which contributes to approximately 50% for traffic congestion.
First, this thesis addresses the fundamental problem of traffic prediction in the presence of traffic incidents by utilizing traffic sensor data & incident reports collected in Los Angeles road networks. The proposed prediction overcomes the deficiency of traditional time-series prediction techniques by considering the unique characteristics for traffic speed time series. Then through the same dataset, this thesis proposes a set of methods to predict the dynamic evolvement for the impact of incidents. Through the surrounding traffic data of traffic incidents, this thesis models the propagation behavior of congestions caused by archived incidents, and develops a set of clustering-based techniques for predicting the similar behavior in the future. Thirdly, besides sensor data, this thesis also mines social media and GPS trajectories for better understanding of the cause of traffic incidents. Specifically, by identifying the unusual travelling behaviors and twitter-like posts from data collected in Beijing, this work detects and analyzes the impact of traffic incidents. Finally, this thesis analyzes the causality relationship among freeway traffic and arterial traffic to provide a comprehensive prediction of incidents’ impact on both freeways and arterial streets. As a result, the next-generation navigation applications built based on the approaches discussed in this thesis can help drivers to effectively avoid the impacted area in real-time and thereby save them considerable amount of travel time.
Location: Ronald Tutor Hall of Engineering (RTH) - 306
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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PhD Defense - Megha Gupta
Wed, May 07, 2014 @ 10:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
University Calendar
Ph.D. Candidate: Megha Gupta
Committee members:
Gaurav Sukhatme (chair)
Stefan Schaal
Bhaskar Krishnamachari (outside member)
Time: May 7, 2014, 10 am
Location: Ronald Tutor Hall (RTH), room 422
Title: Intelligent Robotic Manipulation of Cluttered Environments
Abstract:
Robotic household assistants of the future will need to understand their environment in real-time with high accuracy. There are two problems that make this challenging for robots. First, human environments are typically cluttered, containing a lot of objects of all kinds, shapes and sizes, in close proximity. This introduces errors in the robot's perception and manipulation. Second, human environments are highly varied. Improving a robot's perceptual abilities can tackle these challenge only partially. A robot's ability to manipulate its environment can help in enabling and overcoming the limits of perception.
We test this idea in the context of sorting and searching in cluttered, bounded, and partially observable environments. The inherent uncertainty in the world state forces the robot to adopt an observe-plan-act strategy where perception, planning, and execution are interleaved. Since execution of an action may result in revealing information about the world that was unknown hitherto, a new plan needs to be generated as a consequence of the robots actions . Since manipulation is typically expensive on a robot, our goal is to reduce the number of object manipulations required to complete the desired task.
We present a robust pipeline that combines manipulation-aided perception and grasping in the context of sorting objects on a tabletop. We present an adaptive look-ahead algorithm for exploration by prehensile and non-prehensile manipulation of the objects it contains. Finally, we add contextual structure to the world in the form of object-object co-occurrence relations and present an algorithm that uses context to guide the object search. We evaluate our planners through simulations and real-world experiments on the PR2 robot and show that purposeful manipulation of clutter to aid perception becomes increasingly useful (and essential) as the clutter in the environment increases.
Location: Ronald Tutor Hall of Engineering (RTH) - 422
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
