Browsing by Subject "Cameras"

Now showing 1 - 5 of 5
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    A Comprehensive System for Assessing Truck Parking Availability
    (Center for Transportation Studies, University of Minnesota, 2017-01) Morris, Ted; Murray, Dan; Fender, Kate; Weber, Amanda; Morellas, Vassilios; Cook, Doug; Papanikolopoulos, Nikos
    Commercial heavy vehicle (CHV) drivers are required under federal Hours of Services (HOS) rules to rest and take breaks to reduce driving while fatigued. CHV drivers and operators must balance compliance to the HOS rules against on-time delivery requirements as well as shorter lead times to plan their trips, thereby making location and parking availability of rest area facilities more critical. Without timely, accurate parking availability information, drivers are left with the dilemma of continuing to drive fatigued, drive beyond HOS CHV operation limits, or park illegally on highway shoulders or ramps—all potential safety hazards. In this study, a multi-view camera system was designed and evaluated to detect truck parking space occupancy in real-time through extensive field operational testing. A system architecture was then developed to disseminate up-to-the-minute truck parking information through three separate information delivery systems: 1) Roadside Changeable Message Signs (CMS), 2) Internet/Website information portal, and 3) an onboard geolocation application. The latter application informs the driver of parking availability of one or more parking facilities that are downstream from their current direction of travel. All three notification mechanisms were evaluated during the field test. Survey studies were conducted to provide feedback from commercial heavy vehicle drivers and operators to better understand their perceptions of parking shortages and utility of the parking information delivery mechanisms. Overall, the system has proven to provide 24/7 around-the-clock per-space parking status with no need for manual interventions to correct detection errors, with per parking space accuracy typically equal to or exceeding 95 percent. The concept of operations field tests demonstrated the feasibility of the technical approach and the potential to alter freight borne trip behaviors by allowing drivers and carriers to plan stops and improve trip efficiency.
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    Development of a Multiple-Camera Tracking System for Accurate Traffic Performance Measurements at Intersections
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2013-02) Tang, Hua
    Automatic traffic data collection can significantly save labor work and cost compared to manual data collection. However, automatic traffic data collection has been one of the challenges in Intelligent Transportation Systems (ITS). To be practically useful, an automatic traffic data collection system must derive traffic data with reasonable accuracy compared to a manual approach. This project presents the development of a multiple-camera tracking system for accurate traffic performance measurements at intersections. The tracking system sets up multiple cameras to record videos for an intersection. Compared to the traditional single-camera based tracking system, the multiple-camera one can take advantage of significantly overlapped views of the same traffic scene provided by the multiple cameras such that the notorious vehicle occlusion problem is alleviated. Also, multiple cameras provide more evidence of the same vehicle, which allows more robust tracking of the vehicle. The developed system has mainly three processing modules. First, the camera is calibrated for the traffic scene of interest and a calibration algorithm is developed for multiple cameras at an intersection. Second, the system tracks vehicles from the multiple videos by using powerful imaging processing techniques and tracking algorithms. Finally, the resulting vehicle trajectories from vehicle tracking are analyzed to extract the interested traffic data, such as vehicle volume, travel time, rejected gaps and accepted gaps. Practical tests of the developed system focus on vehicle counts and reasonable accuracy is achieved.
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    Development of a New Tracking System Based on CMOS Vision Processor Hardware, Phase II Prototype Demonstration
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2012-05) Tang, Hua; Peng, Li
    Intelligent transportation systems depend on being able to track vehicle operations and collect accurate traffic data. This project targets a hardware-based video detection system for real-time vehicle detection. To allow real-time detection, customized hardware implementation of the system is targeted instead on the traditional computer-based implementation of the system. The system includes four main processing steps. First, a camera is used to capture images. Second, the captured images are segmented using the Mixture-of-Gaussian algorithm. Without sacrificing the segmentation accuracy, researchers modified the Mixture-of-Gaussian algorithm to allow more efficient and economical hardware implementation in terms of design overhead and hardware resources. Third, the segmentation regions are extracted and validated as the objects of interests. In the last step, the validation result will be wirelessly transmitted to a variable message sign, which displays necessary traffic information. Since the system design includes integration of diverse devices, the video design kit from Xilinx is used. Such a hardware-based vehicle detection system has been experimented tested with practical videos of traffic scene.
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    Implementation of a V2I Highway Safety System and Connected Vehicle Testbed
    (Center for Transportation Studies, University of Minnesota, 2019-04) Hourdos, John; Parikh, Gordon; Dirks, Peter; Lehrke, Derek
    To better prepare for the Connected Vehicle (CV) roadway, RSI has established a CV testbed along a highly crashed section of I-94, building on the Minnesota Traffic Observatory’s existing field lab infrastructure. This real- world testbed was designed to implement and evaluate the next generation of vehicle-based freeway safety applications. The priority of this project was to establish the backbone of the sensor communication network and data collection system along the testbed length.
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    A Tracking-Based Traffic Performance Measurement System for Roundabouts and Intersections
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2012-05) Tang, Hua; Dinh, Hai
    Automatic traffic data collection can significantly save labor work and cost compared to manual data collection. The collected traffic data is necessary for traffic simulation and modeling, performance evaluation of the traffic scene, and eventually (re)design of the traffic scene. However, automatic traffic data collection has been one of the challenges in Intelligent Transportation Systems (ITS). This project presents the development of a single camerabased video system for automatic traffic data collection for roundabouts and intersections. The system targets roundabouts and intersections because no mature data collection systems exist for these traffic scenes yet in contrast to highway scenes. The developed system has mainly processing modules. First, the camera is calibrated for the traffic scene of interest and a novel circle-based calibration algorithm is proposed for roundabouts. Second, the system tracks vehicles from the video by incorporating powerful imaging processing techniques and tracking algorithms. Finally, the resulting vehicle trajectories from vehicle tracking are analyzed to extract the interested traffic data, which includes vehicle volume, vehicle speed (including acceleration/de-acceleration behavior), travel time, rejected gaps, accepted gaps, follow-up time and lane use. Practical tests of the developed system show that it can reliably track vehicles and provide reasonably accurate traffic data in most cases.