Browsing by Author "Morellas, Vassilios"

Now showing 1 - 15 of 15
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    Analysis of a Differential Global Positioning System as a Sensor for Vehicle Guidance
    (Minnesota Department of Transportation, 1996-09) Bodor, Robert; Alexander, Lee; Liao, Chen-fu; Bajikar, Sundeep; Morellas, Vassilios; Donath, Max
    An ongoing research project examines guidance systems, which can take over control of a vehicle if the driver becomes incapacitated. Part of this project includes an evaluation of a Differential Global Positioning System (DGPS) for vehicle-based lane sensing. This report documents the results of tests of the 5 Hz NovAtel RT20 DGPS receiver. A series of 32 static tests found the overall mean and standard deviation for the offset errors within specifications. In a series of dynamic tests, in which the vehicle was driven around the track at speeds of 20-35 miles per hour, after removing the effect of the GPS receiver's latency, the DGPS determined position exhibited a mean offset error of -17.3 cm (-6.82 in) and a mean standard deviation of 25.5 cm (10.1 in) in the direction of vehicle motion. In the direction perpendicular to vehicle motion, the mean offset was 4.57 cm (1.8 in) with a mean standard deviation of 39.6 cm (15.6 in). With no overhead obstructions in these tests, continuous satellite lock was possible. Tests at higher speeds based on a more accurate methodology are planned for the future.
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    and Vassilios Morellas, Pixel layering and layer propagation for video modelling and foreground detection
    (2005-11) Patwardhan, Kedar A.; Sapiro, Guillermo; Morellas, Vassilios
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    Automatic Passenger Counting in the HOV Lane
    (1999-06-01) Pavlidis, Ioannis; Symosek, Peter; Morellas, Vassilios; Fritz, Bernard; Papanikolopoulos, Nikolaos P; Sfarzo, Robert
    This research applied wave band and computer vision methods to automatically count vehicle occupants in the High Occupancy Vehicle (HOV) lane at a high level of accuracy. The research showed that use of near-infrared bandwidth offers potential as a method for developing an automatic vehicle occupant counting system. Near-infrared only can produce images when looking through glass, but not metal or heavy clothes, which limits its accuracy in counting children or occupants resting in vehicles. The mid-infrared camera did not produce clear images at highway speeds. The next step involves additional research into a working device that can count vehicle occupants reliably, including analysis of device performance with more types of vehicles, passengers in the back seats, children in car seats, and passengers lying down.
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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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    Deployment of Practical Methods for Counting Bicycle and Pedestrian Use of a Transportation Facility
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, 2012-01) Somasundaram, Guruprasad; Morellas, Vassilios; Papanikolopoulos, Nikolaos
    The classification problem of distinguishing bicycles from pedestrians for traffic counting applications is the objective of this research project. The scenes that are typically involved are bicycle trails, bridges, and bicycle lanes. These locations have heavy traffic of mainly pedestrians and bicyclists. A vision-based system overcomes many of the shortcomings of existing technologies such as loop counters, buried pressure pads, infra-red counters, etc. These methods do not have distinctive profiles for bicycles and pedestrians. Also most of these technologies require expert installation and maintenance. Cameras are inexpensive and abundant and are relatively easy to use, but they tend to be useful as a counting system only when accompanied by powerful algorithms that analyze the images. We employ state-of-the-art algorithms for performing object classification to solve the problem of distinguishing bicyclists from pedestrians. We detail the challenges that are involved in this particular problem, and we propose solutions to address these challenges. We explore common approaches of global image analysis aided by motion information and compare the results with local image analysis in which we attempt to distinguish the individual parts of the composite object. We compare the classification accuracies of both approaches on real data and present detailed discussion on practical deployment factors.
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    Efficient Similarity Search via Sparse Coding
    (2011-11-21) Cherian, Anoop; Morellas, Vassilios
    This work presents a new indexing method using sparse coding for fast approximate Nearest Neighbors (NN) on high dimensional image data. To begin with we sparse code the data using a learned basis dictionary and an index of the dictionary's support set is next used to generate one compact identifier for each data point. As basis combinations increase exponentially with an increasing support set, each data point is likely to get a unique identifier that can be used to index a hash table for fast NN operations. When dealing with real world data, the identifiers corresponding to the query point and the true nearest neighbors in the database seldom match exactly (due to image noise, distortion, etc.). To accommodate these near matches, we propose a novel extension of the framework that utilizes the regularization path of the LASSO formulation to create robust hash codes. Experiments are conducted on large datasets and demonstrate that our algorithm rivals state-of-the-art NN techniques in search time, accuracy and memory usage.
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    A graph-based foreground representation and its application in example based people matching in video
    (2007-01) Patwardhan, Kedar A.; Sapiro, Guillermo; Morellas, Vassilios
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    A Lateral Dynamic Model of a Tractor-Trailer: Experimental Validation
    (1996-11) Alexander, Lee; Donath, Max; Hennessey, Michael; Morellas, Vassilios; Shankwitz, Craig
    The SAFETRUCK program focuses on preventing accidents on rural highways, especially those associated with run-off-the-road incidents and driver fatigue, by giving the vehicle the ability to steer to the side of the road and come to a safe stop if the driver falls asleep or is otherwise incapacitated. Researchers have equipped a Navistar 9400 series class 8 truck tractor with the sensors and control computers necessary to perform this task. Designing the controller that will steer the truck requires a mathematical model of the lateral response of the truck to steering inputs. In this project, researchers developed a lateral dynamic model by incorporating second order dynamics into the steering axle tires. Simulation of the resulting models indicated dynamic behavior that was close to the experimental data for speeds between 15 and 30 miles per hour. This is the first time that a lateral dynamic model of a truck has been experimentally verified. Both models, however, resulted in experimentally determined values for steering axle cornering stiffness that were considerably smaller than published values for the Goodyear G 159 tires on the truck.
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    Magnetic Lateral Indication System Evaluation
    (Minnesota Department of Transportation, 1997-01) Bajikar, Sundeep; Morellas, Vassilios; Donath, Max
    This report summarizes conclusions and recommendations regarding the Magnetic Lateral Indication System. It analyzes results and conclusions that were derived by 3M and Honeywell, which conducted a feasibility study of a lateral position indication system for vehicles.
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    Monitoring the Use of HOV and HOT Lanes
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2013-01) Holec, Eric; Somasundaram, Guruprasad; Papanikolopoulos, Nikolaos; Morellas, Vassilios
    This report presents the formulation and implementation of an automated computer vision and machine learning based system for estimation of the occupancy of passenger vehicles in high-occupancy vehicles and highoccupancy toll (HOV/HOT) lanes. We employ a multi-modal approach involving near-infrared images and highresolution color video images in conjunction with strong maximum margin based classifiers such as support vector machines. We attempt to maximize the information that can be extracted from these two types of images by computing different features. Then, we build classifiers for each type of feature which are compared to determine the best feature for each imaging method. Based on the performance of the classifiers we critique the efficacy of the individual approaches as the costs involved are significantly different.
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    Practical Methods for Analyzing Pedestrian and Bicycle Use of a Transportation Facility
    (Minnesota Department of Transportation Office of Research Services, 2010-02) Somasundaram, Guruprasad; Morellas, Vassilios; Papanikolopoulos, Nikolaos P.
    The objective of the project is to analyze existing technologies used for the process of generating counts of bicycles and pedestrians in transportation facilities such as walk and bicycle bridges, urban bicycle routes, bicycle trails etc. The advantages and disadvantages of each existing technology which is being applied to counting has been analyzed and some commercially available products were listed. A technical description of different methods that were considered for vision based object recognition is also mentioned along with the reasons as to why such methods were overlooked for our problem. Support Vector Machines were used for classification based on a vocabulary of features built using interest point detectors. After finalizing the software and hardware, five sites were picked for filming and about 10 hours of video was acquired in all. A portion of the video data was used for training and the remainder was used for testing the algorithm’s accuracy. Results of counts are provided and an interpretation of these results is provided in this report. Upon detailed analysis the reasons for false counts and undercounting in some cases have been identified and current work concerns dealing with these issues. Changes are being made to the system to improve the accuracy with the current level of training and make the system available for practitioners to perform counting.
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    A Real-Time Truck Availability System for the State of Wisconsin
    (Center for Transportation Studies, University of Minnesota, 2018-05) Morris, Ted; Henderson, Travis; Morellas, Vassilios; Papanikolopoulos, Nikos
    Independent of truck parking capacity shortages, obtaining reliable and timely information has been receiving considerable attention nationally as of late. The situation has been exacerbated by increasing levels of freightborne truck volumes along many regional and interstate corridors and the need for carriers and drivers to balance efficient transport with required periods to park and rest to minimize driver fatigue. Interstate 94, a nationally designated freight corridor, as it passes through the Upper Midwest, including Wisconsin, shares this problem. A multi-camera computer vision detection system was deployed at a state sponsored rest area truck parking facility 67 miles east of Minneapolis. A key aspect of the system is that it is a completely automated 24/7, non-intrusive, parking detection system; there is no need to intervene with manual resets or re-calibration procedures, and pavements are not disturbed. Secondly, a region-wide truck parking notification architecture, recognized as an emerging national standard, was integrated with the detection system to provide real-time roadside truck parking notifications upstream of the facilities, as well as notification to other third party stakeholders. The overall detection accuracy was between 90 and 95 percent during up-to-the minute, per-space parking status notifications.
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    Safetruck: Sensing and Control to Enhance Vehicle Safety
    (Minnesota Department of Transportation, 1997-12) Alexander, Lee; Bajikar, Sundeep; Lim, Heon-Min; Morellas, Vassilios; Morris, Ted; Donath, Max
    This report summarizes the work performed during the 18-month period ending in December 1997. Researchers investigated the use of differential global positioning systems (GPS), inertial measurement, and other sensing technologies as the basis of a system that would prevent crashes. Such a system attempts to control the vehicle if it leaves the lane because the driver is incapacitated. The report includes in its appendices related work on driver fatigue and a bibliography on the effect of drugs and alcohol on driving behavior. The long-term goal of this research involves development of a "driver-centered" vehicle control system capable of providing lane-keeping feedback to the driver, and, ifnecessary, of imposing aggressive intervention strategies to take over control of the vehicle, steer it to a safe position on the shoulder, and stop it. This research also targets the development of "driver assistive" technologies--such as Heads Up Display and torque feedback supplied by the steering wheel--which provide information to the driver without necessarily requiring computer control of the vehicle. The highlight achievement during this funding period has been the successful demonstration of a GPS-based automated lane-keeping mode of a tractor-trailer on the Minnesota Road Research Project (Mn/ROAD) test track. The report concludes with a strategy for pursuing future deployment.
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    Sensing for HOV/HOT Lanes Enforcement
    (Minnesota Department of Transportation, 2017-02) Morris, Ted; Morellas, Vassilios; Canelon-Suarez, Dario; Papanikolopoulos, Nikolaos
    The use and creation of combined high-occupancy vehicle/high-occupancy toll (HOV/HOT Lanes) have become more common in urban areas since all types of road users can take advantage of the lane either as a high- occupancy vehicle or opting in to pay a congestion adjusted free. However, to maintain working integrity of the lanes for all users, stepped enforcement to discourage cheating has been needed as more lanes are added. This study evaluated the capability of a novel image sensor device to automate detection of in-vehicle occupants to flag law enforcement of HOV/HOT lane violators. The sensor device synchronously captures three co-registered images, one in the visible spectrum and two others in the infrared bands. The key idea is that the infrared bands can enhance correct occupancy detection through known phenomenological spectral properties of objects and humans residing inside the vehicle. Several experiments were conducted to determine this capability across varied conditions and scenarios to assess detection segmentation algorithms of vehicle passengers and drivers. Although occupancy detection through vehicle glass could be achieved in many cases, improvements must be made to such a detection system to increase robustness and reliability as a law enforcement tool. These improvements were guided by the experimental results, as well as suggested methods for deployment if this or similar technologies were to be deployed in the future.
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    Video Detection and Classification of Pedestrian Events at Roundabouts and Crosswalks
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, 2013-08) Morris, Ted; Li, Xinyan; Morellas, Vassilios; Papanikolopoulos, Nikos
    A well-established technique for studying pedestrian safety is based on reducing data from video-based in-situ observation. The extraction and cataloging from recorded video of pedestrian crossing events has largely been achieved manually. Although the manual methods are generally reliable, they are extremely time-consuming. As a result, more detailed, encompassing site studies are not practical unless the mining for these events can be automated. The study investigated such a tool based on utilizing a novel image processing algorithm recently developed for the extraction of human activities in complex scenes. No human intervention other than defining regions of interest for approaching vehicles and the pedestrian crossing areas was required. The output quantified general event indicators—such as pedestrian wait time, and crossing time and vehicle-pedestrian yield behaviors. Such data can then be used to guide more detailed analyses of the events to study potential vehicle-pedestrian conflicts and their causal effects. The evaluation was done using an extensive set of multi-camera video recordings collected at roundabouts. The tool can be used to support other pedestrian safety research where extracting potential pedestrian-vehicle conflicts from video are required, for example at crosswalks at urban signalized and uncontrolled intersections.