Browsing by Author "Phanomchoeng, Gridsada"

Now showing 1 - 5 of 5
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    Directional Sound for Long Distance Auditory Warnings from a Highway Construction Work Zone
    (University of Minnesota Center for Transportation Studies, 2008-12) Phanomchoeng, Gridsada; Rajamani, Rajesh; Hourdos, John
    Directional sound can be used as a warning signal to denote that failure to follow an indicated action could result in serious accidents. In some applications such as to alert a vehicle that is likely to intrude into a highway construction work zone, long distance auditory warnings are necessary. In such cases, directed sound could be utilized to warn the specific vehicle without disturbing other vehicles on the highway. This report reviews the currently available scientific technologies that can potentially be used to develop a long distance auditory warning system for highway work zone applications. Of these, ultrasound based parameter arrays and time delay controlled arrays of compact ordinary speakers are taken up for detailed analysis and experimental evaluation. An ultrasound based parametric array is the most appropriate technology for generating highly directional sound. However, if cost, installation, maintenance, and price are considered, the most suitable technology is found to be arrays of flat panel loudspeakers with time delay control. Such a system can be used to generate directional sound effectively for long distance auditory warnings.
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    Improved Approach to Enforcement of Road Weight Restrictions
    (Minnesota Department of Transportation, 2013-11) Alexander, Lee; Phanomchoeng, Gridsada; Rajamani, Rajesh
    This project focused on the enhancement and evaluation of a battery-less wireless weigh-in-motion (WIM) sensor for improved enforcement of road weight restrictions. The WIM sensor is based on a previously developed vibration energy harvesting system, in which energy is harvested from the vibrations induced by each passing vehicle to power the sensor. The sensor was re-designed in this project so as to reduce its height, allow it to be installed and grouted in an asphalt pavement, and to protect the piezo stacks and other components from heavy shock loads. Two types of software interfaces were developed in the project: a) An interface from which the signals could be read on the MnDOT intranet b) An interface through a wireless handheld display Tests were conducted at MnRoad with a number of test vehicles, including a semi tractor-trailer at a number of speeds from 10 to 50 mph. The sensor had a monotonically increasing response with vehicle weight. There was significant variability in sensor response from one test to another, especially at the higher vehicle speeds. This variability could be attributed to truck suspension vibrations, since accelerometer measurements on the truck showed significant vibrations, especially at higher vehicle speeds. MnDOT decided that the final size of the sensor was too big and could pose a hazard to the traveling public if it got dislodged from the road. Hence the task on evaluation of the sensor at a real-world traffic location was abandoned and the budget for the project correspondingly reduced.
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    Instrumentation of Navistar Truck for Data Collection
    (Minnesota Department of Transportation, 2013-01) Alexander, Lee; Phanomchoeng, Gridsada; Rajamani, Rajesh
    The overarching goal of this project was to instrument the new MnDOT Navistar truck used at MN Road. A rugged data acquisition, data recording and wireless transmission system was established for collection of various sensor signals from the truck. The truck was instrumented with a suite of 20 accelerometers, with these accelerometers being located both on the five axles of the truck and on the tractor and trailer bodies. In addition, the truck was instrumented with a differential GPS system and an inertial measurement unit in the tractor cab. A cRIO-based data acquisition system, a rugged laptop and Labview software together serve as a flexible platform for data acquisition. A wireless communication system has been established to communicate trigger signals to roadside cabinets when the truck is at desired GPS locations on the road. Data recording by in-pavement sensors is triggered by this system. Software has also been set up for automatic downloading of data from the truck to a server on the network at MN Road. The experimental performance of the developed system has been verified by multiple tests conducted by the research team. The above instrumentation of the truck will enable data collection on truck vibrations, enable analysis of correlations between truck vibrations and variations in signals of weigh-inmotion sensors, and enable recording of truck movements and pavement loads at MnROAD.
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    Prediction and Prevention of Tripped Rollovers
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2012-12) Phanomchoeng, Gridsada; Rajamani, Rajesh
    Vehicle rollovers account for a significant fraction of highway traffic fatalities, causing more than 10,000 deaths in the U.S. each year. While active rollover prevention systems have been developed by several automotive manufacturers, the currently available systems address only untripped rollovers. This project focuses on the development of a new real-time rollover index that can detect both tripped and un-tripped rollovers. A new methodology is developed for estimation of unknown inputs in a class of nonlinear dynamic systems. The methodology is based on nonlinear observer design and dynamic model inversion to compute the unknown inputs from output measurements. The developed approach can enable observer design for a large class of differentiable nonlinear systems with a globally (or locally) bounded Jacobian. The developed nonlinear observer is then applied for rollover index estimation. The rollover index estimation algorithm is evaluated through simulations with an industry standard software, CARSIM, and with experimental tests on a 1/8th scaled vehicle. The simulation and experimental results show that the developed nonlinear observer can reliably estimate vehicle states, unknown normal tire forces, and rollover index for predicting both un-tripped and tripped rollovers. The final chapter of this report evaluates the feasibility of rollover prevention for tripped rollovers using currently available actuation systems on passenger sedans.
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    State, parameter, and unknown input estimation problems in active automotive safety applications.
    (2011-09) Phanomchoeng, Gridsada
    A variety of driver assistance systems such as traction control, electronic stability control (ESC), rollover prevention and lane departure avoidance systems are being developed by automotive manufacturers to reduce driver burden, partially automate normal driving operations, and reduce accidents. The effectiveness of these driver assistance systems can be significant enhanced if the real-time values of several vehicle parameters and state variables, namely tire-road friction coefficient, slip angle, roll angle, and rollover index, can be known. Since there are no inexpensive sensors available to measure these variables, it is necessary to estimate them. However, due to the significant nonlinear dynamics in a vehicle, due to unknown and changing plant parameters, and due to the presence of unknown input disturbances, the design of estimation algorithms for this application is challenging. This dissertation develops a new approach to observer design for nonlinear systems in which the nonlinearity has a globally (or locally) bounded Jacobian. The developed approach utilizes a modified version of the mean value theorem to express the nonlinearity in the estimation error dynamics as a convex combination of known matrices with time varying coefficients. The observer gains are then obtained by solving linear matrix inequalities (LMIs). A number of illustrative examples are presented to show that the developed approach is less conservative and more useful than the standard Lipschitz assumption based nonlinear observer. The developed nonlinear observer is utilized for estimation of slip angle, longitudinal vehicle velocity, and vehicle roll angle. In order to predict and prevent vehicle rollovers in tripped situations, it is necessary to estimate the vertical tire forces in the presence of unknown road disturbance inputs. An approach to estimate unknown disturbance inputs in nonlinear systems using dynamic model inversion and a modified version of the mean value theorem is presented. The developed theory is used to estimate vertical tire forces and predict tripped rollovers in situations involving road bumps, potholes, and lateral unknown force inputs. To estimate the tire-road friction coefficients at each individual tire of the vehicle, algorithms to estimate longitudinal forces and slip ratios at each tire are proposed. Subsequently, tire-road friction coefficients are obtained using recursive least squares parameter estimators that exploit the relationship between longitudinal force and slip ratio at each tire. The developed approaches are evaluated through simulations with industry standard software, CARSIM, with experimental tests on a Volvo XC90 sport utility vehicle and with experimental tests on a 1/8th scaled vehicle. The simulation and experimental results show that the developed approaches can reliably estimate the vehicle parameters and state variables needed for effective ESC and rollover prevention applications.