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A particle filter based algorithm was developed to track vehicles in a network of roads under the assumption of sporadic and non-persistent sensor data. It is assumed we have a number of sensors that provide position and velocity information only, which are scattered at possibly uneven intervals throughout the road system of interest. Further, the sensor ranges do not overlap, meaning we do not have...
Estimation of road profile parameters and detection of road pavement failures using in-vehicle sensors such as vertical accelerometers or position sensors is of immense value in a futuristic distributed highway monitoring system. In this paper, a novel road elevation profile model, well suited for analysis using statistical signal processing tools, is developed to characterize road features. We then...
Inclement weather conditions like snowfall adversely affect traffic flow characteristics, necessitating a change in parameters that define the operation of a signalized intersection. A weather-based timing plan selection is needed to maintain a desirable level of operational efficiency. Automatic implementation of weather-based timing at intersections requires accurate and timely detection of snowfall...
This paper presents a method for vehicle localization in urban environment. It combines use of GPS and dead reckoning, fused by extended Kalman filter, and digital map, provided by a geographic information system. This map matching method is founded on set membership estimation theory, and more particularly on ellipsoidal algorithms. Experimental tests, with measurements collected during a travel...
Vehicle presence detectors have become critical elements of traffic management systems, including applications ranging from intersection signal control to freeway congestion monitoring. The need to assess the accuracy and attributes of each of the many types of sensors motivated the California Department of Transportation to construct the Traffic Detector Testbed on I-405 in Southern California. With...
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