Abstract:

Autonomously controlled vehicles utilize various sensors to survey their environment in order to operate independently of human interaction. Such vehicles can work in conjunction with one another to form a convoy with only one human controlled lead car. This technology could be integrated into various subdivisions, including military, commercial, and industrial sectors. In order to develop such technology, a mathematical model which defines the general motion of a vehicle must be constructed. Also, a set of control laws that guide the autonomous vehicle is needed. MATLAB was used to write a simulation program based on the model and control laws to test the autonomous vehicle’s artificial intelligence before implementation onto a physical car. Standard radio controlled (RC) cars are used as the vehicles. The follower vehicles are equipped with Arduino microcontrollers, motor shields, CMUcam2 color tracking cameras, Parallax Ping))) ultrasonic sensors, and servos to carry out all necessary measurements and calculations. Using these components, the distance and offset angle to the vehicle ahead is found and converted to steering angle and motor speed outputs. The process of analyzing, processing, and executing repeats continuously, resulting in efficient function of the autonomous vehicle control systems.

Abstract:

The purpose of this study was to verify a newly developed Winter Storm Scale (WSS) for Nor'easters and other winter storms affecting the Northeastern United States. Like the Fujita Scale and Saffir-Simpson scale for tornadoes and hurricanes, respectively, the WSS will measure the intensity of Nor'easters and other winter storms using a convenient zero to five. Very similar to the Fujita Scale, the WSS values are calculated in a post-storm analysis using maximum sustained wind, wind gust, total storm snowfall, total storm ice accretion, and minimum visibility. The WSS is applied to all storms observed at Newark Liberty International Airport (EWR) from October 1995 to April 2010 which contained at least one surface report of "wintery precipitation" (i.e. snow, freezing rain, sleet, etc.). The calculated WSS values are compared to the Rooney Disruption Scale, an existing storm measurement scale, to investigate the relationship between WSS value and societal impact. Two hypotheses were tested: 1) The distribution of winter storms are such that zeros are more common than fives, and 2) The WSS values, or meteorological ranking, are an acceptable measure of societal disruption (verified by analyzing a scatter plot of WSS values versus Rooney Disruption Scale values).

Abstract:

An autonomous vehicle is any vehicle that can drive itself from one locatin to another without the use of human intervention. When put in a convoy, several autonomous vehicles can follow one lead vehicle and mimic its movements. This can have many uses in the private, commercial, and government sectors. By using a CMUcam2, an Arduino Microprocessor, a Motorshield, and three Remote Controlled (RC) cars, it is possible to successfully create a prototype autonomous convoy based on light detection technology. One of the three RC cars remained unchanged. This car woud act as the Lead Vehicle - the vehicle that the autonomous vehicles would follow. The other two would be interfaced with a CMUcam2, an Arduino Microprocessor, and a Motorshield. These cars would become the two autonomous follower vehicles. The autonomous vehicles worked in several steps. First, the Arduino Microprocessor would send a command to the CMUcam2 telling it to track a certain color. Next, it would send another command asking for information about the color it is tracking. This inormation would be sent back to the Arduino, where it would be processed and used to determine the turning angle and velocity. After the calculations, the Arduino would send commands to the servo motor controlling the angle of the front wheels and the Motorshield controlling the rear wheels. The Motorshield would read the commands, and vary the voltage going to the DC motor controlling the rear wheels, and thus control the speed of the vehicle. When completely interfaced together, this method provides a reliable method to create a convoy of autonomous vehicles.