Controls and Control Theory Commons^™

Path Planning With Deep Neural Networks, Paul Simmerling, Brendan Sayers, Paulo Alcantara Silva

Honors Scholar Theses

This report will cover the work and plans of the ECE 2107 Senior design team. The goal of the project is to design and build a fully autonomous self-driving car. This car will have a complete sensor suite including LIDAR, an IMU, a camera, and encoders. It will be based on a multi-level system where the highest level uses a neural network for advanced signal processing and analysis. The current state of the project is discussed as well as the final results. Project management and other constraints will be briefly investigated. This team is building a self driving car testbed …

Evaluating Driving Performance Of A Novel Behavior Planning Model On Connected Autonomous Vehicles, Keyur Shah

Honors Scholar Theses

Many current algorithms and approaches in autonomous driving attempt to solve the "trajectory generation" or "trajectory following” problems: given a target behavior (e.g. stay in the current lane at the speed limit or change lane), what trajectory should the vehicle follow, and what inputs should the driving agent apply to the throttle and brake to achieve this trajectory? In this work, we instead focus on the “behavior planning” problem—specifically, should an autonomous vehicle change lane or keep lane given the current state of the system?

In addition, current theory mainly focuses on single-vehicle systems, where vehicles do not communicate with …