University Honors

This project presents an open-source simulation benchmark for developing and evaluating sustainable Intelligent Transportation Systems (ITS). Built on top of the OpenCDA and CARLA simulation platforms, the framework extends traditional evaluation metrics such as safety and traffic efficiency by incorporating sustainability, equity, and social inclusion as core performance dimensions. The goal is to provide a flexible and reproducible environment for testing control strategies under realistic multi-vehicle scenarios. To demonstrate the benchmarkís capabilities, we evaluate two vehicle control approaches, a baseline Proportional-Integral-Derivative (PID) controller and a custom energy-aware (ECO) controller, within a cooperative platoon merging scenario. Performance is measured using speed profiles, acceleration smoothness, and a proposed efficiency metric that captures the trade-off between mobility and energy consumption. Results show that the ECO controller improves trajectory smoothness and reduces aggressive acceleration compared to the PID baseline, leading to higher efficiency without significantly degrading travel speed. Furthermore, the benchmark enables systematic analysis of how control strategies respond to varying traffic conditions, highlighting its utility for evaluating robustness and scalability. This work demonstrates how existing autonomous driving simulators can be extended into a broader ITS benchmarking framework, supporting the development of control algorithms that balance efficiency with sustainability and societal considerations.