Autonomous Vehicles

Compositional Systems Lab

Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments

Research team including Dan Work, Miles Churchill, Nate Hamilton, Shumo Cui, R'mani Haulcy, Rahul Bhadani, Rafael Stern, Benjamin Seibold, Matt Bunting, Maria Laura Delle Monache, and Jonathan Sprinkle

The objective of this work is to generate new fundamental science that enables the operation of cyber-physical systems through complex environments. Predicting how a system will behave in the future requires more computing power if that system is complex. Navigating through environments with many obstacles could require significant computing time, which may delay the issue of decisions that have to be made by the on-board algorithms. Fortunately, systems do not always need the most accurate model to predict their behavior.

A Safe Autonomous Vehicle Trajectory Domain Specific Modeling Language For Non-Expert Development

M. Bunting, Zeleke, Y., McKeever, K., and Sprinkle, J., "A Safe Autonomous Vehicle Trajectory Domain Specific Modeling Language For Non-Expert Development", in Proceedings of the International Workshop on Domain-Specific Modeling (DSM 2016), Amsterdam, Netherlands, 2016, p. 42--48 [Online]. Available: http://doi.acm.org/10.1145/3023147.3023154

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