Sean Mcneil Email and Phone Number

At Uber's self-driving vehicle program, I worked as part of a team working in an Agile environment to develop and evolve safety critical, ISO 26262 compliant ECU for self-driving vehicle control.In this role, I configured RTOS and AUTOSAR base software for the PowerPC based ECU. This involved writing C code for peripheral device drivers, implementing state machines for various ECU functions, working with AUTOSAR project configuration tools (Vector DaVinci), and ensuring coverage of high and low-level software requirements. As functionality evolved and exposed issues were patched, I managed the releases of new software for the module, ensuring proper test coverage and review procedures were met and inter-team dependencies were considered and managed.To improve the release process and assist in ensuring requirement coverage, I led the design and implementation of a scalable, real-time Hardware-in-the-Loop testing infrastructure written in C++ for ECU integration and functional safety requirement testing. This provided quicker signal of functionality changes and allowed for full safety confidence before software changes were ever tested on an actual vehicle.Throughout my time in this role, I often represented the team or otherwise participated in meetings and technical design workshops with international OEM partners and suppliers, assisting in initial vehicle platform integration with our technology. These experiences have grown my ability to communicate engineering concepts and develop effective working relationships with people of different tecnical and cultural backgrounds to myself.

With the Vehicle Control team of Uber's self driving vehicle program, I was responsible for issue triage and resolution for the software of the embedded device that served as a gateway between the self-driving compute stack and the base vehicle platform. In this role, I created and managed data analysis tools in Python and C++ for analyzing logged data and reproducing issues on simulated bench setups. I patched issues in the Simulink project and in handwritten C once the team transitioned away from code autogenerated from Simulink models. Once issues were patched, I managed the testing plan creation, oversaw execution, and analyzed results for resolution confirmation.

I was the Controls Team Leader for Georgia Tech's EcoCAR 3 Team. The EcoCAR 3 Competition involved students converting a 2016 Camaro into a fully functioning hybrid-electric vehicle over the course of a 4 year period.My responsibilities were in modeling the vehicle and all of its components as well as developing and testing the supervisory controller code that operates the vehicle's drive-train. The controls code was developed to minimize energy consumption while maximizing performance. This required interfacing with the vehicle's CAN bus, monitoring safety and performance critical parameters of individual components, and implementing safety measures if faults are detected.My system modeling responsibilities included characterization of the vehicle components and modeling the vehicle using Simulink and Stateflow. This involved the modeling of power train components such as the transmission, engine, etc., the stock GM electronic control modules such as the Engine, Transmission, and Electronic Brake Control Modules, and finally, team added components such as the Energy Storage System, inverter, and electric motor. This vehicle model was then used to assess controls strategies during Software and Hardware in the Loop (SIL, HIL) testing using a dSpace unit.

For this internship, I worked with the Vehicle Control team of Uber's self driving vehicle program. I was tasked with design and development of a vehicle dynamics monitoring system for actively validating vehicle stability across a range of anomalous operational domains, such as low friction surfaces and damage to vehicle suspension/drivetrain. This involved developing dynamics models and conducting testing to validate and fit parameters to the models. After an initial fault detector was implemented, the project was evolved to provide dynamic feedback of environmental conditions for use in motion planning to reflect the operational envelope of capability of the vehicle.My work for the internship culminated in a patent for the resulting monitor and its use in motion planning and fleet management.

While interning with General Atomics Aeronautical Systems Inc., I developed models and simulations for aircraft wiring when the Predator B platform is struck by lightning to estimate induced voltages and currents between control modules. I also developed models and simulations to determine the power coupled through antennas to the internal wiring of the aircraft when experiencing a nearby electromagnetic event. Additionally, I designed and conducted tests to validate these theoretical models and used the data collected to refine and improve the models in order to achieve more accurate simulation results. I then compiled the results of the simulations to establish design levels for the induced voltages and currents modules would be required to handle to achieve DO-160 Lightning Certification and worked with design engineers to ensure that these specifications would be met during the design process.

Designed and validated an electric multi-rotor drone to a gas-electric hybrid system for increased flight time and payload capacity with a custom hybrid drivetrain.Designed, built and used custom data acquisitioning equipment.Developed data analysis algorithms and simulation models in Matlab for flight time and efficiency calculations based on variable parameters.