An Electrical Engineer Moving Across Multiple Transportation Sectors

Mr. Shetty is a remarkable engineer, having worked at Tesla, Nuro, and Lyft throughout his career. He graduated from Arizona State University with a Master’s degree in Electrical Engineering. For the past five years, his innovative mind and knowledge led him to design various impactful products. At Tesla, Mr. Shetty worked as a Powertrain Engineer, where he led and worked on the robust system of robots and automation machinery. He also worked in Controls Engineering where he developed software applications on the Tesla Model S and Model X battery pack lines, incorporating Java and Python code in programs.

Currently, he is working at Nuro and is in the process of building driverless robots. Besides constantly working in the engineering field, Mr. Saiman also co-founded Resume Puppy, a site that provides resume-building tricks and techniques for various application types.

During his presentation with Athena Racing Camp participants, Mr. Shetty covered topics based on Self Driving Vehicles, and how they work. They sense and gather environmental information from sensors, perceive to filter, interpret and understand sensor data along, decide to safely choose actions, and actuate to initiate actions.

He explained the different levels of automation, and in what scenarios they are used in particular vehicles. As a brief insight, level zero is no automation. This is where the driver performs all tasks. Level one is driver assistance. The vehicle is controlled by the driver but has some driving assistance features that may be included. Level two is partial automation. This is where the vehicle possesses combined automated functions like acceleration and steering, but nevertheless, the driver needs to be engaged in driving. Level three is conditional automation. At this stage, the driver is still a necessity, but not required to monitor the environment. However, s/he must be ready to take control of the vehicle in case of an emergency. Level four is high automation. Vehicles are capable of performing all driving functions under certain conditions. Yet, the driver still has the option to control the vehicle. Finally, Level five represents full automation. The vehicle is capable of performing all driving functions under all conditions. The driver may have the option to control the vehicle at this point in systemization.

Additionally, Mr. Shetty covered the variety of sensors in a car, and which type is best used given a certain scenario. To name a few out of the GPS: ultrasonic, odometry, central computer, LiDAR, video cameras, and radar sensors (Mr. Siman considered the camera, LiDAR, and radar sensors). Camera sensors are mainly used for the driver to be aware of their surroundings, but the car can also use them for anti-collision technology.

The LiDAR sensor is a form of remote sensing where a pulsed laser representation of light is used to measure variable distances or ranges to the Earth. They also collect information and input it onto a point cloud. Moreover, according to Radar Sensor Definition, radar sensors are conversion devices which “Transform microwave echo signals into electrical signals. They use wireless sensing technology to detect motion by figuring out the object’s position, shape, motion characteristics, and motion trajectory.” As Mr. Shetty explained, cost, noise, range, resolution, and classification wise it is best to use the camera sensor. LiDAR can best be incorporated when considering illumination, height tracking, distance tracking, and classification as well. Finally, radars can also benefit scenarios of illumination, weather, velocity tracking, and distance tracking.

Whilst teaching various parts of machinery, Mr. Shetty talked about how they apply and cooperate with a vehicle in motion. By showing various diagrams in action, understanding the engineering behind automotive mobiles was very intriguing.

ARTICLE WRITTEN BY: Zinia K, Land + Sea + Air camp Atendee