Skills needed for working in Autonomous car technologies

• Author Amit Babel
• DateMay 03 2019

Building Autonomous vehicles is quite a complex task and require varied technical skill sets. Since this is a sunrise industry, not many candidates possess the exact competencies as required by the employers. So how can you leverage your existing skills or enhance them to explore the fantastic career opportunities in this field? 

To answer that, Let’s first review the 5 main building blocks of Autonomous cars:-

Computer Vision – Computer vision is a field of computer science that works on enabling computers to see, identify and process images in the same way that human vision does, and then provide appropriate output. It is like imparting human intelligence and instincts to a computer. In reality, though, it is a difficult task to enable computers to recognize images of different objects. Computer vision is closely linked with artificial intelligence, as the computer must interpret what it sees, and then perform appropriate analysis or act accordingly.

Precision in computer vision is necessary for autonomous cars to operate. Computer vision helps Autonomous cars to perceive the world around them and create a digital map using Computer Vision, Machine Learning and Artificial Intelligence. The input devices for an Autonomous Vehicle are the cameras, radar and lasers.

Sensor Fusion – Sensor fusion is the use of sensory data from multiple sources, combined into one comprehensive result. Using multiple sensors, planners can generate more robust data models or obtain greater numbers of data points for the purposes of a given system. Sensor fusion system is useful in image processing and is the backbone of autonomous car technology as it makes cars more intelligent.

Autonomous cars are fitted with various input devices like sensors – radar, camera, ultrasonic and lidar, that perform various tasks. These sensors complement each other and achieve functions important for the performance of self - driving cars. Autonomous cars can make critical, autonomous decisions using sensor fusion applications and achieve the highest level of safety, reliability and security.

Localization – Localization is an essential part of an Autonomous Vehicle. It uses GPS/INS and odometry to track the Absolute Position of the vehicle in the Global frame and simultaneously uses odometry alone to compute the vehicle's position in an arbitrary Local frame. Using Computer vision and sensor fusion, autonomous cars are able to develop a comprehensive understanding of its environment. To understand where this environment is, it would need to analyze its location.

With localization, autonomous cars are able to locate the precise position and that forms the basis for the decisions on motion planner. Localization involves knowledge of mathematical algorithms and probability calculations along with the study of GPS.

Path Planning – Path planning technology searches for and detects the space and corridors in which a vehicle can drive. It generates paths that maximize the distance between a vehicle and surrounding obstacles. It also helps in finding the shortest or optimal path to the defined destination. Path-planning requires a map of the environment and the car to be aware of its location with respect to the map. Knowledge of GPS and pathfinding algorithms are helpful in this field.

Control – is probably the most important building block of an Autonomous Vehicle. It involves guidance, navigation and motion control systems and requires knowledge of mathematics, engineering and programming to build this function.

How could one enhance the skill sets required for the jobs in autonomous driving cars?

The above building blocks offer challenging career opportunities for the Tech experts. You can polish your skills and enhance the expertise relevant to these domains. There are a number of courses available, both online and physical that you may consider. Massive Open Online Courses [MOOCs] providers such as Udacity, Coursera and Udemy offer modules which are valuable in enhancing your skill sets in the areas mentioned above.  

A few of the interesting ones are listed here -

·       Self - Driving Car Engineer Nanodegree SDCND (Udacity)

·       C++ Nanodegree (Udacity)

·       Deep Learning Nanodegree (Udacity)

·       Machine Learning Nanodegree (Udacity)

·       Computer Vision Nanodegree (Udacity)

·       Visual Perception, Motion Planning, State Estimation and Localization for Self-Driving Cars for Self – driving cars (Coursera)

·       AI Programming with Python Nanodegree (Udacity)

·       Data Structures and Algorithms Nanodegree (Udacity)

·       Robotics Software Engineer (Udacity)

You could also read our first blog on Autonomous cars – A dream career opportunity for Tech Savvy. This blog talks about the fantastic opportunities in Europe for Candidates who are passionate about developing their careers in the field of autonomous driving cars.

Let us know your thoughts.