CASE STUDY

The automotive industry is in the midst of a transition toward producing vehicles that are more aware of their surroundings. For many years, there has been a goal that vehicles should be able to communicate with not only other vehicles (V2V) but also with nearby infrastructure (V2I), Internet-based networks (V2N) and even pedestrians (V2P). Collectively these use cases have become known as vehicle-to-everything (V2X) connectivity. Now, with advances in electronics, sensing technologies and computing techniques such as machine learning and computer vision, this use cases are starting to become reality. New vehicles today are capable of taking a more active role by warning drivers of potential collisions with oncoming vehicles, assisting with emergency braking and monitoring intersections, to name just a few examples. This represents a big step forward from relying on passive safety features such as seat belts and air bags.

 

In the automotive industry, this trend is viewed as the beginning of an evolution to automated and eventually fully autonomous vehicles. In an autonomous vehicle scenario, the vehicle's on-board computers will be fully capable of performing all driving operations on their own, with no human monitoring required. This is still a few years away, but today we are getting closer with the likes of Tesla providing partial automation and Google's self-driving car testing conditional automation.

 

QUESTION

Which hardware and software/firmware are required? with relevant justifications based on chosen scenario.