Automotive Is Now Autonomous. Are You Ready?

May 21, 2025

1.5 Billion. That’s the total number of cars on Earth.

That includes 150 million Toyotas, over 40 million Volkswagens, more than 20 million Mercedes-Benz vehicles — and around 5 million Teslas. Uber alone operates 7.8 million cabs worldwide.

What happens when they all go autonomous?

It’s happening right now. To begin with, Uber operates in 900 cities around the world and has partnered with Google’s Waymo and May Mobility to convert its fleet into fully autonomous vehicles. 150 million people use Uber today — and soon, many of them will be served by autonomous vehicles. 

Beyond Uber, Tesla is launching robotaxis this summer in Texas. Google’s Waymo — the company’s AV subsidiary — has already launched self-driving cab services in many U.S. cities including San Francisco, Phoenix, Los Angeles, and this week, in Boston.

China’s Baidu — a self-driving pioneer — is launching its driverless cab service named Apollo Go in Switzerland this year. Aurora’s already hauling freight with self-driving trucks in Texas.

And it’s not just trucks and cabs — personal vehicles are no exception here. Toyota, Nissan, Volkswagen, Hyundai — they’re all inching toward autonomy. 

This isn’t a pilot phase.  It’s an industrial rollout of Autonomous Vehicles (AVs). This is a platform shift in the automotive space— like the internet in the 1990s or smartphones in the 2000s. 

At the CES ’25 conference, Jensen Huang from NVIDIA called it “the first multi-trillion-dollar robotics industry.” He wasn’t talking about humanoids. He was talking about Autonomous Vehicles.

What This Means for Automotive Engineers

If you’re an automotive engineer today, make no mistake: the ground beneath your feet is "moving". You may not feel it yet. But it's happening — in the code, the factories, the infrastructure.

You might wonder, so what? 

What does that actually change? 

How does it affect my work, my career?

It turns out, the impact is enormous. Two shifts, in particular, stand out.

First, it changes how cars are being designed and built—end to end.

Second, it transforms the very technology that powers them.

Let's start with the first.

Modern car factories don’t resemble the Ford or Volkswagen plants of the past. They look more like Amazon warehouses — with more robots than people. You can still be a mechanical or automotive engineer. But increasingly, the machines you’re designing aren’t cars. They’re robots.

Then, comes the design process.

AI-enabled systems now inform aerodynamics, weight distribution, battery placement, and crash optimization systems. If you don’t understand how these systems work — or worse, don’t care — you’re not just falling behind. You’re becoming irrelevant.

Now, for the second shift: what powers modern cars.

It used to be the engine.

Now, it’s the code. It's intelligence. 

The combustion engine is no longer the heart of a car. The self-driving system is.

This shift didn’t happen overnight. These systems have been decades in the making. From DARPA’s Grand Challenges in the Mojave Desert to Google’s early Firefly prototype, and now, to commercial systems like Waymo — the path to autonomy has been long, but deliberate.

And yet, despite the years of evolution, the core architecture behind these self-driving systems still rests on four core pillars.

The Four Pillars of Autonomy

1. Perception

   Every autonomous vehicle must understand its environment. This is the role of the perception module: enabling the car to see and interpret the world around it. Using sensors like LiDAR, radar, and cameras, the vehicle captures real-time data to construct a detailed 3D view of its surroundings.

   
   

   Perception forms the foundation that allows the vehicle to observe and make sense of the road ahead. It's the core pillar for everything that follows — without it, the car is blind.

   
   

2. Localization

   Seeing the world isn’t enough. To navigate safely, a car needs more than eyes — it needs to know exactly where it is. It needs to track its position with precision.

   You might ask, why not just use GPS or Google Maps? The problem is accuracy. Standard GPS and GPS-enabled applications are off by about a meter. That’s not precise enough when you’re moving at 60 mph and need to know which lane you’re in — with centimeter-level precision.

   
   

   That’s where localization comes in.  Autonomous vehicles combine GPS data with high-definition maps and onboard estimation algorithms to determine their exact position — not just on the road, but within the lane. Without that precision, safe autonomy isn’t possible.

   
   

3. Path Planning

   Once your car knows where it is located and what’s around it, it needs to plan a route to its destination — and do that safely. This is where the path planning algorithms come handy. They enable our car to develop a series of waypoints from source to destination optimized for traffic conditions, pedestrian footprint, passenger comfort and safety.

   
   

4. Motion Control

   Then comes execution. This module converts the route finalized by the path planner into physical action. It activates steering, brakes, and accelerator — all in real time, all within milliseconds.

That’s autonomy. At least the core of it.

But if you want to build this — not just understand it — you need to go further.

You need to study how real companies design each piece. What fails. What scales. 

You need to know how Mercedes does it differently from Waymo. Why Tesla steers away from LiDARs. Why Zoox chose a symmetrical design. What happens when a sensor goes blind or GPS drifts.

You need case studies.You need war stories.You need real-world experience.

Books help. YouTube has its place. But time is limited — and scattered resources often leave you with more questions than answers.

What you need is a structured and application-oriented approach.  That’s the path we followed in building our course on self-driving cars — grounded in first principles and real-world systems.

It’s not just a collection of lectures. It’s a map.

If you are serious about making a dent in your career in the autonomous vehicle space— and don’t want to waste months chasing scattered content — start here.

Take the first step into autonomy. Explore our course on Self-Driving Cars.

Cheers,

Prathamesh

Disclaimer: This blog is for educational purposes only and does not constitute financial, business, or legal advice. The experiences shared are based on past events. All opinions expressed are those of the author and do not represent the views of any mentioned companies. Readers are solely responsible for conducting their own due diligence and should seek professional legal or financial advice tailored to their specific circumstances. The author and publisher make no representations or warranties regarding the accuracy of the content and expressly disclaim any liability for decisions made or actions taken based on this blog.