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Who Will Lead the Race In EV Autonomous Vehicle AI Technology?

Driving forward

Autonomous Electric Vehicles (A-EV) are self-driving vehicles powered by high-quality sensors and advanced technologies like AI at their core. Instead of gasoline, companies employ next-generation technologies, including Fourth Industrial Revolution (4IR) technologies, to develop A-EVs. 

These vehicles are designed to match traditional cars' driving comfort and confidence with human drivers. A-EVs are developed with the primary goal of minimizing the use of fossil-fuel internal combustion engines. Given the increasing global net emissions across industries, A-EVs are a potential step towards achieving zero emission and green AI goals for potentially reducing the carbon footprint of the automobile industry.

Among recent developments, a report by Mark Gurman from Bloomberg reveals that Apple.Inc is accelerating its efforts to develop an electric car with full self-driving capabilities. But an exciting aspect of this project is the inclusion of Apple's silicon experts instead of automotive engineers responsible for providing the tech upgrades such as AI, chips, and other sensors to fulfill this ambitious project. 

Matt Hamblen from Fierceelectronics revealed that the car chip design and the advanced sensors for self-driving cars are likely to be used on retrofitted vehicles that were previously tested in California. On the AI aspect of this development, the chip is built with the neural processing technology required for self-driving. You may achieve top navigation and driving accuracy, but the chip will require a cooling system. 

Another report on the electric vehicle market by Jennifer Sor from  INSIDER suggests Tesla as the ultimate winner in the race of autonomous vehicles. As per the report, Tesla is ahead of competitors in the electric vehicle market and has a significant advantage in the A-EV sector. The reason is Tesla's powerful grasp in both the EV and energy markets, as A-EVs require robotics and AI and advances in battery technology, which gives these vehicles the edge to lower costs.

Cathie Wood, CEO of ARK Investment Management, discusses Tesla being the frontrunner in autonomous taxi platform strategy, more than any other competitors in the market, such as Chinese EV company BYD. That is because the focus area is not enough on autonomous vehicles, where Tesla models are already high quality. Wood suggests that Tesla comes with a price but also offers the best range and performance in the market.

Tesla Essentials for A-EVs

Other factors that make Tesla a winner in this segment is because of their advanced range of AI technologies that, include:

  • FSD Chip
  • Dojo Chip
  • Dojo System
  • Neural Networks
  • Autonomy  Algorithms
  • Code Foundations
  • Evaluation Infrastructure

Another company that is a true contender in line with the mass production of EVs is Ford. The company is doubling its efforts in developing automated driving technology. Recently, Ford announced their platform Latitude AI which aims to fulfill the promise of making driving more enjoyable in self-driving vehicles. Ford has also released massive amounts of data from their self-driving vehicle testing to facilitate advanced research for autonomous vehicle technologies. This self-driving dataset is open to people from academia and other researchers.

Ford is focusing on developing an intelligent and advanced version of their BlueCruise adaptive cruise control system which will provide new features such as hands-free lane changing and repositioning, and predictive speed assistance, including already existing features of their systems such as lane centering, street sign recognition and hands-free driving on the highway. The new features will likely be offered from the 2023 Ford Mustang March E-Select and Lincoln Navigator Standard models.

New Entrants in the A-EV Software Market

Founded in 2017, Ghost is pioneering autonomous-driving software solutions for consumer cars. Ghost Autonomy, an AI software, is the core of Ghost technologies, capable of identifying obstacles, scene perception, route planning and driving, and even understanding the driver's intent. 

Critical features of this uniquely advanced software include perception that processes data from raw camera and radar inputs to create an understanding of the relevant vehicle, determining the obstacles, and perform real-time road configurations. Next is the new driving program that analyzes outputs from the perception and performs various tasks, such as executing safety standards and defensive maneuvers to ensure optimal driving comfort, safety, and appropriate driving routes.

Driving maneuvers range from lane centering, and maintaining appropriate distance, to merging and changing desired lanes. Ghost autonomy software executes critical actions such as precise actuating, steering, acceleration, and braking. Likewise, defensive maneuvers include 360-degree perception and reaction times at least three times faster than a human driver. In the event of any dangerous obstacle, Ghost can execute aggressive brakes and swerving to avoid such life-threatening obstacles on the road.

Finally, navigation and route optimization allow you to overtake slow-moving vehicles and drive in the designated lanes. Additionally, the OTA connectivity ensures you keep tracking traffic data in real time and optimizing routing decisions.

Summary

More recently, the rapid developments in the A-EV segment have made investors and analysts rethink the A-EV market projections. With the capability to contribute towards decarbonization efforts, renewable energy-powered A-EVs are likely to bridge the gap between lowering emissions and increased reliance on self-driving vehicles. We are witnessing breakthrough AI inventions in this segment, and companies are increasingly investing in intelligent autonomous software solutions. These technologies have become faster, safe, and more scalable while equipping cars with advanced capabilities. Many new AI solutions for A-EVs have reached L4 system autonomy with multi-layered redundancy components to enable attention-free driving assistance to overcome the worst scenarios on the road today.