Although autonomous technologies haven't reached wide scale adoption yet, many have already been tested and protoyped. With deployment imminent, we analyzed the four largest technical challenges facing autonomous vehicles today. Developing solutions to tackle these specific challenges will be compulsory to accelerate the deployment of level 5 automation.

1. Improving Data Collection & Processing for Better Vehicles
2. Optimizing AI & Machine Learning for Safer and Better Performance
3. Transitioning Autonomous Hardware & Software from Testing to Production
4. Growing Public Sector Integration & Regulation
   

We sat down with Dr. Joe Xing, Director of Artificial Intelligence for AV at Borgward R&D, to learn more about their behavior learning and AI safety platform for self-driving cars.

Check out this exclusive in-depth interview to learn all about:

• The potential of Borgward's AI platform to transform autonomous driving as a whole
• Advice for fellow automakers who may be relying too heavily on sensors and field testing
• The most accurate way for self-driving cars to predict human uncertainty on the road
• Borgward's key objectives/priorities for the next 2-5 years
• What to look forward at the Autonomous Vehicles Summit
• And much more!
  
  

The drive towards autonomous vehicles will encounter many challenges and several of them will revolve around data. The scale of the task of creating a car which can drive more reliably than a human cannot be underestimated. In just one day, a test autonomous vehicle produces as much data as the Hubble telescope produces in a whole year. Many companies involved in the development of self-driving cars have turned to deep learning techniques to reach their goals, which means analyzing vast amounts of data from many vehicles. Moreover, this data must be stored and managed effectively in order to train the neural networks which will eventually control autonomous vehicles.

Autonomous vehicles have gone beyond a concept to being accepted as the future of mobility, but the motor industry has plenty to grapple with in order to make that a reality. High profile accidents involving autonomous cars have highlighted that various technical barriers still remain in terms of scalability and deployment. Consumer confidence is essential to the introduction of self-driving vehicles, while regulators at state and federal level will require robust safety protocols.

Read our latest Automotive IQ technical paper on “Intelligently developing and testing the AI safety case” by Professors Amnon Shashua and Shai Shalev-Shwartz, for free here:

Learn how to determine validation testing scenarios for an ADAS functionality by reading ZF’s proposal on ADAS testing scenarios; presented by Functional Safety Experts Gaetano Fiaccola and Oleg Kirovskii.

According to vehicle traffic data, about 89.8% of accidents are triggered by driver’s erroneous decision-making, comprising more than one million incidents worldwide every year. As the automotive sector grows and autonomies driving technologies mature, the industry is turning to relieving traffic accidents, that will offer the consumer all the trust needed to take the plunge into self-driving vehicles. For software developers and system architects, the question becomes more pressing: How to make AI algorithms good and safe enough to fulfill drivers’ expectations? Learn more in our latest Automotive IQ article that you download for free here:According to vehicle traffic data, about 89.8% of accidents are triggered by driver’s erroneous decision-making, comprising more than one million incidents worldwide every year. As the automotive sector grows and autonomies driving technologies mature, the industry is turning to relieving traffic accidents, that will offer the consumer all the trust needed to take the plunge into self-driving vehicles. For software developers and system architects, the question becomes more pressing: How to make AI algorithms good and safe enough to fulfill drivers’ expectations? Learn more in our latest Automotive IQ article that you download for free here:

The Autonomous Vehicles Summit surveyed 325+ global automotive leaders to identify where car manufacturers are on their journey towards autonomous, how they’re capitalizing on this opportunity for reinvention and the key challenges they’re facing as a result. This report aims to not only present a snapshot of the current state of autonomous, but also enable the development of a new set of industry benchmarks, best practices and innovative solutions.

Cellular and terrestrial Wi-Fi networks have played an integral role in the development of connected cars, delivering software updates, critical information, and mapping data. As the industry continues to move towards autonomous vehicles, satellite data will have an equally crucial role in providing highly accurate and precise mapping data for self-driving cars.

The global market for connected vehicles continues to grow at pace and the introduction of 5G networks is predicted to have a significant impact on the development of fully autonomous cars.