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Challenges Impacting the Future of AV


The automotive industry has been working vigorously to increase the number of self-driving vehicles on the road. Systems engineering company Waymo, previously known as Google’s self-driving car project, weighs in on the challenges facing autonomous vehicles of the future.

One challenge for systems engineering companies is the complexity of the technology needed to develop and operate a fully autonomous vehicles. Fully autonomous cars require an endless number of hardware and software components and algorithms that enable AV companies to see the vehicle’s surroundings. This allows them to understand what is happening around the car before charting the course from A to B. The advancement of autonomous vehicles will depend on how well companies continue to find innovative ways to seamlessly integrate complexities into the vehicles.

In order to create a more robust environment for self-driving vehicles, it will be crucial to find new ways to improve the efficiency of lidar, radar and camera sensor technology. The future of AV needs to focus on more capable, longer-range sensors with more energy efficient chips. Deep learning is another key to the improvement of AV. This is a machines ability to continually analyse and adapt to new situations which is more efficient than a traditional engineering approach. This can help an AVs performance in unpredictable scenarios such an object flying off the bed of a truck and landing in front of the vehicle.

Another foreseeable challenge in the advancement of AV is the need for more talent. The need to develop smarter technology increases across all sectors of the industry means finding new ways to attract engineers, developers and designers. As companies chase the same talents, it becomes difficult to find and keep them on board.

In order for self-driving vehicle to function as intended, it needs to communicate with its surroundings. Also known as vehicle-to-infrastructure communication, this is the ability of an AV to communicate with smart traffic light systems, creating a more robust environment for testing. Developing more cohesive infrastructure is pivotal to creating safer and more seamless self-driving experience for customers.

Testing and validation has a major impact on the development of autonomous vehicles. The advancement of AV technology will require companies to rely more on simulated data testing, which will enable them to run thousands of variations of driving scenarios. Read more here.

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