For Volvo, Autonomous Driving Won’t Mean The End of Manual Driving
The new self-driving cars are making their way to the public purchasing arena. There are thoughts, however, that this is not exactly what the entirety of the general population wants.
The new self-driving cars are making their way to the public purchasing arena. There are thoughts, however, that this is not exactly what the entirety of the general population wants. Volvo is considering the fact that many people actually enjoy driving. They have indicated that they are considering a self-driving automobile that allows for the owner to choose when to use this function. Perhaps the car will only offer the self-driving option on the freeway, requiring a manual operation on regular roads, this would leave people able to use their time more wisely on long commutes, by not having to worry about driving the car the entire time.
However, this could present a problem if the vehicle is not able to auto-drive in all situations. It concerns that people who need a self-driving car due to lack of driving skills will not be able to use this Volvo product. If manual operation is the only option off of the freeway, an elderly person will not be able to use the vehicle at all. Some people need the complete availability of a self-driving car. Hopefully, Volvo will take notice of these concerns before a design and production are considered complete. There are many uses for the self-driving cars in today’s societies. It is thought, by some, to be a waste of technology to manufacture a car with only partial self-driving abilities. As these self-driving automobiles become more of a regular appearance on our roads, the many complications and concerns will have to be worked out.
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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