Autonomous vehicle maintenance will shift towards predictive maintenance and away from the current reactive approach, thanks to the advanced technologies incorporated in these vehicles.
All vehicles require maintenance at some point or another, and autonomous vehicles are no exception to this rule. Autonomous vehicles are gaining prominence, and they might replace our traditional vehicles sooner than you think. Autonomous vehicles have different operating model than conventional vehicles. Thus, autonomous vehicle maintenance, too, will require a different approach than conventional practices. As these autonomous vehicles are laden with advanced IoT sensors and technologies such as computer vision, artificial intelligence, and machine learning, their maintenance approach shall be dictated by these technologies. The current approach of reactive maintenance will be replaced by predictive maintenance with the help of the data generated by these technologies. Here’s a look at how autonomous vehicle maintenance might look like in the future:
Technology-Aided Autonomous Vehicle Maintenance
The concept of predictive maintenance is nothing new. However, the current approach to predictive maintenance relies on statistics and trials. These could only give us an idea about the ‘mean-time for failure’ of various parts of automobiles. However, with autonomous vehicles, predictive maintenance can be carried out in its true form in real-time with the help of hardware and software incorporated in the vehicles. IoT sensors allow the collection and monitoring of data in real-time. This data can be leveraged by artificial intelligence to monitor the vehicle in real-time accurately and inform the driver of maintenance issues. This will help identify problems quickly and help save costs usually associated with delayed repairs. It will truly alert the driver of a breakdown before it happens. Drivers can have a complete overview of their vehicle’s condition and can be assured that they won’t face any unexpected maintenance issues. The data collected by the IoT sensors can also be leveraged by the automobile manufacturers to design better vehicle parts. As these vehicles share data among themselves and the manufacturer, it gives the business a broad understanding of their vehicles’ performance in different driving conditions. They can then design new autonomous vehicles that are efficient, cost-effective, and low on maintenance.
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Challenges for Autonomous Vehicle Maintenance
Autonomous vehicle maintenance, with the help of IoT, will not face significant challenges as such. However, the two challenges that might prove to be a small hurdle are:
In the case of a true-autonomous vehicle, the driver will be eliminated from the vehicle. This will cause an issue if the vehicle faces a breakdown on the road and requires primary human intervention to replace the failed parts. A human driver or an assistant will always be a requirement, even in case of a truly autonomous vehicle.
Another issue that might cause a hindrance is the failure of the sensors themselves. The sensors can get damaged and collect inaccurate data. An autonomous vehicle operating with a faulty sensor can prove to be hazardous on the road. This, too, will require human intervention as the final step. Thus, the challenges faced in autonomous vehicle maintenance can be usually overcome by having a continuous human presence inside the vehicle.
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With the mainstream adoption of autonomous vehicle maintenance, autonomous vehicles will let humans know their maintenance needs before we ask. These vehicles will be able to tell us ahead of time what possibly could go wrong. Thus eventually, the end-to-end lifecycle of vehicles, and not just their operation, can be automated in the near future.
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About The Author
Ibrar Ayyub
I am an experienced technical writer holding a Master's degree in computer science from BZU Multan, Pakistan University. With a background spanning various industries, particularly in home automation and engineering, I have honed my skills in crafting clear and concise content. Proficient in leveraging infographics and diagrams, I strive to simplify complex concepts for readers. My strength lies in thorough research and presenting information in a structured and logical format.
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