{"id":326,"date":"2020-08-25T17:49:00","date_gmt":"2020-08-26T00:49:00","guid":{"rendered":"https:\/\/blog.damonmotorcycles.com\/?p=326"},"modified":"2023-01-04T16:31:21","modified_gmt":"2023-01-05T00:31:21","slug":"motorcycle-ai-create-safest-electric-motorcycle","status":"publish","type":"post","link":"https:\/\/damon.com\/blog\/motorcycle-ai-create-safest-electric-motorcycle\/","title":{"rendered":"How We\u2019re Using Motorcycle AI to Create the Safest Electric Motorcycle"},"content":{"rendered":"\n

Motorcycle technology has come on leaps and bounds in the last five years. This begs the question: What will the upcoming five years hold? At this point, Motorcycle AI is a high contender for the next big innovation for futuristic motorcycles. <\/p>\n\n\n\n

Self-learning technology is already a huge part of our lives. Industries such as healthcare and eCommerce greatly benefit from this technology – and the motorcycle industry is no exception. Thanks to machine learning, electric motorcycles can now learn and adapt to each individual rider to improve the riding experience with every journey. That being said, the most influential way in which self-learning technology has revolutionized riding is perhaps through motorcycle safety.

While motorcycling is classed as a more dangerous form of transportation compared to the rest, it’s the most common worldwide. So a logical application where technology can help is augmenting rider awareness, resulting in safer motorcycle riders. <\/p>\n\n\n\n

Damon<\/a> is just one of the motorcycle manufacturers that are starting to focus more on motorcycle safety. This is evident in our in-house industry-disrupting software. From our 100% electric powertrain, HyperDrive\u2122, to our award-winning CoPilot\u2122, Advanced Warning System for Motorcycles (AWSM), our technology helps us reach our goal of no fatal accidents on any of our bikes by 2030. So, how did we innovate existing transportation technology to make an award-winning safety system? Let\u2019s break it down.<\/p>\n\n\n\n\n\n

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Damon HyperSport Prototype and Honda Motorcycle Parked in Vancouver<\/em><\/figcaption><\/figure>\n\n\n\n\n\n

Step 1: Deconstruct the Average Motorcycle Journey<\/h2>\n\n\n\n

The first step was to deconstruct how motorcycles navigate through the many hazards on an average journey. Furthermore, we also needed to understand the dynamics of a collision. <\/p>\n\n\n\n

Collision avoidance systems are already a reality in cars. Moreover, many of the major auto manufacturers even developed fully autonomous vehicles. Some of the same principles apply to riding. However, due to the nature of how a motorcyclist moves through traffic, there needs to be some differences. The next step was to further explore these differences.<\/p>\n\n\n\n

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HyperSport Prototype<\/em><\/figcaption><\/figure>\n\n\n\n\n\n

Step 2: Take the Existing ADAS\u2019 for Cars and Adapt It for Motorcycling<\/h2>\n\n\n\n

The auto industry has invested a lot of time and money in advanced driver-assistance systems (ADAS). This is extremely positive. It\u2019s been responsible for producing faster processors and more complex sensors with smaller footprints. In a recent study of people who bought cars with ADAS, over half said it prevented a crash in the first 90 days<\/a> of ownership. <\/p>\n\n\n\n

That being said, it\u2019s different in the motorcycle industry. This is because motorcycles are inherently different from any other vehicle on the road. <\/p>\n\n\n\n

This difference can be characterized by the following unique vehicle dynamics:<\/p>\n\n\n\n