The electric assisted bikes came forth as a new mode of transportation in humans by overcoming the typical barriers of traditional bikes. Rapid development of artificial intelligence has greatly promoted the progress of unmanned driving, as self-driving cars, unmanned aerial vehicles, and so on. Understanding the essential and lacking determinants for the activity of interest, a new AI model is being deployed with energy efficient and emission free transportation. An AI integrated Autonomous vehicle is one that can drive itself from a starting point to a predetermined destination in “Cyber-Bike” mode, uses various in-vehicle technologies and sensors. The model compromises with design and fabrication of electric bikes which makes use of electric energy as the primary source and solar energy by attaching solar panels. And there is also a provision for charging the battery by ejecting it from the main system. It can use any of the alternative sources required at that point of time. The electrical power generated which is used to run the bike can give better fuel economy compared to conventional vehicles, better performance and also cause less air pollution. Every module of AI is integrated into an application which can be handled smoothly instead of any remote device.

CyberBike technology will be able to provide certain advantages compared to human- driven vehicles. One such budding advantage is that they provide increased safety on the road, and automated vehicles could potentially decrease the number of casualties as the software used in them is expected to make fewer errors when comparison to humans. A decrease in the number of accidents could also reduce traffic congestion, which is a further added edge posed by autonomous vehicles. Another possible advantage of automated driving is that people who are not able to drive – due to factors like age and disabilities could be able to use CyberBikes as more convenient transport systems. The new Cyberbike Curve-125 AI can attain from the ground truth of the throttle to updating live and upcoming scenarios.

The whole model is built by using AI technologies and IOT making it distinctive from the existing ones. Cyber Bike is a concept driven technology that uses Artificial intelligence which can recognise faces, gestures, learn and track routes and identify different locations. Object detection is carried out totally by training the objects using a Deep Learning model. Every vehicle moving back and forth is considered as an object, can be detected automatically and decisions are made within no time. The most characteristic feature of cyber Bike is, it is an assist-enabled bike suggesting shortest routes, recognised locations throughout the destination. Overcoming the climatic conditions on-road, every object can be tackled and recognized using the deep learning models giving the best input in response. The models are trained and set at higher potential ways to navigate through all the possible locations.

Various control problems in unmanned vehicles can be actively dealt with the deep reinforcement learning method. In reinforcement learning, the autonomous bikes can learn to amend their actions according to the rewards or punishments when interacting with surrounding environments. DRL can learn the perspective ability of both deep learning and decision-making strategically. The three predominant autonomous vehicle sensors are camera, radar and lidar. Working together, they provide the bike visuals of its surroundings and help it detect the speed and distance of nearby objects, as well as their three-dimensional shape. The other sensors used in cyberbike are Throttle Position, Transmission sensor, Wheel-speed and Oxygen sensors. The Real- time battery consumption, range, distance travelled, time taken, and all other related stats will also be calculated by Artificial intelligence systems.

The solitary aspects that make up the autonomous vehicle to the human eye like AI assisted chatbot which is capable of understanding rider’s intent by responding to it with relatable content. The voice assistance will play a key role in autonomous future bikes making the rider’s to pave the path behind the wheels ensuring risk free factors. The latest OTA technology primarily targets an improved touchscreen and navigation experience through high-end tracking. Geofencing is one of the features which is helpful in the security strategy model as it provides security when there are predefined borders for the bikes done by the positioning technology attached to a server. It is a complete device with an operable touch screen which can be accessed in a smooth way to get all the related service information at a glance.

These autonomous bikes help the riders to track the vehicle through mobile application and can also find the shortest distance using GPS location tracking to their destinations while riding. An automatic alert system is integrated to the using AI technologies assuring the rider to receive end to end notifications such as real-time traffic updates, directions to their desired destinations, accidents etc. The bike is completely keyless which automatically activates and deactivates by making it extremely comfortable for the users ensuring security. The bike can control multiple functions remotely using the mobile app with just a click. E-call systems automatically alarm rescue teams in case of emergency conditions and at the same serves as a theft protection. Vehicle status is known beforehand to the users to handle risks corroborate to have a safe and secure travel. With just a tap on the Screen, the driver is connected to the pulse hub for a host of information services. It also allows the user to get the route assistance from the hub if the user is unaware of the locations. The user may place a range of requests while driving on roads which will be handled by the customer service any time.

An application as a whole serves all the features components embedded with the technologies which can drive together providing secure and shielded rides. The autonomous vehicles will become a reality on our roads in the near future. However, the nonappearance of a human driver requires specialized answers for a scope of issues, and these are as yet being created and streamlined. Advances in self-governing driving prepare for an energizing future where individuals presently don't need to drive, and this change will occur inside our lifetime. Our work is a little advanced towards this worldwide objective, which will require the consolidated endeavors of various partners and industry in the coming years.