With the relaxation of self-driving regulations in many countries, companies at full fledge are developing their self-driving vehicles and making their way onto the public roads. The pace at which the technology is developing has created risk for the traditional manufacturers being overtaken by technological firms. Therefore it results in the collaboration or partnership between the traditional and technological firms. Autonomous vehicle technology is based on complex algorithms, and sensors to create a digital world that helps the autonomous vehicle to orient their position on the road and identify obstacles, cyclist, and pedestrians. Such systems are incredibly difficult to design and produce and they must be programmed to cope with a limitless number of variables collected at real time on roads.

This makes the machine-learning the basis for autonomous systems, artificial intelligence could be the next disruptor in the autonomous vehicle technology. The sensors like radar, camera and LiDAR produce huge amount of data that needs to be analyzed at real time and the vehicle has to act upon in synchronization with the data. Among all the sensors, LiDAR requires huge amount of computing power to interpret all of the data collected by the sensor for constantly changing road conditions and traffic situations. This is where deep learning systems help to drive and develop decision-making processes like a human. Several companies, such as tech giants and startups are developing AI systems for autonomous vehicles. Artificial Intelligence is the next new thing which will drive the autonomous vehicle market. Many companies collaborating the artificial intelligence and LiDAR technology for enabling the driverless vehicle. The LiDAR performs the data collection work and artificial intelligence provide the processing of the collected data and helps AVs in taking the decisions on road.

Combining Artificial Intelligence with LiDAR is considered as one of major opportunities for manufacturers. Also, this trend has been seen to be followed by many leading players. For instance, Ford invested $1 billion in the Argo AI, and this investment was aimed to develop the artificial intelligence for Ford’s level 4 autonomous vehicle by 2021. In October 2017, Argo AI acquired Princeton Lightwave a Geiger-mode LiDAR manufacturer company, with an extensive experience in the development and commercialization of LiDAR sensors. The strategy behind the acquisition was to increase the range, resolution, and field of view of LiDAR sensors by lowering the costs in order to initiate mass production at earliest. Also, NVIDIA, with its DRIVE PX AI platform and Pegasus AI, the company is offering OEMs with the AI platform to enable fully autonomous drive. Apple is also initiating the AI and automotive sensor integration. In December 2017 the AEye Inc, introduced iDAR which is a new form of intelligent data collection that enables rapid perception and path planning for the autonomous vehicle application. The iDAR combines the MOEMS (micro-optical mechanical) LiDAR which is integrated with a low-light camera and embedded artificial intelligence.

Many companies are pushing this trend of AI and sensor integration, its seems that consumers don’t have to wait long for experiencing the ride in autonomous vehicles.

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