SensingTo reliably and safely operate an autonomous vehicle, usually a mixture of sensors is utilized.Typical sensors include lidar (Light Detection and Ranging), stereo vision, GPS and IMU.Modern self-driving cars generally use Bayesian simultaneous localization and mapping (SLAM) algorithms,which fuse data from multiple sensors and an off-line map into current location estimates and map updates. Waymo has developed a variant of SLAM with detection and tracking of other moving objects (DATMO), which also handles obstacles such as cars and pedestrians. Simpler systems may use roadside real-time locating system (RTLS) technologies to aid localization.
National securityIn the 2020s, from the importance of the automotive sector to the nation, self-driving car has become a topic of national security. The concerns regarding cybersecurity and data protection are not only important for user protection, but also in the context of national security. The trove of data collected by self-driving cars, paired with cybersecurity vulnerabilities, creates an appealing target for intelligence collection. Self-driving cars are required to be considered in a new way when it comes to espionage risk.
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