While still at the early stages, with a lot challenges related (lack of standards and more), we are moving steadily and surely toward the future of fully driverless cars. This means that, highly accurate, real-time maps are essential. All autonomous and driverless vehicle maps will need to combine accuracy, environmental models, and real-time attributes allowing positional and temporal awareness.
In combination with sensors that provide real-time visibility on a vehicle’s
immediate environs for last-minute obstacle detection and collision avoidance, maps extend this visibility to allow
vehicles to anticipate those situations long before the sensors would even have
to detect them.
Maps need to work in harmony with ADAS sensors to
dramatically improve overall accuracy and predictability.
Standards and open platform approaches seamlessly allow vehicles to exchange real-time
map attributes between each other.
According to ABI Research, the biggest challenge for the new mapping
paradigm is the lack of standards coupled with high levels of fragmentation in
the automotive industry; and many players, like ADAS vendor Mobileye, are vying
to play a role in map data crowdsourcing and proposing and/or imposing their
own proprietary approaches.