Digital mapping specialist DeepMap has launched RoadMemory, a crowdsourced mapping service.

RoadMemory is designed to allow car makers to create and roll out quickly large-scale digital maps from data collected from their own fleets of passenger vehicles and trucks. 

The new service is designed to expand geographic coverage more quickly and support hands-off autonomous driving features.

The service includes driver support features such as highway assist, intelligent braking, and traffic jam pilot.

RoadMemory will automatically build maps using crowdsourced data collected from on-car sensors such as cameras, radars, and newly-available automotive-grade LiDARs. 

The firm says that RoadMemory is sensor-agnostic and provides flexibility to automakers who require an open system and a choice of sensors to meet their needs.

RoadMemory will work hand-in-hand with DeepMap HDR (High-Definition Reference), DeepMap’s high-fidelity mapping offering. 

James Wu, Co-Founder and CEO of DeepMap, said: “RoadMemory addresses the immediate autonomy needs of near-term production vehicles while providing a natural roadmap for future higher levels of autonomy. DeepMap is offering a future-proof ‘best of both worlds’ approach which leverages the sensor capabilities available in cars today while increasing the fidelity of maps over time as cars become more capable.”

Mark Wheeler, Co-Founder and CTO of DeepMap, said: “Automated driver assistance and Level 2+ through Level 3 capabilities have become a critical battleground for automakers. Camera and LiDAR sensors are starting to ramp and proliferate for near-term production models. In tandem, automakers are evaluating and choosing their map source. DeepMap is providing a future-proof mapping solution for crowdsourced data that will enable more advanced functionality over time as the vehicle sensors improve and coverage expands.”

Wheeler added: “Building maps has been a large and expensive undertaking until now. DeepMap leverages state-of-the-art AI and mapping technologies built from the ground up for machines, by those same machines. Now it is possible to create the large-scale, fresh, accurate, open, and economical maps the transportation industry needs to advance to higher levels of autonomy.”