Problem Statement: Autonomous cars will require the most sophisticated Smart Vision and on-board intelligence of all vehicles. Such smart vehicles require sensors, two layers of software (identification and classification), as well as algorithms and actuators. While there are today tens of developers of Nano Devices and Modules, sensors, software, algorithms, and actuators for such vehicles, Original Equipment Manufacturers (OEMs), as well 1st Tier Suppliers are confronted to a fuzzy puzzle of products specifications and suppliers. As a result, significant investments and lead-time are wasted. In addition, technologies are still progressing and photonics are expected to play a growing role, thanks to the increased miniaturization, the better performances and the lower power consumption they allow but very little has been done so far in this direction.
Proposed Solution: To address these concerns, NanoPhot Consortium was created under ALEO leadership. The international partners of the NanoPhot project share complementary experiences and are used to work together. They have already developed key technologies that shall be integrated in the present project, the objective of which is to offer a nano-photonics based global, diversified, and higher performance solution to this issue. As an important preliminary remark, it must be noted that NanoPhot does not discriminate between levels of vehicle autonomies L3, L4 or L5 as Nano Devices and Modules are essentially quite similar. Of course, this is not true for the sensors themselves as they are highly dependent on the autonomous level. Nanophotonics devices and modules proposed by NanoPhot can serve as a game changer in this worldwide race for Smart Autonomous Vehicles (SAV), while presenting several modules, working in both visible and Infra-Red (IR), both day light and night vision, and which have been developed and, with adequate research and funding, can be integrated in Smart Vision new modules, enabling better four steps: 1) Forecast, 2) Understand, 3) Deduct and 4) Decide.
Smart Autonomous Vehicles sensors