With Mobility-as-a-Service (MaaS) seen as a key element of smart mobility, one factor that will be critical to growth is robotic vehicle technology, which in turn will be highly reliant on embedded sensors .
In this scenario, high-end sensor technology and raw computing power will be at the core of continued market disruption, and according to market research, sensors for robotic vehicles will become their own industry and are projected to grow at a CAGR of 51% over the next 15 years %. and strategy consultancy Yole Developpement (Yole). In a new report, "Sensors for Robotic Mobility 2020," the company said it expects to generate $900 million in revenue by 2024, $3.4 billion in 2028, and $17 billion in 2032, There will be a million robots roaming our streets.
The sensor revenue data in 2024 is divided into $400 million for lidar, $60 million for radar, $160 million for camera, $230 million for IMU and $20 million for GNSS equipment. The division between the different sensor modes may not remain the same over the next 15 years.
Robotic Vehicle Sensor Systems Revenue Forecast
Robotic Vehicle Sensor Systems Revenue Estimated to 2032
So, what challenges does Yole see in the development of smart transportation? It said current modes of travel were facing five major constraints. First in the most vulnerable way, pedestrian safety is deteriorating. Second, public transportation is challenged in terms of efficiency and cost in the major cities where people tend to live today. Third, cars are no longer the mobility solution they used to be. Congestion and cost of ownership are undermining this option. Fourth, air traffic is currently expanding rapidly, but travel remains difficult as city-to-airport connections remain poor. Fifth, there is an urgent need for urgent change due to the CO2 emissions caused by all current modes of travel. Regulators and customers are willing to make changes both top-down and bottom-up.
Pierre Cambou, chief analyst at Yole, said the travel industry will have to adapt and for some this will be a huge opportunity. He said: "Robotic mobility clearly checks all the right boxes in this regard. The combination of all these new modes, whether it is autonomous vehicles, space shuttles or electric VTOL aircraft, will provide Suburban, city-to-city 'MaaS'. Previous forms of mobility won't go away, just like movie theaters will still exist when TVs are deployed on a mass scale. Robotic car technology will power Netflix's mobility by 2032, regardless of naysayers sex."
He added: "Disruption is spreading to our streets and cities. Mobility has defined the way humans have organized society for years, and our world is currently being reimagined around a new generation of robotic vehicles." Companies most attracted to the MaaS market It's companies like Google, Baidu, Amazon, and Uber, which are expected to be worth $2.4 trillion over the next decade. An additional $1.1 trillion will be generated through the sale of personally owned self-driving cars, with the added value of autonomous driving suggesting a total value of $3.5 trillion by 2032.
Robotic vehicles aren't concerned with cost and long-term reliability, which are the main concerns of other cars, Juul said. What matters is the immediate availability, performance and supportability of its sensor suite. Robotic sensor data flow is limited by downstream computing power. Previous generations of robots were in the hundreds of tops (millions of operations per second), while the latest robotic vehicles are in the order of a thousand tops (Tops). This provides a limited increase in sensor data flow, which is related to what Yole calls "Moore's Law". The required computing power increases with the square of the dataflow input. The number of sensing cameras, radars, and lidars will grow at a much slower rate than the capabilities of robotic vehicle computers.
The solution to data sparsity is for roboticists to use "better" data, meaning sensors bring in other types of information. The quality of information has improved, not the quantity. In addition to industrial-grade cameras and radar, they make heavy use of 3D sensing lidar, navigation-grade GNSS devices and IMUs, and more recently thermal infrared cameras.
Innovative Solutions for Automotive Sensing and Computing
Future Innovations in Automotive Sensing and Computing
Market and revenue forecasts in the report suggest that 2020 will be the year the first robotic vehicles are industrialized. For initial fleet manufacturing, the report predicts that spending on sensing equipment will take the highest share, accounting for 36 percent of total costs. Sensing equipment spending will still account for 28% of total robotic vehicle hardware capex by 2032. The use of solid state and the advantages of technology expansion will help reduce the price of sensing equipment, while the performance of this equipment will also increase. The total cost of the robot car will be reduced to $124,000 by 2032.
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