LONDON, May 25, 2015 /PRNewswire/ -- WinterGreen Research announces that it has published a new study Robot Cars and Trucks: Market Shares, Strategy, and Forecasts, Worldwide, 2015 to 2021. The 2015 study has 413 pages, 156 tables and figures.
Worldwide markets are poised to achieve significant growth as robot cars and trucks permit users to implement automated driving. Fleet vehicles from Uber, Google and similar users are likely to be the early adopter groups.
IBM and Google are sure to be a significant software vendors for all the robot car and truck market participants. IBM has a huge head start with its excellent middleware branded integrated solutions that are hardened and reliable. Google has mindshare and early market success with its early market trials.
As automated process hits the auto industry as a disruptive force, it parallels the automated piloting of the airline industry that saw significant labor savings implementation. Automated vehicle driving can be done anywhere just by connecting the car to integrated adaptive cruise control, adaptive steering and braking, and lane assist systems all working off one central processor.
Robot cars and trucks incrementally add automated process to driving. As software is added to cars and trucks it is done in concert with modification to the steering, breaking, and other automotive systems. Autonomous functions for vehicles are increasingly adopted.
Change is incremental, we do not have fully functioning robot cars immediately, rather, steering, collision avoidance, parking, test driving, series of camera and radar based monitoring systems, lane assist, and adaptive cruise control are being implemented, presaging rapid adoption of robot cars and trucks as the various functions mature and work in the real world.
According to Susan Eustis, team leader for the preparation of the study, "The market for robot car and truck vehicles is anticipated to expand in parallel with the deployment of appropriate roadway controls funded by government programs. The large public investments for robot vehicles so far has been for development of technology that works for military purposes. The extension of this type of automated system to commercial fleet vehicles will be rapid after 2020"
The robot car designs amalgamate a group of features to represent an automated process solution. These include the hardware, the software middleware, the steering system, adaptive cruise control, numerous software applications, an integrated systems approach, and related services. Significant investments in research and development are necessary as the emerging robot cars and trucks industry builds on incremental technology roll outs.
Robot car and truck commercial autonomous car market shipments forecasts indicate that markets beginning to develop in 2015 will rise to $868 million by 2021. Growth is a result of various moves toward autonomous vehicles that park themselves, provide automated steering, are used as test vehicles, are used as mapping vehicles, and that provide driver alerts but fall sort of complete robotically operated car vehicles.
Market driving forces relate primarily to the need for increased safety and personalization for autos. Car manufacturers are positioning with robot car models to meet demand at the high end. Many robot vehicle car vendors are making automation for personal vehicles and trucks a reality.
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This robot car and truck shipment analysis is based on consideration of the metrics for the number of cars shipped, percent of cars outfitted with automated cruise control, and probable market penetrations of robot cars. Experience using the robot cars and trucks is another factor that contributes to development of triangulation regarding market forecasts for the sector.
Robot Cars and Trucks, Robot Cars and Trucks, Robot steering, Robot breaking, Robot automotive systems, Autonomous functions for vehicles , Collision avoidance, Automated parking, Robot Parking, Robot test driving, Car cameras, Truck follow me systems, Radar based monitoring systems, Lane assist, Adaptive cruise control
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