The technology industry continues to be a hotbed of innovation, with activity driven by the progress in robotics technology, characterised by enhancements in sensors, machine learning, artificial intelligence AI), and creation of robots with superior capabilities and versatility, and growing importance of technologies such as AI-assisted safety and control systems, sensors and detectors, traffic management software, and automated traffic signal control. Emerging technologies such as connected and autonomous vehicles (CAVs) are expected to shape the future of traffic management. In the last three years alone, there have been over 3.6 million patents filed and granted in the technology industry, according to GlobalData’s report on Innovation in Robotics: Autonomous traffic control system. Buy the report here.
However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilising and reaching maturity.
Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have.
300+ innovations will shape the technology industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the technology industry using innovation intensity models built on over 2.5 million patents, there are 300+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, AI-assisted inspection, anti-collision LiDAR, and 3d object sensing are disruptive technologies that are in the early stages of application and should be tracked closely. Autonomous harvesters, cleaning robots, and line follower robots are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas, welding robot and robotic vision are now well established in the industry.
Innovation S-curve for robotics in the technology industry
Autonomous traffic control system is a key innovation area in robotics
An autonomous traffic control system is a technologically advanced system that employs sensors, cameras, and other cutting-edge technologies to observe and regulate traffic movements. Its purpose is to alleviate congestion, enhance travel efficiency, and bolster driver safety by automatically adapting traffic signals, lane allocations, and related variables. Additionally, the system can be leveraged for providing real-time guidance for public transportation and managing incidents on the road.
GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 60+ companies, spanning technology vendors, established technology companies, and up-and-coming start-ups engaged in the development and application of autonomous traffic control system.
Key players in autonomous traffic control system – a disruptive innovation in the technology industry
‘Application diversity’ measures the number of different applications identified for each relevant patent and broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of different countries each relevant patent is registered in and reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Patent volumes related to autonomous traffic control system
Source: GlobalData Patent Analytics
Intel is one of the leading patent filers in autonomous traffic control system. The company’s patents are aimed at systems and methods for detecting and responding to cut in vehicles, and for navigating while taking into consideration an altruistic behaviour parameter.
In one implementation, a navigation system for a host vehicle may include a data interface and at least one processing device. At least one processing device may be programmed to receive, via the data interface, a plurality of images from at least one image capture device associated with the host vehicle.
It can also identify at least one target vehicle in an environment of the host vehicle, determine one or more situational characteristics associated with the target vehicle, determine a current value associated with an altruistic behaviour parameter, based on analysis of the plurality of images.
Autonomous traffic control system can improve traffic safety and efficiency, reduce environmental impact, integrate with public transportation, enable effective incident management, adapt to evolving needs, and contribute to the development of smart and sustainable cities. To further understand how robotics is disrupting the technology industry, access GlobalData’s latest thematic research report on Robotics – Thematic Research Report.