TECHNOLOGY
There are multiple factors that determine safety and efficiency on the road . With more possibilities for danger and potential delays around every corner , drivers are less able than computers to see all the signs and determine the best course of action . In a heartbeat – or even less than – an advanced driver assistance system ( ADAS ) can save a life or direct a driver along a route that shaves minutes off their travel times .
Making use of an abundance of data , ADAS systems encompass various functions : a lane control mechanism , found in the most recent cars ; emergency braking and pedestrian detection ; and parking assistance . In fact , they ’ re becoming so smart that they can determine when the driver is drowsy or driving under the influence of illegal substances .
However , these systems , especially when combined with the data demands of the future ’ s autonomous vehicles , will require considerable improvements on current networking capabilities . Building networks and ecosystems that can handle the sheer volume of data these systems will generate – thought to be as much as 40TB of data an hour from cameras , radar , and other sensors from driverless cars – will determine the success , the safety , and the experience of autonomous driving , Jordan MacPherson , Director of Product Operations at Park Place Technologies , explained recently to AI Magazine .
“ Investing in resilient , cyber secure and agile cloud computing strategies , that utilise powerful compute and ignite realtime analysis and decision making from edge devices is absolutely crucial ,” he explains . “ It ’ s critical now , not tomorrow . We are already driving partially automated , intelligent cars – but they are about to get smarter .”
ADAS no longer a luxury ADAS was once a luxury provided by the premium segment OEMs but with edge computing and networking solutions becoming more affordable , ADAS has found a new position in the market , according to a report by STL Partners .
Companies like Mobileye , Netradyne & DrivebuddyAI aim to reduce the number of road traffic accidents through deploying AI to the edge to create a safer driving experience . By using radar / lidar / camera sensors on powerful edge compute systems , more frames per second of video can be analysed , with fewer redundancies .
As predicted in a report by Gartner , the benefits of 5G and edge computing could contribute to the greater use of edge applications within the automotive sector .
“ Workloads that are not safetycritical – infotainment and smart traffic management , for example – could start to shift to the edge from onboard or in the cloud . Eventually , 5G connectivity could reduce latency to the point that certain safety-critical functions could begin to be augmented by the edge infrastructure , rather than relying solely on onboard systems .”
112 June 2023