This information can be used to activate the appropriate response through the Road Incident Management System, remedy the situation and inform road users — in real time.
“One can also look at how these different objects interact with one another, for example to detect unusual vehicle behaviour, like a vehicle stopping on the freeway.
“If a vehicle is detected moving to the side of the road and coming to a standstill and pedestrians are detected moving towards the vehicle and enter the vehicle, this can be classified as an informal pickup. As more and more data is collected, these trends can either aid road authorities with infrastructure planning such as drop-off/pickup points or aid law enforcement to stop illegal pickups if it is considered a safety risk.”
Sanral's TIH-acknowledged technology of this nature comes with significant risks. “However, all efforts are being made to understand how to effectively use the technology while maintaining strict compliance with legislation as it relates to the privacy of road users,” he said.
Some of the ways to mitigate these potential privacy risks, he said, are to use strict security and access controls.
“The intention is not to observe individuals, but rather to identify trends and incidents to inform appropriate response and interventions.”
Van Breda said while this technology is still in the exploratory phase in SA, countries like China use machine learning to incorporate facial recognition for law enforcement. They are able to identify the driver of a vehicle and instantly issue fines, if that driver does not have a valid driver’s licence, he said.
TimesLIVE
Facial recognition tech, data learning for road safety being studied by Sanral hub
Image: Thapelo Morebudi / Sunday Times
Sanral says its technical innovation hub (TIH) is probing the extent to which machine learning can be harnessed in the quest to improve road safety, reduce congestion and inform infrastructure development.
Ruan van Breda, mechatronic engineer at TIH, said: “Machine learning can be used to detect and segment objects within a camera frame (each frame of a video is analysed as a still image). These objects can then be classified based on pre-trained image classifiers.
“Within the road environment, this allows one to detect and classify different type of vehicles, pedestrians, different types of animals, cyclists, etc.”
Currently there is already ample data available for these classification types. However, Van Breda said these genres can be further expanded through the creation of custom data sets and training classifiers, to be able to distinguish, for example, between slow moving traffic and a road traffic crash.
This can also be used to create new classification classes based on unique experiences, or the requirements of the road authority such as fire or protest detection, and foreign objects such as rocks.
Decision on the fate of e-tolls cannot be delayed again, says AA
This information can be used to activate the appropriate response through the Road Incident Management System, remedy the situation and inform road users — in real time.
“One can also look at how these different objects interact with one another, for example to detect unusual vehicle behaviour, like a vehicle stopping on the freeway.
“If a vehicle is detected moving to the side of the road and coming to a standstill and pedestrians are detected moving towards the vehicle and enter the vehicle, this can be classified as an informal pickup. As more and more data is collected, these trends can either aid road authorities with infrastructure planning such as drop-off/pickup points or aid law enforcement to stop illegal pickups if it is considered a safety risk.”
Sanral's TIH-acknowledged technology of this nature comes with significant risks. “However, all efforts are being made to understand how to effectively use the technology while maintaining strict compliance with legislation as it relates to the privacy of road users,” he said.
Some of the ways to mitigate these potential privacy risks, he said, are to use strict security and access controls.
“The intention is not to observe individuals, but rather to identify trends and incidents to inform appropriate response and interventions.”
Van Breda said while this technology is still in the exploratory phase in SA, countries like China use machine learning to incorporate facial recognition for law enforcement. They are able to identify the driver of a vehicle and instantly issue fines, if that driver does not have a valid driver’s licence, he said.
TimesLIVE
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