A Microsoft Research AI project is automating driver's license tests
Road safety has become a key issue in a country like India and a key factor in addressing this is changing how driver's licences are issued. In a move to solve this problem, Microsoft Research has launched a project, which automates driver’s license tests.
Called HAMS or Harnessing AutoMobiles for Safety, this Microsoft Research AI project is currently enabling the Regional Transport Office in Dehradun, Uttarakhand to use smartphone-based technology to automate driver’s license testing.
According to a statement by Microsoft Research, driver license testing is a pressing problem.
For instance, a survey by SaveLIFE Foundation in India reports that a whopping 59 percent of respondents did not give a test to obtain a driving license. The challenges with this system range from the subjectivity of each evaluator to the burden of evaluation falling solely on human shoulders.
Microsoft Research’s HAMS project enables the driver’s license testing to be an objective and transparent process that helps grant licenses to well-tested drivers.
“The main challenge in the traditional driver’s license test is the burden placed on the human evaluators and the resulting subjectivity that a candidate faces. Automation using HAMS technology can not only help relieve evaluators of the burden but also make the process objective and transparent for candidates,” says Venkat Padmanabhan, Deputy Managing Director, Microsoft Research India, who started the HAMS project in 2016.
One such partnership with the Institute of Driving and Traffic Research (IDTR), a joint venture between the Department of Transport of State Governments and Maruti Suzuki India Limited, India’s largest passenger car manufacturer, resulted in the implementation of HAMS as a smartphone-based driving test system for issuing driver’s licenses.
HAMS, in its general incarnation, uses the smartphone’s front and rear cameras, and other sensors, to monitor the driver (for instance, their gaze) and the road scene in front (for instance, the distance to the vehicle in front), simultaneously.
It employs advanced Artificial Intelligence (AI) models, which the team has developed for efficient and robust operation.
For driving tests, HAMS has been customised to include capabilities such as precise tracking of the vehicle’s trajectory during designated test manoeuvres, for instance, parallel parking or negotiating a roundabout.
(Edited by Saheli Sen Gupta)
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