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Microsoft automates driving license tests

DigitalCIO Bureau by DigitalCIO Bureau
November 6, 2019
in Tech News
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Source: TIMESOFINDIA.COM

Driver license testing is a pressing problem; for instance, a survey by SaveLIFE Foundation in India reports that a whopping 59% of the respondents did not give a test to obtain a driving license.

Microsoft is working with the Regional Transport Office (RTO) of Dehradun to automate driving license tests through its system named HAMS (Harnessing AutoMobiles for Safety). HAMS was originally conceived as a system to monitor drivers and their driving, with the aim of improving road safety. Driver training and testing are the foundations to this goal. Driver license testing is a pressing problem; for instance, a survey by SaveLIFE Foundation in India reports that a whopping 59% of the respondents did not give a test to obtain a driving license.

For driving tests, HAMS has been customized to include capabilities such as precise tracking of the vehicle’s trajectory during designated test manoeuvres, for instance, parallel parking or negotiating a roundabout. This tracking enables HAMS to determine precisely, for instance, whether the driver stopped in the middle of a manoeuvre for longer than is permitted or tried to course correct by rolling forward and backward alternately more times than allowed.n 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. HAMS 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.

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