Are There Any Loopholes in the Electronic Monitoring of Subject Three?
2 Answers
No. Below is a detailed introduction to the relevant information: Introduction: The road driving skills test for Subject Three generally includes: vehicle preparation, simulated lighting test, starting, driving in a straight line, gear shifting operations, changing lanes, parking by the roadside, going straight through intersections, turning left at intersections, turning right at intersections, crossing pedestrian crossings, passing school zones, passing bus stops, meeting oncoming vehicles, overtaking, making U-turns, and nighttime driving. Notes: Candidates must complete the corresponding lighting operations according to the voice prompts. It is essential to be very familiar with these operations and not make any mistakes. Answering one question incorrectly will deduct 100 points, wasting a precious exam opportunity! Therefore, familiarizing yourself with the lighting operations before the exam will basically prevent you from failing on this aspect.
From a technical perspective, let me discuss the vulnerabilities in electronic proctoring systems. These systems monitor the examination process using cameras, GPS, and sensors, which are theoretically advanced but practically flawed. For instance, sensors can malfunction due to environmental interference, such as rain blurring the camera lens, leading to incorrect judgments of a candidate’s turning maneuvers. GPS positioning may also drift, marking safe operations as errors. Additionally, the software algorithms are imperfect, especially when handling sudden road scenarios—like a vehicle cutting in—where the system might miss critical details. These issues stem from insufficient early-stage technology investment and inadequate testing. Although improvements have been made in recent years, including AI-assisted reviews, vulnerabilities still occur. To truly resolve these, continuous hardware upgrades and enhanced data training are necessary to ensure more accurate scoring. In summary, vulnerabilities are inherent, but iterative optimization can mitigate risks—absolute fairness cannot be guaranteed by the system alone.
