In order to improve the efficiency of safety performance test for intelligent
vehicles and construct the test case set quickly, critical scenarios based on
graded hazard disposal model of human drivers are proposed, which can be used
for extraction of test cases for safety performance. Based on the natural
driving data in China Field Operational Test (China-FOT), the four-stage
collision avoidance process of human drivers is obtained, including steady
driving stage, risk judgment stage, collision reaction stage and collision
avoidance stage. And there are two human driver states: general state and alert
state. Then the graded hazard disposal model of human drivers is constructed.
According to the parameter distribution of natural driving data, the risk
perception point, risk response point and collision reaction time of
deceleration scenario and cut-in scenario are obtained, and the deceleration
gradient and the maximum deceleration of each collision avoidance difficulty
level are determined. For deceleration scenario and cut-in scenario, the
parameter range is determined to generalize logical scenarios. Then based on the
graded hazard disposal model of human drivers, the critical scenarios at the
preventable and unpreventable boundaries are obtained through simulation
calculation. As the concrete scenarios with high value for safety extracted from
the massive logical scenarios, the critical scenarios are used to construct the
test case set in the safety performance test for intelligent vehicles. For
deceleration scenario, 507 critical scenarios are obtained from 10,000 logical
scenarios, which increases the test efficiency by 19.72 times. For cut-in
scenario, 5,121 critical scenarios are obtained from 270,000 logical scenarios,
which increases the test efficiency by 52.72 times.