Abstract
A braking index that incorporates the risk perception of human drivers has been developed to estimate how many drivers would brake in a given situation. We used agent simulations to verify whether incorporating the braking index can improve the efficiency of the agents’ movement in the whole space. The completion time and the number of collisions were measured to compare the simple avoidance algorithm without the braking index and the proposed algorithm with it. While a simple avoidance algorithm showed a strong trade-off between the completion time and the number of collisions, the proposed algorithm resulted in an efficient movement with a shorter time and fewer collisions. More efficient movement could be achieved by incorporating human risk perception because the risk of collision with others was individually evaluated according to others’ position and direction, and only as much avoidance as necessary was performed.
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