Pedestrian Kernel Density Estimates: The Individual Approach

The pedestrian density evaluation problem can be generally perceived as a sampling exercise. Assuming a density distribution inside the analysed area is already generated, the task its to generate a number characterizing the state of an area (detector estimates) or the surroundings of a pedestrian (individual approach). Application of individual density may be crucial e.g. to calibrate any microscopic model or to measure any interaction between pedestrians. Thus, this contribution deals with the individual concept using a conic kernel to generate the density distribution ensuring a pedestrian blurring with great performance. Then the density in pedestrian surroundings of an arbitrary shape with a specific range for a specific pedestrian is defined using kernel distributions. The influence of the shape of pedestrian surroundings and its size described by parameter r are presented suing quantitative metrics. The following type of surroundings (using a different r) are examined: circle (radius); ellipse (length of semi-axes) and sector (radius, angle) which are rotated in accordance with a direction of a pedestrian movement.