SdS - TP5

Files

static.txt

The static file contains the static information for the system, the structure is:

area_width area_height
comfort_radius wall_comfort_radius
pref_speed pref_time max_speed
main_agent_radius main_agent_mass
obstacle_1_radius obstacle_1_mass
.
.
.
obstacle_n_radius obstacle_n_mass

dynamic.txt

The dynamic file contains the initial positions and velocities for all the particles, the structure is:

0
main_agent_x main_agent_y main_agent_vx main_agent_vy
obstacle_1_x obstacle_1_y obstacle_1_vx obstacle_1_vy
.
.
.
obstacle_n_x obstacle_n_y obstacle_n_vx obstacle_n_vy

The contents of each line have spaces in between.

output.txt

The output file contains the positions and velocities for all objects in the simulation. It is the simulation output and the structure is:

0
main_agent_x main_agent_y main_agent_vx main_agent_vy
obstacle_1_x obstacle_1_y obstacle_1_vx obstacle_1_vy
.
.
.
obstacle_n_x obstacle_n_y obstacle_n_vx obstacle_n_vy
time_1
main_agent_x main_agent_y main_agent_vx main_agent_vy
obstacle_1_x obstacle_1_y obstacle_1_vx obstacle_1_vy
.
.
.
obstacle_n_x obstacle_n_y obstacle_n_vx obstacle_n_vy
...
time_m
main_agent_x main_agent_y main_agent_vx main_agent_vy
obstacle_1_x obstacle_1_y obstacle_1_vx obstacle_1_vy
.
.
.
obstacle_n_x obstacle_n_y obstacle_n_vx obstacle_n_vy

Generation

To generate dynamic input, a python script is used:

python3 generator/generate_configuration.py -W 18 -H 9 -p 10 -pr 0.5 -pv 1.3 -cr 0.9 -r 0.5 -bl 2 -m 70 -wr 0.6 -ps 1.3 -pt 0.5 -ms 2 -at 4

This will generate an area of 14x7 (width x height) with 10 people obstacles of 0.15m radius with Y velocity of 3. Agents are generated in columns with a 1m of offset from the borders. The comfort radius for the main person is 0.5m and it's radius 0.2m.

Simulation

To run the simulation run:

java -jar ./target/sds-tp5-1.0-jar-with-dependencies.jar -sf ./parsable_files/static.txt -df ./parsable_files/dynamic.txt -dt 0.001 -dt2 0.01

Statistics

To run save the results of the run to stats.txt:

python3 post/postprocessing.py -s

To get the mean and standard deviation graphs for time travelled, distance travelled and mean velocity respectively:

python3 post/postprocessing.py -p pt
python3 post/postprocessing.py -p pd
python3 post/postprocessing.py -p pv
python3 post/postprocessing.py -p pc

The

Visualization

To postprocess for visualization run:

python3 ./visualization/process.py

Useful Links

• Paper por Predictive Collision Avoidance
• Site for Predictive Collision Avoidance papers