Duckietown Challenges Home Challenges Submissions

Challenge "mooc-visservoing"

Challenge description

This is the challenge to test the Visual Lane Servoing of the MOOC’s robot vision exercise.

For more information about the “Self-Driving Cars with Duckietown” MOOC, visit duckietown.org.

Leaderboard

Submissions

Challenge logistics

Scoring

Scoring criteria

These are the metrics defined:

Major infractions - in-drivable-lane_median

This is the median of the time spent outside of the drivable zones. For example this penalizes driving in the wrong lane.

Lateral deviation - deviation-center-line_median

This is the median lateral deviation from the center line.

Traveled distance - driven_lanedir_consec_median

This is the median distance traveled, along a lane. (That is, going in circles will not make this metric increase.)

This is discretized to tiles.

Survival time - survival_time_median

This is the median survival time. The simulation is terminated when the car goes outside of the road or it crashes with an obstacle or pedestrian.

Dependencies

Dependencies

No dependencies

Details

Technical details

Evaluation steps details

Evaluation step sim

Timeout 10000.0

This is the Docker Compose configuration skeleton:

version: '3'
services:
    evaluator:
        image: docker.io/andreacensi/duckietown-challenges@sha256:755fdf643d60b0e94770382182e3e152f952529298058ee987511343c950ec36
        environment:
            experiment_manager_parameters: 'episodes_per_scenario: 3

                episode_length_s: 60.0

                min_episode_length_s: 0.0

                seed: 20200922

                physics_dt: 0.05

                max_failures: 2

                fifo_dir: /fifos

                sim_in: /fifos/simulator-in

                sim_out: /fifos/simulator-out

                sm_in: /fifos/scenario_maker-in

                sm_out: /fifos/scenario_maker-out

                timeout_initialization: 120

                timeout_regular: 120

                port: 10123

                scenarios:

                - /scenarios

                '
        ports:
        - '10123'
    simulator:
        image: docker.io/andreacensi/duckietown-challenges@sha256:f6e97655c6dbe5966e76cbba2afb40fb8b138b1c95181b8e862852ae64b20356
        environment:
            AIDONODE_CONFIG: "env_constructor: Simulator\nenv_parameters:\n  max_steps:\
                \ 500001 # we don't want the gym to reset itself\n  domain_rand: 0\n\
                \  camera_width: 640\n  camera_height: 480\n  distortion: true\n \
                \ num_tris_distractors: 0\n  #color_ground: [0, 0, 0] # black\n  #color_sky:\
                \ [0, 0, 0.1] # dark blue\n  enable_leds: true\n\nterminate_on_ool:\
                \ false\nterminate_on_out_of_tile: true\nterminate_on_collision: true\n\
                topdown_resolution: 900\nmax_pixel_mov: 1000\ndebug_profile: False\n\
                debug_profile_summary: True\n"
            AIDONODE_DATA_IN: /fifos/simulator-in
            AIDONODE_DATA_OUT: fifo:/fifos/simulator-out
    solution-ego0:
        image: SUBMISSION_CONTAINER
        environment:
            AIDONODE_NAME: ego0
            AIDONODE_DATA_IN: /fifos/ego0-in
            AIDONODE_DATA_OUT: fifo:/fifos/ego0-out

The text SUBMISSION_CONTAINER will be replaced with the user containter.

Resources required for evaluating this step

Cloud simulations1