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README.md
README.md
 
 
evaluate_defix.py
evaluate_defix.py
 
 
requirements.txt
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run_evaluation.sh
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README.md

DeFIX

Detecting and Fixing Failure Scenarios with Reinforcement Learning in Imitation Learning Based Autonomous Driving

List of CARLA Scenarios

Scenario ID Scenario Name
0 Dynamic Vehicle Collision
1 Emerging Pedestrian Collision
2 Stuck Vehicle & Static Objects
3 Vehicle Running Red Light
4 Crossing Signalized Traffic Intersections
5 Crossing Un-signalized Intersections

Provision Steps

  • move 'resnet50' file to directory: <DeFIX_PATH/checkpoint/models/>
  • specify which RL agents to evaluate in <DeFIX_PATH/defix/evaluate.py> script
  • imitation learning models should be inside "DeFIX_PATH/checkpoint/models/imitation/" folder
  • all reinforcement learning models should be inside "DeFIX_PATH/checkpoint/models/reinforcement/" folder
  • policy classifier model should be inside "DeFIX_PATH/checkpoint/models/policy_classifier/" folder

Prepare Necessary Directory Exports to Bashrc

gedit ~/.bashrc

export DeFIX_PATH=PATH_TO_MAIN_DeFIX_REPO
export CARLA_ROOT=PATH_TO_CARLA_ROOT_SH

export SCENARIO_RUNNER_ROOT="${DeFIX_PATH}/scenario_runner"
export LEADERBOARD_ROOT="${DeFIX_PATH}/leaderboard"
export PYTHONPATH="${CARLA_ROOT}/PythonAPI/carla/":"${SCENARIO_RUNNER_ROOT}":"${LEADERBOARD_ROOT}":"${CARLA_ROOT}/PythonAPI/carla/dist/carla-0.9.10-py3.7-linux-x86_64.egg":${PYTHONPATH}

source ~/.bashrc

Run Carla Server on GPU

cd $CARLA_ROOT
./CarlaUE4.sh -prefernvidia

Run Evaluation of DeFIX Methodology

cd $DeFIX_PATH/defix
. run_evaluation.sh