learning-barrier-certificates-for-neural-path-tracking-control-of-self-driving-vehicles-extension
Science Score: 26.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
-
○Academic publication links
-
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (6.2%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: ZhizhenQin
- License: mit
- Default Branch: main
- Size: 8.57 MB
Statistics
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Learning Barrier Certificates for Neural Path Tracking Control of Self Driving Vehicles - Extension
An extension of paper Learning Barrier Certificates for Neural Path Tracking Control of Self Driving Vehicles is contained in the PDF file, with the following sections
- Pseudocodes
- Policy Learning
- Learning Low-Dimensional Barriers under Partial Observability
- Estimating Range of Dynamics near Samples
- Finding Boundary Counterexamples for Retraining
- Using the Learned Barrier Function for Safety Monitor
- Hyper-parameters and Details of Experiments
Below we present figures contained in the original and extended paper.
Pseudocodes
Training the Barrier Function
Cerifying the Barrier Function
Dynamic Model Trajectories Illustration
Plotting of trajectories of the dynamic model, with x, y axes as angle and distance errors, and z axis as:
Longitudinal Speed | Lateral Speed | Yaw Rate
:-------------------------:|:------------------------:|:-------------------------:
|
|
Flow Chart of Overall Pipeline
Vehicle Dynamics Models
Kinematic Model | Dynamic Model
:-------------------------:|:------------------------:
|
Barrier Functions
The barrier functions on kinematic model, dynamic model and TORCS environment
Kinematic Model (3D) | Dynamic Model (2D) | TORCS (2D)
:-------------------------:|:------------------------:|:-------------------------:
|
|
Safety Monitor
Backward reachable states for dynamic model, evaluated on a maximum curvature of 0.15, for 50 time steps
Path with Curvature 0.15 (Curve to Left) | Path with Curvature 0.15 (Curve to Right) | Safety Monitor
:-------------------------:|:------------------------:|:-------------------------:
|
|

Importance of Retraining
The barrier function for dynamic model obtained after the initial training and after the final retraining, projected in the dimensions of angle and distance error
Initial Barrier | Final Barrier
:-------------------------:|:------------------------:
|
Vector Fields of Dynamic Model
Close to Collected Trajectories | Whole Certification Grid
:-------------------------:|:------------------------:
|
Barrier Behavior of TORCS Environment
Owner
- Name: Zhizhen Qin
- Login: ZhizhenQin
- Kind: user
- Repositories: 1
- Profile: https://github.com/ZhizhenQin