Driving Style Recognition Using Interval Type-2 Fuzzy Inference System and Multiple Experts Decision Making

Created by Iago Pachêco Gomes at USP - ICMC, University of São Paulo - Institute of Mathematics and Computer Science

(waiting for the result of the submission to Expert Systems with Applications)

Introduction

T2FIS Driving Style is an implementation of a Driving Style Recognition using Interval Type-2 Fuzzy Inference System [1]. This repository has the codes to extract the data sequences from Argoverse's trajectory prediction dataset; the codes to calculate the features vectors; the implementation of clustering algorithms (Kmeans, Fuzzy C-means, Gaussian Mixture Models Clusteris, and Agglomerative Hierarchical Clustering) used to compare the results; and, the implementations of Type-1 and Type-2 Fuzzy Inference Systems.

License

Apache License 2.0

Citation

Usage

Requirements

• Python 3.8
• skfuzzy 0.2 (https://pythonhosted.org/scikit-fuzzy/)
• scikit-learn 0.23.2 (https://scikit-learn.org/stable/)
• PyIT2FLS 0.6.1 (https://haghrah.github.io/PyIT2FLS/examples.html)
• Argoverse API (https://github.com/argoai/argoverse-api)

Features

Dataset

1. Follow the instructions to install the Argoverse dataset API at: https://github.com/argoai/argoverse-api
2. Download training and validation datasets for Motion Forecasting v1.1

Sequences Extraction

1. at features/argoverse_template:

python extract_sequences.py --data_dir 
   
     --features_dir 
    
      --mode 
     
       --batch_size 500 --obs_len 5 --filter 
      

      
     
    
   

2. at features:

python compute_features.py --data_dir 
   
     --features_fir 
    
      --mode 
     
       --batch_size 100 --obs_len 5 --filter 
      

      
     
    
   

Clustering

Fuzzy Inference Systems

References

[1] (under revision) GOMES, Iago Pachêco; WOLF, Denis Fernando. Driving Style Recognition Using Interval Type-2 Fuzzy Inference System and Multiple Experts Decision Making. Expert Systems with Applications. 2021.

Contact

If you find any bug or issue of the software, please contact 'iagogomes at usp dot br' or 'iago.pg00 at gmail dot com'