Precise prediction of gap acceptance at uncontrolled road sections is important for developing real-time applications such as Advanced Warning and Safety System (AWSS). The paper applies and compares prediction results of three non-parametric models, namely, SVM, Decision tree and Random Forest algorithm.
This work was accepted as a full paper at the 8th International Conference on Ambient Systems, Networks and Technologies (ANT-2017) held in Madeira, Portugal. The publication can be accessed from Sciencedirect using this link.
DT.R: Implementation of Decision tree algorithm
svm.py: Implementation of Support Vector Machine and Ramdom Forest algorithm
roc.py: Plots the ROC curves for all the algorithms
Rakshita