A maximum likelihood method for driver-specific critical-gap estimation.
Dennis OrthDorothea KolossaMilton Sarria PajaKersten SchallerAndreas PechMartin HeckmannPublished in: Intelligent Vehicles Symposium (2017)
Keyphrases
- maximum likelihood
- clustering method
- high accuracy
- detection method
- parameter estimation
- significant improvement
- experimental evaluation
- computer vision
- monte carlo simulation
- segmentation method
- cost function
- preprocessing
- neural network
- classification accuracy
- pairwise
- detection algorithm
- computational complexity
- objective function
- synthetic data
- feature selection
- high precision
- density estimation
- estimation algorithm
- maximum likelihood estimation
- estimation accuracy