Estimation of driver awareness of pedestrian based on Hidden Markov Model

Minh Tien Phan (1) , Vincent Frémont (1, 2) , Indira Thouvenin (1, 2) , Mohamed Sallak (1, 2) , Véronique Cherfaoui (1, 2)

1 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]
2 Labex MS2T - Laboratoire d'Excellence "Maîtrise des Systèmes de Systèmes Technologiques"

Understanding driver behaviors is an important need for the Advanced Driver Assistance Systems. In particular, the pedestrian detection systems become extremely distracting and annoying when they inform the driver with unnecessary warning messages. In this paper, we propose to study the driver behaviors whenever a pedestrian appears in front of the vehicle. A method based on the driving actions and the Hidden Markov Model (HMM) algorithm is developed to classify the driver awareness of pedestrian and the driver unawareness of pedestrian. The method is successfully validated using the collected data from the experiments that are conducted on a driving simulator. Furthermore, two simple methods based on the static parameters such as the Time-To-Collision and the Required Deceleration Parameter are also applied to our problem and are compared to the proposed method. The result shows a significant improvement of the HMM-based method compared to the simple ones.

Mots clés: Hidden Markov Model; Index Terms—Driver Behaviors; Pedestrian Safety; Situation Awareness; Driving Simulation

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]; Robotique [cs.RO]

Minh Tien Phan, Vincent Frémont, Indira Thouvenin, Mohamed Sallak, Véronique Cherfaoui. Estimation of driver awareness of pedestrian based on Hidden Markov Model. IEEE Intelligent Vehicles Symposium (IV 2015), Jun 2015, Seoul, South Korea. pp.970-975, ⟨10.1109/IVS.2015.7225810⟩. ⟨hal-01260394⟩