HMM and HSS Based Social Behavior of Intelligent Vehicles for Freeway Entrance Ramp
Author(s) -
Guangming Xiong,
Yong Li,
Shiyuan Wang,
Xiaoyun Li,
Peng Liu
Publication year - 2014
Publication title -
international journal of control and automation
Language(s) - English
Resource type - Journals
eISSN - 2207-6387
pISSN - 2005-4297
DOI - 10.14257/ijca.2014.7.10.08
Subject(s) - computer science , hidden markov model , automotive engineering , transport engineering , engineering , speech recognition
In this paper, a novel approach of intelligent vehicle to interact and cooperate with other human driving vehicles is proposed at the freeway entrance ramp scenario. The system consists of a Safety Alert Module and Vehicle Control Module. The Safety Alert System module includes intention estimation and conflict judgment. A two dimension Hidden Markov Model (2DHMM) is used to estimate social vehicle’s driving intention in the intention estimation module. Then the conflict judgment module predicts the potential conflicts between the intelligent vehicle and social vehicle. Moreover, the hybrid state system (HSS) is introduced to control the intelligent vehicle while considering its decision making, states and dynamics. Co-simulation using PreScan and Simulink is conducted. The experiment results show that the intelligent vehicle performs well with a commendable social behavior in the freeway entrance ramp.
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