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논문검색

HMM and HSS Based Social Behavior of Intelligent Vehicles for Freeway Entrance Ramp

초록

영어

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.

목차

Abstract
 1. Introduction
 2. System Structure
 3. Driver Intention Estimation
  3.1. Hidden Markov Models
  3.2. Forward Algorithm
  3.3. Two-dimension HMM
 4. Decision-making Model
 5. Hybrid State System
 6. Simulation Experiments
  6.1. Driving Intention Estimation of Social Vehicle
  6.2. Intelligent Vehicle’s Interaction with Social Vehicles
 7. Conclusions
 Acknowledgements
 References

저자정보

  • Guangming Xiong Intelligent Vehicle Research Center, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, China
  • Yong Li Intelligent Vehicle Research Center, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, China
  • Shiyuan Wang Intelligent Vehicle Research Center, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, China
  • Xiaoyun Li Intelligent Vehicle Research Center, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, China
  • Peng Liu Electrical and Computer Engineering Department, The Ohio-State University, Columbus, OH, USA

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