Vehicle Turning Intention Prediction Based on Data-Driven Method with Roadside Radar and Vision Sensor

Jyun Hong He, Yen Lin Chen, Xiu Zhi Chen, Hsin Han Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The trajectory tracking and turning intention prediction of vehicles at intersections are a vital part of smart traffic safety. With the height limitation, traffic objects are often obscured by other vehicles that easily results in blind spots for the visual sensing system. This paper summarizes the author's practice of a roadside unit composed of monitors and radar sensors to track and predict behavioral intentions of traffic objects, and develop a stable system based on the fusion of radar and image sensing information to reduce the danger caused by the steering of other vehicles that are not predicted by the driving sight and the blind angle of the on-board sensor. The roadside unit is installed at the intersection to collect vehicle data on the road, such as position, speed, and direction. An artificial neural network based on LSTM-GAN is used to process data and predict vehicle turning intention. The research case shows that the proposed model has about 91% prediction accuracy.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665433280
DOIs
Publication statusPublished - 2021
Event8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021 - Penghu, Taiwan
Duration: 2021 Sep 152021 Sep 17

Publication series

Name2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021

Conference

Conference8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
Country/TerritoryTaiwan
CityPenghu
Period2021/09/152021/09/17

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Instrumentation

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