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A Personalized Adaptive Trajectory Prediction Method Based on Driving Style and Intention

A driving style and trajectory prediction technology, applied in the field of intelligent transportation, can solve the problems of not being able to obtain or perceive driving data in time, and achieve the effect of assisting driving, guaranteeing prediction accuracy, and expanding the application field

Active Publication Date: 2022-04-12
YANGTZE DELTA REGION INST (QUZHOU) UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0006] Finally, in the dense vehicle communication network based on 5G (5th Generation Mobile Communication Technology, 5G) vehicle-to-vehicle (V2V) communication technology, due to factors such as urban obstacles, extreme weather, and frequency reuse The impact will make the self-driving vehicle may not be able to obtain or perceive all the driving data of the surrounding vehicles in a timely manner within the specified time

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  • A Personalized Adaptive Trajectory Prediction Method Based on Driving Style and Intention
  • A Personalized Adaptive Trajectory Prediction Method Based on Driving Style and Intention
  • A Personalized Adaptive Trajectory Prediction Method Based on Driving Style and Intention

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Embodiment Construction

[0042] Such as figure 1 As shown, in the future urban intelligent transportation system, the roadside unit (Road Side Unit, RSU) and the vehicle-mounted unit (On Board Unit, OBU) equipped with 5G Vehicle to Everything (V2X) technology jointly build a vehicle-road network collaboration System, through the 5G-V2X communication protocol to realize the direct communication between V2V and Vehicle to RSU (V2R). At the same time, RSU can also send query requests (RSU to CN, R2C) to remote servers through the core network (Core Network, CN). Combined with road test perception and on-board perception, a variety of sensors jointly complete the collection of traffic information such as vehicles, roads, and the environment, enabling intelligent coordination and cooperation between vehicles and infrastructure, while coping with severe weather, co-frequency interference, etc. Realize safe and reliable automatic driving with vehicle-road coordination.

[0043] Assuming that the total numb...

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Abstract

The invention discloses a personalized adaptive trajectory prediction method based on driving style and intention, which includes the following steps: S1, classify driving style; S2, identify driving intention: divide into nine driving intentions in three dimensions, They are deceleration left lane change, uniform speed left lane change, acceleration left lane change, deceleration straight, uniform speed straight, acceleration straight, deceleration right lane change, uniform speed right lane change and acceleration right lane change; S3, missing data filling: using LSTM network to estimate the missing data; S4, trajectory prediction: use LSTM for trajectory prediction. The present invention considers the personalized driving behaviors of different drivers by judging the driving style and identifying the driving intention, and realizes the prediction accuracy guarantee in the case of incomplete data through the method of missing data estimation and prediction, thereby realizing personalized self-adaptive Trajectory prediction, improving the accuracy of trajectory prediction and improving the safety of autonomous vehicles.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation, in particular to a personalized adaptive trajectory prediction method based on driving style and intention. Background technique [0002] In recent years, global positioning technology has developed rapidly and has been widely used in intelligent transportation systems. At the same time, the prediction of the future trajectory of surrounding vehicles in advanced driver assistance systems is one of the key directions of current research. Because in actual road driving, autonomous vehicles will inevitably have frequent interactions with other traffic participants, so the driving strategy planning of autonomous vehicles has a close relationship with the driving behavior of surrounding vehicles. In order to ensure safe driving in a dynamically changing traffic environment, autonomous vehicles need to have the ability to predict the evolution of future traffic conditions, especiall...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B60W60/00B60W40/09B60W50/00
CPCB60W60/0027B60W40/09B60W50/00B60W2050/0029B60W2050/0019
Inventor 韦云凯张陈瑜马立香冷甦鹏杨鲲刘强沈军
Owner YANGTZE DELTA REGION INST (QUZHOU) UNIV OF ELECTRONIC SCI & TECH OF CHINA