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Rolling horizon state estimator

A technology of state estimation and rolling time domain, applied in the direction of dynamic tree, time register, dynamic search technology, etc., can solve the problems of limited data volume and high cost

Pending Publication Date: 2022-03-01
MITSUBISHI ELECTRIC CORP
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this approach requires the high cost of transmitting and processing all the data, and constraints on communication bandwidth and computing power can limit the amount of data

Method used

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  • Rolling horizon state estimator
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Embodiment Construction

[0056] System Overview

[0057] Figure 1A and Figure 1BA block diagram of a receding horizon state estimator 100 for estimating the state of a vehicle 101 based on a prediction horizon is shown according to some embodiments. The rolling time-domain state estimator borrows some principles from the model predictive controller (MPC), and while satisfying the constraints on the state estimation accuracy of each time step in the prediction time domain, the iterative finite prediction time-domain optimization based on the cost function is used to A subset of external sensors is selected at each time step, with a cost function describing the total communication cost of obtaining external measurements over the forecast time domain. In this way, the rolling temporal state estimator is able to predict future events when selecting a subset of external sensors for each time step to ensure consistent constraint satisfaction while reducing the communication cost of external measurements....

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Abstract

A rolling horizon state estimator that estimates the state of a vehicle, thereby reducing the overall communication cost of acquiring external measurements over a predicted horizon, where the state estimation accuracy of a time step is a function of the state estimation accuracy of a previous time step. For each time step of the predictive time domain, the estimator selects a subset of external sensors having a precision estimation state sufficient to meet constraints on the state estimation precision of the corresponding time step, while reducing the total communication cost for acquiring external measurements over the predictive time domain. The estimator requests external measurements from the subset of external sensors determined for the current time step, and estimates a state of the vehicle using the internal measurements and the requested external measurements.

Description

technical field [0001] The present invention relates generally to automated driving and advanced driver assistance systems, and more particularly to the constrained estimation of vehicle states subject to the communication costs of acquiring measurements. Background technique [0002] Reliable state estimation of vehicles is a critical part of autonomous driving and advanced driver assistance systems (ADAS). For example, one component in autonomous vehicles and ADAS is the motion planner, which acquires information about the surrounding environment and computes a trajectory profile to (usually in the presence of moving obstacles) from the current Position Navigate towards the target position. As another example, ADAS such as lane changing systems require precise information about where a vehicle is located relative to other vehicles at the current time and at some time in the future. [0003] To this end, modern vehicles sometimes employ various sensors for estimating or m...

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Application Information

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IPC IPC(8): B60W60/00G01S13/86G01S13/931G06N5/00
CPCB60W60/00G01S13/86G01S13/931B60W2050/065B60W2420/54B60W2556/35G06N5/01B60W2420/408B60W2420/403G05D1/0088B60W2554/801B60W40/00B60W50/0097G06F17/11G06F17/17G07C5/0808
Inventor 安希振C·丹尼尔森
Owner MITSUBISHI ELECTRIC CORP