Algorithm for Predicting the Trajectory of Road Users to Automate Control of an Autonomous Vehicle

Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2 Pub Date : 2020-12-17 DOI:10.51130/graphicon-2020-2-4-53

A. Azarchenkov, M. Lyubimov

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引用次数: 1

Abstract

One of the problems faced by developers of artificial intelligence algorithms when creating car control systems is that the actions of other road users are difficult to predict and have a large variability. Even if we assume that all actions comply with traffic rules and participants do not make mistakes, that is, to bring the actual environment closer to the ideal, the task of automating vehicle control still contains many difficulties. This paper describes what difficulties exist in the field of predicting the trajectory of objects, shows concepts that will help in solving this problem, and also describes a particular method of forecasting, which allows you to make a forecast for cars moving along traffic lanes. The main forecasting stages and the results of testing the method collected by using a ready-made data set are given. The results presented in the form of a set of metrics, are compared with another algorithm for predicting trajectories. As a result, the advantages and disadvantages of the created solution were identified.

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预测道路使用者轨迹的自动驾驶汽车自动控制算法

人工智能算法的开发人员在创建汽车控制系统时面临的一个问题是，其他道路使用者的行为难以预测，并且具有很大的可变性。即使我们假设所有的行为都符合交通规则，参与者不犯错，即使实际环境更接近理想，车辆自动控制的任务仍然包含许多困难。本文描述了预测物体轨迹领域存在的困难，展示了有助于解决这一问题的概念，并描述了一种特殊的预测方法，该方法允许您对沿交通车道行驶的汽车进行预测。给出了预测的主要阶段和利用已有数据集对方法进行测试的结果。结果以一组度量的形式呈现，并与另一种预测轨迹的算法进行了比较。因此，确定了所创建的解决方案的优点和缺点。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2

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