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多准则评价法在运动规划方案选择中的应用。

Multi-Criteria Evaluation for Sorting Motion Planner Alternatives.

机构信息

Department of Engineering Mechanics, KTH Royal Institute of Technology, Teknikringen 8, SE-100 44 Stockholm, Sweden.

Advanced Vehicle Engineering Centre, School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK.

出版信息

Sensors (Basel). 2022 Jul 11;22(14):5177. doi: 10.3390/s22145177.

Abstract

Automated vehicles are expected to push towards the evolution of the mobility environment in the near future by increasing vehicle stability and decreasing commute time and vehicle fuel consumption. One of the main limitations they face is motion sickness (MS), which can put their wide impact at risk, as well as their acceptance by the public. In this direction, this paper presents the application of motion planning in order to minimise motion sickness in automated vehicles. Thus, an optimal control problem is formulated through which we seek the optimum velocity profile for a predefined road path for multiple fixed journey time (JT) solutions. In this way, a Pareto Front will be generated for the conflicting objectives of MS and JT. Despite the importance of optimising both of these, the optimum velocity profile should be selected after taking into consideration additional objectives. Therefore, as the optimal control is focused on the MS minimisation, a sorting algorithm is applied to seek the optimum solution among the pareto alternatives of the fixed time solutions. The aim is that this solution will correspond to the best velocity profile that also ensures the optimum compromise between motion comfort, safety and driving behaviour, energy efficiency, journey time and riding confidence.

摘要

自动驾驶汽车有望在不久的将来通过提高车辆稳定性、减少通勤时间和车辆燃料消耗,推动交通环境的发展。它们面临的主要限制之一是运动病(MS),这可能会危及它们的广泛影响以及公众对它们的接受程度。在这方面,本文提出了运动规划的应用,以最大限度地减少自动驾驶汽车中的运动病。因此,通过寻求最佳速度轮廓为多个固定旅行时间 (JT) 解决方案的预定义道路路径,制定了一个最优控制问题。通过这种方式,将为 MS 和 JT 这两个冲突的目标生成 Pareto 前沿。尽管优化这两个目标都很重要,但在选择最佳速度轮廓时,应考虑其他目标。因此,由于最优控制专注于最小化运动病,因此应用了排序算法来在固定时间解决方案的 Pareto 替代方案中寻找最优解决方案。目的是,该解决方案将对应于最佳速度轮廓,该轮廓还确保运动舒适性、安全性和驾驶行为、能源效率、旅行时间和骑行信心之间的最佳折衷。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd81/9316958/04f20a7a1a4e/sensors-22-05177-g005.jpg

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