In this article, we present a motion-planning framework that leverages expert bus driver behavior, increasing the safety and maneuverability of autonomous buses. Autonomous vehicles will increase the safety, quality, and efficiency of transportation systems. However, to deploy this technology in urban public transport, many challenges related to self-driving buses still need to be addressed. Unlike passenger cars, buses have long and wide dimensions and a distinct chassis configuration, which significantly challenges their maneuverability. To deal with their special dimensions, we introduce a novel optimization objective that centers their whole body as they travel along a road. Furthermore, we present new environment classification schemes that enable self-driving buses to take advantage of their distinct chassis configuration, namely, the elevated overhangs, to increase maneuverability. Finally, we offer a novel collision checking method that explicitly considers a bus's front wheels and how they can protrude from beneath the chassis when maneuvering near stops. We demonstrate the benefits of our framework through experiments using an autonomous bus in real road scenarios.

中文翻译：

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公交车自动驾驶：一种新颖的运动规划方法


在本文中，我们提出了一个运动规划框架，该框架利用专家公交车司机的行为，提高自动驾驶公交车的安全性和可操作性。自动驾驶汽车将提高交通系统的安全性、质量和效率。然而，要将这项技术部署到城市公共交通中，仍需要解决与自动驾驶公交车相关的许多挑战。与乘用车不同，客车具有长而宽的尺寸和独特的底盘配置，这对它们的机动性提出了很大的挑战。为了处理它们的特殊尺寸，我们引入了一种新颖的优化目标，当它们沿着道路行驶时，该目标将它们的整个身体集中在中心。此外，我们提出了新的环境分类方案，使自动驾驶公交车能够利用其独特的底盘配置（即高悬垂）来提高机动性。最后，我们提供了一种新颖的碰撞检查方法，该方法明确考虑了公共汽车的前轮以及它们在停靠站附近行驶时如何从底盘下方突出。我们通过在真实道路场景中使用自动驾驶巴士进行实验来展示我们框架的优势。