Leading Autonomous Transportation Toward Winter Conditions

自动驾驶汽车正在进入加拿大，为它们安全融入社会所做的准备必须与它们预计将造成的破坏程度相当。近年来，智能交通系统的进步以惊人的速度发展。更好的传感器和更强的计算能力推动了这些技术飞跃。这种颠覆性的创新为更多的加拿大公司打开了新的运输市场的大门，但同时也迫使政策制定者进入未知的领域。虽然许多公司声称已经开发出了高度自主的车辆，但人们对这种系统在恶劣气象条件下的安全性仍然存在疑问。该研究计划解决了与自主移动的系统相关的挑战，例如自主汽车，与现实世界环境的复杂性有关。考虑到复杂环境的不确定性方面，为导航算法开辟了新的视角。在今后五年中，将特别注意在与严酷的冬季条件有关的具有挑战性的环境中的航行，这一问题尚未得到充分考虑。这项研究计划的新奇在于使用配备激光器（光探测和测距，或激光雷达）的各种自主移动的系统在现场进行的广泛实验。定位和地图绘制的突破性进展有望推动自主移动的系统何时何地可以有效安全地使用的界限。该计划进一步分为四个具体目标：（1）将鲁棒优化理论集成到传统的基于激光雷达的配准算法中;（2）改进基于激光雷达的配准算法的不确定性估计;（3）设计更好的算法来维护复杂、动态和非结构化环境中的3D地图;（4）设计更好的算法来维护复杂、动态和非结构化环境中的3D地图。（4）实现车辆在多个季节和恶劣气象条件下自动驾驶的长期实验。考虑到目前对自动驾驶汽车的兴奋，该计划背后的研究具有重要意义。一方面，该计划的成果将通过为复杂的3D环境中的自主导航提供创新解决方案，促进移动的机器人技术的研究。另一方面，他们将通过提供有关冬季条件下自主移动的系统安全性的投入，在向新交通解决方案过渡的关键时期支持工业和政治利益相关者。这项研究的结果还将对汽车以外的不同行业产生涟漪反应，例如采矿，林业和农业，这些行业需要在恶劣条件下使用本地化车辆，以及依赖于精确定位特效的娱乐行业。

Autonomous cars are coming to Canada and preparing for their safe integration into society must be on a par with the level of disruption they are expected to cause. In recent years, advancements in intelligent transportation systems have progressed at a tremendous speed. Those technological leaps were pushed forward by better sensors and increased computation power. This disruptive innovation opens the door to a new transportation market accessible to more Canadian companies but, at the same time, forces policymakers into unknown territories. Although many companies claim to have developed vehicles with high levels of autonomy, doubts remain regarding the safety of such systems in difficult meteorological conditions.This research program addresses challenges related to autonomous mobile systems, such as autonomous cars, in relation to the complexity of real-world environments. Considering the uncertainty aspects of complex environments opens new perspectives on navigation algorithms. During the next five years, special attention will be paid to navigation in challenging environments related to harsh winter conditions, a problem which has not received sufficient consideration. The novelty of this research program lies in the extensive experiments to be performed in the field using various autonomous mobile systems equipped with a laser (light detection and ranging, or lidar). Breakthroughs in localization and mapping are expected to push the boundaries of where and when autonomous mobile systems can be used effectively and safely. This program is further divided into four specific objectives: (1) to integrate robust optimization theory into traditional lidar-based registration algorithms; (2) to improve the uncertainty estimation for lidar-based registration algorithms; (3) to design better algorithms to maintain 3D maps in the context of complex, dynamic, and unstructured environments; and (4) to realize a long-term experiment wherein a vehicle must drive autonomously through multiple seasons and difficult meteorological conditions.The research behind this program is highly significant considering the current excitement around autonomous vehicles. On the one hand, outcomes of the program will foster research in mobile robotics by providing innovative solutions for autonomous navigation in complex 3D environments. On the other hand, they will support both industrial and political stakeholders during the critical transition period toward new transportation solutions by giving inputs about the safety of autonomous mobile systems in winter conditions. The results of this research will also have a ripple effect on different industry sectors beyond automotive, such as mining, forestry, and agriculture, which required localized vehicles in harsh conditions, and the entertainment industry, which relies on accurate localization for special effects.