论文标题
DLCSS:动态最长的共同子序列
DLCSS: Dynamic Longest Common Subsequences
论文作者
论文摘要
自动驾驶是朝着更光明,更可持续的未来的关键技术。为了实现这种未来,有必要在共享的移动性模型中利用自动驾驶汽车。但是,为了评估两个或多个路由请求是否有可能进行共享的乘车,这是一项计算密集的任务,如果通过重新安排来完成。在这项工作中,我们提出了动态最长的常见子序列算法,以便对两种途径进行快速和成本效益的兼容性比较,而动态地仅包含适合共享跳闸的路线的一部分。基于此,还可以估计,满足当地出行需求可能需要多少个自动驾驶汽车。这可以帮助提供者估算必要的车队规模,决策者更好地了解出行模式和城市以扩展必要的基础设施。
Autonomous driving is a key technology towards a brighter, more sustainable future. To enable such a future, it is necessary to utilize autonomous vehicles in shared mobility models. However, to evaluate, whether two or more route requests have the potential for a shared ride, is a compute-intensive task, if done by rerouting. In this work, we propose the Dynamic Longest Common Subsequences algorithm for fast and cost-efficient comparison of two routes for their compatibility, dynamically only incorporating parts of the routes which are suited for a shared trip. Based on this, one can also estimate, how many autonomous vehicles might be necessary to fulfill the local mobility demands. This can help providers to estimate the necessary fleet sizes, policymakers to better understand mobility patterns and cities to scale necessary infrastructure.