Generation of Lane-Level Road Networks Based on a Trajectory-Similarity-Join Pruning Strategy
Generation of Lane-Level Road Networks Based on a Trajectory-Similarity-Join Pruning Strategy
复制标题
基于轨迹相似性连接剪枝策略的车道级道路网络生成
DOI：
10.3390/ijgi8090416
复制
发表时间：
2019
影响因子：
3.4
通讯作者：
Hongjuan Zhang
中科院分区：
文献类型：
--
作者：
Ling Zheng;Huashan Song;Bijun Li;Hongjuan Zhang
随着自动驾驶的发展，车道级地图引起了人们的极大关注。车道级道路网是车道级地图的重要组成部分，高效、低成本、自动生成车道级道路网变得越来越重要。我们在这里提出了一种新方法，该方法仅使用基于自动驾驶车辆的位置信息和现有车道级道路网络，从现有的道路级专业调查中生成车道级道路网络，而无需车道细节。此方法使用车道中心线与相应路段中心线之间的平行关系。由于直接逐点计算是巨大的，我们提出了一种方法的基础上的一个冗余相似连接修剪策略（TSJ-PS）。此方法使用筛选和验证搜索框架。该算法首先基于最小距离进行快速分割，然后利用两条轨迹的相似性对轨迹相似连接进行剪枝。然后，利用未修剪的轨迹点，利用仿真变换模型计算车道的中心线轨迹。最后，我们通过在一条真实的道路上的实验，验证了算法的有效性，并生成了一个车道级的道路网络。
With the development of autonomous driving, lane-level maps have attracted significant attention. Since the lane-level road network is an important part of the lane-level map, the efficient, low-cost, and automatic generation of lane-level road networks has become increasingly important. We propose a new method here that generates lane-level road networks using only position information based on an autonomous vehicle and the existing lane-level road networks from the existing road-level professionally surveyed without lane details. This method uses the parallel relationship between the centerline of a lane and the centerline of the corresponding segment. Since the direct point-by-point computation is huge, we propose a method based on a trajectory-similarity-join pruning strategy (TSJ-PS). This method uses a filter-and-verify search framework. First, it performs quick segmentation based on the minimum distance and then uses the similarity of two trajectories to prune the trajectory similarity join. Next, it calculates the centerline trajectory for lanes using the simulation transformation model by the unpruned trajectory points. Finally, we demonstrate the efficiency of the algorithm and generate a lane-level road network via experiments on a real road.