A high-quality fresh high-definition (HD) map is vital in enhancing transportation efficiency and safety in autonomous driving. Vehicle-based crowdsourcing offers a promising approach for updating HD maps. However, recruiting crowdsourcing vehicles involves making the challenging tradeoff between the HD map freshness and recruitment costs. Existing studies on HD map crowdsourcing often (1) prioritize maximizing spatial coverage and (2) overlook the dual role of crowdsourcing vehicles in HD maps, as vehicles serve both as contributors and customers of HD maps. This motivates us to propose the Dual-Role Age of Information (AoI) based Incentive Mechanism (DRAIM) to address these issues. % Specifically, we propose the trajectory age of information, incorporating the expected AoI of the HD map and the trajectory, to quantify a vehicle's HD map usage utility, which is freshness- and trajectory-dependent. DRAIM aims to achieve the company's tradeoff between freshness and recruitment costs.

翻译：高质量且新鲜的高清地图对于提升自动驾驶中交通效率与安全性至关重要。基于车辆的众包为高清地图更新提供了一种有前景的方法。然而，招募众包车辆需要在高清地图新鲜度与招募成本之间做出具有挑战性的权衡。现有关于高清地图众包的研究通常（1）优先最大化空间覆盖，且（2）忽视了众包车辆在高清地图中的双重角色——车辆既是高清地图的贡献者也是其客户。这促使我们提出基于双角色年龄信息（Dual-Role Age of Information，AoI）的激励机制（DRAIM）来解决这些问题。具体而言，我们提出了轨迹年龄信息，其融合了高清地图的预期AoI与轨迹，以量化车辆对高清地图的使用效用，该效用取决于新鲜度与轨迹。DRAIM旨在实现公司在新鲜度与招募成本之间的权衡。