III: Small: Towards Highly Accurate Map Services

地图服务，包括找到到达某个目的地的路线或搜索附近的设施，已经为各种无处不在的服务和应用提供了动力，包括交通、基于位置的服务、拼车和更广泛的快递行业。所有这类服务的一个主要假设是底层地图是准确的，这并不总是正确的。地图存在各种各样的不准确性，这影响了地图服务的最佳性。虽然对于不准确可能只意味着几分钟延迟的偶然用户来说，这可能是可以接受的，但对于支持大量用户的地图服务的应用程序来说，情况并非如此。最近的报告显示，美国的地图不准确每年给快递公司造成数十亿美元的损失。这一趋势只会随着在线购物者和乘客的增加而加剧，这将把流量从普通用户转移到快递公司和拼车服务上。该项目旨在开展研究，开发必要的知识，并建立软件基础设施，以显著提高底层地图的准确性，这将直接影响地图服务的效率。该项目旨在通过利用两个正交的方向来实现其目标。首先，构建全球范围内最全面、最精确的地图，对地图的定义更宽泛，超越了传统的地图拓扑，包含了交通相关元数据的更丰富的定义，没有这些定义，大多数地图服务的精度都会很低。这是通过利用轨迹数据和开源地图来识别和推断缺失信息来实现的。其次，开发新技术，提高查询处理器在精确构建的地图上的准确性。这可以通过理解查询处理器的错误模式并使用它来校准查询结果来实现，同时利用精确构建的映射及其元数据。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Map services, including finding the route to a certain destination or searching for nearby facilities, have empowered a variety of ubiquitous services and applications, including transportation, location-based services, ride-sharing, and a broader delivery industry. A major assumption for all such services is that the underlying map is accurate, which is not always true. Maps suffer from all sorts of inaccuracies that impact the optimality of map services. While this may be acceptable for causal users where inaccuracy may only mean few minutes of delay, it is not the case for applications that support map services for large numbers of users. Recent reports show that map inaccuracy in the USA costs delivery companies alone billions of dollars annually. This trend is just going to increase with the increase of online shoppers and riders, which shifts traffic from casual users to delivery companies and ride sharing services. This project aims to conduct research, develop requisite knowledge, and build software infrastructure that will significantly boost the accuracy of the underlying map, which will have a direct impact on map services efficiency.The project aims to achieve its goals through exploiting two orthogonal directions. First, building the most comprehensive and accurate maps worldwide, with a broad definition of a map that goes beyond the traditional map topology to a richer definition that includes traffic-related metadata, without which, most of map services will have low accuracy. This is achieved through harnessing trajectory data and open-source maps to identify and infer missing information. Second, developing new techniques that would increase the accuracy of query processors over the accurately built maps. This is achieved through understanding the error patterns of query processors and using it to calibrate the query results, while taking advantage of the accurately built maps and their metadata.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.