III: Small: Towards Highly Accurate Map Services

III：小：迈向高精度地图服务

• 批准号: 2203553
• 负责人: Mohamed Mokbel
• 金额: $ 60万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2203553&HistoricalAwards=false
• 关键词: III; Small; Towards; Highly; Accurate

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.

地图服务，包括查找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支持，包括交通、基于位置的服务、乘车共享和更广泛的送货行业。所有此类服务的一个主要假设是底层地图是准确的，但这并不总是正确的。地图存在各种影响地图服务最优性的不准确性。虽然这对于临时用户来说可能是可以接受的，因为不准确可能只意味着几分钟的延迟，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，美国地图不准确每年仅给快递公司造成数十亿美元的损失。随着在线购物者和乘客的增加，这种趋势只会增加，从而将流量从休闲用户转移到送货公司和乘车共享服务。该项目旨在进行研究、开发必要的知识并构建软件基础设施，以显着提高底层地图的准确性，这将对地图服务效率产生直接影响。该项目旨在通过利用两个正交方向来实现其目标。首先，构建全球最全面、最准确的地图，地图的广泛定义超越了传统的地图拓扑，具有更丰富的定义，其中包括与交通相关的元数据，否则大多数地图服务的准确性都会很低。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。这是通过了解查询处理器的错误模式并使用它来校准查询结果，同时利用精确构建的地图及其元数据来实现的。该奖项反映了 NSF 的法定使命，并通过使用基金会的评估进行评估，被认为值得支持。智力价值和更广泛的影响审查标准。

项目成果

A Demonstration of KAMEL: A Scalable BERT-based System for Trajectory Imputation

KAMEL 演示：基于 BERT 的可扩展轨迹插补系统

• DOI: 10.1145/3555041.3589733
• 发表时间: 2023-06
• 期刊: ACM SIGMOD Conference on Management of Data
• 作者: Musleh, Mashaal;Mokbel, Mohamed
• 通讯作者: Mokbel, Mohamed

Network-less trajectory imputation

无网络轨迹插补

• DOI: 10.1145/3557915.3560942
• 发表时间: 2022-11
• 期刊: ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
• 作者: Elshrif, Mohamed M.;Isufaj, Keivin;Mokbel, Mohamed F.
• 通讯作者: Mokbel, Mohamed F.

Let's speak trajectories

说一下轨迹

• DOI: 10.1145/3557915.3560972
• 发表时间: 2022-11
• 期刊: ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
• 作者: Musleh, Mashaal;Mokbel, Mohamed F.;Abbar, Sofiane
• 通讯作者: Abbar, Sofiane