SCC-IRG Track 2: Towards Quality Aware Crowdsourced Road Sensing for Smart Cities

SCC-IRG 第 2 轨：迈向智慧城市的质量意识众包道路传感

• 批准号: 1737590
• 负责人: Chunming Qiao
• 金额: $ 100万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1737590&HistoricalAwards=false
• 关键词: SCC; IRG; Track; Towards; Quality

With nearly a billion automobiles on the road today, the current transportation systems have begun to show signs of serious strain, such as congestions, traffic accidents, road surface defects, and malfunctioning traffic regulation infrastructures. Therefore, it is of great importance to collect and disseminate road/traffic condition information accurately, efficiently, and timely. Traditionally, road and traffic monitoring are conducted through either stationary sensors or instrumented probe vehicles. Unfortunately, the prohibitively high deployment cost of such devices makes it impossible to achieve large-scale deployment, leading to limited road coverage and delayed information update. To mitigate these problems, this project develops QuicRoad, a Quality of Information (QoI) aware crowdsourced road sensing system that can collect road/traffic information from a variety of sources, including smartphones, social media and transportation authorities (as well as future connected vehicles), and then distribute the collected information in real time. The PIs team up with local transportation agencies in the Buffalo-Niagara region on applications related to road surface and traffic condition monitoring, border crossing delay estimation, and incident management.This project integrates across both social and technological research dimensions. In the technological dimension, it leads to a novel Quality of Information (QoI) aware information integration framework that can jointly optimize the estimation of the QoI of various sources, and the information-integration as well as decision-making process. In the social dimension, it answers fundamental questions such as whether and to what degree the road/traffic condition information provided by the proposed QuicRoad system would change the social behavior of the travelers. By seamlessly integrating the technological and social dimensions, the proposed research can not only improve the coverage and quality of assisted driving and road navigation services for travelers, but also support policy-making in traffic planning and operations by transportation authorities. The research will potentially benefit a wide spectrum of real-world road sensing applications aimed at improving road safety, mitigating traffic congestions, and reducing fuel consumption and emissions, and eventually contribute to building a sustainable society.

如今，随着近十亿辆汽车的发展，当前的运输系统已经开始显示出严重应变的迹象，例如拥塞，交通事故，道路表面缺陷以及交通不便的基础设施。因此，准确，有效，及时地收集和传播道路/交通状况信息非常重要。传统上，道路和交通监控是通过固定传感器或仪器探针车进行的。不幸的是，此类设备的高度部署成本使得无法实现大规模部署，从而导致道路覆盖范围有限和信息延迟。为了减轻这些问题，该项目开发了Quicroad，信息质量（QOI）意识到众包的道路传感系统，可以从各种来源收集道路/交通信息，包括智能手机，社交媒体和运输部门（以及未来的连接车辆），然后实时分发收集的信息。 PIS与布法罗 - 尼亚加拉地区的当地运输机构合作，涉及与道路表面和交通状况监测，过境延迟估算以及事件管理有关的应用。该项目跨越社会和技术研究维度。在技​​术维度中，它导致了新的信息质量（QOI）意识集成框架，可以共同优化各种来源的QOI估计以及信息融合以及决策过程。在社会方面，它回答了基本问题，例如拟议的Quicroad系统提供的道路/交通状况信息是否以及在何种程度上会改变旅行者的社会行为。通过无缝整合技术和社会层面，拟议的研究不仅可以改善旅行者的辅助驾驶和道路导航服务的覆盖范围和质量，而且还可以支持交通当局在交通计划和运营中的决策。这项研究可能会受益于广泛的现实道路传感应用，旨在改善道路安全，减轻交通拥堵，减少燃料消耗和排放，并最终有助于建立可持续的社会。

项目成果

Travel purpose inference with GPS trajectories, POIs, and geo-tagged social media data

• DOI: 10.1109/bigdata.2017.8258062
• 发表时间: 2017-12
• 期刊: 2017 IEEE International Conference on Big Data (Big Data)
• 作者: Chuishi Meng;Yu Cui;Qi He;Lu Su;Jing Gao

A Reliability-Aware Vehicular Crowdsensing System for Pothole Profiling

• DOI: 10.1145/3369815
• 发表时间: 2019-12
• 期刊: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
• 作者: Weida Zhong;Qiuling Suo;Fenglong Ma;Yunfei Hou;Abhishek Gupta;C. Qiao;Lu Su

Towards the Inference of Travel Purpose with Heterogeneous Urban Data

利用异构城市数据推断出行目的

• DOI: 10.1109/tbdata.2019.2921823
• 发表时间: 2022
• 期刊: IEEE Transactions on Big Data
• 影响因子: 7.2
• 作者: Meng, Chuishi;Cui, Yu;He, Qing;Su, Lu;Gao, Jing
• 通讯作者: Gao, Jing

Thanos: Incentive Mechanism with Quality Awareness for Mobile Crowd Sensing

• DOI: 10.1109/tmc.2018.2868106
• 发表时间: 2019-08-01
• 期刊: IEEE TRANSACTIONS ON MOBILE COMPUTING
• 影响因子: 7.9
• 作者: Jin, Haiming;Su, Lu;Xu, Jinhui
• 通讯作者: Xu, Jinhui

Forecasting current and next trip purpose with social media data and Google Places

• DOI: 10.1016/j.trc.2018.10.017
• 发表时间: 2018-12-01
• 期刊: TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
• 影响因子: 8.3
• 作者: Cui, Yu;Meng, Chuishi;Gao, Jing
• 通讯作者: Gao, Jing