research-article

A Reliability-Aware Vehicular Crowdsensing System for Pothole Profiling

Authors:

Abhishek Gupta,

Lu SuAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 3, Issue 4

Article No.: 160, Pages 1 - 26

https://doi.org/10.1145/3369815

Published: 14 September 2020 Publication History

Abstract

Accurately profiling potholes on road surfaces not only helps eliminate safety related concerns and improve commuting efficiency for drivers, but also reduces unnecessary maintenance cost for transportation agencies. In this paper, we propose a smartphone-based system that is capable of precisely estimating the length and depth of potholes, and introduce a holistic design on pothole data collection, profile aggregation and pothole warning and reporting. The proposed system relies on the built-in inertial sensors of vehicle-carried smartphones to estimate pothole profiles, and warn the driver about incoming potholes. Because of the difference in driving behaviors and vehicle suspension systems, a major challenge in building such system is how to aggregate conflicting sensory reports from multiple participating vehicles. To tackle this challenge, we propose a novel reliability-aware data aggregation algorithm called Reliability Adaptive Truth Discovery (RATD). It infers the reliability for each data source and aggregates pothole profiles in an unsupervised fashion. Our field test shows that the proposed system can effectively estimate pothole profiles, and the RATD algorithm significantly improves the profiling accuracy compared with popular data aggregation methods.

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Cited By

Yu ZZhao LCui HSong YLiu YLuo YGuo B(2024)CrowdKit: A Generic Programming Framework for Mobile Crowdsensing ApplicationsIEEE Transactions on Mobile Computing10.1109/TMC.2024.338157823:11(10584-10597)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TMC.2024.3381578
Gao JPan YZhang XHan QHu Y(2024)Sharing instant delivery UAVs for crowdsensingComputers and Industrial Engineering10.1016/j.cie.2024.110100191:COnline publication date: 18-Jul-2024
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Starace LRocco Di Torrepadula FDi Martino SMazzocca N(2023)Vehicular Crowdsensing with High-Mileage Vehicles: Investigating Spatiotemporal Coverage Dynamics in Historical Cities with Complex Urban Road NetworksJournal of Advanced Transportation10.1155/2023/86684732023(1-15)Online publication date: 12-May-2023
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Index Terms

A Reliability-Aware Vehicular Crowdsensing System for Pothole Profiling
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing systems and tools
2. Networks
  1. Network types
    1. Cyber-physical networks
      1. Sensor networks

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 3, Issue 4

December 2019

873 pages

EISSN:2474-9567

DOI:10.1145/3375704

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Copyright © 2019 ACM.

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Publication History

Published: 14 September 2020

Published in IMWUT Volume 3, Issue 4

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Cited By

Yu ZZhao LCui HSong YLiu YLuo YGuo B(2024)CrowdKit: A Generic Programming Framework for Mobile Crowdsensing ApplicationsIEEE Transactions on Mobile Computing10.1109/TMC.2024.338157823:11(10584-10597)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TMC.2024.3381578
Gao JPan YZhang XHan QHu Y(2024)Sharing instant delivery UAVs for crowdsensingComputers and Industrial Engineering10.1016/j.cie.2024.110100191:COnline publication date: 18-Jul-2024
https://dl.acm.org/doi/10.1016/j.cie.2024.110100
Starace LRocco Di Torrepadula FDi Martino SMazzocca N(2023)Vehicular Crowdsensing with High-Mileage Vehicles: Investigating Spatiotemporal Coverage Dynamics in Historical Cities with Complex Urban Road NetworksJournal of Advanced Transportation10.1155/2023/86684732023(1-15)Online publication date: 12-May-2023
https://doi.org/10.1155/2023/8668473
Wang LCheng YYang DXu HWang XGuo BYu Z(2023)Mobile Crowdsourcing Task Offloading on Social Collaboration Networks: An Empirical StudyMobile Crowdsourcing10.1007/978-3-031-32397-3_17(433-457)Online publication date: 21-Apr-2023
https://doi.org/10.1007/978-3-031-32397-3_17
Sun WSrinivasan K(2022)On the Feasibility of Securing Vehicle-Pavement InteractionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35172306:1(1-24)Online publication date: 29-Mar-2022
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Li DXiao BPan H(2022)Estimating severe irregularities of road ahead based on preceding vehicle responsesControl Engineering Practice10.1016/j.conengprac.2022.105300127(105300)Online publication date: Oct-2022
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El hafidy ARachad TIdri AZellou A(2021)Gamified Mobile Applications for Improving Driving BehaviorMobile Information Systems10.1155/2021/66770752021Online publication date: 1-Jan-2021
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Zhong WSuo QGupta AJia XQiao CSu L(2021)MetaTPProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/34780835:3(1-28)Online publication date: 14-Sep-2021
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Zhu YGupta AHu SZhong WSu LQiao C(2021)Driver Behavior-aware Parking Availability Crowdsensing System Using Truth DiscoveryACM Transactions on Sensor Networks10.1145/346020017:4(1-26)Online publication date: 16-Jul-2021
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Zhao YLiu C(2021)Social-Aware Incentive Mechanism for Vehicular Crowdsensing by Deep Reinforcement LearningIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2020.301426322:4(2314-2325)Online publication date: Apr-2021
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