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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.<\/jats:p>","DOI":"10.1145\/3369815","type":"journal-article","created":{"date-parts":[[2019,12,12]],"date-time":"2019-12-12T13:16:03Z","timestamp":1576156563000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["A Reliability-Aware Vehicular Crowdsensing System for Pothole Profiling"],"prefix":"10.1145","volume":"3","author":[{"given":"Weida","family":"Zhong","sequence":"first","affiliation":[{"name":"SUNY Buffalo, USA"}]},{"given":"Qiuling","family":"Suo","sequence":"additional","affiliation":[{"name":"SUNY Buffalo, USA"}]},{"given":"Fenglong","family":"Ma","sequence":"additional","affiliation":[{"name":"Pennsylvania State University, University Park, Pennsylvania, USA"}]},{"given":"Yunfei","family":"Hou","sequence":"additional","affiliation":[{"name":"California State University San Bernardino, San Bernardino, California, USA"}]},{"given":"Abhishek","family":"Gupta","sequence":"additional","affiliation":[{"name":"SUNY Buffalo, USA"}]},{"given":"Chunming","family":"Qiao","sequence":"additional","affiliation":[{"name":"SUNY Buffalo, USA"}]},{"given":"Lu","family":"Su","sequence":"additional","affiliation":[{"name":"SUNY Buffalo, Buffalo, New York, USA"}]}],"member":"320","published-online":{"date-parts":[[2020,9,14]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.pmcj.2015.10.019"},{"key":"e_1_2_1_2_1","volume-title":"Retrieved","author":"The American Automobile Association","year":"2016","unstructured":"The American Automobile Association . 2016 . Pothole Damage Costs Drivers $3 Billion Annually Nationwide . Retrieved February 17, 2016 from http:\/\/news.aaa-calif.com\/news\/pothole-damage-costs-drivers-3-billion-annually-nationwide The American Automobile Association. 2016. Pothole Damage Costs Drivers $3 Billion Annually Nationwide. Retrieved February 17, 2016 from http:\/\/news.aaa-calif.com\/news\/pothole-damage-costs-drivers-3-billion-annually-nationwide"},{"key":"e_1_2_1_3_1","unstructured":"Dimitri P Bertsekas. 1999. Nonlinear programming. Athena scientific Belmont.  Dimitri P Bertsekas. 1999. Nonlinear programming. Athena scientific Belmont."},{"key":"e_1_2_1_4_1","volume-title":"Proceedings of the 2nd International Conference on Information Technology and Computer Networks. 48--53","author":"Buza Emir","year":"2013","unstructured":"Emir Buza , Samir Omanovic , and Alvin Huseinovic . 2013 . Pothole detection with image processing and spectral clustering . 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