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Driver Behavior-aware Parking Availability Crowdsensing System Using Truth Discovery

delete2021-07-16
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PRE
AI
Y
Yi Zhu *
A
Abhishek Gupta
S
Shaohan Hu
W
Weida Zhong
L
Lü Su
C
Chunming Qiao
DOI:10.1145/3460200delete
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Abstract

Abstract

En 中文
Spot-level parking availability information (the availability of each spot in a parking lot) is in great demand, as it can help reduce time and energy waste while searching for a parking spot. In this article, we propose a crowdsensing system called SpotE that can provide spot-level availability in a parking lot using drivers' smartphone sensors. SpotE only requires the sensor data from drivers' smartphones, which avoids the high cost of installing additional sensors and enables large-scale outdoor deployment. We propose a new model that can use the parking search trajectory and final destination (e.g., an exit of the parking lot) of a single driver in a parking lot to generate the probability profile that contains the probability of each spot being occupied in a parking lot. To deal with conflicting estimation results generated from different drivers, due to the variance in different drivers' parking behaviors, a novel aggregation approach SpotE-TD is proposed. The proposed aggregation method is based on truth discovery techniques and can handle the variety in Quality of Information of different vehicles. We evaluate our proposed method through a real-life deployment study. Results show that SpotE-TD can efficiently provide spot-level parking availability information with a 20% higher accuracy than thestate-of-the-art.
Keywords:
Mobile sensing
parking availability
crowdsourcing
truth discovery
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Journal

ACM Transactions on Sensor Networks cover
ACM Transactions on Sensor Networks
IF:
4.7
Papers:
994
Citations:
2.0K

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S
state university of new york (suny) system
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Papers: 5.8W
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U
university at buffalo, suny
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international business machines (ibm)
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