Pavement Management Utilizing Mobile Crowd Sensing

Abstract

Pavement management, which is vital in road transportation and maintenance, is facing some troubles, such as high costs of labors and machineries, low detecting efficiency, and low update rate of pavement conditions by means of traditional detection ways. Benefiting from the development of mobile communication, mobile computing, and mobile sensing techniques, the intelligence of mobile crowd sensing (MCS), which mainly relies on ubiquitous mobile smart devices in people’s daily lives, has overcome the above drawbacks to a large extent as one new effective and simple measure for pavement management. As a platform for data collection, processing, and visualization, a common smart device can utilize inertial sensor data, photos, videos, subjective reports, and location information to involve the public in pavement anomalies detection. This paper systematically reviewed the studies in this field from 2008 to 2018 to establish an overall knowledge. Through literature collection and screening, a database of studies was set up for analysis. As a result, the year profile of publications and distribution of research areas indicate that there has been a constant attention from researchers in various disciplines. Meanwhile, the distribution of research topic shows that inertial sensors embedded in smartphones have been the most popular data source. Therefore, the process of pavement anomalies detection based on inertial data was reviewed in detail, including preparatory, data collection, and processing phases of the previous experiments. However, some of the key issues in the experimental phases were investigated by previous studies, while some other challenges were not tackled or noticed. Hence, the challenges in both experiment and implementation stages were discussed to improve the studies and practice. Furthermore, several directions for future research are summarized from the main issues and challenges to offer potential opportunities for more relevant research studies and applications in pavement management.

Information Acquisition Incentive Mechanism Based on Evolutionary Game Theory

“…Parameter Settings of the Reverse Auction Competing. In a fixed region where information collection is required, the group sensing system consists of information collection employees and information collection platforms [30]. In the initial state, N employees are randomly distributed in the specified region.…”

Participant Recruitment Method Aiming at Service Quality in Mobile Crowd Sensing

“…How to achieve a game equilibrium between platforms and users is an important direction of current academic research. In addition to the above two main goals, the number of participants in each task, the number of tasks assigned by each participant, the quality of the data submitted by participants, and the total distance a participant needs to move to complete tasks are all in the selection process, which need to be considered [20]. Participant selection, as the core key issue in the field of MCS, is the focus and difficulty of current research.…”

A bibliometric and scientometric review of research on crowdsourcing in smart cities

“…Some existing reviews of the literature are limited either to a single type of crowdsourcing (for example, mobile crowd sensing (MCS), as mentioned in ref. [10] or to a certain application area for smart cities, for example, pavement management [16] or public security [17]. In summary, a systematic analysis of the existing research and trends for applying crowdsourcing in smart cities is still needed.…”