Bayesian framework for mobility pattern discovery using mobile network events

Understanding human mobility patterns is of great importance for planning urban and extra-urban spaces and communication infrastructures. The omnipresence of mobile telephony in today’s society opens new avenues of discovering the patterns of human mobility by means of analyzing cellular network data. Of particular interest is analyzing passively collected Network Events (NEs) due to their scalability. However, mobility pattern analysis based on network events is challenging because of the coarse granularity of NEs. In this paper, we propose network event-based Bayesian approaches for mobility pattern recognition and reconstruction, mode of transport recognition and modeling the frequent trajectories

Uses and Challenges of Collecting LiDAR Data from a Growing Autonomous Vehicle Fleet: Implications for Infrastructure Planning and Inspection Practices

Autonomous vehicles (AVs) that utilize LiDAR (Light Detection and Ranging) and other sensing technologies are becoming an inevitable part of transportation industry. Concurrently, transportation agencies are increasingly challenged with the management and tracking of large-scale highway asset inventory. LiDAR has become popular among transportation agencies for highway asset management given its advantage over traditional surveying methods. The affordability of LiDAR technology is increasing day by day. Given this, there will be substantial challenges and opportunities for the utilization of big data resulting from the growth of AVs with LiDAR. A proper understanding of the data size generated from this technology will help agencies in making decisions regarding storage, management, and transmission of the data. The original raw data generated from the sensor shrinks a lot after filtering and processing following the Cache county Road Manual and storing into ASPRS recommended (.las) file format. In this pilot study, it is found that while considering the road centerline as the vehicle trajectory larger portion of the data fall into the right of way section compared to the actual vehicle trajectory in Cache County, UT. And there is a positive relation between the data size and vehicle speed in terms of the travel lanes section given the nature of the selected highway environment