On-Board Data Management Layer: Connected Vehicle as Data Platform

Abstract

For connected vehicles, as well as generally for the transportation sector, data are now seen as a precious resource. They can be used to make right decisions, improve road safety, reduce CO2 emissions, or optimize processes. However, analyzing these data is not so much a question of which technologies to use, but rather about where these data are analyzed. Thereby, the emerging vehicle architecture has to become a data-oriented architecture based on embedded computing platforms and take into account new applications, artificial intelligence elements, advanced analytics, and operating systems. Accordingly, in this paper, we introduce the concept of data management to the vehicle by proposing an on-board data management layer, so that the vehicle can play the role of data platform capable of storing, processing, and diffusing data. Our proposed layer supports analytics and data science to deliver additional value from the connected vehicle data and stimulate the development of new services. In addition, our data platform can also form or contribute to shaping the backbone of data-driven transport. An on-board platform was built where the dataset size was reduced 80% and a rate of 99% accuracy was achieved in a 5 min traffic flow prediction using artificial neural networks (ANNs).

Smart Mobility with Big Data: Approaches, Applications, and Challenges

“…Moreover, in [15], the authors implemented an artificial neural network (ANN) composed of three layers to predict traffic flow. The ANN was trained to exploit forward propagation and backpropagation learning according to the date, time, traveler's vehicle, commercial vehicles, number of vehicles occupying the road segment, and vehicle speed.…”

“…In this section, we review the applications of data generated by connected vehicles in depth, as well as research conducted to date. The authors of [15] introduced the concept of data management for vehicles by proposing an onboard data management layer so that the vehicle can serve as a data platform that can store, process, and share data. Moreover, the authors of [76] proposed ThinGs in a fog (TGIF), a system designed to support interdisciplinary research within a wide range of IoT applications.…”