An Overview of Community Detection Methods in Transportation Networks

The Internet of thing (IoT) has a variety of application domains including the transportation systems. Indeed, the future of transportation lies not only in building new roads, but also increasingly in using the internet. Internet enables elements within the transportation system such as vehicles, roads, traffic lights, etc. to become intelligent by embedding them with sensors and allowing them to communicate with each other through wireless technologies in order to improve mobility, safety and sustainability. Even though persons are equipped with wearable sensors or simply use their mobile to connect to the other elements. All these devices are connected to form a network. This network can be exploited to extract valuable information to improve the provided services such as reducing traffic congestion, making efficient matching between the demand and offer in term of passenger transportation and so on. Various knowledge can be extracted from a network such as overlapping networks detection, intruder detection, community detection ... In this paper we focus on community detection. We begin by presenting various community detection algorithms in real world networks and then we give an overview of the existing methods used for community detection in the structure of transportation network.