332 / 2019-02-20 20:05:28

A directional transmission method of urban traffic congestion source information by using complex network theory

Urban traffic congestion,spatial analysis,complex network,big data,urban planning

全体主题 > Big data in Urban Planning and Management

The problems of urban traffic congestion, as an important urban disease, involves the physical and mental health of each urban dwellers, and has a serious negative impact on urban development. Recently, the researchers use big data (such as mobile signaling data, vehicle travel trajectory, etc.) to study the problem of traffic jams of city road sections and have achieved great success. However, there are still the following problems to be solved: Firstly, most of the urban traffic congestion information is only provided to the public by the geography location style but the researchers lack information about which sections cause traffic congestion. In other words, the distribution of the source of urban traffic congestion is unknown. Secondly, how to send congestion information more accurately to the public who may will enter the congested road section. In fact, the congestion information is often widely reported in the city, but cannot be transmitted in different road sections of the city according to a certain priority. Therefore, a directional delivery method of urban traffic congestion information by using complex network theory is proposed in this paper.
As we all know, if the traffic trajectory is matched to the road sections, the spatial distribution of people's trajectory can be transformed into the relationship network among the road sections in the city. In other words, we can transform the trajectory information of people into the road section relationship network. Then, when the urban traffic congestion occurs in a certain road section, we can know which road sections are most relevant to this road section according to the road section relationship network. For example, by using the community detection method based on complex network theory, we can divide the road section relationship network into some communities. This method of community detection in this article is also known as community discovery, which is able to partition an entire network into tightly connected sub-networks. The "community" in the literature does not have a strict definition; it can be understood as a class of nodes with the same characteristics. Because the road sections belong to the same community are the most relevant, so we can prioritize the dissemination of congestion information in this community. Furthermore, we think other methods of complex network theory can also handle the transmission of congestion information better and better. More importantly, this way of thinking can help us better understand the operation law of urban traffic congestion.