01595094

Component

This paper explores the impact of information sharing on road traffic networks using a two-layer, agent-based, and day-to-day traffic network model. The first layer (cyber layer) represents a conceptual communication network where travellers share travel information. The second layer (physical layer) captures the day-to-day operations in a transport network where individual travellers seek to minimize their own travel costs. A key hypothesis in this model is that instead of having perfect information, travellers form individual groups, in which travel information is shared and utilized for routing decisions. The formation of groups occurs in the cyber layer according to percolation theory, which describes the formation of connected clusters (groups) in a random graph. This is the first paper to use percolation theory to capture the disaggregated and distributed nature of travel information sharing. The authors present a numerical study that focuses on the convergence of the transport network, when a range of percolation rates are considered. The findings suggest a positive correlation between the percolation rate and the speed of convergence, which is validated through statistical analysis.

This paper was sponsored by TRB committee ADB30 Standing Committee on Transportation Network Modeling.

01584066

16-5882

English

19p

2016

Transportation Research Board 95th Annual Meeting

Digital/other

Figures; References; Tables

Advanced traveler information systems; Intelligent agents; Networks; Real time information; Routing; Traffic models

Data and Information Technology; Highways

Transportation Research Board Annual Meeting 2016 Paper #16-5882

TRIS, TRB, ATRI

Jan 12 2016 6:36PM