1 research outputs found
Empowered by Wireless Communication: Self-Organizing Traffic Collectives
In recent years, tremendous progress has been made in understanding the
dynamics of vehicle traffic flow and traffic congestion by interpreting traffic
as a multi-particle system. This helps to explain the onset and persistence of
many undesired phenomena, e.g., traffic jams. It also reflects the apparent
helplessness of drivers in traffic, who feel like passive particles that are
pushed around by exterior forces; one of the crucial aspects is the inability
to communicate and coordinate with other traffic participants. We present
distributed methods for solving these fundamental problems, employing modern
wireless, ad-hoc, multi-hop networks. The underlying idea is to use these
capabilities as the basis for self-organizing methods for coordinating data
collection and processing, recognizing traffic phenomena, and changing their
structure by coordinated behavior. The overall objective is a multi-level
approach that reaches from protocols for local wireless communication, data
dissemination, pattern recognition, over hierarchical structuring and
coordinated behavior, all the way to large-scale traffic regulation. In this
article we describe three types of results: (i) self-organizing and distributed
methods for maintaining and collecting data (using our concept of Hovering Data
Clouds); (ii) adaptive data dissemination for traffic information systems;
(iii) methods for self-recognition of traffic jams. We conclude by describing
higher-level aspects of our work.Comment: 28 pages, 9 figures; to appear in ACM Transactions on Autonomous and
Adaptive Systems (TAAS