Access Type

Open Access Dissertation

Date of Award

January 2014

Degree Type

Dissertation

Degree Name

Ph.D.

Department

Electrical and Computer Engineering

First Advisor

Le Yi Wang

Abstract

Highway platooning of vehicles has been identified as a promising framework in

developing intelligent transportation systems. By autonomous or semi-autonomous

vehicle control and inter-vehicle coordination, an appropriately managed platoon can

potentially offer enhanced safety, improved highway utility, increased fuel economy,

and reduced emission. This thesis is focused on quantitative characterization of impact

of communication information structures and contents on platoon safety. By

comparing different information structures which combine front sensors, rear sensors,

and wireless communication channels, and different information contents such

as distances, speeds, and drivers' actions, we reveal a number of intrinsic relationships

between vehicle coordination and communications in platoons. Typical communication

standards and related communication latency and package loss are used

as benchmark cases in our study. These findings provide useful guidelines for information

harmonization module (IHM) design in sensor selections, communication

resource allocations, and vehicle coordination. Two new weighted multi-information

structure control and information data rate control are proposed. Both control methods

have been validated by experimental simulation and finite element analysis, and

also show a surprising improvement of communication resources usage with data rate

control. The results for the proposed module are new in the literature for vehicle

platoon control. A new method is introduced to enhance feedback robustness against

communication gain uncertainties. The method employs a fundamental property in

stochastic differential equations to add a scaled stochastic dither under which tolerable

gain uncertainties can be much enlarged, beyond the traditional deterministic

optimal gain margin. Algorithms, stability, convergence, and robustness are presented

for first-order systems. Extension to higher-dimensional systems is further discussed.

Simulation results are used to illustrate the merits of this methodology.

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