Vehicle platoons are efficient, closely-spaced groups of robotically controlled vehicles which travel at high speeds down the road, similar to carts in a train. Within this thesis, a promising control algorithm for vehicle platooning is explored. The control algorithm was previously demonstrated in a sterile setting which significantly reduced the challenges facing full-scale implementation of platoons, most notably loss of shared data and imprecision within the data. As found within this work, transmission loss and imprecise position, velocity, and acceleration data significantly degraded the control algorithm's performance. Vehicles in the platoon became more closely spaced, changed speeds more frequently, and expended far more energy than necessary. Introducing a measure of each following vehicle's position with respect to the lead vehicle into the control algorithm noticeably reduced platoon contraction. Adjusting the control algorithm's responsiveness based on what data was successfully received reduced the speed-variations by vehicles. Finally, using past behavior to predict the next acceleration reduced the energy used by each vehicle. Combining these modifications with a model of the proposed communication scheme shows platoons of up to 25 vehicles are feasible.

Variation analysis, or tolerance analysis as it is sometimes called, is typically used to predict variation in critical dimensions in assemblies by calculating the stack-up of the contributing component variations. It is routinely used in manufacturing and assembly environments with great success. Design engineers are able to account for the small changes in dimensions that naturally occur in manufacturing processes, in equipment, and due to operators and still ensure that the assemblies will meet the design specifications and required assembly performance parameters. Furthermore, geometric variation not only affects critical fits and clearances in static assemblies, it can also cause variation in the motion of mechanisms, and their dynamic performance. The fact that variation and motion analysis are both dependent upon the geometry of the assembly makes this area of study much more challenging. This research began while investigating a particular application of dynamic assemblies - automobiles. Suspension and steering systems are prime examples dynamic assemblies. They are also critical systems, for which small changes in dimension can cause dramatic changes in the vehicle performance and capabilities. The goals of this research were to develop the tools necessary to apply the principles of static variation analysis to the kinematic motions of mechanisms. Through these tools, suspension and steering systems could be analyzed over a range of positions to determine how small changes in dimensions could affect the performance of those systems. There are two distinct applications for this research, steering systems and suspension systems. They are treated separately, as they have distinct requirements. Steering systems are mechanisms, for which position information is most critical to performance. In suspension systems, however, the higher order kinematic terms of velocity and acceleration often are more important than position parameters.