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This paper evaluates the use of a low cost inertial navigation system (INS) combined with Carrier-Phase Differential GPS (DGPS), to provide continuous position and attitude estimation for the control of a farm tractor. The INS system is used for dead-reckoning navigation to control the vehicle through short GPS outages. An Extended Kalman filter combines INS and Doppler radar measurements with cm-level Carrier-Phase Differential GPS measurements for continuous position and attitude estimation of the tractor. Results are given which verify the ability of the INS system to provide a heading accuracy within ±0.6° for control of the tractor. Additionally it is shown that the dead-reckoning system can provide position and attitude estimation to control the tractor to within ±0.3 meters through a short GPS outage.

As global navigation satellite systems (GNSS) such as GPS have grown more pervasive, the use of GNSS to automatically control ground vehicles has drawn increasing interest. This cutting-edge resource offers you a thorough understanding of this emerging application area of GNSS. Written by highly-regarded authorities in the field, this unique reference covers a wide range of key topics, including ground vehicles models, psuedolites, highway vehicle control, unmanned ground vehicles, farm tractors, and construction equipment. The book is supported with over 150 illustrations and more than 180 equations.

This paper investigates the use of GPS to estimate vehicle sideslip and tire information. Both a one antenna GPS antenna/receiver and dual GPS antenna method are studied. Analysis of the accuracy that can be achieved using the two different GPS solutions is provided. The algorithms are then validated on a fully instrumented Infiniti G35 sedan. Experimental data is given showing the performance of the GPS based sideslip estimates compared against a simple bicycle model and a Datron™ velocity sensor.

Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each other in close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-truck autonomy is easily integrated on existing platforms, reduces delivery times, and reduces greenhouse gas emissions via fuel economy benefits. Level 1 SAE fuel studies were performed on class-8 trucks operating with the Auburn Cooperative Adaptive Cruise Control (CACC) system, and fuel savings up to 10-12% were seen. Enabling platooning autonomy required the use of radar, global positioning systems (GPS), and wireless vehicle-to-vehicle (V2V) communication. Poor measurements and state estimates can lead to incorrect or missing positioning data, which can lead to unnecessary dynamics and finally wasted fuel.