William Travis

A Study of the Effect of Various Vehicle Properties on Rollover Propensity

This paper investigates the effect of various vehicle parameters on rollover propensity using computer simulation. The computer simulation’s accuracy is verified by comparing it to experimental data from NHTSA’s Phase IV testing on rollover of passenger vehicles. The vehicle model used in the simulation study considers the non-linear, transient dynamics of both yaw and roll motion. The vehicle model is subjected to a specific steering input defined by NHTSA, the Fishhook 1a. A correlation between the vehicle parameter of center of gravity location and rollover propensity is found using the validated vehicle simulation.

UGV Trailer Position Estimation Using a Dynamic Base RTK System

In this paper, an algorithm for a dynamic base real-time kinematic (DRTK) GPS is presented and a novel application to the guidance and control of a mobile robot pulling a trailer is discussed. The DRTK system is used to estimate the relative position between the robot and trailer in the autonomous system described, and the results are compared to traditional methods utilizing an optical encoder. Geometry error is analytically predicted and the influence on trailer position is shown. Experimental results show a marginal accuracy improvement over a properly calibrated encoder based system but a significant improvement when calibration errors are present.

SciAutonics-Auburn Engineering’s Low Cost High Speed ATV for the 2005 DARPA Grand Challenge

This paper presents a summary of SciAutonics-Auburn Engineering’s efforts in the 2005 DARPA Grand Challenge. The areas discussed in detail include the team makeup and strategy, vehicle choice, software architecture, vehicle control, navigation, path planning, and obstacle detection. In particular, the advantages and complications involved in fielding a low budget all-terrain vehicle are presented. Emphasis is placed on detailing the methods used for high-speed control, customized navigation, and a novel stereo vision system. The platform chosen required a highly accurate model and a well-tuned navigation system in order to meet the demands of the Grand Challenge. Overall, the vehicle completed three out of four runs at the National Qualification Event and traveled 16 miles in the Grand Challenge before a hardware failure disabled operation. The performance in the events is described, along with a success and failure analysis.

Corridor navigation with a LiDAR/INS Kalman filter solution

Autonomous capability requires reliable and robust navigation solutions in multiple environments. GPS has become an effective tool but is not suitable for all environments. Laser scanners are quickly making their presence known in the navigation field and are proven to have a variety of uses. This paper investigates the use of LiDAR within an indoor corridor environment (i.e. hallway) to update IMU measurements. The LiDAR is combined with an IMU in a Kalman filter to produce estimates of vehicle velocity, heading, lateral error, and sensor biases. It is shown how this combination is effective in providing accurate state estimates while removing sensor errors due to noise and bias.

RASCAL - an autonomous ground vehicle for desert driving in the DARPA Grand Challenge 2005

The DARPA Grand Challenge is a competition of autonomous ground vehicles in the Mojave desert, with a prize of } for the winner. This event was organized in 2004 and held annually at least until 2007, until a team wins the prize. The teams are coming from various background, but the rule that no US government funding or technology that was created with US government funding could be used for this competition, prevented some of the well established players to participate. The team SciAutonics/Auburn-Engineering continues their effort to build a system for participation in this challenge, based on the 2004 entry RASCAL. The main focus in the system design is on improvements of the design from 2004. Novel sensing modalities the team plans to use in 2005, are a stereo vision system and a radar system for obstacle detection. Offline simulation allows to analyze situations in the laboratory and to replay recordings from sensors. The Grand Challenge 2005 takes place on October 8, and the SciAutonics/Auburn team intends to compete with the improved RASCAL system.

Trajectory duplication using relative position information for automated ground vehicle convoys

A strategy to enhance the accuracy of path following for autonomous ground vehicles in a convoy is presented. GPS carrier measurements are used to estimate relative position with sub-two centimeter accuracy and a change in position to millimeter accuracy. These estimates are used in conjunction with three methods presented that enable a following vehicle to replicate a lead vehiclepsilas path of travel while both are in motion and not in sight of one another. Accuracies of the methods achieved in simulation are shown with discussion on the benefits and shortcomings of each method. Simulation results show a 1.6 meter error at a 50 m following distance. Discussion explains the inaccuracies are due to the limitations inherent in the selected vehicle controller and not necessarily in the trajectory duplication methods.

Cascaded observers to improve lateral vehicle state and tyre parameter estimates

This paper proposes a method to produce high update, accurate, observable estimates of vehicle sideslip, utilising a two antenna GPS system. Measurements are blended with a kinematic Kalman filter to get high update sideslip estimates, which are used to predict the Dugoff tyre parameters. The parameters are then used in a model-based Kalman filter, which can provide more accurate vehicle state estimates even in the event of a GPS outage. Tyre force estimation is tested with experimental data on high and low friction surfaces, and validated by the performance of the model-based Kalman filter using the identified tyre parameters.

Automated short distance vehicle following using a dynamic base RTK system

Real-time results from a close distance vehicle platoon in which the lead vehicle was man driven and the following vehicle was automated are shown. A dynamic base RTK (DRTK) algorithm was used to determine a precise relative position vector between the vehicles. The vector was used as a means of controlling the following vehicle to the lead vehicles path of travel. The DRTK algorithm, control concept and automated convoy are described. Results show the accuracy of the DRTK algorithm to be centimetre level and demonstrate the feasibility of the control concept. An expression for the theoretical error is provided.

Compensation of vehicle dynamic induced navigation errors with dual antenna GPS attitude measurements

This paper examines the effect of sideslip on typical kinematic navigation models that neglect lateral vehicle dynamics. A kinematic model accounting for sideslip and requiring no knowledge of vehicle parameters was developed. The expanded model shows improvements to traditional modelling and emphasises the need to include sideslip for improved navigational accuracy with and without GPS. Future control systems, such as lane keeping, will require this higher accuracy to perform properly. Sideslip was calculated using a dual antenna GPS receiver and only required simple geometric vehicle knowledge. A non-linear vehicle simulation was developed and used to demonstrate the effects of sideslip on navigation solutions in a controlled setting. Experimental data is examined from an emergency lane change manoeuvre to display errors in navigation estimates caused by sideslip. Results show the model including sideslip provides a higher accuracy navigation estimate.

Reliable architecture of an embedded stereo vision system for a low cost autonomous vehicle

In the 2005 DARPA Grand Challenge, five vehicles completed a preset course of 210 kilometers through desert dirt roads, completely driven by onboard automatic systems. This major achievement was accompanied by great progress of other vehicles which participated too but did not complete the course due to various reasons. The automatic vehicle RASCAL is one example of these vehicles: with its on-board autonomous capabilities, it reached a distance of 25.7 autonomously driven kilometers. One of the sensors implemented on RASCAL was a low-cost embedded stereo vision system. This dependable embedded system was based on a DSP platform and employed a novel software framework to guarantee reliable operations in the desert. This paper provides an overview on that particular subsystem