Keith Redmill

Automated lane change controller design

The primary focus of study in this paper is the background control theory for automated lane change maneuvers. We provide an analytic approach for the systematic development of controllers that will cause an autonomous vehicle to accomplish a smooth lane change suitable for use in an Automated Highway System. The design is motivated by the discontinuous availability of valid preview data from the sensing systems during lane-to-lane transitions. The task is accomplished by the generation of a virtual yaw reference and the utilization of a robust switching controller to generate steering commands that cause the vehicle to track that reference. In this way, the open loop lane change problem is converted into an equivalent virtual reference trajectory tracking problem. The approach considers optimality in elapsed time at an operating longitudinal velocity. Although the analysis is performed assuming that the road is straight, the generalization of the proposed algorithm to arbitrary road segments is rather straightforward. The outlined lane change algorithm has been implemented and tested on The Ohio State University test vehicles. Some of the experimental results are presented at the conclusion of this paper.

Systems for Safety and Autonomous Behavior in Cars: The DARPA Grand Challenge Experience

In this paper, we review technologies for autonomous ground vehicles and their present capabilities in research and in the automotive market. We outline technology requirements for enhanced functions and for infrastructure development. Since the recent Grand Challenge competition is a major force to advance technology in this field, we specifically refer to our experiences in developing a participating vehicle. We present a multisensor platform that has been proven in an off-road environment. It combines different sensing modalities that inherently yield uncertain information. Finite-state machines are formulated to generate rule-based autonomous behavior that enables fully autonomous off-road driving. Overall, the intent of the paper is to evaluate approaches and technologies used in the two Grand Challenges as they contribute to the needs of autonomous cars on the road

Cooperative Adaptive Cruise Control Implementation of Team Mekar at the Grand Cooperative Driving Challenge

This paper presents the cooperative adaptive cruise control implementation of Team Mekar at the Grand Cooperative Driving Challenge (GCDC). The Team Mekar vehicle used a dSpace microautobox for access to the vehicle controller area network bus and for control of the autonomous throttle intervention and the electric-motor-operated brake pedal. The vehicle was equipped with real-time kinematic Global Positioning System (RTK GPS) and an IEEE 802.11p modem installed in an onboard computer for vehicle-to-vehicle (V2V) communication. The Team Mekar vehicle did not have an original-equipment-manufacturer-supplied adaptive cruise control (ACC). ACC/Cooperative adaptive cruise control (CACC) based on V2V-communicated GPS position/velocity and preceding vehicle acceleration feedforward were implemented in the Team Mekar vehicle. This paper presents experimental and simulation results of the Team Mekar CACC implementation, along with a discussion of the problems encountered during the GCDC cooperative mobility runs.

DGPS/INS integrated positioning for control of automated vehicle

In recent years, the Global Positioning System (GPS) has solidified its presence as a dependable means of navigation by providing absolute positioning in various applications. While GPS alone can provide position information, it has several weaknesses, such as low data output rate and vulnerability to external disturbances. We explore the feasibility of an integrated positioning system using a differential GPS (DGPS) and an inertial navigation system (INS) for the control of an automated vehicle. An extended Kalman filter which combines the measurements from the DGPS, INS, and vehicle sensors to produce estimates of various vehicle states is derived. A methodology which, using map data, converts position measurements to vehicle lateral offset and desired speed, as applicable for the control of an automated vehicle, is presented. An analysis of the overall closed-loop vehicle control system is discussed. Finally, the performance of the proposed control scheme is examined through field tests conducted on two different vehicle platforms, an automated golfcart and a drive-by-wire Honda Accord sedan.

A robust video based traffic light detection algorithm for intelligent vehicles

Recently, researches on intelligent vehicles which can drive in urban environment autonomously become more popular. Traffic lights are common in cities and are important cues for the path planning of intelligent vehicles. In this paper, a robust and efficient algorithm to detect traffic lights based on video sequences captured by a low cost off-the-shelf video camera is proposed. The algorithm models the hue and saturation according to Gaussian distributions and learns their parameters with training images. From learned models, candidate regions of the traffic lights in the test images can be extracted. Post processing method which takes account of the shape information is applied to the candidate regions. Furthermore, detection results of the previous image frames are aggregated in order to provide a more robust result. Experimental results on several video sequences captured in typical urban environment prove the effectiveness of the proposed algorithm.

Evaluation of intersection collision warning system using an inter-vehicle communication simulator

An inter-vehicle communication (IVC) simulator has been developed to evaluate an intersection collision warning system. Various representative intersection collision scenarios are simulated. The physical and media access control layer of the wireless communication network are modelled in the IVC simulator for transmission of collision warning messages. The results show that such a collision warning strategy is a viable way for reducing the collisions at the intersections.

Steering and lane change: a working system

In this paper, steering control of ground vehicles is studied and the lane keeping and lane changing algorithms of the 1997 NAHSC OSU Demo Vehicles are presented. The proposed lateral controller uses preview orientation information, longitudinal velocity measurement and a yaw rate sensor output to steer the vehicle autonomously. The only input to the system is the steering angle on the front tires generated through a motor installed on the rack which is also used for driver assist power steering (EPS). Various experimental results that are taken on the HOV lanes of I-15 in San Diego, CA are presented to justify the performance of the developed controller.

Ohio State University at the 2004 DARPA Grand Challenge: developing a completely autonomous vehicle

The DARPA Grand Challenge is a field test designed to accelerate R&D in autonomous ground vehicles that save lives on the future battlefield. At Ohio State University, we have extensive experience in developing autonomous ground vehicles. Our goal was to create a completely autonomous vehicle that could negotiate most of the GC 04 route and perhaps even finish the race. To achieve our goal, we needed to conquer three main technical challenges. The first was to install drive-by-wire technology in the vehicle and to modify the vehicle to fulfill DARPA safety requirements. The second challenge was to provide sensing and information fusion algorithms. The third challenge was control.

Team TerraMax and the DARPA grand challenge: a general overview

The Defense Advanced Research Projects Agency (DARPA), is an agency of the United States Government, has issued a challenge to developers of off-road autonomous ground vehicles to design and build a vehicle that can complete a lengthy and difficult off road course across desert southwest areas of the United States. A one million dollar US prize is available to the team that completes the 200-250 mile course first and in less than 10 hours. This paper describes the Team TerraMax entry to the March, 2004 race event. Vehicle hardware and drive by wire actuators, internal and external sensing systems, sensor fusion, and high and low level control systems are described.

An Integrated 802.11p WAVE DSRC and Vehicle Traffic Simulator With Experimentally Validated Urban (LOS and NLOS) Propagation Models

The IEEE 802.11p, 1609.3, and 1609.4 WAVE standards are designed to facilitate intervehicle communication and ultimately improve traffic safety. Multiple safety applications and control algorithms have been proposed to use 802.11p Dedicated Short-Range Communication (DSRC) radios and message structures. An urban environment provides many challenges for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. These include multiple propagation paths and many occlusions, particularly in areas where V2V messages would be most useful such as blind spots, buildings, and other obstructions. The dense urban environments and high concentration of vehicles make it difficult to predict how reliable this communication will be. The Ohio State Universitys Vehicle and Traffic Simulator (VaTSim) is designed as a microsimulator of traffic. This paper describes the incorporation of V2V communication into VaTSim using Network Simulator 3 (NS3) and physical layer modeling to determine how different road layouts and building configurations will affect 802.11p communication. This paper explains the theory used to define the simulated line-of-sight (LOS) propagation, non-LOS (NLOS) propagation calculations, channel switching congestion, and the experiments performed to validate the models and the simulation.