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Vehicle tracking problem is of crucial importance in intelligent vehicles research, as it is amongst the basic components of any comprehensive situation awareness technology. In mixed-traffic environments, where vehicles with varying degrees of sensing and communication capabilities coexist, the vehicle-tracking problem becomes particularly more demanding. In this paper, a collaborative vehicle tracking approach is presented, where onboard sensing and inter-vehicular communication resources are utilized in an efficient manner to provide track lists to all participating vehicles in a mixed-traffic environment. The approach is implemented on SimVille, our indoor testbed for urban driving, in accordance with our system development philosophy. The performance of the approach is evaluated using entropy values of vehicle tracks-an information theoretic measure of uncertainty. The experimental results of our scaled-down tests demonstrate the effectiveness of our approach.

The Ohio State University has fielded teams at all three of the DARPA Grand Challenge and DARPA Urban Challenge autonomous vehicle competitions, using three very different vehicle platforms. In this paper we present our experiences in these competitions, comparing and contrasting the different requirements, strategies, tasks, and vehicles developed for each challenge. We will discuss vehicle control and actuation, sensors, sensor interpretation, planning, behavior, and control generation. We will also discuss lessons learned from the engineering and implementation process for these three vehicles.

This paper focuses on the design of a self-optimizing nonlinear controller for a “simplified” pneumatic brake system in the continuous time domain. The specific controller under investigation periodically excites the brake system in the direction towards the maximum tire forces without apriori knowledge on the initial direction of motion. The nonlinearity and complexity of pneumatic systems (as opposed to hydraulics) introduce a higher level challenge. The developed controller employs multiple observers to estimate tire forces in a highly unpredictable environment with bounded parameter uncertainties. The controller explicit inputs are the wheel speeds and chamber pressures. A longitudinal accelerometer is also recommended.

The Ohio State University Center for Intelligent Transportation Research (CITR) has developed three automated vehicles demonstrating advanced cruise control, automated steering control for lane keeping, and autonomous behavior including automated stopping and lane changes in reaction to other vehicles. Various sensors were used, including a radar reflective stripe system and a vision based system for lane position sensing, a radar system and a scanning laser rangefinding system for the detection of objects ahead of the vehicle, and various supporting sensors including side looking radars and an angular rate gyroscope. These vehicles were demonstrated at the National Automated Highway System Consortium (NAHSC) 1997 Technical Feasibility Demonstration in a scenario involving mixed autonomous and manually driven vehicles. This paper describes the demonstration, the vehicle sensing, control, and computational hardware, and the vehicle control software.

This paper is concerned with Advanced Transportation Systems, in particular, the design of controllers for Fully-Automated Vehicle Operation. We specifically consider the design and implementation of a lateral controller for a cooperative vehicle system being developed at The Ohio State University. The objective of the lateral controller is to steer the vehicle to follow a retroreflector stripe placed on the roadway pavement using radar sensors. The structure and the parameters of the controller are determined during simulations and analytic studies. The controller models are then downloaded into two high-speed computer systems which are interconnected to simulate the operation of the closed loop system in real time and provide a “hardware-in-the-loop” environment. Finally, the computer containing the controller dynamics is installed in the vehicle and field experiments are conducted.

The state of Ohio has recognized the importance and potential impact of Intelligent Vehicle-Highway Systems (IVHS) to its citizens and business enterprises. In response to the identified need, a small group of individuals representing Federal and state government, academia, and the private sector have worked together over the past year to initiate a statewide IVHS effort. This initiative is referred to as IVHS~Ohio. The objective of the effort is to "coordinate and foster a public, private, and academic partnership to make the urban and rural surface transportation system in the state of Ohio significantly safer, more effective, and more efficient by accelerating the identification, development, integration, and deployment of IVHS technologies." A May 1993 symposium was attended by over 220 people from government, academia, and the private sector. The result was a unanimous decision to establish a statewide IVHS program.