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Guiding a remote vehicle when real time image transmission is not possible is an important problem in the field of teleoperation. In such a situation, it is impractical to put an operator behind a steering wheel and expect accurate steering. In semi-autonomous teleoperation, an operator designates the path that the vehicle should follow in an image of the scene transmitted from the vehicle, and the vehicle autonomously follows this path. Previous techniques for semi-autonomous teleoperation require stereo image data, or inaccurately track paths on non-planar terrain. STRIPE is a method for accurate semi-autonomous teleoperation using monocular image data. By combining techniques in computer control, artificial intelligence, and intelligent user interfaces, we are designing a unique system for remote operation of a vehicle across low-bandwidth and high-delay transmission links.

An important part of ITS (Intelligent Transportation Systems, formerly IVHS) is the development of collision avoidance systems. These systems continuously sense the dynamic state of the vehicle and the roadway situation, and they assess the potential for a collision. When the system determines that an emergency situation might be developing, it warns the driver to take evasive action. Such countermeasure systems must be subjected to rigorous testing to ensure reasonable performance in all foreseeable circumstances and effectiveness in reducing the incidence of collisions. The efficiency and safety of testing can be greatly enhanced by using a dynamic simulation of a vehicle in near-collision situations and “equipping” the vehicle with a proposed collision avoidance system. This paper discusses the development and application of a time-domain simulation code based on a dynamic model of the driver/vehicle/counter-measure system.

Research in Intelligent Transportation Systems (ITS) has been increasingly focussed on the development of Collision Avoidance Systems (CAS). A CAS would reduce the incidence of collisions by providing warnings to the driver to take evasive action. Because single vehicle roadway departures, also known as Run-off-Road (ROR) events, are a cause of a significant portion of vehicle accidents and fatalities, an effective CAS for ROR can potentially improve highway safety dramatically. The development of performance specifications for CAS for ROR events is a part of an ongoing three-phase program for NHTSA (National Highway Traffic Safety Administration). This paper focusses on the development and application of a powerful simulation tool, RORSIM, for CAS assessments over a wide range of environmental, roadway, driver, vehicle and CAS operating conditions. The results of CAS effectiveness studies are presented.

Hydrogen-powered vehicles offer the promise of significantly reducing the amount of pollutants that are expelled into the environment on a daily basis by conventional hydrocarbon-fueled vehicles. While very promising from an environmental viewpoint, the technology and systems that are needed to store the hydrogen (H2) fuel onboard and deliver it to the propulsion system are different from what consumers, mechanics, fire safety personnel, the public, and even engineers currently know and understand. As the number of hydrogen vehicles increases, the likelihood of a rollover or collision of one of these vehicles with another vehicle or a barrier will also increase.

Extensive modeling and simulation studies have been carried out to evaluate the performance of systems for avoiding run-off-road crashes. Results show that the effectiveness of in-vehicle crash avoidance systems depends on how well they can be tailored to specific vehicle, driver, and roadway characteristics. To this end, a major focus of these studies is the development of improved driver lane-keeping models based on statistical analyses of data collected in driving experiments conducted on highways, rural roads, and test tracks. In recent simulation studies using improved driver models, the performance of crash avoidance systems in tractor-trailers and passenger cars has been compared over a wide range of incipient run-off-road crash conditions. Heavy trucks present a greater challenge for run-off-road crash avoidance systems, because they slightly but frequently leave the lane even under controlled driving, and because they are less stable during recovery maneuvers.

In this paper we present recent advances in developing and validating the safeguarded teleoperation approach to time-delayed remote driving. This approach shares control of the rover using a command fusion strategy: In benign situations, users remotely drive the rover; in hazardous situations, a safeguarding system running on-board the rover overwrites user commands to ensure vehicle safety. This strategy satisfies users, because it allows them to drive (except in hazardous situations), while maintaining the integrity of the rover and mission. We present results from experiments on untrained teleoperators with and without safeguarding, which reveal needs to be met by future user interfaces. We describe three technical advances in safeguarding: improving the accuracy of dead reckoning by a factor of 2, speeding up the controller by a factor of 18, and developing an area-based rather than a path-based obstacle avoidance planner in order to circumvent map merging problems.

This paper describes Battelle's effort to demonstrate a bio-based, environmentally friendly, Type I, non-glycol deicer, called D3: Degradable by Design Deicer™. AMS 1424 D tests conducted by SMI and AMIL indicate this aircraft deicing fluid (ADF) meets the established physical properties, material compatibility, corrosion resistance, and deicing performance requirements. Its biological oxygen demand (BOD5) and lethal concentrations (LC50) are less than half of conventional Type I propylene glycol (PG) ADF levels. Spray tests were conducted in the McKinley Climatic Chamber at Eglin Air Force Base, and aircraft flight tests were conducted at the Niagara Falls Air Reserve Station.