AAA

Abstract: We present a new approach to automated scenario-based testing of the safety of autonomous vehicles, especially those using advanced artificial intelligence-based components, spanning both simulation-based evaluation as well as testing in the real world. Our approach is based on formal methods, combining formal specification of scenarios and safety properties, algorithmic test case generation using formal simulation, test case selection for track testing, executing test cases on the track, and analyzing the resulting data. Experiments with a real autonomous vehicle at an industrial testing facility support our hypotheses that (i) formal simulation can be effective at identifying test cases to run on the track, and (ii) the gap between simulated and real worlds can be systematically evaluated and bridged.

Abstract: New automobiles provide a variety of features that allow motorists to perform a plethora of secondary tasks unrelated to the primary task of driving. Despite their ubiquity, surprisingly little is known about how these complex multimodal in-vehicle information systems (IVIS) interactions impact a driver’s workload. The current research sought to address three interrelated questions concerning this knowledge gap: (1) Are some task types more impairing than others? (2) Are some modes of interaction more distracting than others? (3) Are IVIS interactions easier to perform in some vehicles than others? Depending on the availability of the IVIS features in each vehicle, our testing involved an assessment of up to four task types (audio entertainment, calling and dialing, text messaging, and navigation) and up to three modes of interaction (e.g., center stack, auditory vocal, and the center console). The data collected from each participant provided a measure of cognitive demand, a measure of visual/manual demand, a subjective workload measure, and a measure of the time it took to complete the different tasks. The research provides empirical evidence that the workload experienced by drivers systematically varied as a function of the different tasks, modes of interaction, and vehicles that we evaluated. This objective assessment suggests that many of these IVIS features are too distracting to be enabled while the vehicle is in motion. Greater consideration should be given to what interactions should be available to the driver when the vehicle is in motion rather than to what IVIS features and functions could be available to motorists.

Abstract: The TravTek (travel-technology) project is being developed for the entire Orlando area. This project is a partnership consisting of the Federal Highway Administration, the Florida Department of Transportation, the City of Orlando, General Motors, and the American Automobile Association. The objectives of the TravTek project are to: • Explore the feasibility of ADIS and their acceptability to drivers. • Determine whether Advanced Driver Information System (ADIS) can improve utilization of the highway system, increase safety, improve travel time, and reduce fuel consumption. • Gain insights into how to build the next generation of ADIS. The TravTek vehicle equipment will be installed in 100 General Motors 1992 Oldsmobile Toronados. Seventy-five or more of these automobiles will be dedicated for daily rental to travelers while the remaining vehicles will be leased to high mileage local drivers. The TravTek demonstration projects consists of three principal subsystems: • In-Vehicle System - the system in the vehicle which provides the driver with routing and other travel information. The in-vehicle system development is the responsibility of General Motors. • Traffic Management Center (TMC) - collects data concerning traffic conditions from various state and municipal agencies, including TravTek vehicles, and then transmits this information back to the car's In-Vehicle System. The TMC is the responsibility of the FHWA, Florida DOT, and the City of Orlando. • TravTek Information and Services Center (TISC) - The TravTek Information and Services Center will support day-to-day operations of the TravTek experiment. The TISC is is the responsibility of AAA.