Safety warning systems, such as forward collision warning (FCW), will require the use of warnings about immediate traffic threats without an annoying rate of false alarms and nuisance alerts. Both false alarm and nuisance alerts conditions will be reduced by system intelligence that integrates driver state and intent information. When a driver is cognitively and visually attending to the lead vehicle, for example, the warning thresholds can be altered to delay the onset of the alarm or reduce the intrusiveness of the alerting stimuli. When a driver intends to pass and is accelerating towards a lead vehicle, the audio stimulus might be suppressed in order to reduce the alert annoyance. Decreasing the number of false positives may reduce the tendency for drivers to disregard safety system warnings. The SAVE-IT program will focus directly on the major causes of vehicle crashes, as revealed by crash-statistics analyses. This comprehensive program will provide a framework for adaptive interface systems and expedite the development of applied safety management solutions.
1.3.2 Distraction Mitigation
Near term solutions have focused on improving designs to minimize driver head down and hands-off-wheel time in addition to reducing the cognitive load on the driver. Through the application of human factors principles, vehicle systems designers have mapped vehicle interfaces to more closely match user expectations. Other improvements emerge through innovative applications of technology. Voice recognition and text to speech capability offer significant advances. By linking voice control capability with other technologies, a driver may use the cellular phone or compose email, with higher efficiency than ever before. Additional technology such as Head-Up Displays (HUD) and steering wheel controls further reduce driver distraction. These interface technologies offer a promising start to the distraction mitigation problem, but may not represent the entire solution because they may not offer a substantial reduction in cognitive distraction. Several studies have demonstrated that cognitively taxing non-driving tasks can negatively impact driving task performance, even when the driver has “eyes on road and hands on wheel” (e.g., Recarte & Nunes, 2000; Lee, Caven, Haake, & Brown, 2000).
Although substantial improvements continue to be made within specific interface components, the system interface as a whole may become increasingly complex as it integrates a wider range of sub-components. To counteract this expansion in complexity, the human-machine interface must evolve into one that provides synergistic consideration of all safety aspects of the driving experience. The future will require not only those user interfaces that are available today, but advanced integrated solutions that fuse driver and automobile. By incorporating sensors and algorithms that measure the driver’s visual and cognitive involvement in the driving task, distraction mitigation systems will be capable of countering the most significant sources of driver distraction.
1.4 Program Plan Summary
In order to achieve the SAVE-IT program objectives, the SAVE-IT system may include the following subsystems: forward collision warning (FCW), adaptive cruise control (ACC), mobile multi-media, and driver state monitoring comprised of a HMI fusion processor (HMIP), an intent monitor, an eye tracking system, and a heart rate and respiration monitor.
Human factors research will determine the important variables in the areas of driver state monitoring, situational threat assessment, and adaptive countermeasures. Additionally, data fusion algorithms will be developed, integrated, and validated as part of the system development process. Integrated system development will evolve into a simulation study and a road-worthy prototype vehicle for an evaluation of safety benefits. Due to the complexity and breadth of this development effort, the development process will rely heavily on well-established principles of systems engineering. As such, the activities of the program are separated into the following phases over the course of three years.
Phase 0: ISS development and frame-work (complete)
ISS second-generation concept vehicle platform
Preliminary distraction mitigation and adaptive safety warning countermeasures concepts
Phase I: Foundational research and concept development (1 year)
Human factors research to determine diagnostic measures in the areas of cognitive and visual distraction, intent, driving performance, telematics demand, and driving task demand
Identification of the crash scenarios against which the system will be designed to mitigate
Adaptive interface modeling and conceptual architecture development
Upon completion of Phase I, resultant data from respective tasks will be reviewed to assess whether adaptive interface technology is a viable option for mitigating distraction-related crashes. Adaptive interface technology will be demonstrated as viable if three criteria are met. First, the proof of concept, employing the adaptive interface technology for distraction mitigation and safety warning systems, is demonstrated in terms of effectiveness and driver acceptance. Second, the deployment of adaptive interface is technically feasible in terms of the demonstrated capability and availability of sensors, actuators, and workload/distraction manager. Third, diagnostic measures of driver distraction and workload (e.g., visual and cognitive distraction) can be identified. The deliverables from Phase I, including research reports from respective tasks and a vehicle demonstration of selected adaptive interface technology, will also serve to determine whether these criteria have been met successfully and guide the development of the Phase II implementation plan.
In order to achieve the stated objectives of the SAVE-IT program, the team will leverage their respective internal activities and expertise in a synergistic team approach. Although advanced technologies may be employed to meet the program objectives, candidate technologies will be evaluated and selected based on commercial viability and robustness. This section describes the systematic technical plan that will be executed to design, implement, and evaluate a fully integrated SAVE-IT system.