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Making manned and remotely-controlled wheeled and tracked vehicles easier to drive, especially off-road, is of great interest to the U.S. Army. If vehicles are easier to drive (especially closed hatch) or if they are driven autonomously, then drivers could perform additional tasks (e.g., operating weapons or communication systems), leading to reduced crew sizes. Further, poorly driven vehicles are more likely to get stuck, roll over, or encounter mines or improvised explosive devices, whereby the vehicle can no longer perform its mission and crew member safety is jeopardized. HMI technology and systems to support human drivers (e.g., autonomous driving systems, in-vehicle monitors or head-mounted displays, various control devices (including game controllers), navigation and route-planning systems) need to be evaluated, which traditionally occurs in mission-specific (and incomparable) evaluations.

Engaging in visual-manual tasks such as selecting a radio station, adjusting the interior temperature, or setting an automation function can be distracting to drivers. Additionally, if setting the automation fails, driver takeover can be delayed. Traditionally, assessing the usability of driver interfaces and determining if they are unacceptably distracting (per the NHTSA driver distraction guidelines and SAE J2364) involves human subject testing, which is expensive and time-consuming. However, most vehicle engineering decisions are based on computational analyses, such as the task time predictions in SAE J2365. Unfortunately, J2365 was developed before touch screens were common in motor vehicles.

As new technology is added to vehicles and traffic congestion increases, there is a concern that drivers will be overloaded. As a result, there has been considerable interest in measuring driver workload. This can be achieved using many methods, with subjective assessments such as the NASA Task Loading Index (TLX) being most popular. Unfortunately, the TLX is unanchored, so there is no way to compare TLX values between studies, thus limiting the value of those evaluations. In response, a method was created to anchor overall workload ratings. To develop this method, 24 subjects rated the workload of clips of forward scenes collected while driving on rural, urban, and limited-access roads in relation to 2 looped anchor clips. Those clips corresponded to Level of Service (LOS) A and E (light and heavy traffic) and were assigned values of 2 and 6 respectively.

This paper explores the potential safety performance of “Future Generation” automated speed control crash avoidance systems for Commercial Vehicles. The technologies discussed in this paper include Adaptive Cruise Control (ACC), second and third generation Forward Collision Avoidance and Mitigation Systems (F-CAM) comprised of Forward Collision Warning (FCW) with Collision Mitigation Braking (CMB) technology as applied to heavy trucks, including single unit and tractor semitrailers. The research [1[ discussed in this paper is from a study conducted by UMTRI which estimated the safety benefits of current and future F-CAM systems and the comparative efficacy of adaptive cruise control. The future generation systems which are the focus of this paper were evaluated at two separate levels of product refinement, “second generation” and “third generation” systems.

This paper contains an analysis of the potential safety benefits of electronic stability control (ESC) for single unit trucks and tractor semitrailers within the U.S. operating environment. It is based on research projects [1,2] which combined hardware-in-the-loop simulation and vehicle testing with the analysis of independent crash datasets using engineering and statistical techniques to estimate the probable safety benefits of stability control technologies for 5-axle tractor-semitrailer vehicles and single unit trucks. The characteristics of ESC-relevant crashes involving these two vehicle classes were found to be very different as were the control strategies needed for crash avoidance. Rollover was the dominant ESC relevant crash type for tractor semitrailers while loss of control was the dominant ESC relevant crash for straight trucks.

This paper (1) summarizes previous human factors/safety research on parking (8 studies, mostly over 20 years old), (2) provides statistics for 10,400 parking-related crashes in Michigan from 2000-2002, and (3) summarizes interviews with 6 insurance agents concerning parking crashes. These sources indicate: 1 About 1/2 to 3/4 of parking crashes involve backing, often into another moving vehicle while emerging from a parking stall. 2 Eight-and-a-half foot-wide stalls had higher crash rates than wider stalls. 3 Most parallel parking crashes occur on major streets, not minor streets. 4 Lighting and driver impairment were minor factors in parking crashes.

This paper provides background and suggestions for safety research for the Army's 21st Century Truck program (21T). The goal of that program is to reduce large truck related fatalities by 50 percent by the year 2010. As background for the proposed research program, this paper contrasts military and civilian trucks and their drivers. Based on that information and considerations of new technology, human factors research needs are identified in the areas of: 1. driver workload measures and assessment 2. collision avoidance and warning systems 3. night vision 4. interface integration 5. baseline studies of driving 6. in-vehicle interfaces 7. alertness monitoring