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This paper characterizes the capability of a rear-end crash avoidance system based on data collected from a field operational test. The system performs forward crash warning and adaptive cruise control functions. The test consists of 66 subjects who drove 10 equipped vehicles on public roads over 157,000 km. System characterization addresses the ability of the forward-looking sensor suite to maintain in-path target tracking and discern between in-path and out-of-path targets; the efficacy of the alert logic in warning the driver to driving conflicts that may lead to rear-end crashes; and the visibility, audibility, and readability of information displayed by the driver-vehicle interface.

This paper presents recent results of on-going research to build new maps of driver performance in car-following situations. The novel performance map is comprised of four driving states: low risk, conflict, near crash, and crash imminent - which correspond to advisory warning, crash imminent warning, and crash mitigation countermeasures. The paper addresses two questions dealing with the approach to quantify the boundaries between the driving states: (1) Do the quantified boundaries strongly depend on the dynamic scenario encountered in the driving environment? and (2) Do the quantified boundaries vary between steering and braking driver responses? Specifically, braking and steering driver performances are examined in two car-following scenarios: lead vehicle stopped and lead vehicle moving at lower constant speed.

This paper describes an algorithm that identifies the state of traffic ahead of a moving vehicle using onboard sensors. This algorithm approximates the level of service as defined in the Highway Capacity Manual, which portrays a range of traffic conditions on a particular type of roadway facility. The traffic state forms an independent variable in an evaluation plan to assess the benefits and capability of an automotive rear-end crash avoidance system in a field operational test. The algorithm utilizes inputs from vehicle sensors, onboard radar, global positioning system, and digital map to classify the traffic ahead into light, medium, and heavy states. Basically, the algorithm segregates the roadway into four different categories based on the road type (freeway or non-freeway), posted speed limit, and traffic flow conditions.

This paper describes the safety evaluation results from a Field Operational Test (FOT) of an Intelligent Cruise Control (ICC) system. The primary goal of this evaluation was to determine safety effects of the ICC system. Safety surrogate measures were established and examined for normal driving situations as well as for safety–critical situations. It was found that use of the ICC system in the FOT was generally associated with safer driving compared to manual control and is projected to result in net safety benefits if widely deployed.

The potential safety benefits of an Intelligent Cruise Control (ICC) system are assessed in terms of the number of rear-end crashes that might be avoided on U.S. freeways if all vehicles were equipped with such a system. This analysis utilizes naturalistic driving data collected from a field operational test that involved 108 volunteers who drove ten passenger cars for about 68 and 35 thousand miles in manual and ICC control modes, respectively. The effectiveness of the ICC system is estimated at about 17 percent based on computer simulations of two rear-end precrash scenarios that are distinguished by whether the following vehicle encounters a suddenly-decelerating or slow-moving lead vehicle. The ICC system has the potential to eliminate approximately 13 thousand policereported rear-end crashes on U.S. freeways, using 1996 national crash statistics.

This paper describes the concept of using state space boundaries to evaluate the safety effects of longitudinal collision avoidance systems from data produced in field operational tests. The boundaries are represented in terms of the relative range and range rate between a lead vehicle and the vehicle hosting the collision avoidance system. Phase plane diagrams are used to illustrate the state space boundaries. Parameters of curves representing the boundaries were selected such that the boundaries would be fairly well distributed over the range vs. range-rate space with the ones closer to the horizontal axis (range = 0) being indicative of a relatively higher hazard potential. The application of these state space boundaries is examined with data available from a recently completed field operational test sponsored by the National Highway Traffic Safety Administration.