Refine Your Search

Search Results

Viewing 1 to 9 of 9
Technical Paper

Identification of Traffic States From Onboard Vehicle Sensors

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.
Technical Paper

Characterizing the Capability of a Rear-End Crash Avoidance System

This paper presents a framework to characterize the capability of an automotive rear-end crash avoidance system that integrates forward crash warning and adaptive cruise control functionalities. This system characterization describes the operational performance of the system and its main components in the driving environment, based on data to be collected from instrumented vehicles driven by volunteer subjects as their own vehicles under real-world conditions. This characterization is pursuing a number of objectives dealing with the capability of system components including the forward-looking sensor suite, alert logic, automatic vehicle controls, and driver-vehicle interface. A number of subobjectives and concomitant measures are delineated. Examples are provided to illustrate the analysis process of this framework based on data recently collected from system verification tests.
Technical Paper

Exploratory Analysis of Pre-Crash Sensing Countermeasures

This paper presents results from an exploratory analysis of pre-crash sensing countermeasures. This analysis consists of a technology review, development of a methodology to estimate safety benefits based on the total harm concept, identification of crashworthiness scenarios and their harm units, and estimation of safety benefits for brake assist and driver seat position adjustment. Using 1996-2003 Crashworthiness Data System databases, crashworthiness scenarios and harm units of passenger cars are identified from a crash analysis of all single event frontal impacts by combining codes from six variables: frontal impact offset, air bag deployment, seat belt use, driver weight, seat track position, and Delta V. Preliminary results show that brake assist and driver seat position adjustment have the potential to reduce the total harm of passenger cars involved in rear-end crashes.
Technical Paper

Driver/Vehicle Characteristics in Rear-End Precrash Scenarios Based on the General Estimates System (GES)

Dynamically-distinct precrash scenarios in rear-end collisions were identified in a recent study conducted by the Volpe National Transportation Systems Center, of the United States Department of Transportation, Research and Special Programs Administration, in conjunction with the National Highway Traffic Safety Administration (NHTSA) using NHTSA's General Estimates System (GES) crash database from 1992 through 1996. Precrash scenarios represent vehicle dynamics immediately prior to a collision. This paper provides a statistical description of the five most frequently-occurring rear-end precrash scenarios in terms of vehicle and driver characteristics, using the 1996 GES database.
Technical Paper

Safety Evaluation Results from the Field Operational Test of an Intelligent Cruise Control (ICC) System

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.
Technical Paper

Estimation of Crash Injury Severity Reduction for Intelligent Vehicle Safety Systems

A novel methodology is presented to estimate the safety benefits of intelligent vehicle safety systems in terms of reductions in the number of collisions and the number and severity of crash-related injuries. In addition, mathematical models and statistics are provided to support the estimation of the crash injury reduction factor in rear-end, lane change, and single vehicle roadway departure collisions. Simple models based on Newtonian mechanics are proposed to derive Δv, the change in speed that a vehicle undergoes as a consequence of crashing. Statistics on the distribution of vehicle types and weights in the United States are supplied, which are needed for Δv estimation. Moreover, mathematical equations are derived to estimate the average harm per collision. Finally, statistics on the average harm per occupant are obtained from the 1994 and 1995 Crashworthiness Data System crash databases.
Technical Paper

Safety Benefits Estimation of an Intelligent Cruise Control System Using Field Operational Test Data

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.
Technical Paper

Analysis of Off-Roadway Crash Countermeasures for Intelligent Vehicle Applications

This paper analyzes off-roadway crash countermeasure systems in support of the United States (U.S.) Department of Transportation's Intelligent Vehicle Initiative. Off-roadway crashes transpire when a moving vehicle departs the travel roadway and then experiences its first harmful event. This paper defines off-roadway crashes and describes their pre-crash scenarios and crash contributing factors. This information is then utilized to develop countermeasure concepts and concomitant functional requirements to warn drivers of imminent road edge crossing or vehicle control loss on straight or curved roadways. A technology survey follows to assess the status of state-of-the-art technologies within the categories of vehicle-based, infrastructure-based, or cooperative vehicle-infrastructure systems. This paper concludes with forecasts of the progression of future countermeasure systems towards the realm of cooperative technologies.
Technical Paper

Analysis of Braking and Steering Performance in Car-Following Scenarios

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.