Search Results

Many vehicles are currently equipped with active safety systems that can detect vulnerable road users like pedestrians and bicyclists, to mitigate associated conflicts with vehicles. With the advancements in technologies and algorithms, detailed motions of these targets, especially the limb motions, are being considered for improving the efficiency and reliability of object detection. Thus, it becomes important to understand these limb motions to support the design and evaluation of many vehicular safety systems. However in current literature, there is no agreement being reached on whether or not and how often these limbs move, especially at the most critical moments for potential crashes. In this study, a total of 832 pedestrian walking or cyclist biking cases were randomly selected from one large-scale naturalistic driving database containing 480,000 video segments with a total size of 94TB, and then the 832 video clips were analyzed focusing on their limb motions.

As part of active safety systems for reducing bicyclist fatalities and injuries, Bicyclist Pre-Collision System (BPCS), also known as Bicyclist Autonomous Emergency Braking System, is being studied currently by several vehicles manufactures. This paper describes the development of a surrogate bicyclist which includes a surrogate bicycle and a surrogate bicycle rider to support the development and evaluation of BPCS. The surrogate bicycle is designed to represent the visual and radar characteristics of real bicyclists in the United States. The size of bicycle surrogate mimics the 26 inch adult bicycle, which is the most popular adult bicycle sold in the US. The radar cross section (RCS) of the surrogate bicycle is designed based on RCS measurement of the real adult sized bicycles.

Pedestrian Automatic Emergency Braking (PAEB) for helping avoiding/mitigating pedestrian crashes has been equipped on some passenger vehicles. Since approximately 70% pedestrian crashes occur in dark conditions, one of the important components in the PAEB evaluation is the development of standard testing at night. The test facility should include representative low-illuminance environment to enable the examination of the sensing and control functions of different PAEB systems. The goal of this research is to characterize and model light source distributions and variations in the low-illuminance environment and determine possible ways to reconstruct such an environment for PAEB evaluation. This paper describes a general method to collect light sources and illuminance information by processing large amount of potential collision locations at night from naturalistic driving video data.

According to the U.S. National Highway Traffic Safety Administration, 743 pedal cyclists were killed and 48,000 were injured in motor vehicle crashes in 2013. As a novel active safety equipment to mitigate bicyclist crashes, bicyclist Pre-Collision Systems (PCSs) are being developed by many vehicle manufacturers. Therefore, developing equipment for evaluating bicyclist PCS is essential. This paper describes the development of a bicycle carrier for carrying the surrogate bicyclist in bicyclist PCS testing. An analysis on the United States national crash databases and videos from TASI 110 car naturalistic driving database was conducted to determine a set of most common crash scenarios, the motion speed and profile of bicycles. The bicycle carrier was designed to carry or pull the surrogate bicyclist for bicycle PCS evaluation. The carrier is a platform with a 4 wheel differential driving system.

In order to help avoid or mitigate rear-end collisions a Pre-Collision System (PCS) was developed. The purpose of this study is to clarify the Time-to-Collision (TTC) distribution when approaching a lead vehicle under normal driving condition. To enhance the effectiveness of PCS, warnings and/or automatic brake activation should happen as early as possible, however, if too early there is a high possibility of false warnings or activations, which is not desirable. If the distribution of distance to a lead vehicle under normal driving conditions is quantified, an approach limit can be estimated. In this study, we try to clarify a TTC distribution that is approximated by a log-normal distribution. Then, we investigate the Enhanced Time-to-Collision (ETTC) that is the secondary predictive value of TTC. And, we clarify the log-normal distribution of ETTC is a more stable approximator of normal driving than a log-normal distribution of TTC.

Animal-vehicle collision (AVC) is a significant safety issue on American roads. Each year approximately 1.5 million AVCs occur in the U.S., the majority of them involving deer. The increasing use of cameras and radar on vehicles provides opportunities for prevention or mitigation of AVCs, particularly those involving deer or other large animals. Developers of such AVC avoidance/mitigation systems require information on the behavior of encountered animals, setting characteristics, and driver response in order to design effective countermeasures. As part of a larger study, naturalistic driving data were collected in high AVC incidence areas using 48 participant-owned vehicles equipped with data acquisition systems (DAS). Continuous driving data including forward video, location information, and vehicle kinematics were recorded. The respective 11TB dataset contains 35k trips covering 360K driving miles.

EXPERIMENTAL ANALYSIS for the increase of the radiator cooling air has been performed with special attention to the utilization of air pressure in high-speed running conditions. Measurements of pressure distributions at the radiator cooling air intake showed that the prevention of the occurrence of separations around the bumper is the efficient method to increase the cooling air. Furthermore, the optimum configuration for the radiator cooling air discharge has also been experimentally studied using a simplified model which simulates the under part of the engine compartment. These improvements made the vehicle radiator cooling air volume increase 14% under high-speed running conditions.

This paper presents the development of an autonomous on-road vehicle. First the visual guidance system of a newly developed experimental vehicle is described. Then visual navigation algorithms for human-like lane tracking are proposed and their workability is shown with some actual navigation test results. Finally discussions are made on the feasibility of visual navigation technology.