Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Jeff Allen Greenberg is active.

Publication


Featured researches published by Jeff Allen Greenberg.


Transportation Research Record | 2003

Driver Distraction: Evaluation with Event Detection Paradigm

Jeff Allen Greenberg; Louis Tijerina; Reates Curry; Bruce Artz; Larry Cathey; Dev S. Kochhar; Ksenia Kozak; Mike Blommer; Peter R. Grant

The effects of eight in-vehicle tasks on driver distraction were measured in a large, moving-base driving simulator. Forty-eight adults, ranging in age from 35 to 66, and 15 teenagers participated in the simulated drive. Hand-held and hands-free versions of phone dialing, voicemail retrieval, and incoming calls represented six of the eight tasks. Manual radio tuning and climate control adjustment were also included to allow comparison with tasks that have traditionally been present in vehicles. During the drive the participants were asked to respond to sudden movements in surrounding traffic. The driver’s ability to detect these sudden movements or events changed with the nature of the in-vehicle tasks that were being performed. Driving performance measures such as lane violations and heading error were also computed. The performance of the adult group was compared with the performance of the teenage drivers. Compared with the adults, the teens were found to choose unsafe following distances, have poor vehicle control skills, and be more prone to distraction from hand-held phone tasks.


Human Factors and Ergonomics Society Annual Meeting : 16/10/2006 - 20/10/2006 | 2006

Evaluation of Lane Departure Warnings for Drowsy Drivers

Ksenia Kozak; Jochen Pohl; Wolfgang Birk; Jeff Allen Greenberg; Bruce Artz; Mike Blommer; Larry Cathey; Reates Curry

Lane departure warning (LDW) is a driver warning system designed to reduce the number of unintended lane departures. We addressed warning effectiveness and customer acceptance when the unintended lane departures are the result of drowsy driving. Thirty-two adults who were sleep deprived for 23 hours participated in the study and drove Fords VIRTTEX driving simulator. Four Human Machine Interfaces (HMI) for LDW were evaluated: Steering Wheel Torque, Rumble Strip Sound, Steering Wheel Vibration and Head Up Display. A yaw deviation technique was used to produce controlled lane departures in the first two hours of the drive while for the last 20 minutes driver-initiated lane departures were analyzed. The Steering Wheel Vibration HMI, accompanied by Steering Wheel Torque, was found to be the most effective HMI for LDW in a group of drowsy drivers, with faster reaction times and smaller lane excursions. The Vibration HMI was also perceived by the drowsy drivers to be acceptable and helpful.


Proceedings of the Human Factors and Ergonomics Society Annual Meeting | 2000

Surrogate Measures of Visual Demand while Driving

Eugene Farber; Myra Blanco; Jim Foley; Reates Curry; Jeff Allen Greenberg; Colleen Serafin

A driving simulator study involving a total of 40 participants was conducted in one dynamic and two static data collection environments: driving in the simulator, parked in the simulator and in a static test mock-up. Participants were asked to perform tasks on a navigation system, a cellular telephone and a compact disk player. Total task time was measured in all environments and lane violations were measured in the dynamic environment. Task times measured in the static environments were found to be good predictors of both dynamic task time and lane violations.


Proceedings of the Human Factors and Ergonomics Society Annual Meeting | 2005

Leading Indicators of Drowsiness in Simulated Driving

Ksenia Kozak; Reates Curry; Jeff Allen Greenberg; Bruce Artz; Mike Blommer; Larry Cathey

Drowsiness while driving was measured using three measures: a physiological measure of eye closure, a sustained reaction time task and a subjective assessment. The study was conducted in Fords VIRTTEX driving simulator. Thirty-two adults who were sleep deprived for 24 hours and six adults who had a full night of sleep participated in the study. The performance of the sleep-deprived group was compared with that of the control group. Sleep-deprived drivers had significantly longer PVT reaction times, a greater number of lapses, higher PERCLOS values and perceived themselves as sleepier than did the control group. This study demonstrated the ability to successfully implement drowsiness measures in a driving simulator. The advantage of a three-hour simulator drive in providing increasing levels of drowsiness in each subject was established. These findings provide metrics that can be used to evaluate the efficacy and acceptability of safety systems for drowsy drivers.


Vehicle System Dynamics | 2009

Analysing classes of motion drive algorithms based on paired comparison techniques

Peter R. Grant; Mike Blommer; Bruce Artz; Jeff Allen Greenberg

A paired comparison experiment using 23 subjects was run on the VIRTTEX driving simulator to compare a lane position based motion drive algorithm (MDA) with a classical MDA for a highway speed, lane change manoeuvre. Two different tuning states of the lane position algorithm and four different tuning states for the classical algorithm were tested. The subjective fidelity of the six different motion cases was compared with each other and a Bradley–Terry model was fit to find the fidelity merit of each case. In addition, the driving performance of the subjects for six motion cases was recorded and compared. The motion-tuning cases were selected such that the trade-off in motion quality between overall motion scaling and motion shape distortion (shape-error), as well as the trade-off between lateral specific force and roll-rate motion errors, could be studied. It was found that when the overall scaling is the same, drivers perform better with the lane position algorithm than with the the classical algorithm. A well-tuned, manoeuvre-specific, classical MDA, however, did achieve a subjective fidelity level on a par with the lane position MDA. A generically tuned classical MDA, however, has a significantly reduced fidelity and driving performance when compared with a lane position algorithm with the same scale factor. A strong trade-off between motion shape-errors and overall motion scaling was found. A small increase in motion cue shape-error, combined with an increase in the scale factor from 0.3 to 0.5, led to improved performance and increased subjective fidelity. The results of the experiment also suggest that simulator motion can be improved by reducing the angular-rate shape-error at the expense of the specific force shape-error (while keeping the total normalised shape-error constant).


Transportation Research Record | 2010

Effects of Adaptive Lane Departure Warning System on Driver Response to a Surprise Event

Louis Tijerina; Mike Blommer; Reates Curry; Jeff Allen Greenberg; Dev S. Kochhar; Craig John Simonds; David Watson

A lane departure warning (LDW) system monitors the current lane position of a vehicle and presents a driver alert when one of the vehicles front tires crosses a threshold, for example, the nearest lane line. The primary intent of such warning systems is to prevent or mitigate road departures and related crashes caused by driver distraction or drowsiness. The present evaluation compared adaptive and nonadaptive versions of an LDW system. The adaptive version adapted to the drivers state, whereas the nonadaptive version did not. The adaptive LDW system alerted the driver only if a driver state monitor (DSM) indicated that the driver was looking away from the road ahead for 2 s or longer at about the time when a lane line was crossed. Forty volunteers drove a high-fidelity, moving-base driving simulator in a study to compare driver responses to a surprise lane departure when they used a nonadaptive LDW system and then an adaptive LDW system or vice versa. The results indicated that in the adaptive LDW mode, 13 subjects (34%) either experienced delayed activation of the LDW alert or received no LDW alert at all when they should have, primarily because of both the 2-s rule in the adaptive LDW algorithm and DSM registration issues. The adaptive LDW resulted in significantly larger lane excursions at the onset of the LDW alert compared with those that occurred in the non-adaptive LDW mode. These results highlight the dependence of the performance effects of adaptive systems on system hardware, algorithms, and algorithm parameters.


Transportation Research Record | 2009

Immediate Recall of Driver Warnings in Forward Collision Warning Scenarios

Reates Curry; Mike Blommer; Jeff Allen Greenberg; Louis Tijerina

This paper describes driver recall performance for a forward collision warning (FCW) alert immediately after a critical lead vehicle braking event. A sample of 120 younger and older test participants, balanced by gender, participated in a study of alternative FCW alerts in the Ford Motor Company VIRTTEX driving simulator. A baseline group of participants received no FCW support. Each of the other participants experienced one and only one FCW alert type, visual, auditory, or both. Half of the participants who received an FCW alert had been given knowledge that such a system was in the test vehicle, and half of the participants had been told nothing. A digit-reading distraction task was presented repeatedly during the test drive. The last repetition of this task coincided with the lead vehicle braking event and FCW. Immediately after the event, test participants were asked if they had received a warning and, if so, what they recalled about it. Results were analyzed for those 93 warned test participants who interrupted the digit-reading task to respond to the FCW alert. Approximately 26% of these test participants did not remember receiving a warning at all. Only 58% of the test participants who recollected a warning could accurately recall its modality in all its details, although nearly 90% of those who received the combined audio and video warning recalled at least one of the modalities correctly. Those who received FCW information before the drive had significantly greater recollection than those who were not given any FCW a priori information. Age and gender differences were not statistically significant. The implications of these results are discussed.


Transportation Research Record | 2011

Simulator Study of Effects of Alternative Distraction Mitigation Strategies in Driver Workload Manager

Louis Tijerina; Mike Blommer; Reates Curry; Jeff Allen Greenberg; Dev S. Kochhar; Craig John Simonds; Duncan Watson

This simulator study examined a workload manager developed by Delphi Electronics for the SAVE-IT program and the effects of several different workload mitigation strategies on driver response to a surprise forward collision hazard. The strategies included no in-vehicle task or distraction (baseline); task allowed; task interrupted; and task denied. Forty-eight test participants (24 males and 24 females) between 35 and 55 years of age were randomly assigned in groups of 12 (balanced for gender) to each of the four conditions. Each participant then drove in the Ford VIRTTEX moving-base driving simulator on simulated urban and rural roads and was asked to perform various in-vehicle tasks. During a requested in-vehicle information system task, a vehicle parked on the side of the road would suddenly enter the travel lane, and the drivers response was assessed. Braking response to this critical event indicated no significant differences in mean brake response time as a function of type of mitigation strategy or gender. However, variability in driver responses was significantly less in the task denied condition as compared with the other conditions, possibly because drivers were sensitized to an increased driving demand. Three of 12 test participants in the task interrupted condition showed relatively large brake reaction times attributable to long delays between initial foot motion and braking onset. This delay may indicate an additional delay associated with processing the task interruption and the forward collision warning event itself. Recommendations are provided for further research and for mitigation and driver alerting on the basis of a workload managers assessment of the driving situation.


Journal of the Acoustical Society of America | 2000

An auditory model for the prediction of detection thresholds of impulsive sound events

Scott Amman; Mike Blommer; Jeff Allen Greenberg

Impulsive sound events such as squeaks and rattles experienced in a vehicle can be a major source of customer dissatisfaction. These events almost always occur in the presence of some sort of background noise (e.g., wind, road and powertrain noise). When complete elimination of the impulsive sound event is either not possible, or too costly, the same effect can be had by pushing the level of the sound below the detection threshold. This paper describes the development of an auditory model that has the ability to predict detection thresholds of impulsive sound events in the presence of noise. The model was initially developed using equal‐energy exponentially damped sinusoids with center frequencies of 250, 500, 1000, 2000, 4000 and 8000 Hz mixed with pink noise. It was then validated using four different squeak and rattle sounds each mixed with three background noises recorded in a vehicle (wind, smooth and rough road noise). An up–down Levitt procedure was used for threshold determination. Two subjects pa...


Archive | 2008

Vehicle Information Display And Method

David Watson; Angela L. Watson; Sohel Merchant; Craig Sandvig; Ivette Hernandez; Steven Bishop; Engin Erdogan; Altay Jun Wakui Sendil; Susanne Stage; Ryan J. Skaff; Derek Hartl; James Belloli; Jeff Allen Greenberg; Michael Blommer

Collaboration


Dive into the Jeff Allen Greenberg's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge