scholarly journals Some On-Road Glances are More Equal Than Others: Measuring Engagement in the Driving Task

2019 ◽  
Vol 63 (1) ◽  
pp. 1986-1990
Author(s):  
Liberty Hoekstra-Atwood ◽  
David Prendez ◽  
John L. Campbell ◽  
Christian M. Richard
Keyword(s):  
System Design ◽  
Eye Movement ◽  
Task Analysis ◽  
Driver Distraction ◽  
Driver Training ◽  
Video Recordings ◽  
Infrastructure Design ◽  
Driving Scenario ◽  
Driving Task ◽  
Machine Interface

The current work examines a methodology developed for assessing driver attention management using high-precision eye glances towards safety-relevant driving information. The Task Analysis Eye Movement Overlay (TAEMO) method uses task analyses, video recordings of a driving scenario, and eye glance data toward visual keys that drivers sample during the driving scenario to directly measure driver engagement. This methodology has applications for evaluating infrastructure design, driver impairment assessment, driver training, driver distraction research, and vehicle human-machine interface (HMI) system design.

The Effects of Telematics on Driver Distraction

2002 ◽  
Vol 46 (22) ◽  
pp. 1868-1870 ◽  
Author(s):  
Patrick Siebert ◽  
Mustapha Mouloua ◽  
Kendra Burns ◽  
Jennifer Marino ◽  
Lora Scagliola ◽  
...  
Keyword(s):  
Secondary Task ◽  
Cell Phone ◽  
Driving Simulator ◽  
Systems Design ◽  
Driver Distraction ◽  
Cellular Phones ◽  
Driver Safety ◽  
A Cell ◽  
Driving Task ◽  
Simulated Driving Task

This study used both cellular phones and analogue radio to measure driver distraction and workload in a low fidelity driving simulator. Thirty-four participants performed a simulated driving task while using either a cell phone or a radio in conjunction with a secondary task assessing their spare attentional capacity. The results showed that more lane deviations were made during the cell phone and radio tuning use than both of the pre-allocation and Post-allocation phases. The secondary task errors were also higher during both the cell phone and radio tuning allocation phase than the pre-allocation and post-allocation phases. These findings indicate the greater workload load levels associated with the use of telemetric devices. These findings have major implications for driver safety and telemetric systems design.

The development of a graphical man-machine interface for computer-aided control system design

1986 ◽  
Vol 18 (7) ◽  
pp. 395 ◽  
Author(s):  
H.A. Barker ◽  
M. Chen ◽  
P.W. Grant ◽  
C.P. Jobling ◽  
P. Townsend
Keyword(s):  
Control System ◽  
System Design ◽  
Control System Design ◽  
Computer Aided ◽  
Machine Interface ◽  
Man Machine Interface

A Methodology for Predicting Crew Workload in New Weapon Systems

1986 ◽  
Vol 30 (7) ◽  
pp. 633-637 ◽  
Author(s):  
Theodore B. Aldrich ◽  
Sandra M. Szabo
Keyword(s):  
System Design ◽  
Flight Control ◽  
Computer Models ◽  
Human Operator ◽  
Weapon Systems ◽  
Single Operator ◽  
Machine Interface ◽  
Man Machine Interface ◽  
Operator Workload ◽  
Total Workload

The Army currently is evaluating the feasibility of single-crewmember operation of a multipurpose, lightweight helicopter, designated the LHX. To determine if a single operator can perform the LHX scout and attack missions, 29 mission segments were analyzed for excessive workload. The mission segments were divided into flight control, support, and mission functions; the functions were divided into performance elements (tasks) and were positioned on mission segment timelines. For each performance element, the man-machine interface was identified and estimates of the visual, auditory, cognitive, and psychomotor components of workload were assigned. The mission/task/workload data were used to build one- and two-crewmember computer models designed to predict total workload and to identify overloads in each mission segment. Two baseline analyses were conducted to predict workload under low-automation conditions for one- and two-crewmember LHX configurations. In addition, iterative analyses were conducted to predict the reduction in workload associated with each of 26 individual automation options and 16 combinations of options. The methodology provides a systematic means of predicting human operator workload in advance of system design.

scholarly journals Influence of Adaptive Human–Machine Interface on Electric-Vehicle Range-Anxiety Mitigation

2020 ◽  
Vol 4 (1) ◽  
pp. 4
Author(s):  
Antonyo Musabini ◽  
Kevin Nguyen ◽  
Romain Rouyer ◽  
Yannis Lilis
Keyword(s):  
Electric Vehicle ◽  
Autonomous Vehicle ◽  
Human Machine Interface ◽  
Traffic Light ◽  
Automated Driving ◽  
Range Anxiety ◽  
Driving Task ◽  
Machine Interface ◽  
Emergency Stop ◽  
Save Energy

The electrification of vehicles is without a doubt one of the milestones of today’s automotive technology. Even though industry actors perceive it as a future standard, acceptance, and adoption of this kind of vehicles by the end user remain a huge challenge. One of the main issues is the range anxiety related to the electric vehicle’s remaining battery level. In the scope of the H2020 ADAS&ME project, we designed and developed an intelligent Human Machine Interface (HMI) to ease acceptance of Electric Vehicle (EV) technology. This HMI is mounted on a fake autonomous vehicle piloted by a hidden joystick (called Wizard of Oz (WoZ) driving). We examined 22 inexperienced EV drivers during a one-hour driving task tailored to generate range anxiety. According to our protocol, once the remaining battery level started to become critical after manual driving, the HMI proposed accurate coping techniques to inform the drivers how to reduce the power consumption of the vehicle. In the following steps of the protocol, the vehicle was totally out of battery, and the drivers had to experience an emergency stop. The first result of this paper was that an intelligent HMI could reduce the range anxiety of the driver by proposing adapted coping strategies (i.e., transmitting how to save energy when the vehicle approaches a traffic light). The second result was that such an HMI and automated driving to a safe spot could reduce the stress of the driver when an emergency stop is necessary.

scholarly journals The Role of Cue Utilization during a Simulated Driving Scenario

2019 ◽  
Vol 63 (1) ◽  
pp. 848-852
Author(s):  
Daniel Sturman ◽  
Mark W. Wiggins
Keyword(s):  
Performance Metrics ◽  
Cerebral Oxygenation ◽  
Driving Performance ◽  
Cognitive Resources ◽  
Cue Utilization ◽  
Simulated Driving ◽  
Driving Scenario ◽  
Driving Task ◽  
And Performance ◽  
Simulated Driving Task

The present study was designed to establish whether a cue-based assessment of driving could predict cognitive load and performance during a simulated driving task. Following an assessment of cue utilization in the domain of driving, participants completed a moderate workload simulated driving task, during which cerebral oxygenation, eye behavior, and driving performance metrics were recorded. During the simulated driving task, participants with higher cue utilization recorded smaller increases in cerebral oxygenation in the prefrontal cortex relative to baseline, and smaller mean fixation dispersions, compared to participants with lower cue utilization. There were no statistically significant differences in the number of speed exceedances nor missed traffic signals based on cue utilization. These outcomes suggest that participants with higher cue utilization were able to allocate fewer cognitive resources to the simulated driving task, while maintaining an equivalent level of driving performance, compared to participants with lower cue utilization.

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