Can driving condition prompt systems improve passenger comfort of intelligent vehicles? A driving simulator study

2021 ◽  
Vol 81 ◽  
pp. 240-250
Author(s):  
Yuxi Guo ◽  
Qinyu Sun ◽  
Yanqi Su ◽  
Yingshi Guo ◽  
Chang Wang
Keyword(s):  
Driving Simulator ◽  
Intelligent Vehicles ◽  
Passenger Comfort ◽  
Driving Condition ◽  
Simulator Study

scholarly journals How Do Drivers Respond to Silent Automation Failures? Driving Simulator Study and Comparison of Computational Driver Braking Models

2019 ◽  
Vol 62 (7) ◽  
pp. 1212-1229
Author(s):  
Giulio Bianchi Piccinini ◽  
Esko Lehtonen ◽  
Fabio Forcolin ◽  
Johan Engström ◽  
Deike Albers ◽  
...  
Keyword(s):  
Prediction Model ◽  
Computational Models ◽  
Driving Simulator ◽  
Reaction Times ◽  
Automated System ◽  
Cruise Control ◽  
Automated Driving ◽  
Driver Response ◽  
Driving Condition ◽  
Simulator Study

Objective This paper aims to describe and test novel computational driver models, predicting drivers’ brake reaction times (BRTs) to different levels of lead vehicle braking, during driving with cruise control (CC) and during silent failures of adaptive cruise control (ACC). Background Validated computational models predicting BRTs to silent failures of automation are lacking but are important for assessing the safety benefits of automated driving. Method Two alternative models of driver response to silent ACC failures are proposed: a looming prediction model, assuming that drivers embody a generative model of ACC, and a lower gain model, assuming that drivers’ arousal decreases due to monitoring of the automated system. Predictions of BRTs issued by the models were tested using a driving simulator study. Results The driving simulator study confirmed the predictions of the models: (a) BRTs were significantly shorter with an increase in kinematic criticality, both during driving with CC and during driving with ACC; (b) BRTs were significantly delayed when driving with ACC compared with driving with CC. However, the predicted BRTs were longer than the ones observed, entailing a fitting of the models to the data from the study. Conclusion Both the looming prediction model and the lower gain model predict well the BRTs for the ACC driving condition. However, the looming prediction model has the advantage of being able to predict average BRTs using the exact same parameters as the model fitted to the CC driving data. Application Knowledge resulting from this research can be helpful for assessing the safety benefits of automated driving.

A Driving Simulator Study of the Performance Effects of Low Blood Alcohol Concentration

1996 ◽  
Vol 40 (18) ◽  
pp. 943-946 ◽  
Author(s):  
R. Wade Allen ◽  
Zareh Parseghian ◽  
Anthony C. Stein
Keyword(s):  
Divided Attention ◽  
Driving Simulator ◽  
Blood Alcohol Concentration ◽  
Large Body ◽  
Alcohol Concentration ◽  
Blood Alcohol ◽  
Performance Effects ◽  
Driving Task ◽  
Simulator Study ◽  
And Performance

There is a large body of research that documents the impairing effect of alcohol on driving behavior and performance. Some of the most significant alcohol influence seems to occur in divided attention situations when the driver must simultaneously attend to several aspects of the driving task. This paper describes a driving simulator study of the effect of a low alcohol dose, .055 BAC (blood alcohol concentration %/wt), on divided attention performance. The simulation was mechanized on a PC and presented visual and auditory feedback in a truck cab surround. Subjects were required to control speed and steering on a rural two lane road while attending to a peripheral secondary task. The subject population was composed of 33 heavy equipment operators who were tested during both placebo and drinking sessions. Multivariate Analysis of Variance showed a significant and practical alcohol effect on a range of variables in the divided attention driving task.

RETRACTED: Impact of Information Bandwidth of In-Vehicle Technologies on Young Drivers’ Attention Maintenance Performance: A Driving Simulator Study

2017 ◽  
Vol 61 (1) ◽  
pp. 1639-1643
Keyword(s):  
Human Factors ◽  
Driving Simulator ◽  
Young Drivers ◽  
Simulator Study ◽  
Vehicle Technologies ◽  
Maintenance Performance

This proceedings paper was inadvertently published after the authors notified the journal of their desire to withdraw the paper from the conference. The paper was not actually presented at the conference. This retraction is being issued at the authors’ request. The Journal, Human Factors, and SAGE apologize to the authors and readers for the inadvertent publication.

Advance Information on the Road: A Simulator Study of the Effect of Road Markings

1976 ◽  
Vol 18 (6) ◽  
pp. 521-532 ◽  
Author(s):  
Harald Witt ◽  
Carl G. Hoyos
Keyword(s):  
Driving Simulator ◽  
Driving Behavior ◽  
Speed Profile ◽  
The Road ◽  
Positive Effects ◽  
Road Signs ◽  
Advance Information ◽  
Simulator Study ◽  
On The Road ◽  
Accident Statistics

Accident statistics and studies of driving behavior have shown repeatedly that curved roads are hazardous. It was hypothesized that the safety of curves could be improved by indicating in advance the course of the road in a more effective way than do traditional road signs. A code of sequences of stripes put on right edge of the pavement was developed to indicate to the driver the radius of the curve ahead. The main characteristic of this code was the frequency of transitions from code elements to gaps between elements. The effect of these markings was investigated on a driving simulator. Twelve subjects drove on simulated roads of different curvature and with different placement of the code in the approach zone. Some positive effects of the advance information could be observed. The subjects drove more steadily, more precisely, and with a more suitable speed profile.

scholarly journals Investigating the impact of Innovative Treatments on Driving Behavior at School Bus Stops: A Driving Simulator Study

2021 ◽  
Author(s):  
Mustafa Suhail Almallah ◽  
Shabna Sayed Mohammed ◽  
Qinaat Hussain ◽  
Wael K. M. Alhajyaseen
Keyword(s):  
Driving Simulator ◽  
Driving Behavior ◽  
School Bus ◽  
School Buses ◽  
Bus Stop ◽  
Typical Condition ◽  
Simulator Study ◽  
And Control ◽  
The Impact ◽  
Traveling Speed

The illegal overtaking/crossing of stopped school buses has been identified as one of the leading causes of students’ injuries and fatalities. The likelihood of students in getting involved in a school bus-related crash increases during loading/unloading. The main objective of this driving simulator study was to study the effectiveness of different treatments in improving students’ safety by reducing the illegal overtaking/crossing of stopped school buses. Treatments used in this research are LED, Road Narrowing and Red Pavement. All proposed treatments were compared with the control condition (i.e., typical condition in the State of Qatar). Seventy-two subjects with valid Qatari driving license were invited to participate in this study. Each subject was exposed to three situations (i.e., Situation 1: the school bus is stopped in the same traveling direction, Situation 2: the school bus is stopped in the opposite traveling direction, Situation 3: the school bus is not present at the bus stop). Results showed that LED and Road Narrowing treatments were effective in reducing the illegal overtaking/crossing of stopped school buses. Moreover, the stopping behavior for drivers in LED and Road Narrowing was more consistent compared to the Red Pavement and control conditions. Finally, LED and Road Narrowing treatments motivated drivers to reduce their traveling speed by 5.16 km/h and 5.11 km/h, respectively, even with the absence of the school bus. Taking into account the results from this study, we recommend the proposed LED and Road Narrowing as potentially effective treatments to improve students’ safety at school bus stop locations.

Head Scanning Behavior Predicts Hazard Detection Safety Before Entering an Intersection

2021 ◽  
pp. 001872082110391
Author(s):  
Steven W. Savage ◽  
Lily Zhang ◽  
Garrett Swan ◽  
Alex R. Bowers
Keyword(s):  
Eye Movements ◽  
Head Movement ◽  
Driving Simulator ◽  
Training Programs ◽  
Relative Importance ◽  
Driver Training ◽  
Hazard Detection ◽  
Simulator Study ◽  
Older Subjects ◽  
Scanning Behavior

Objective We conducted a driving simulator study to investigate scanning and hazard detection before entering an intersection. Background Insufficient scanning has been suggested as a factor contributing to intersection crashes. However, little is known about the relative importance of the head and eye movement components of that scanning in peripheral hazard detection. Methods Eleven older (mean 67 years) and 18 younger (mean 27 years) current drivers drove in a simulator while their head and eye movements were tracked. They completed two city drives (42 intersections per drive) with motorcycle hazards appearing at 16 four-way intersections per drive. Results Older subjects missed more hazards (10.2% vs. 5.2%). Failing to make a scan with a substantial head movement was the primary reason for missed hazards. When hazards were detected, older drivers had longer RTs (2.6s vs. 2.3s), but drove more slowly; thus, safe response rates did not differ between the two groups (older 83%; younger 82%). Safe responses were associated with larger (28.8° vs. 20.6°) and more numerous (9.4 vs. 6.6) gaze scans. Scans containing a head movement were stronger predictors of safe responses than scans containing only eye movements. Conclusion Our results highlight the importance of making large scans with a substantial head movement before entering an intersection. Eye-only scans played little role in detection and safe responses to peripheral hazards. Application Driver training programs should address the importance of making large scans with a substantial head movement before entering an intersection.

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