Dataset Information

Driving With Hemianopia X: Effects of Cross Traffic on Gaze Behaviors and Pedestrian Responses at Intersections.

ABSTRACT:

Purpose

We conducted a driving simulator study to investigate the effects of monitoring intersection cross traffic on gaze behaviors and responses to pedestrians by drivers with hemianopic field loss (HFL).

Methods

Sixteen HFL and sixteen normal vision (NV) participants completed two drives in an urban environment. At 30 intersections, a pedestrian ran across the road when the participant entered the intersection, requiring a braking response to avoid a collision. Intersections with these pedestrian events had either (1) no cross traffic, (2) one approaching car from the side opposite the pedestrian location, or (3) two approaching cars, one from each side at the same time.

Results

Overall, HFL drivers made more (p < 0.001) and larger (p = 0.016) blind- than seeing-side scans and looked at the majority (>80%) of cross-traffic on both the blind and seeing sides. They made more numerous and larger gaze scans (p < 0.001) when they fixated cars on both sides (compared to one or no cars) and had lower rates of unsafe responses to blind- but not seeing-side pedestrians (interaction, p = 0.037). They were more likely to demonstrate compensatory blind-side fixation behaviors (faster time to fixate and longer fixation durations) when there was no car on the seeing side. Fixation behaviors and unsafe response rates were most similar to those of NV drivers when cars were fixated on both sides.

Conclusion

For HFL participants, making more scans, larger scans and safer responses to pedestrians crossing from the blind side were associated with looking at cross traffic from both directions. Thus, cross traffic might serve as a reminder to scan and provide a reference point to guide blind-side scanning of drivers with HFL. Proactively checking for cross-traffic cars from both sides could be an important safety practice for drivers with HFL.

SUBMITTER: Xu J

PROVIDER: S-EPMC9309302 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:PurposeVehicle-pedestrian conflicts are common at road intersections when traffic lights change. However, the impact of traffic light on transportation safety and efficiency remains poorly understood.MethodsA two-stage study was used to survey the proportion of intersections with conflicting traffic lights and the related transportation efficiency and safety were evaluated as well. First, a cross-sectional study estimated the proportion of signalized intersections with conflicting left-turning vehicle-pedestrian traffic lights in Changsha city, China. Second, a natural experiment compared transportation efficiency and safety between intersections with and without conflicting left-turning vehicle-pedestrian traffic lights. Risky conflicts, where motor vehicles violated laws and failed to yield to pedestrians in crosswalk were used as a surrogate for transportation safety. The number of motor vehicles and pedestrians passing through the intersections per second and per meter were used to estimate transportation efficiency. Data were collected and analyzed in 2015 (from March to December). A search of online news from domestic media sources was also conducted to collect pedestrian injury data occurring at the intersections.ResultsAbout one-fourth (57/216) intersections had conflicting left-turning traffic lights (95% CI: 20.5%, 32.3%). Risky vehicle-pedestrian conflicts were more frequently observed at intersections with conflicting lights compared to those without (incidence rate ratio (IRR) = 3.13; pedestrians: IRR = 4.02), after adjusting for type of day (weekday vs. weekend), the time period of observation, and motor vehicles traffic flow. Intersections without conflicting vehicle-pedestrian traffic lights had similar transportation efficiency to those with conflicting lights after controlling for covariates (p > 0.05). The systematic review of news media reports yielded 10 left-turning vehicle-pedestrian crash events between 2011 and 2017, involving 11 moderate or severe pedestrian injuries and 3 fatal pedestrian injuries.ConclusionOver one-fourth of road intersections in Changsha city, China have conflicting left-turning traffic lights. Conflicting traffic lights cannot improve transportation efficiency, but increase risky conflicts between vehicles and pedestrians.

Project description:ObjectiveRoad traffic injuries (RTIs) are recognized as one of the most important causes of morbidity and mortality throughout the world, especially in developing countries. Human behavior is reportedly one of the critical factors in the occurrence of such injuries. The purpose of this study is to evaluate the correlation of abnormal driving behaviors with the frequency and severity of RTIs among drivers in Hamadan, west of Iran.MethodsThe present cross-sectional study was conducted on 800 people driving, who were selected by multistage cluster sampling technique. Data were collected using a three-part self-administered questionnaire including demographic, social and driving characteristics; the Manchester driver behavior questionnaire (DBQ); as well as information on a history of the occurrence of the injuries caused by the crashes and the severity of them. Data were statistically analyzed using numerical indices, linear regression analysis, Pearson correlation, ordinal logistic regression model and multinomial logistic regression.ResultsThe highest and lowest mean percentages of abnormal driving behavior were related to unintentional violations (19.13) and Lapses (16.44), respectively. "Changing radio stations and listening to music while driving", "overtaking a driver who drives slowly", and "unintentionally exceeding the speed limit" were the three highest behaviors associated with road traffic injuries, with the mean and standard deviation of (1.93 ± 1.4), (1.90±1.4), (1.58±1.3), respectively. Age, gender, educational level, driving experience and driving hours during the day were significantly associated with DBQ dimensions and severity of road traffic injuries.ConclusionsThe results of this study showed that socio-demographic characteristics were significantly correlated with driving behavior. In addition, driving behaviors were correlated with traffic crashes and the resulting injuries. The findings of this study can be utilized to develop driving behavior interventions among the drivers.

Project description:Human performance in natural environments is deeply impressive, and still much beyond current AI. Experimental techniques, such as eye tracking, may be useful to understand the cognitive basis of this performance, and "the human advantage." Driving is domain where these techniques may deployed, in tasks ranging from rigorously controlled laboratory settings through high-fidelity simulations to naturalistic experiments in the wild. This research has revealed robust patterns that can be reliably identified and replicated in the field and reproduced in the lab. The purpose of this review is to cover the basics of what is known about these gaze behaviors, and some of their implications for understanding visually guided steering. The phenomena reviewed will be of interest to those working on any domain where visual guidance and control with similar task demands is involved (e.g., many sports). The paper is intended to be accessible to the non-specialist, without oversimplifying the complexity of real-world visual behavior. The literature reviewed will provide an information base useful for researchers working on oculomotor behaviors and physiology in the lab who wish to extend their research into more naturalistic locomotor tasks, or researchers in more applied fields (sports, transportation) who wish to bring aspects of the real-world ecology under experimental scrutiny. Part of a Research Topic on Gaze Strategies in Closed Self-paced tasks, this aspect of the driving task is discussed. It is in particular emphasized why it is important to carefully separate the visual strategies driving (quite closed and self-paced) from visual behaviors relevant to other forms of driver behavior (an open-ended menagerie of behaviors). There is always a balance to strike between ecological complexity and experimental control. One way to reconcile these demands is to look for natural, real-world tasks and behavior that are rich enough to be interesting yet sufficiently constrained and well-understood to be replicated in simulators and the lab. This ecological approach to driving as a model behavior and the way the connection between "lab" and "real world" can be spanned in this research is of interest to anyone keen to develop more ecologically representative designs for studying human gaze behavior.