Drivers’ eye movements as a function of collision avoidance warning conditions in red light running scenarios

The intersection collision avoidance warning systems (ICAWSs) have substantial potentials in improving driving performance and reducing the number and severity of intersection collisions, through helping drivers timely detect hazardous conflicting vehicles in precrash scenarios. However, the influences of ICAWS on drivers’ visual performance have barely been discussed. This study focuses on exploring the patterns in drivers’ eye movements as a function of ICAWS’s warning conditions in red light running scenarios based on a driving simulation experiment. Two types of speech warning conditions including warning timings (varied form 2.5 s to 5.5 s) and directional information (with or without) are examined, and the no-warning condition is the baseline. The results revealed that more subjects would be likely to benefit from the ICWAS under the earlier warning timings. The warning condition of 4.5 s ahead of a collision had the best effectiveness in terms of visual performances. Under such a warning timing, drivers had shorter fixation duration and higher frequency of searching for the red light running (RLR) vehicles. Compared to the warning condition without directional information, the directional warning information could capture drivers’ attention more efficiently, help driver direct fixations toward the RLR vehicles more quickly and lead to more scanning activities. Compared to female drivers, male drivers had more scanning activities when approaching intersections, detected the RLR vehicles more quickly and were more likely to avoid the RLR collisions. Besides, the experiment results indicated that the female drivers were more inclined to trust the warning information and got more benefits from the RLR-ICAWS in terms of the crash risk reduction rate than male drivers. Finally, the conclusions lead the way toward warning condition design recommendations for improving the effectiveness of the RLR-ICAWSs.     

The impact on alcohol-related collisions of the partial decriminalization of impaired driving in British Columbia,Canada

Introduction

The purpose of this paper is to assess the impact of administrative sanctions introduced as part of a new law for drinking drivers in British Columbia, Canada. The new law, known as immediate roadside prohibitions (IRP), aimed to increase the efficiency of police and courts for processing drinking drivers, thereby increasing the certainty of their being apprehended and punished. However, in order to maintain these efficiencies, sanctions under this new law largely replaced laws under the Criminal Code of Canada for Driving While Impaired (DWI) by alcohol, which had more severe penalties but lower certainty of punishment. We examined whether the intervention was related to abrupt significant declines in three types of alcohol-related collisions (i.e. fatalities, injuries or property damage only) compared to the same type of collisions without alcohol involvement.

Methods

An interrupted time series design, with a non-equivalent control was used, testing for an intervention effect. Monthly rates of the three types of collisions with and without alcohol involvement were calculated for the 15-year period before and the 1-year period after implementation of the new law. ARIMA time series analysis was conducted controlling for trend effects, seasonality, autocorrelation, and collisions without alcohol.

Results

Significant average declines (p < 0.05) in alcohol-related collisions were found as follows: 40.4% for fatal collisions, 23.4% for injury collisions and 19.5% for property damage only collisions. No significant effects were found for any of the three comparable non-alcohol-related types of collisions.

Conclusions

These results suggest that provincial law of administrative sanctions for drinking drivers and associated publicity was more effective for minimizing alcohol-related collisions than laws under the Canadian Criminal Code.     

Correlation processing of narrow-spectrum signals with unknown parameters in a passive multiposition instrument for measuring the coordinates of continuous radiation sources

A method of increasing the accuracy characteristics of passive multiposition measuring instruments when receiving narrow-spectrum signals, based on converting the initial signal spectrum in order to narrow the main lobe of the autocorrelation or cross-correlation functions of the received signal, is proposed.Translated from Izmeritelnaya Tekhnika, No. 10, pp. 49–52, October, 2004.     

Examining driver behavior at the onset of yellow in a traffic simulator environment: Comparisons between random parameters and latent class logit models

This study involves an examination of driver behavior at the onset of a yellow signal indication. Behavioral data were obtained from a driving simulator study that was conducted through the National Advanced Driving Simulator (NADS) laboratory at the University of Iowa. These data were drawn from a series of events during which study participants drove through a series of intersections where the traffic signals changed from the green to yellow phase. The resulting dataset provides potential insights into how driver behavior is affected by distracted driving through an experimental design that alternated handheld, headset, and hands-free cell phone use with “normal” baseline driving events. The results of the study show that male drivers ages 18–45 were more likely to stop. Participants were also more likely to stop as they became more familiar with the simulator environment. Cell phone use was found to some influence on driver behavior in this setting, though the effects varied significantly across individuals. The study also demonstrates two methodological approaches for dealing with unobserved heterogeneity across drivers. These include random parameters and latent class logit models, each of which analyze the data as a panel. The results show each method to provide significantly better fit than a pooled, fixed parameter model. Differences in terms of the context of these two approaches are discussed, providing important insights as to the differences between these modeling frameworks.