Estimating vehicle speed by analyzing the acoustic frequency of dashboard camera sound

Dashboard cameras are now widely distributed and help determine the cause of traffic accidents and vehicle speed. The simplest method to calculate the accident vehicle's speed uses a specific section's driving distance and time, determining the average speed. However, we cannot determine whether the vehicle was accelerating or decelerating. In addition, setting the reference point of the specific road section is difficult if the video is too dark or the resolution is too low. Therefore, this study aimed to calculate vehicle speed using sound data from dashboard camera videos. Herein, we suggest a method to calculate the speed of a vehicle in an accident by analyzing the engine sound frequency. Furthermore, our method was verified experimentally and in an actual case. We found that this method could obtain more information than other dashboard camera speed calculations, such as when the vehicle accelerates, decelerates, and shifts gears. However, torque converter slips increased error in the speed calculations. Therefore, we propose using the engine's sound obtained from dashboard camera videos to calculate vehicle speed if the torque converter slip is not severe.

Predictors of traffic events due to hypoglycemia in adults with type 1 diabetes: A Brazilian prospective cohort study

BACKGROUND

Individuals with type 1 diabetes (T1D) are exposed to an elevated risk of automobile accidents especially because of hypoglycemia that impairs physiological and defense responses.

OBJECTIVES

To assess local risk factors for traffic events in T1D adult Brazilian patients.

METHODS

This is a prospective study and 12-month follow-up to assess predictors for traffic events on a cohort of drivers with T1D (n = 168) in Brazil. The inclusion criteria for participants were Brazilian nationality, age ≥ 18 years-old, diagnosis of T1D for more than one year, driving license B, C or D categories (four-wheel vehicles), driving three-times per week or more, and checking blood glucose twice-daily or more. The primary outcome was hypoglycemia driving mishaps assessed by a seven-query questionnaire about the past 30 days. Secondary outcomes included driving mishaps not related to hypoglycemia. Statistical analysis was performed through Poisson regression models with robust variance estimarion, in which the measure of association is the relative risk.

RESULTS

A total of 109 participants completed the 12-month follow-up. Most of them were men (66%) and 37 ± 11 years-old, and had a mean HbA1c of 8.2% (66 mmol/mol). In the follow up, the incidence of traffic events was high (70.6%); however, only a minority was attributed to hypoglycemia as the cause of the reported event (19.3%). The best predictors for new traffic events due to hypoglycemia were those related to driving characteristics. The best of them was a history of episodes of hypoglycemia while driving [RR 3.40 (1.22-9.43); p < 0.05].

CONCLUSIONS

We found that previous episodes of hypoglycemia while driving significantly increase the risk of new traffic events and are the best predictor for it. This highlights the need to assess the risks of traffic accidents especially in people who have had experienced episodes of hypoglycemia while driving.

Hospital-Based Case Series Analysis of Road Traffic Trauma Patients in Sri Lanka

Road traffic accidents claim many lives each year worldwide and cause significant disability among survivors. Resulting socioeconomic burden is severe in low- and middle-income countries. Global emphasis currently focuses on trauma education and prevention in addition to improving post-injury care. Sri Lankan government recently made compulsory legislation to improve the safety standards of imported motor vehicles. Such regulations would not directly protect vulnerable road users (VRUs) who form the main bulk of Sri Lankan and South Asian automobile trauma casualties. With the objective of reviewing the management outcome of automobile trauma in order to correlate the potential impact of new legislation on injury prevention, data of all admitted road traffic injury victims were audited for 2 months. Out of 473 eligible cases (332 (70.2%)—males; mean age 37.2 years), there were 14 (3%) fatalities. Of 459 (97%) survivors, 77 (16%) suffered major injuries. Twelve out of 14 (85.7%) fatalities, 64 of 77 (83.1%) survivors with major injuries and 263 of 382 (68.8%) cases of lesser injuries were VRUs (p value = 0.02: chi-square). VRUs had a significantly higher mean Injury Severity Score (ISS) of 10.96 ± 8.43 SD than non-VRUs who had a mean ISS of 8.14 ± 6.04 SD (p = 0.003: t test). Among all survivors, 33/39 (84.6%) with permanent disability, 95/110 (86.4%) with temporary disability and 199/310 (64.2%) with no residual disability were VRUs (p value < 0.0001: chi-square). Of 222 drivers/riders, 45 (20.3%) had consumed alcohol prior to the incident and 20 (9%) were driving without a valid licence. Thirty-four out of 162 (21%) motor bike travellers were not wearing a protecting helmet. Results denote that VRUs suffer significant majority of the fatalities and major injuries after road traffic trauma and to have higher residual temporary/permanent disability among survivors. Recent compulsory motor vehicle safety measures are unlikely to directly protect majority of automobile trauma victims in Sri Lanka. To obtain a higher impact on road traffic injury prevention, main emphasis has to be given to improve the safety standards of VRUs in developing countries.

Stroke while driving: Frequency and association with automobile accidents

Background Cardiovascular events while driving have occasionally been reported. In contrast, there have been few studies on stroke while driving. Aim The objectives of this study were to (1) report the frequency of stroke while driving and (2) evaluate its association with automobile accidents. Methods Clinical data prospectively acquired between January 2011 and December 2016 on 2145 stroke patients (1301 with ischemic stroke, 585 with intracerebral hemorrhage, and 259 with subarachnoid hemorrhage) were reviewed to identify patients who sustained a stroke while driving. The ratio of driving to performing other activities was evaluated for each stroke type. Furthermore, the drivers' response to stroke was reviewed to understand how automobile accidents occurred. Results Among the 2145 patients, 85 (63 ischemic stroke, 20 intracerebral hemorrhage, and 2 subarachnoid hemorrhage) sustained a stroke while driving. The ratio of driving to performing other activities was significantly higher in ischemic stroke (4.8%) than in intracerebral hemorrhage (3.4%) or subarachnoid hemorrhage (0.8%). A majority of drivers either continued driving or pulled over to the roadside after suffering a stroke. However, 14 (16%) patients were involved in automobile accidents. In most patients, an altered mental status due to severe stroke was the presumed cause of the accident. Conclusion Stroke occurred while driving in 4.0% of all strokes and accidents occurred in 16% of these instances.

Risk factors for automobile accidents caused by falling asleep while driving in obstructive sleep apnea syndrome

PURPOSE

We examined the risk factors for automobile accidents caused by falling asleep while driving in subjects with obstructive sleep apnea syndrome (OSAS).

METHODS

We asked licensed drivers with history of snoring and excessive daytime sleepiness who had undergone polysomnography (PSG) at the Department of Sleep Medicine/Sleep Disorders Center at Aichi Medical University Hospital to complete the questionnaires on accidents caused by falling asleep while driving. As a subjective measure of sleepiness, we used the Epworth sleepiness scale (ESS). Based on PSG results, 2387 subjects diagnosed with OSAS were divided into three groups according to apnea-hypopnea index (AHI): mild-to-moderate (5 ≤ AHI < 30), severe (30 ≤ AHI < 60), and very severe (AHI ≥ 60). We performed univariate and multivariate logistic regression on variables that might explain falling asleep at the wheel.

RESULTS

We compared results between each group and simple snorers (394 subjects with AHI < 5) and found the group with very severe OSAS reported significantly higher rates of driving when drowsy and having accidents in the past 5 years due to falling asleep.

CONCLUSIONS

Our multivariate analysis suggests that scores on the ESS and patient-reported frequency of feeling drowsy while regular driving and working are related to automobile accidents caused by falling asleep while driving.