Effect Evaluation of Forward Collision Warning System Using IoT Log and Virtual Driving Simulation Data

Advanced driver-assistance systems (ADAS) are primarily known for their positive impact in improving the safety of drivers. Previous studies primarily analyzed the positive effects of ADAS with short-term experiments and accident data without considering the long-term changes in drivers’ safety perception. The human factor is the most dominant among factors that cause traffic accidents, and safety effect evaluation should be performed considering changes in human errors. To this end, this study classified the safety effect of ADAS-forward collision warning (FCW) on taxi drivers in Seoul into behavioral control and attitude change to perform analysis on respective factors. With regard to behavioral control, virtual driving simulation was used to analyze the reaction time of drivers and deceleration rate, and for attitude change, autoregressive integrated moving average (ARIMA) time series analysis was employed to predict the long-term perception change of drivers. The analysis results indicated that, in terms of behavioral control, ADAS-FCW reduces the cognitive reaction time of drivers in risk situations on the road, similar to the findings in previous studies. However, in terms of attitude change, ADAS-FCW has the adverse long-term effect of increasing violations in maintaining safety distance in the case of nighttime-drivers under 60 years old. As can be seen from these results, new technologies in the road safety arena can have a short-term effect of improving safety with behavioral control but may have a negative impact in the long term. The results of this study are expected to provide a theoretical basis for reference in the safety evaluation of ADAS and traffic safety facilities.

Assessing pavement conditions and their effect on road safety: Ontario experience

The increasing need to rebuild and repair Ontario highways has motivated this research aimed at maximizing the efficiency of pavement maintenance and design. The first of two complementary objectives were to evaluate the safety improvements of reduced pavement roughness on two-lane undivided Ontario highways using the Empirical Bayes and Cross-Sectional analysis methods. The second objective was to improve the prediction of pavement distress and surface roughness by examining the impact of local calibration of prediction models. The findings suggest that better pavement conditions can reduce the severity of fatal and injury collisions by as much as 12% in some cases and therefore that pavement maintenance decisions should incorporate road safety when assessing cost-life analysis. The results provide a basis for those decisions in that they can be used to estimate the safety effect of a specific improvement in roughness.

Assessing pavement conditions and their effect on road safety: Ontario experience

The increasing need to rebuild and repair Ontario highways has motivated this research aimed at maximizing the efficiency of pavement maintenance and design. The first of two complementary objectives were to evaluate the safety improvements of reduced pavement roughness on two-lane undivided Ontario highways using the Empirical Bayes and Cross-Sectional analysis methods. The second objective was to improve the prediction of pavement distress and surface roughness by examining the impact of local calibration of prediction models. The findings suggest that better pavement conditions can reduce the severity of fatal and injury collisions by as much as 12% in some cases and therefore that pavement maintenance decisions should incorporate road safety when assessing cost-life analysis. The results provide a basis for those decisions in that they can be used to estimate the safety effect of a specific improvement in roughness.

Observational Before and After Safety Study of Installing Signals at Rural Intersections: Using the Empirical Bayes (EB) and Conventional Methods

Signalizing an intersection usually results in a reduction in right-angle and left-turn crashes, and an increase in rear-end crashes. This study used the conventional and Empirical Bayes (EB) before and after methods on 45 treated sites (converted from stop to signal control) in California and Minnesota to estimate the safety effect of having signals installed. The results confirm the belief that right-angle and left-turn crashes are reduced and rear-end crashes increase. However, these effects cannot be used to quantitatively assess the benefit gained from the reduction in right-angle and left-turn crashes against the increase in rear-end crashes, simply because crash types have different severities. By performing an economic examination of the safety effects, this study was able to show that by installing signals on 45 treated sites, there was a positive aggregate economic benefit of $155,883,978 which represents a 69 percent reduction in cost. This translated into $616,142 per site-year.

Observational Before and After Safety Study of Installing Signals at Rural Intersections: Using the Empirical Bayes (EB) and Conventional Methods

Signalizing an intersection usually results in a reduction in right-angle and left-turn crashes, and an increase in rear-end crashes. This study used the conventional and Empirical Bayes (EB) before and after methods on 45 treated sites (converted from stop to signal control) in California and Minnesota to estimate the safety effect of having signals installed. The results confirm the belief that right-angle and left-turn crashes are reduced and rear-end crashes increase. However, these effects cannot be used to quantitatively assess the benefit gained from the reduction in right-angle and left-turn crashes against the increase in rear-end crashes, simply because crash types have different severities. By performing an economic examination of the safety effects, this study was able to show that by installing signals on 45 treated sites, there was a positive aggregate economic benefit of $155,883,978 which represents a 69 percent reduction in cost. This translated into $616,142 per site-year.

Small UAV SHM System Functional Hazard Analysis

The safety assessment process tailored to Remotely Piloted Aircraft Systems (RPAS) applications has been discussed briefly. The modified Hazard Reference System for STANAG 4703 Category UAV including Non Safety Effect (NSE) severity category has been proposed. The Functional Hazard Analysis (FHA) for small Unmanned Aerial Vehicle (UAV) Structural Health Monitoring (SHM) system has been conducted.