Improvement of riding licensing criteria based on rider's braking capability: A preliminary study.

Speeding is the factor that usually associated with fatal accident. However, riders have tendency to exceed their vehicle's speed above the regulated speed. Therefore, the likelihood of traffic accidents is significantly influenced by braking ability. Unfortunately, the braking capability has not been accommodated properly in the accident risk management, such as riding license obtaining mechanism. This paper focuses on the possibility of the development of riding licensing criteria based on rider's braking capability. The parameters used in the analysis are the safety factor and margin of safety, due to the differences in riders' braking capability. All the input data were collected from the result of previous related studies. Although the sample size is varied but data source was taken from relevant objects studies. The result of this study showed that impact speed and/or rider's involvement in fatal crashes could be reduced by increasing their braking ability. It strongly indicates that each rider should realize that their speed choices should be suited to their braking ability which could be increased during the riding licensing practical test. The utilization of a rider's braking abilities, which could provide a minimum margin of safety, should therefore be taken into consideration as a basis for the criteria used to obtain a riding license.

Injury risk curves to guide safe speed limits on Swedish roads using German crash data supplemented with estimated non-injury crashes.

Vision Zero postulates that no one should be killed or seriously injured in road traffic; therefore, it is necessary to define evidence-based speed limits to mitigate impact severity. The overall aims to guide the definition of safe speeds limits by establishing relations between impact speed and the risk of at-least-moderate (MAIS2+) and at-least-severe (MAIS3+) injuries for car occupants in frontal and side crashes in Sweden. As Swedish in-depth data are unavailable, the first objective was to assess the applicability of German In-depth Accident Study (GIDAS) data to Sweden. The second was to create unconditional injury risk curves (risk of injury given involvement in any crash), rather than risk curves conditional on the GIDAS sampling criterion of suspected-injury crashes. Thirdly, we compared the unconditional and conditional risk curves to quantify the practical implications of this methodological choice. Finally, we provide an example to demonstrate how injury risk curves facilitate the definition of safe, evidence-based speed limits in Sweden. Characteristics important for the injury outcome were similar between GIDAS and Swedish data; therefore, the injury risk curves using German GIDAS data are applicable to Sweden. The regression models yielded the following results for unconditional injury risk curves: 10 % MAIS2+ at 25 km/h impact speed for frontal head-on crashes, 20 km/h for frontal car-to-object crashes, 55 km/h in far-side crashes, and 45 km/h in near-side crashes. A 10 % MAIS3+ risk was reached between 70 and 75 km/h for all crash types. Conditional injury risk curves gave substantially different results; the 10 % MAIS3+ risk in near-side crashes was 140 km/h, twice the unconditional value. For example, if a 10 % MAIS3+ risk was acceptable, treating remaining uncertainty conservatively, assuming compliance with speed limits and that Automated Emergency Braking takes 20 km/h of the travel speed before impact in longitudinal traffic, the safe speed limit for car occupants on most Swedish roads would be 80 km/h and 60 km/h in intersections.

Assessing the applicability of impact speed injury risk curves based on US data to defining safe speeds in the US and Sweden.

Vision Zero is an approach to road safety that aims to eliminate all traffic-induced fatalities and lifelong injuries. To reach this goal, a multi-faceted safe system approach must be implemented to anticipate and minimize the risk associated with human mistakes. One aspect of a safe system is choosing speed limits that keep occupants within human biomechanical limits in a crash scenario. The objective of this study was to relate impact speed and maximum delta-v to risk of passenger vehicle (passenger cars and light trucks and vans) occupants sustaining a moderate to fatal injury (MAIS2+F) in three crash modes: head-on vehicle-vehicle, frontal vehicle-barrier, and front-to-side vehicle-vehicle crashes. Data was extracted from the Crash Investigation Sampling System, and logistic regression was used to construct the injury prediction models. Impact speed was a statistically significant predictor in head-on crashes, but was not a statistically significant predictor in vehicle-barrier or front-to-side crashes. Maximum delta-v was a statistically significant predictor in all three crash modes. A head-on impact speed of 62 km/h yielded 50% (±27%) risk of moderate to fatal injury for occupants at least 65 years old. A head-on impact speed of 82 km/h yielded 50% (±31%) risk of moderate to fatal injury for occupants younger than 65 years. Compared to the impact speeds, the maximum delta-v values yielding the same level of risk were lower within the head-on crash population. A head-on delta-v of 40 km/h yielded 50% (±21%) risk of moderate to fatal injury for occupants at least 65 years old. A head-on delta-v of 65 km/h yielded 50% (±33%) risk of moderate to fatal injury for occupants younger than 65 years. A maximum delta-v value of approximately 30 km/h yielded 50% (±42%) risk of MAIS2+F injury for passenger car occupants in vehicle-vehicle front-to-side crashes. A maximum delta-v value of approximately 44 km/h yielded 50% (±24%) risk of MAIS2+F injury for light truck and van occupants, respectively, in vehicle-vehicle front-to-side crashes.

Casualty risk of e-bike rider struck by passenger vehicle using China in-depth accident data.

Objective: Traffic deaths involving e-bike (electric bike) riders are increasing in China. This study aims to quantitatively investigate the association between e-bike rider casualty and impact speed in electric bike-passenger vehicle collisions based on China in-depth accident study data.Methods: According to the collision location and driving direction of the e-bike and the vehicle, electric bike-passenger vehicle collisions are divided into five collision types: frontal collision, e-bike side collision, vehicle side collision, scrape collision and rear-end collision. Since e-bike side collision (the side of e-bike impacted with the front of vehicle) is the leading type and has the highest likelihood of severe or fatal injury in all collision types, e-bike side collisions are further selected to build the casualty risk functions of e-bike rider in relation to the rider age and the impact speed (vehicle impact speed and e-bike impact speed).Results: The analysis results show that, as for e-bike side collisions and e-bike impact speed is 20 km/h, the fatality risk of riders is approximately 2.9% at vehicle impact speed of 30 km/h, 23% at 50 km/h, 50% at 60 km/h, and 90% at 80 km/h. Rider age is also significantly associated with a higher risk of severe and fatality injury. The e-bike impact speed is not significantly associated with the severe and fatality risk in e-bike side collisions.Conclusions: The findings of this study provide meaningful insights to formulate effective policies especially for speed limit management to improve the safety of e-bikes.

The relationship between impact speed and the probability of pedestrian fatality during a vehicle-pedestrian crash: A systematic review and meta-analysis.

BACKGROUND: Pedestrians struck in motorised vehicle crashes constitute the largest group of traffic fatalities worldwide. Excessive speed is the primary contributory factor in such crashes. The relationship between estimated impact speed and the risk of a pedestrian fatality has generated much debate concerning what should be a safe maximum speed limit for vehicles in high pedestrian active areas. METHODS: Four electronic databases (MEDLINE, EMBASE, COMPENDEX, and SCOPUS) were searched to identify relevant studies. Records were assessed, and data retrieved independently by two authors in adherence with the PRISMA statement. The included studies reported data on pedestrian fatalities from motorised vehicle crashes with known estimated impact speed. Summary odds ratios (OR) were obtained using meta-regression models. Time trends and publication bias were assessed. RESULTS: Fifty-five studies were identified for a full-text assessment, 27 met inclusion criteria, and 20 were included in a meta-analysis. The analyses found that when the estimated impact speed increases by 1 km/h, the odds of a pedestrian fatality increases on average by 11% (OR = 1.11, 95% CI: 1.10-1.12). The risk of a fatality reaches 5% at an estimated impact speed of 30 km/h, 10% at 37 km/h, 50% at 59 km/h, 75% at 69 km/h and 90% at 80 km/h. Evidence of publication bias and time trend bias among included studies were found. CONCLUSIONS: The results of the meta-analysis support setting speed limits of 30-40 km/h for high pedestrian active areas. These speed limits are commonly used by best practice countries that have the lowest road fatality rates and that practice a Safe System Approach to road safety.

Pedestrian fatality and impact speed squared: Cloglog modeling from French national data.

OBJECTIVE: The present study estimates pedestrians' risk of death according to impact speed when hit by a passenger car in a frontal collision. METHODS: Data were coded for all fatal crashes in France in 2011 and for a random sample of 1/20th of all road injuries for the same year and weighted to take into account police underreporting of mild injury. A cloglog model was used to optimize risk adjustment for high collision speeds. The fit of the model on the data was also improved by using the square of the impact speed, which best matches the energy dissipated in the collision. RESULTS: Modeling clearly demonstrated that the risk of death was very close to 1 when impact speeds exceeded 80 km/h. For speeds less than 40 km/h, because data representative of all crashes resulting in injury were used, the estimated risk of death was fairly low. However, although the curve seemed deceptively flat below 50 km/h, the risk of death in fact rose 2-fold between 30 and 40 km/h and 6-fold between 30 and 50 km/h. For any given speed, the risk of death was much higher for more elderly subjects, especially those over 75 years of age. These results concern frontal crashes involving a passenger car. Collisions involving trucks are far less frequent, but half result in the pedestrian being run over, incurring greater mortality. CONCLUSIONS: For impact speeds below 60 km/h, the shape of the curve relating probability of death to impact speed was very similar to those reported in recent rigorous studies. For higher impact speeds, the present model allows the curve to rise ever more steeply, giving a much better fit to observed data. The present results confirm that, when a pedestrian is struck by a car, impact speed is a major risk factor, thus providing a supplementary argument for strict speed limits in areas where pedestrians are highly exposed.

Validation of pedestrian throw equations by video footage of real life pedestrian/vehicle collisions.

A total of 11 real life vehicle/pedestrian collisions in 2012-2014 were captured by CCTV cameras/car cameras in Hong Kong. Some of the footage was recorded in HD format at 30 frames per second, enabling accurate determinations of impact speeds with pedestrians, exact points of impacts and final rest positions of pedestrians as well as kinematics of the collisions. The calculated impact speeds from footage analysis were used to validate the published empirical and semi-empirical pedestrian throw equations. The applicability of these equations to collisions on sloped carriageways was discussed. The presented results, including 6 forward projection trajectory cases, enrich the existing limited real life data from footage analysis for further validation of the published methodologies.

The influence of vehicle front-end design on pedestrian ground impact.

Accident data have shown that in pedestrian accidents with high-fronted vehicles (SUVs and vans) the risk of pedestrian head injuries from the contact with the ground is higher than with low-fronted vehicles (passenger cars). However, the reasons for this remain poorly understood. This paper addresses this question using multibody modelling to investigate the influence of vehicle front height and shape in pedestrian accidents on the mechanism of impact with the ground and on head ground impact speed. To this end, a set of 648 pedestrian/vehicle crash simulations was carried out using the MADYMO multibody simulation software. Impacts were simulated with six vehicle types at three impact speeds (20, 30, 40km/h) and three pedestrian types (50th % male, 5th % female, and 6-year-old child) at six different initial stance configurations, stationary and walking at 1.4m/s. Six different ground impact mechanisms, distinguished from each other by the manner in which the pedestrian impacted the ground, were identified. These configurations have statistically distinct and considerably different distributions of head-ground impact speeds. Pedestrian initial stance configuration (gait and walking speed) introduced a high variability to the head-ground impact speed. Nonetheless, the head-ground impact speed varied significantly between the different ground impact mechanisms identified and the distribution of impact mechanisms was strongly associated with vehicle type. In general, impact mechanisms for adults resulting in a head-first contact with the ground were more severe with high fronted vehicles compared to low fronted vehicles, though there is a speed dependency to these findings. With high fronted vehicles (SUVs and vans) the pedestrian was mainly pushed forward and for children this resulted in high head ground contact speeds.

Impact depth and the interaction with impact speed affect the severity of contusion spinal cord injury in rats.

Spinal cord injury (SCI) biomechanics suggest that the mechanical factors of impact depth and speed affect the severity of contusion injury, but their interaction is not well understood. The primary aim of this work was to examine both the individual and combined effects of impact depth and speed in contusion SCI on the cervical spinal cord. Spinal cord contusions between C5 and C6 were produced in anesthetized rats at impact speeds of 8, 80, or 800 mm/s with displacements of 0.9 or 1.5 mm (n=8/group). After 7 days postinjury, rats were assessed for open-field behavior, euthanized, and spinal cords were harvested. Spinal cord tissue sections were stained for demyelination (myelin-based protein) and tissue sparing (Luxol fast blue). In parallel, a finite element model of rat spinal cord was used to examine the resulting maximum principal strain in the spinal cord during impact. Increasing impact depth from 0.9 to 1.5 mm reduced open-field scores (p<0.01) above 80 mm/s, reduced gray (GM) and white matter (WM) sparing (p<0.01), and increased the amount of demyelination (p<0.01). Increasing impact speed showed similar results at the 1.5-mm impact depth, but not the 0.9-mm impact depth. Linear correlation analysis with finite element analysis strain showed correlations (p<0.001) with nerve fiber damage in the ventral (R(2)=0.86) and lateral (R(2)=0.74) regions of the spinal cord and with WM (R(2)=0.90) and GM (R(2)=0.76) sparing. The results demonstrate that impact depth is more important in determining the severity of SCI and that threshold interactions exist between impact depth and speed.

Relative fatality risk curve to describe the effect of change in the impact speed on fatality risk of pedestrians struck by a motor vehicle.

Models describing the relation between impact speed and fatality risk for pedestrians struck by a motor vehicle have frequently been used by practitioners and scientists in applying an S curve to visualize the importance of speed for the chance of survival. Recent studies have suggested that these risk curves are biased and do not give representative risk values. These studies present new fatality risk curves that show much lower risks of fatality than before, which has caused confusion and misconceptions about how these new curves should be interpreted, and how this should affect speed management policy. The aim here is to deepen the understanding of the implications this new knowledge has for urban speed policies by analyzing (1) what the most reliable knowledge is for this relation today and what limitations it has, (2) how these risk curves are interpreted today, and what limitations this interpretation has and (3) what the risk curves say about the importance of speed and speed changes. This paper proposes an additional tool, the relative fatality risk curve, to help prevent misconceptions. The proposed relative risk ratios and curves show that, even though the most recent results indicate that the risk is lower than assumed by the older models, the fatality risk is still as sensitive to speed changes as before.

Debiasing overoptimistic beliefs about braking capacity.

We investigated, using questionnaires, different strategies for removing drivers' overoptimism (Svenson et al., 2012a) about how fast their speed could be decreased when they were speeding compared with braking at the speed limit speed. Three different learning groups and a control group made collision speed judgments. The first learning group had the distance a car travels during a driver's reaction time for each problem. The second group had this information and also feedback after each judgment (correct speed). The third group judged collision speed but also braking distance and received correct facts after each problem. The control group had no information at all about reaction time and the distance traveled during that time. The results suggested the following rank order from poor to improved performance: control, group 1, group 3 and group 2 indicating that information about distance driven during a driver's reaction time improved collision speed judgments and that adding stopping distance information did not add to this improvement.