Analysis of car-to-bicycle approach patterns for developing active safety devices

Traumatic pedestrian and bicyclist injuries associated with intoxication

BACKGROUND

Drug and alcohol use are risk factors for trauma among operators of motor vehicles and contribute to trauma in pedestrians and bicyclists. We describe the prevalence of drug and alcohol use and clinical consequences in a cohort of pedestrians and bicyclists with trauma.

METHODS

We analyzed a 25-month data set of 916 trauma team activations from January 2017-January 2019 at an urban, level I trauma center. Blood ethanol levels and urine toxicology screens were obtained in 94 pedestrian and bicyclist trauma activations. We compared pedestrians or bicyclists with a positive urine or blood screen (n = 69) to those with negative screens (n = 25). We conducted a retrospective chart review to determine mechanism of injury, injury pattern, and disposition from the emergency department (ED).

RESULTS

Overall, 38 (55%) of injured patients with positive screen were pedestrians and 31 (45%) were bicyclists. Fentanyl was the most commonly detected drug (n = 38; 40%), followed by opiates (n = 27; 29%), and tetrahydrocannabiol (THC) (n = 23; 25%). Twenty-one patients were positive for ethanol. Pedestrians and bicyclists with positive toxicology screens were significantly more likely to sustain fractures (p < .01), require an operative procedure (p < .05), or intensive care unit admission (p < .05).

CONCLUSION

Our study builds on previous literature which suggests that intoxicated bicyclists and pedestrians suffer frequent and more severe injury than their sober counterparts. Public health campaigns should educate bicyclists and pedestrians about the risks of cycling or walking in areas of road traffic while under the influence of alcohol or illicit drugs.

Validation of driver support system based on real-world bicycle and motor vehicle flows

The incidence of traffic accidents in Japan has been decreasing annually. Nineteen percent of all accidents involve bicycles, with 51 % of these accidents being at road crossing intersections. Therefore, to reduce the number of accidents, this study analyses driving and cycling characteristics and proposes suitable collisions prevention methods. First, the study measured traffic environment variables using video cameras at a target non-signalized intersection and analyzed the speed and time to intersection of bicycles and motor vehicles. Thus, 47 dangerous situations were observed via the video analysis, and most of these situations occurred when the vehicle's time to intersection ranged from 0.50 to 0.75 s and the bicycle's speed ranged from 2.0-3.0 m/s. Second, using the results of video camera analysis as experimental parameters (e.g., the speed and timing of the presence of the bicycle), this study conducted an experiment with a driving simulator to investigate the effect of warning drivers about the risk of collision. A driver support system was then utilized to provide acoustic and optical warnings to drivers. The experiments revealed that the motor vehicle time to the anticipated collision point (V-TTC) increased with the use of a driver support system. Significant differences between experiments with and without driver support systems were observed when the calculated time between the bicycle and the motor vehicle was 0.25 and 0.50 s. Therefore, when the calculated time was 0.25 and 0.50 s, a driver support system, indicating the presence of a bicycle, was effective in preventing an intersection collision.

Cycle Logistics Projects in Europe: Intertwining Bike-Related Success Factors and Region-Specific Public Policies with Economic Results

The aim of this paper is to investigate whether and which specific, distinctive characteristics of European cycle logistics projects and the corresponding supporting policies have an impact on their economic performances in terms of profit and profitability. First, we identify project success factors by geographic area and project-specific characteristics; then, we statistically test possible dependence relationships with supporting policies and economic results. Finally, we provide a value-based identification of those characteristics and policies which more commonly lead to better economic results. This way, our work may serve as a basis for the prioritization and contextualization of those project functionalities and public policies to be implemented in a European context. We found that cycle logistics projects in Europe achieve high profit and profitability levels, and the current policies are generally working well and supporting them. We also found that profit and profitability vary across the bike model utilized: mixing cargo bikes and tricycles generates the highest profit and profitability, whilst a trailer–tricycle–cargo bike mix paves the way for high volumes and market shares.

AEB effectiveness evaluation based on car-to-cyclist accident reconstructions using video of drive recorder

OBJECTIVE

Though autonomous emergency braking (AEB) systems for car-to-cyclist collisions have been under development, an estimate of the benefit of AEB systems based on an analysis of accident data is needed for further enhancing their development. Compared to the data available from in-depth accident data files, data provided by drive recorders can be used to reconstruct car-to-cyclist collisions with greater accuracy because the position of cyclists can be observed from the videos. In this study, using data from drive recorders, the performance and limitations of AEB systems were investigated.

METHOD

Data of drive recorders involving taxi-to-cyclist collisions were collected. Using the images collected from the drive recorders of those taxis, 40 cases of 90° car-to-cyclist intersection collisions were reconstructed using PC-Crash. Then, the collisions were reconstructed again utilizing car models with AEB systems installed while changing the sensor's field of view (FOV) and the delay time of initiating vehicle deceleration.

RESULTS

The angle of FOV has a significant influence on avoiding car-to-cyclist collisions. Using a 50° FOV with a braking delay time of 0.5 s resulted in avoiding 6 collisions, and using a 90° FOV resulted in avoiding an additional 14 collisions. Even when installing an ideal AEB system providing 360° FOV and no delay time for braking, 8 collisions were not avoided, though the impact velocities were reduced for all of these remaining collisions. These collisions were caused by the cyclists' sudden appearance in front of cars, and the time-to-collision (TTC) when the cyclists appeared was less than 0.9 s.

CONCLUSION

The AEB systems were effective for mitigating collisions that occurred due to driver perception delay. Because cyclists have a traveling velocity, a wide-angle FOV is effective for reduction of car-to-cyclist intersection collisions. The reduction of delay time in braking can reduce the number of collisions that are close to the braking performance limit. The collisions that remained even with an ideal AEB system in the PC-Crash simulation indicate that such collisions could still occur for autonomous cars if the traffic environment does not change.

Difference between car-to-cyclist crash and near crash in a perpendicular crash configuration based on driving recorder analysis

Analyzing a crash using driving recorder data makes it possible to objectively examine factors contributing to the occurrence of the crash. In this study, car-to-cyclist crashes and near crashes recorded on cars equipped with advanced driving recorders were compared with each other in order to examine the factors that differentiate near crashes from crashes, as well as identify the causes of the crashes. Focusing on cases where the car and cyclist approached each other perpendicularly, the differences in the car's and cyclist's parameters such as velocity, distance and avoidance behavior were analyzed. The results show that car-to-cyclist crashes would not be avoidable when the car approaching the cyclist enters an area where the average deceleration required to stop the car is more than 0.45 G (4.4 m/s²). In order for this situation to occur, there are two types of cyclist crash scenarios. In the first scenario, the delay in the drivers' reaction in activating the brakes is the main factor responsible for the crash. In this scenario, time-to-collision when the cyclist first appears in the video is more than 2.0 s. In the second scenario, the sudden appearance of a cyclist from behind an obstacle on the street is the factor responsible for the crash. In this case, the time-to-collision is less than 1.2 s, and the crash cannot be avoided even if the driver exhibited avoidance maneuvers.

Time-to-collision analysis of pedestrian and pedal-cycle accidents for the development of autonomous emergency braking systems

The aim of this study was to describe the position of pedestrians and pedal cyclists relative to the striking vehicle in the 3 s before impact. This information is essential for the development of effective autonomous emergency braking systems and relevant test conditions for consumer ratings. The UK RAIDS-OTS study provided 175 pedestrian and 127 pedal-cycle cases based on in-depth, at-scene investigations of a representative sample of accidents in 2000-2010. Pedal cyclists were scattered laterally more widely than pedestrians (90% of cyclists within around ±80° compared to ±20° for pedestrians), however their distance from the striking vehicle in the seconds before impact was no greater (90% of cyclists within 42 m at 3 s compared to 50 m for pedestrians). This data is consistent with a greater involvement of slow moving vehicles in cycle accidents. The implication of the results is that AEB systems for cyclists require almost complete 180° side-to-side vision but do not need a longer distance range than for pedestrians.

Driver braking behavior analysis to improve autonomous emergency braking systems in typical Chinese vehicle-bicycle conflicts

Bicycling is one of the fundamental modes of transportation especially in developing countries. Because of the lack of effective protection for bicyclists, vehicle-bicycle (V-B) accident has become a primary contributor to traffic fatalities. Although AEB (Autonomous Emergency Braking) systems have been developed to avoid or mitigate collisions, they need to be further adapted in various conflict situations. This paper analyzes the driver's braking behavior in typical V-B conflicts of China to improve the performance of Bicyclist-AEB systems. Naturalistic driving data were collected, from which the top three scenarios of V-B accidents in China were extracted, including SCR (a bicycle crossing the road from right while a car is driving straight), SCL (a bicycle crossing the road from left while a car is driving straight) and SSR (a bicycle swerving in front of the car from right while a car is driving straight). For safety and data reliability, a driving simulator was employed to reconstruct these three scenarios and some 25 licensed drivers were recruited for braking behavior analysis. Results revealed that driver's braking behavior was significantly influenced by V-B conflict types. Pre-decelerating behaviors were found in SCL and SSR conflicts, whereas in SCR the subjects were less vigilant. The brake reaction time and brake severity in lateral V-B conflicts (SCR and SCL) was shorter and higher than that in longitudinal conflicts (SSR). The findings improve their applications in the Bicyclist-AEB and test protocol enactment to enhance the performance of Bicyclist-AEB systems in mixed traffic situations especially for developing countries.

Association of Impact Velocity with Serious-injury and Fatality Risks to Cyclists in Commercial Truck-Cyclist Accidents

This study aimed to clarify the relationship between truck-cyclist collision impact velocity and the serious-injury and fatality risks to cyclists, and to investigate the effects of road type and driving scenario on the frequency of cyclist fatalities due to collisions with vehicles. We used micro and macro truck-cyclist collision data from the Japanese Institute for Traffic Accident Research and Data Analysis (ITARDA) database. We classified vehicle type into five categories: heavy-duty trucks (gross vehicle weight [GVW] ≥11 × 10³ kg [11 tons (t)], medium-duty trucks (5 × 10³ kg [5 t] ≤ GVW < 11 × 10³ kg [11 t]), light-duty trucks (GVW <5 × 10³ kg [5 t]), box vans, and sedans. The fatality risk was ≤5% for light-duty trucks, box vans, and sedans at impact velocities ≤40 km/h and for medium-duty trucks at impact velocities ≤30 km/h. The fatality risk was 6% for heavy-duty trucks at impact velocities ≤10 km/h. Thus, the fatality risk appears strongly associated with vehicle class and impact velocity. The results revealed that a 10 km/h reduction in impact velocities could mitigate the severity of cyclist injuries at impact velocities ≥30 km/h for all five vehicle types. The frequency of cyclist fatalities at intersections with traffic signals involving heavy-duty trucks was significantly higher during daytime than that at nighttime. Fatalities involving vehicles making a left turn generally increased with vehicle weight. The frequency of cyclist fatalities involving vehicles making a left turn was the largest for heavy-duty trucks both during daytime (67.6%) and at nighttime (52.3%).

Traffic Accidents Involving Cyclists Identifying Causal Factors Using Questionnaire Survey, Traffic Accident Data, and Real-World Observation

The purpose of this study is to clarify the mechanism of traffic accidents involving cyclists. The focus is on the characteristics of cyclist accidents and scenarios, because the number of traffic accidents involving cyclists in Tokyo is the highest in Japan. First, dangerous situations in traffic incidents were investigated by collecting data from 304 cyclists in one city in Tokyo using a questionnaire survey. The survey indicated that cyclists used their bicycles generally while commuting to work or school in the morning. Second, the study investigated the characteristics of 250 accident situations involving cyclists that happened in the city using real-world bicycle accident data. The results revealed that the traffic accidents occurred at intersections of local streets, where cyclists collided most often with vehicles during commute time in the morning. Third, cyclists' behavior was observed at a local street intersection in the morning in the city using video pictures. In one hour during the morning commute period, 250 bicycles passed through the intersection. The results indicated that one of the reasons for traffic accidents involving cyclists might be the combined effect of low visibility, caused by the presence of box-like building structures close to the intersections, and the cyclists' behavior in terms of their velocity and no confirming safety. It was observed that, on average, bicycle velocity was 3.1 m/s at the initial line of an intersection. The findings from this study could be useful in developing new technologies to improve cyclist safety, such as alert devices for cyclists and vehicle drivers, wireless communication systems between cyclists and vehicle drivers, or advanced vehicles with bicycle detection and collision mitigation systems.