Single-bicycle crashes in Finland - Characteristics and safety recommendations

PROBLEM

Increasing the role of cycling is necessary to reduce physical inactivity. While promoting cycling, attention should also be given to traffic safety. Hence, a better understanding on the underlying factors and safety recommendations of cyclist crashes is needed. This study aims to increase knowledge on fatal single-bicycle crashes (SBCs), where other road users are not collided with.

METHOD

Data from in-depth investigated fatal cyclist crashes in Finland is analyzed from 2010 to 2019. The study presents descriptive analysis of the characteristics, underlying factors, and safety recommendations of SBCs (n = 82) and other cyclist crashes (n = 151). Logistic regression analysis and chi-squared tests were performed to identify significant characteristics for SBCs.

RESULTS

Fatal SBCs commonly involved people aged 60 or older, males, and cyclist not wearing a helmet. Cyclist's health issues influenced the crash in 62.2% of the SBCs. Compared to other cyclist crashes, health issues, alcohol, males, other crash locations than intersections, and weekends were highlighted in SBCs. Safety recommendations emphasized human factors, such as informing cyclist about underlying factors and the use of safety equipment.

DISCUSSION

In addition to human factors, the safety recommendations included suggestions regarding the bicycle, the traffic environment, and traffic regulations. This highlights the need to focus on different safety improvement actions to reduce SBCs. This study identified key characteristics of SBCs, which may help traffic safety authorities address this road safety issue and ultimately help to promote cyclist safety.

PRACTICAL APPLICATIONS

Cooperation between the actors including health care providers and the police is also proposed to address cyclists' health issues that contribute to SBCs.

How automated vehicles should operate to avoid fatal crashes with cyclists?

The study assesses what kind of features would allow highly automated vehicles' (HAVs) safe operation in encounters with cyclists and allow avoiding fatal crashes between cyclists and passenger cars. Five features of HAVs' capabilities are formed based on previous studies and evaluated qualitatively using data from fatal crashes between driver-managed passenger cars and cyclist in Finland. By analysing these crashes, it is assessed which features HAVs should have in order to avoid each crash in a hypothetical setting, in which driver-managed cars would be replaced by HAVs. The necessary features of HAVs for crash avoidance are analysed crash-by-crash by considering the obligation to yield, visual obstacles at the crash scene and driver's behaviour prior to the crash. In order to avoid different types of fatal crashes with cyclists, the HAVs should be able to recognize nearby cyclists (feature 1), be aware of the priority rules in various intersections and traffic situations (2), indicate its intentions to cyclists (3), maintain safe driving patterns and anticipate future situations (4), and assess cyclists' intentions (5). Albeit the number of different features to allow crash avoidance is only five, implementing these features is a considerable challenge for HAVs' programming and design, as these should function in various and complex traffic situations. The study discloses the complexity in the encounters between HAVs and cyclists, which are to be considered in further studies and real-world implementations.

The most difficult at-fault fatal crashes to avoid with current active safety technology

OBJECTIVE

We studied which current fatal at-fault crashes would occur despite the most advanced current active safety devices (up to SAE level 2 of driving automation) and how frequent these crashes would be.

METHODS

We carried out a cross-sectional study of passenger cars that were first registered during the period 1st January 2010 to 31st December 2017 in Finland. To gain the true exposure for these cars, we accessed the national Vehicular and Driver Data Register to obtain the mileage information and the registration count for the study period of 2010-17. Similarly, we accessed the registry of Finnish road accident investigation teams and included all fatal at-fault crashes among the cars in our study for the same period. We used a real world reference technology for each active safety system in our analysis and chose one car brand as an example. This gave us exact system specifications and enabled testing the operation of the systems on the road. We performed field tests to gain further information on the precise operation of the safety systems in different operating conditions. Finally, we gathered all information on the studied active safety systems and analyzed the investigated at-fault fatal crashes case-by-case using our four level method.

RESULTS

Cars in our study were the primary party in 113 investigated fatal accidents during the years 2010-17. In 87 of the accidents, the leading cause of death was the injuries due to the crash, and these cases were classified as "unavoidable" (n = 58, 67 %), "avoidable" (n = 26, 30 %) or unsolved (n = 3, 3 %). Of the 58 "unavoidable" crashes 21 (36 %) were suicides, 21 (36%) involved active driver input which would have prevented the safety system operation, 15 (17 %) featured circumstances beyond the safety system performance and in one loss-of-control crash the driver had disabled the relevant safety system (electronic stability control). The registration years of the cars in our study (2010-17) totaled 3,772,864 and during this period, the cars travelled 75.9 billion kilometers. The crash incidence of the "unavoidable" at-fault fatal crashes was 0.76-0.80 fatal crashes per billion kilometers and 15-16 fatal crashes per million registration years.

CONCLUSIONS

We calculated a crash incidence for the "unavoidable" crashes which was 20-27% smaller than the observed crash rate of ESC-fitted passenger cars in our previous study. We concluded that suicides, active driver input until the crash, and challenging weather and road conditions are the most difficult factors for current active safety systems. Our analysis did not account for issues such as system usability or driver acceptance and therefore our results should be regarded as something that is currently theoretically achievable. However, the observed incidence is a good reference for automated driving development and the crash rate of automated cars.