Prospective assessment of the effectiveness of autonomous emergency braking in car-to-cyclist accidents in France

An adapted taxonomy and framework for monitoring road safety strategies: a case study of Morocco

Traditional approaches to monitoring road safety have primarily focused on measuring outcomes such as the number of fatalities and injuries. While effective in capturing overall trends, this macroscopic approach often overlooks the underlying causes of unsafe conditions. Recognizing these limitations, many countries now embrace a safe system-based approach, which emphasizes a holistic view of road safety, considering various elements and their interactions. In response to this shift, this study introduces a five-step framework designed to provide comprehensive coverage and tailored assistance in selecting and utilizing appropriate Road Safety Indicators (RSIs) for more effective performance monitoring. The framework integrates a novel RSIs taxonomy aligned with critical elements of the safe system. It also incorporates an MCDA-based approach to account for decision-makers' preferences when selecting suitable RSIs. A case study demonstrates the practical application of the proposed steps, including the identification, classification, selection, and development of descriptive sheets for each selected RSI, as well as the continuous updating of the RSIs set. The findings offered valuable insights into the commonly used indicators in international road safety reports, while also revealing the limitations of currents metrics and data in fully capturing critical elements and hierarchical level within the road safety management system.

Change in the collision avoidance performance of autonomous emergency braking systems

OBJECTIVE

This study quantifies the change in collision avoidance performance of autonomous emergency braking (AEB) systems for traffic accidents in Japan since 2015.

METHOD

This study used data on Japanese traffic accidents compiled by Japan's National Police Agency. The data included only accidents involving loss of or injury to human life; accidents involving only property damage were excluded. We restricted our analysis to collisions between two 4-wheel vehicles and considered only collisions for which we could determine whether the primary party's car was equipped with an AEB system. Both Poisson and negative binomial mixed-effects regression analyses were conducted using the data for 2021 and 2022 to measure the collision avoidance performance of first registered cars in 2015 to 2020 equipped with AEB systems compared with cars without AEB systems first registered in 2015. Collision avoidance performance was measured for 2 types of intervehicle collisions: rear-end collisions and right-turn collisions. Collision avoidance performance for rear-end collisions was also measured for each of the 3 car types-Standard, small, and light cars.

RESULTS

The collision reduction rate for rear-end collisions increases with the year of first registration and for cars equipped with AEB systems first registered in 2020 compared with non-AEB-equipped cars first registered in 2015 is 69.2% (95% confidence interval [CI] 67.0%-71.1%), indicating that the performance of AEB systems has dramatically improved in terms of preventing rear-end collisions. For right-turn collisions, the rate increased to 20.4% (95% CI 5.9%-32.6%) for cars equipped with AEB systems first registered in 2019. However, no clear trend is observed.

CONCLUSIONS

This study evaluated a time series of the collision reduction performance of AEB systems using an original methodology. Japan's New Car Assessment Program (JNCAP) has included AEB's effectiveness in reducing damage from traffic collisions as an evaluation item since FY2014. The results could demonstrate the effectiveness of JNCAP.

Utilising Human Crash Tolerance to Design an Interim and Ultimate Safe System for Road Safety

Many jurisdictions globally have adopted a zero road trauma target by 2050 and an interim target of a 50% reduction by 2030. The objective of this study was to investigate what the road system will need to look like in order to achieve these respective targets. Utilising human tolerance to injury as the key design factor, this study defined the combination of vehicle, infrastructure, and travel speed requirements to manage crash energy in order to: 1. prevent all fatalities and serious injuries by 2050 in an Ultimate Safe System scenario; and 2. significantly reduce fatalities and severe injuries by 2030 in an Interim Safe System scenario. Victoria, Australia and its Movement and Place (M&P) framework was employed as a case study. With the vehicle and infrastructure countermeasures currently available coupled with appropriate travel speeds it is possible to construct an Ultimate Safe System that can manage crash forces to achieve zero trauma and an Interim Safe System that can significantly reduce the most severe injuries in Victoria. This study has demonstrated a potential pathway from the current situation to 2030 and then 2050 that can achieve safety targets while meeting the core objectives of the transport system.

Quantifying the Lost Safety Benefits of ADAS Technologies Due to Inadequate Supporting Road Infrastructure

Advanced driver assistance systems (ADAS) provide warnings to drivers and, if applicable, intervene to mitigate a collision if one is imminent. Autonomous emergency brakes (AEB) and lane keep assistance (LKA) systems are mandated in several new vehicles, given their predicted injury and fatality reduction benefits. These predicted benefits are based on the assumption that roads are always entirely supportive of ADAS technologies. Little research, however, has been conducted regarding the preparedness of the road network to support these technologies in Australia, given its vastly expansive terrain and varying road quality. The objective of this study was to estimate what proportion of crashes that are sensitive to AEB and LKA, would not be mitigated due to unsupportive road infrastructure, and therefore, the lost benefits of the technologies due to inadequate road infrastructure. To do this, previously identified technology effectiveness estimates and a published methodology for identifying ADAS-supportive infrastructure availability was applied to an estimated AEB and LKA-sensitive crash subset (using crash data from Victoria, South Australia and Queensland, 2013–2018 inclusive). Findings demonstrate that while the road networks across the three states appeared largely supportive of AEB technology, the lack of delineation across arterial and sub-arterial (or equivalent) roads is likely to have serious implications on road safety, given 13–23% of all fatal and serious injury (FSI) crashes that occurred on these road classes were LKA-sensitive. Based on historical crash data, over 37 fatalities and 357 serious injuries may not be avoided annually across the three Australian states based on the lack of satisfactory road delineation on arterial and sub-arterial (or equivalent) roads alone. Further, almost 24% of fatalities in Victoria, 24% of fatalities in Queensland and 21% of fatalities in South Australia (that are AEB- or LKA-sensitive) are unlikely to be prevented, given existing road infrastructure. These figures are conservative estimates of the lost benefits of the technologies as they only consider fatal and serious injury crashes and do not include minor injury or property damage crashes, the benefits of pedestrian-sensitive AEB crashes in high-speed zones or AEB fitted to heavy vehicles. It is timely for road investments to be considered, prioritised and allocated, given the anticipated penetration of the new technologies into the fleet, to ensure that the road infrastructure is capable of supporting the upcoming fleet safety improvements.

On the importance of driver models for the development and assessment of active safety: A new collision warning system to make overtaking cyclists safer

The total number of road crashes in Europe is decreasing, but the number of crashes involving cyclists is not decreasing at the same rate. When cars and bicycles share the same lane, cars typically need to overtake them, creating dangerous conflicts-especially on rural roads, where cars travel much faster than cyclists. In order to protect cyclists, advanced driver assistance systems (ADAS) are being developed and introduced to the market. One of them is a forward collision warning (FCW) system that helps prevent rear-end crashes by identifying and alerting drivers of threats ahead. The objective of this study is to assess the relative safety benefit of a behaviour-based (BB) FCW system that protects cyclists in a car-to-cyclist overtaking scenario. Virtual safety assessments were performed on crashes derived from naturalistic driving data. A series of driver response models was used to simulate different driver reactions to the warning. Crash frequency in conjunction with an injury risk model was used to estimate the risk of cyclist injury and fatality. The virtual safety assessment estimated that, compared to no FCW, the BB FCW could reduce cyclists' fatalities by 53-96% and serious injuries by 43-94%, depending on the driver response model. The shorter the driver's reaction time and the larger the driver's deceleration, the greater the benefits of the FCW. The BB FCW also proved to be more effective than a reference FCW based on the Euro NCAP standard test protocol. The findings of this study demonstrate the BB FCW's great potential to avoid crashes and reduce injuries in car-to-cyclist overtaking scenarios, even when the driver response model did not exceed a comfortable rate of deceleration. The results suggest that a driver behaviour model integrated into ADAS collision threat algorithms can provide substantial safety benefits.

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.