Testing the acceptability of motorcycle-AEB system: Use of unanticipated interventions as a reliable surrogate of genuinely unexpected events.

OBJECTIVE: Active safety systems such as motorcycle autonomous emergency braking (MAEB) capable of ensuring effectiveness and safe rider-vehicle interaction present many potential benefits to reduce road fatalities but also many challenges. The whole development cycle of MAEB requires research through extensive field tests that reproduce unexpected interventions or real-life driving situation before the system can be available to the end-user. This study aims to better understand the rider's kinematic response required to control the stability of the rider-motorcycle system, as well as the extent of unexpectedness perceived by participants under different degrees of awareness of automatic braking (AB) activation. METHODS: We compared responses to AB in anticipated and (un)anticipated conditions and in a condition that was intended to be genuinely unexpected (Out of the Blue). Twenty men and women, wearing an inertial measurement unit on their upper-back, rode a scooter-type motorcycle with two front wheels simulating urban riding maneuvers on a closed test-track. Three automatic braking (AB) profiles were tested in different sessions, ranged from 3 to 5 m/s2 deceleration and 15 to 25 m/s3 braking-jerk. Differences between AB conditions were analyzed using linear mixed models. RESULTS: The unanticipated condition was perceived as fairly unexpected (rated between Quite Unexpected and Very Unexpected). Out of the Blue condition was on average close to the highest level of unexpectedness (Completely Unexpected). The exposure to unanticipated AB events resulted in upper-body response with larger peaks of pitch rate (0.20 to 0.77 rad/s higher) and acceleration (1.0 to 2.3 m/s2 higher) than those of anticipated. Participants showed less postural stability during unanticipated events taking longer both to start correcting the initial forward lean and to fully stabilize balance. Unanticipated and Out of the Blue conditions did not differ in either the amplitude of the kinematic variables or the time-to-peak pitch rate. CONCLUSIONS: The kinematic response of the rider's upper-body was found to be a reliable estimator of unexpectedness in AB. The findings suggest that unanticipated AB events while the rider engages in riding tasks can enable testing aimed at designing MAEB systems and assessing end-user acceptance in a reliable manner and within ethical safety limits.

Motorcycle curve assist: A novel approach based on active speed control for crash injury reduction.

OBJECTIVE: Safely negotiating curves with a powered-two-wheeler (PTW) requires a high level of skill, and a significant proportion of PTW crashes have a curve involvement. This study aimed to estimate the applicability, potential benefits and feasibility of novel Motorcycle Curve Assist (MCA). The system is designed to operate an emergency control of the speed of a motorcycle approaching a bend at an inappropriate speed. METHODS: First, the MCA system intervention was defined. Second, the applicability of the system and an estimate of its potential benefits was performed based on a PTW crash database. Motorcyclists' injury risk estimates, MCA working parameters and timing of intervention were employed to estimate the potential injury reduction of applicable crash types. Third, a field test campaign involving 29 common riders as participants was conducted to investigate the real-world applicability and acceptability among end-users of the system deployment in one relevant riding condition adopting a range of parameters of intervention. RESULTS: In the crash database, 23% of cases had curve involvement and after detailed analysis, 14% resulted to be suitable for MCA (60% of cases with curve involvement). The potential relative injury risk reduction considering only the benefits due to crash speed reduction ranged from 3-9% for MAIS2+ to 9-27% for MAIS3+ injuries. Field tests were performed in corners approached at an average speed of 28.7 km/h and an average lean angle of 20°. The system provided a mean deceleration of 0.33 g reached with a fade-in jerk of 1.73 g/s, for an average total duration of 0.59 s. For the field test component, participants reported good controllability of the system, with no incipient loss of control recorded nor reported by participants. CONCLUSIONS: The proposed approach for MCA implementation showed considerable potential benefits in terms of injury reduction. The intervention with the defined working parameters was considered feasible by a sample of end-users. When integrated with an intervention logic capable of predicting emergency situations while approaching curves, MCA will be a technology capable of assisting PTW riders in conditions where other available active safety systems do not.

Estimation of Head Accelerations in Crashes Using Neural Networks and Sensors Embedded in the Protective Helmet.

Traumatic Brain Injuries (TBIs) are one of the most frequent and severe outcomes of a Powered Two-Wheeler (PTW) crash. Early diagnosis and treatment can greatly reduce permanent consequences. Despite the fact that devices to track head kinematics have been developed for sports applications, they all have limitations, which hamper their use in everyday road applications. In this study, a new technical solution based on accelerometers integrated in a motorcycle helmet is presented, and the related methodology to estimate linear and rotational acceleration of the head with deep Artificial Neural Networks (dANNs) is developed. A finite element model of helmet coupled with a Hybrid III head model was used to generate data needed for the neural network training. Input data to the dANN model were time signals of (virtual) accelerometers placed on the inner surface of the helmet shell, while the output data were the components of linear and rotational head accelerations. The network was capable of estimating, with good accuracy, time patterns of the acceleration components in all impact conditions that require medical treatment. The correlation between the reference and estimated values was high for all parameters and for both linear and rotational acceleration, with coefficients of determination (R2) ranging from 0.91 to 0.97.

Investigating the feasibility of motorcycle autonomous emergency braking (MAEB): Design criteria for new experiments to field test automatic braking.

Autonomous Emergency Braking (AEB) was proved to be an effective and reliable technology in reducing serious consequences of road vehicles crashes. However, the feasibility in terms of end-users' acceptability for the AEB for motorcycles (MAEB) still has to be evaluated. So far, only Automatic Braking (AB) activations in straight-line motion and decelerations up to 2 m/s2 were tested with common riders. This paper presents a procedure which provides comprehensive support for the design of new experiments to further investigate the feasibility of MAEB among end-users. Additionally, this method can be used as a reference for designing tests for other advanced rider assistance systems.•A comprehensive literature review was carried out to investigate previous findings related to MAEB. After that, a series of pilot tests using an automatic braking device on an instrumented motorcycle were performed.•The specifications for new AB experiments were defined (in terms of test conditions, participants requirements, safety measures, test vehicles and instrumentation).•A test protocol was defined to test the system in different riding conditions and with different AB working parameters. A proposal for the data analysis was presented.

Human error in motorcycle crashes: A methodology based on in-depth data to identify the skills needed and support training interventions for safe riding.

OBJECTIVE: Human error by either rider or other vehicle driver is the primary contributing factor in crashes involving powered-two-wheelers. A human-factor-based crash analysis methodology is key to enhancing the road safety effectiveness of rider training interventions. Our aim is to define a methodology that uses in-depth data to identify the skills needed by riders in the highest risk crash configurations to reduce casualty rates. METHODS: The methodology is illustrated through a case study using in-depth data of 803 powered-two-wheeler crashes. Seven types of high-risk crash configuration based on pre-crash trajectories of the road-users involved were considered to investigate the human errors as crash contributors. Primary crash contributing factor, evasive maneuvers performed, horizontal roadway alignment and speed-related factors were identified, along with the most frequent crash configurations and those with the greatest risk of severe injury. RESULTS: Straight Crossing Path/Lateral Direction was the most frequent crash configuration and Turn Across Path/Opposing Direction was identified as that with the highest risk of serious injury. Multi-vehicle crashes cannot be considered as a homogenous category of crashes to which the same human failure is attributed, as different interactions between motorcyclists and other road users are associated with both different types of human error and different rider reactions. Human error in multiple-vehicle crashes differed between those configurations related to crossroads and those related to rear-end and head-end crashes. Both single-vehicle crashes and multi-vehicle head-on crashes frequently occur along curves. The involved collision avoidance maneuvers of the riders differed significantly among the highest risk crash configurations. The most relevant lack of skills are identified and linked to their most representative context. In most cases a combination of different skills was required simultaneously to avoid the crash. CONCLUSIONS: The results contribute to understand the motorcyclists' responses in high-risk crash scenarios. The findings underline the need to group accident cases, beyond the usual single-vehicle versus multi-vehicle collision approach. The different interactions with other road users should be considered to identify the competencies of the motorcyclists needed to reduce crash risks. Our methodology can be applied to increase the motorcyclists' safety by supporting preventive actions based on riders' training and eventually ADAS design.

Field testing the applicability of motorcycle autonomous emergency braking (MAEB) during pre-crash avoidance maneuver.

OBJECTIVE: Autonomous Emergency Braking (AEB) is a promising technology for crash avoidance or pre-crash impact speed reduction through the automatic application of braking force. Implementation of AEB technology on motorcycles (MAEB) is still problematic as its interaction with the rider may compromise the safety. In previous studies, MAEB interventions at low decelerations were shown to be easily manageable by common riders in straight line condition, but they were not previously tested in lateral maneuvers such as lane change and swerving, which are common in pre-crash situations. The objective of this paper is to assess the applicability of MAEB activation during lateral avoidance maneuver and to estimate its benefits in this scenario. METHODS: Field tests were carried out involving common riders as participants, using a test protocol developed on the experience of previous studies. The test vehicle was a sport-touring motorcycle equipped with an automatic braking system that could be activated remotely by researchers to simulate MAEB intervention. The motorcycle was equipped with outriggers to prevent capsizing. The Automatic Braking (AB) interventions using a nominal deceleration of 0.3 g were deployed at pseudo-random times in conditions of straight-line travel and a sharp lane-change maneuver emulating a pre-crash avoidance action. The straight-line trials were used as the reference condition for analysis. RESULTS: Thirty-one participants experienced AB interventions in straight-line and lane-change at an average speed of 44.5 km/h. The automatic braking was deployed in all the key phases of the avoidance maneuver. The system reached a deceleration of 0.3 g for a time of intervention of approximately 1 s. The participants were consistently able to control the vehicle during the automatic braking interventions and were always able to complete the lane-change maneuver. The speed reductions obtained with the AB interventions during lane change were very similar to those obtained in the straight-line conditions. CONCLUSIONS: MAEB interventions with decelerations up to 0.3 g can be easily managed by motorcycle riders not only in straight-line conditions but also during an avoidance maneuver. Further investigations using higher deceleration values are now possible.

E-bikers' braking behavior: Results from a naturalistic cycling study.

Objective: The number of e-bike users has increased significantly over the past few years and with it the associated safety concerns. Because e-bikes are faster than conventional bicycles and more prone to be in conflict with road users, e-bikers may need to perform avoidance maneuvers more frequently. Braking is the most common avoidance maneuver but is also a complex and critical task in emergency situations, because cyclists must reduce speed quickly without losing balance. The aim of this study is to understand the braking strategies of e-bikers in real-world traffic environments and to assess their road safety implications. This article investigates (1) how cyclists on e-bikes use front and rear brakes during routine cycling and (2) whether this behavior changes during unexpected conflicts with other road users.Methods: Naturalistic data were collected from 6 regular bicycle riders who each rode e-bikes during a period of 2 weeks, for a total of 32.5 h of data. Braking events were identified and characterized through a combined analysis of brake pressure at each wheel, velocity, and longitudinal acceleration. Furthermore, the braking patterns obtained during unexpected events were compared with braking patterns during routine cycling.Results: In the majority of braking events during routine cycling, cyclists used only one brake at a time, favoring one of the 2 brakes according to a personal pre-established pattern. However, the favored brake varied among cyclists: 66% favored the rear brake and 16% the front brake. Only 16% of the cyclists showed no clear preference, variously using rear brake, front brake, or combined braking (both brakes at the same time), suggesting that the selection of which brake to use depended on the characteristics of the specific scenario experienced by the cyclist rather than on a personal preference. In unexpected conflicts, generally requiring a larger deceleration, combined braking became more prevalent for most of the cyclists; still, when combined braking was not applied, cyclists continued to use the favored brake of routine cycling. Kinematic analysis revealed that, when larger decelerations were required, cyclists more frequently used combined braking instead of single braking.Conclusions: The results provide new insights into the behavior of cyclists on e-bikes and may provide support in the development of safety measures including guidelines and best practices for optimal brake use. The results may also inform the design of braking systems intended to reduce the complexity of the braking operation.

A comparative analysis of MAIDS and ISO13232 databases for the identification of the most representative impact scenarios for powered 2-wheelers in Europe.

OBJECTIVE: The ISO13232 standard provides guidelines and methodologies for research on the effectiveness of protective devices fitted to motorcycles. The accident database used to develop the standard was composed of 2 data sets from Hannover and Los Angeles, dating from 1996. This study aims to apply the methodology outlined in the standard to a more recent European accident database to determine whether the set of the 7 most relevant impact configurations identified in the ISO13232 are representative of the European context. METHODS: The ISO13232 database was rebuilt from the data tables attached to the standard and processed according to the procedure described in ISO13232-Part 2, to ensure reproducibility of the results. The comparison data set was extracted from the Motorcycle Accidents In-Depth Study (MAIDS) database. Data were then coded, processed, and analyzed using the ISO13232 methodology. To eliminate any subjectivity in the selection process of the configurations, a new ranking criterion (configuration risk index, CRI) was implemented. The CRI combined the evaluation of an accident configuration's frequency of occurrence and its harmfulness. RESULTS: Comparison of the frequency ranking of the impact configurations from the 2 databases revealed some notable differences. Five of the 10 most important configurations were common to both databases, although ranking order differed. CRI-based selection led to differences in ranking orders. The CRI allowed better identification of the most important configurations and it was employed to define the proposed new set of configurations. CONCLUSION: A new set of 7 accident configurations was defined by applying the ISO13232 procedure to the MAIDS data and ranking the results with a newly proposed method. The final set had only one configuration in common with those defined in the ISO13232, testifying to the importance of defining an updated and more representative set of configurations for the European context.

Are automatic systems the future of motorcycle safety? A novel methodology to prioritize potential safety solutions based on their projected effectiveness.

OBJECTIVE: Motorcycle riders are involved in significantly more crashes per kilometer driven than passenger car drivers. Nonetheless, the development and implementation of motorcycle safety systems lags far behind that of passenger cars. This research addresses the identification of the most effective motorcycle safety solutions in the context of different countries. METHODS: A knowledge-based system of motorcycle safety (KBMS) was developed to assess the potential for various safety solutions to mitigate or avoid motorcycle crashes. First, a set of 26 common crash scenarios was identified from the analysis of multiple crash databases. Second, the relative effectiveness of 10 safety solutions was assessed for the 26 crash scenarios by a panel of experts. Third, relevant information about crashes was used to weigh the importance of each crash scenario in the region studied. The KBMS method was applied with an Italian database, with a total of more than 1 million motorcycle crashes in the period 2000-2012. RESULTS: When applied to the Italian context, the KBMS suggested that automatic systems designed to compensate for riders' or drivers' errors of commission or omission are the potentially most effective safety solution. The KBMS method showed an effective way to compare the potential of various safety solutions, through a scored list with the expected effectiveness of each safety solution for the region to which the crash data belong. A comparison of our results with a previous study that attempted a systematic prioritization of safety systems for motorcycles (PISa project) showed an encouraging agreement. CONCLUSIONS: Current results revealed that automatic systems have the greatest potential to improve motorcycle safety. Accumulating and encoding expertise in crash analysis from a range of disciplines into a scalable and reusable analytical tool, as proposed with the use of KBMS, has the potential to guide research and development of effective safety systems. As the expert assessment of the crash scenarios is decoupled from the regional crash database, the expert assessment may be reutilized, thereby allowing rapid reanalysis when new crash data become available. In addition, the KBMS methodology has potential application to injury forecasting, driver/rider training strategies, and redesign of existing road infrastructure.

Assessing the potential benefits of the motorcycle autonomous emergency braking using detailed crash reconstructions.

OBJECTIVE: The aim of this study was to assess the feasibility and quantitative potential benefits of a motorcycle autonomous emergency braking (MAEB) system in fatal rear-end crashes. A further aim was to identify possible criticalities of this safety system in the field of powered 2-wheelers (PTWs; e.g., any additional risk introduced by the system itself). METHODS: Seven relevant cases from the Swedish national in-depth fatal crash database were selected. All crashes involved car-following in which a non-anti-lock braking system (ABS)-equipped motorcycle was the bullet vehicle. Those crashes were reconstructed in a virtual environment with Prescan, simulating the road scenario, the vehicles involved, their precrash trajectories, ABS, and, alternatively, MAEB. The MAEB chosen as reference for the investigation was developed within the European Commission-funded Powered Two-Wheeler Integrated Safety (PISa) project and further detailed in later studies, with the addition of the ABS functionality. The boundary conditions of each simulation varied within a range compatible with the uncertainty of the in-depth data and also included a range of possible rider behaviors including the actual one. The benefits of the MAEB were evaluated by comparing the simulated impact speed in each configuration (no ABS/MAEB, ABS only, MAEB). RESULTS: The MAEB proved to be beneficial in a large number of cases. When applicable, the benefits of the system were in line with the expected values. When not applicable, there was no clear evidence of an increased risk for the rider due to the system. DISCUSSION AND LIMITATIONS: MAEB represents an innovative safety device in the field of PTWs, and the feasibility of such a system was investigated with promising results. Nevertheless, this technology is not mature yet for PTW application. Research in the field of passenger cars does not directly apply to PTWs because the activation logic of a braking system is more challenging on PTWs. The deployment of an autonomous deceleration would affect the vehicle dynamics, thus requesting an additional control action of the rider to keep the vehicle stable. In addition, the potential effectiveness of the MAEB should be investigated on a wider set of crash scenarios in order also to avoid false triggering of the autonomous braking.

Analysis of the minimum swerving distance for the development of a motorcycle autonomous braking system.

In the recent years the autonomous emergency brake (AEB) was introduced in the automotive field to mitigate the injury severity in case of unavoidable collisions. A crucial element for the activation of the AEB is to establish when the obstacle is no longer avoidable by lateral evasive maneuvers (swerving). In the present paper a model to compute the minimum swerving distance needed by a powered two-wheeler (PTW) to avoid the collision against a fixed obstacle, named last-second swerving model (Lsw), is proposed. The effectiveness of the model was investigated by an experimental campaign involving 12 volunteers riding a scooter equipped with a prototype autonomous emergency braking, named motorcycle autonomous emergency braking system (MAEB). The tests showed the performance of the model in evasive trajectory computation for different riding styles and fixed obstacles.