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

Effect of advanced rider assistance system on powered two wheelers crashes

Advanced Rider Assistance Systems (ARAS) are solutions developed to reduce the crashes rate of Powered Two Wheelers (PTWs). They assist riders in their driving task by transmitting information on their environment or by automatically controlling the dynamics of their vehicle. This study describes a methodology for evaluating the impact of 14 ARAS on PTWs crashes. This methodology consists first of establishing links between ARAS functionalities and riders' failures in crashes situations. Then, an analysis of real crashes cases was conducted using two reals crashes databases: the "In-depth crashes investigation at the Laboratory of Accident Mechanisms Analysis (LMA)" in Salon-de-Provence, France, and the "Initiative for the Global harmonization of Accidents Data". A total of 390 crashes were analyzed. The results showed that ARAS had an influence on 61.5% of the crashes studied. ARAS benefits at the French national level were also assessed, with a weighting of the results obtained. In the French national data, the Anti-lock Braking System had the highest overall impact among the ARASs, estimated to have influenced 39.1% of crashes. Next, emergency braking systems influenced 30.1% of crashes, and an anti-collision warning system had an impact on 29.8% of crashes. This work provided an initial assessment of the most promising technologies for PTWs road safety. It could be used to guide industry and road safety policy towards the development of the most beneficial systems, and the introduction of standards or regulations.

Exploratory analysis of evasion actions of powered two-wheeler conflicts at unsignalized intersection

The study investigates the braking and steering evasions of powered two-wheelers (PTWs) during severe conflicts observed at an unsignalized intersection. Traffic conflicts were detected using a surrogate safety indicator called anticipated collision time (ACT). Then the peak-over-threshold approach was used to identify the severe conflicts and the evasive actions. Conflicts between right-turning PTWs and through-moving vehicles, through-moving PTWs crossing through-moving vehicles, and merging/diverging PTWs were analyzed using the minimum ACT (ACTmin), maximum deceleration rate (DRmax), maximum yaw rate (YRmax), and time of evasive action (TEA). The evasive actions were classified into five categories: driver/rider error, no-evasion, braking-only, steering-only, and both braking and steering. Analysis reveals that right-turning PTWs experience higher crash risk (0.7 %) than the other movements. PTW riders primarily employ extreme steering maneuvers (greater than 13 degrees/s) to evade conflicts, whereas braking rates lie in the normal ranges (less than 1.5 m/s2). The time of evasive action varies between 2.04 and 2.44 s, with the right-turning PTW riders responding early. Through-moving riders commit errors while evading severe conflicts and perform fewer evasive actions than right-turning and merging/diverging riders. Right-turning riders perform more steering-only evasions than braking-only, whereas the riders involved in the other two conflicts execute more braking-only evasions. These findings suggest that conflict type influences riders' braking and steering responses. Hence, future applications in advanced driver/rider assistance systems and training programs should consider appropriate evasive action strategies for different conflict types.

Motorcycle emergency steering assistance: A systematic approach from system definition to benefit estimation and exploratory field testing

Braking assistance systems are already contributing to improving motorcyclists' safety, however, research on emergency systems acting on the steering is lacking. These systems, already available for passenger cars, could prevent or mitigate motorcycle crashes in which safety functions based only on braking are ineffective. The first research question was to quantify the safety impact of diverse emergency assistance systems acting on the steering of a motorcycle. For the most promising system, the second research question was to assess the feasibility of its intervention using a real motorcycle. Three emergency steering assistance systems were defined in terms of Functionality, Purpose, and Applicability: Motorcycle Curve Assist (MCA), Motorcycle Stabilisation (MS), and Motorcycle Autonomous Emergency Steering (MAES). Experts evaluated each system's applicability and effectiveness based on the specific crash configuration (using Definitions for Classifying Accidents - DCA), the Knowledge-Based system of Motorcycle Safety (KBMS), and the In-Depth Crash Reconstruction (IDCR). An experimental campaign was conducted with an instrumented motorcycle to assess the rider's reaction to external steering input. A surrogate method for an active steering assistance system imparted external steering torques in correspondence with a lane change to analyse the effect of the steering inputs on motorcycle dynamics and rider controllability. MAES globally got the best score for each assessment method. MS received better evaluations than MCA in two out of three methods. The union of the three systems covered a sizeable fraction of the crashes considered (maximum score in 22.8% of the cases). An estimation of the injury potential mitigation, based on injury risk functions for motorcyclists, was made for the most promising system (MAES). The field test data and video footage showed no instability or loss of control, despite the high intensity (>20Nm) of the external steering input. The rider interviews confirmed that the external action was intense but manageable. For the first time, this study presents an exploratory assessment of the applicability, benefits, and feasibility of motorcycle safety functions acting on the steering. MAES, in particular, was found applicable to a relevant share of crashes involving motorcycles. Remarkably, applying an external action to produce a lateral avoidance manoeuvre proved feasible in a real-world test setting.

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.

Motorcycle That See: Multifocal Stereo Vision Sensor for Advanced Safety Systems in Tilting Vehicles

Advanced driver assistance systems, ADAS, have shown the possibility to anticipate crash accidents and effectively assist road users in critical traffic situations. This is not the case for motorcyclists, in fact ADAS for motorcycles are still barely developed. Our aim was to study a camera-based sensor for the application of preventive safety in tilting vehicles. We identified two road conflict situations for which automotive remote sensors installed in a tilting vehicle are likely to fail in the identification of critical obstacles. Accordingly, we set two experiments conducted in real traffic conditions to test our stereo vision sensor. Our promising results support the application of this type of sensors for advanced motorcycle safety applications.

Further development of Motorcycle Autonomous Emergency Braking (MAEB), what can in-depth studies tell us? A multinational study

OBJECTIVE

In 2006, Motorcycle Autonomous Emergency Braking (MAEB) was developed by a European Consortium (Powered Two Wheeler Integrated Safety, PISa) as a crash severity countermeasure for riders. This system can detect an obstacle through sensors in the front of the motorcycle and brakes automatically to achieve a 0.3 g deceleration if the collision is inevitable and the rider does not react. However, if the rider does brake, full braking force is applied automatically. Previous research into the potential benefits of MAEB has shown encouraging results. However, this was based on MAEB triggering algorithms designed for motorcycle crashes involving impacts with fixed objects and rear-end crashes. To estimate the full potential benefit of MAEB, there is a need to understand the full spectrum of motorcycle crashes and further develop triggering algorithms that apply to a wider spectrum of crash scenarios.

METHODS

In-depth crash data from 3 different countries were used: 80 hospital admittance cases collected during 2012-2013 within a 3-h driving range of Sydney, Australia, 40 crashes with Injury Severity Score (ISS)>15 collected in the metropolitan area of Florence, Italy, during 2009-2012, and 92 fatal crashes that occurred in Sweden during 2008-2009. In the first step, the potential applicability of MAEB among the crashes was assessed using a decision tree method. To achieve this, a new triggering algorithm for MAEB was developed to address crossing scenarios as well as crashes involving stationary objects. In the second step, the potential benefit of MAEB across the applicable crashes was examined by using numerical computer simulations. Each crash was reconstructed twice-once with and once without MAEB deployed.

RESULTS

The principal finding is that using the new triggering algorithm, MAEB is seen to apply to a broad range of multivehicle motorcycle crashes. Crash mitigation was achieved through reductions in impact speed of up to approximately 10 percent, depending on the crash scenario and the initial vehicle pre-impact speeds.

CONCLUSIONS

This research is the first attempt to evaluate MAEB with simulations on a broad range of crash scenarios using in-depth data. The results give further insights into the feasibility of MAEB in different speed ranges. It is clear then that MAEB is a promising technology that warrants further attention by researchers, manufacturers, and regulators.