Sonstige
The advent of active safety systems calls for the development of appropriate testing methods. These methods aim to assess the effectivity of active safety systems based on criteria such as their capability to avoid accidents or lower impact speeds and thus mitigate the injury severity. For prospective effectivity studies, simulation becomes an important tool that needs valid models not only to simulate driving dynamics and safety systems, but also to resolve the collision mechanics. This paper presents an impact model which is based on solving momentum conservation equations and uses it in an effectivity study of a generic collision mitigation system in reconstructed real accidents at junctions. The model assumes an infinitely short crash duration and computes output parameters such as post-crash velocities, delta-v, force directions, etc. and is applicable for all impact collision configurations such as oblique, excentric collisions. Requiring only very little computational effort, the model is especially useful for effectivity studies where large numbers of simulations are necessary. Validation of the model is done by comparison with results from the widely used reconstruction software PC-Crash. Vehicles involved in the accidents are virtually equipped with a collision mitigation system for junctions using the software X-RATE, and the simulations (referred to as system simulations) are started sufficiently early before the collision occurred. In order to assess the effectivity, the real accident (referred to as baseline) is compared with the system simulations by computing the reduction of the impact speeds and delta-v.
This work describes the results of the experimental activity, illustrating the driving behavior observed in different conditions, relating them to the different methods of ADAS intervention and comparing the driver behavior without ADAS. In the present study, driver behavior was studied in road accidents involving elderly pedestrians, with different ADAS HMIs, as a base to develop a driver model in near missing pedestrian accidents. A literature research was conducted with the aim of finding out the main influencing factors, including environment, boundary conditions, configuration of impact, pedestrian and driver information, when pedestrian fatalities occur and an analysis of frequent road accidents was conducted to get more detailed information about the driver- behavior. In order to obtain more detailed information about pedestrian accidents, real road accidents were reconstructed with multibody simulations on PC-Crash and, by the comparison between literature findings and reconstructions, a generic accident scenario was defined. The generic accident scenario was implemented on the full scale dynamic driving simulator in use at the Laboratory for Safety and Traffic Accident Analysis (LaSIS, University of Florence, Italy) in order to analyse the driving behaviors of volunteers, also considering the influence of ADAS devices. Forty-five young volunteers were enrolled for this study, resulting in forty valid tests on different testing scenarios. Two different scenarios consisted in driving with or without ADAS in the vehicle. Different kinds of ADAS, acoustic and optical, with different time of intervention were tested in order to study the different reactions of the driver. The tests showed some interesting differences between driver's behavior when approaching the critical situation. Drivers with ADAS reacted earlier, but more slowly, depending also on the type of alarm, and often with double reaction when braking. In fact, the results of the activity showed that with ADAS intervention the time to collision (TTC) increases, but the reaction time and braking modality change: a) there is a sort of "latency" time between the accelerator pedal release and the brake pressure; b) the brake pressure is initially less intense. So the driver only partially takes advance from the TTC increase. These differences were valued not only qualitatively, but quantitatively as well. This work revealed to be useful to improve the knowledge of drivers" behavior, in order to realize a driver model that can be implemented to help attaining and assessing higher levels of automation through new technology.