Kotte Jens, Schmeichel Carsten, Zlocki Adrian, Gathmann Hauke, Eckstein Lutz
a Forschungsgesellschaft Kraftfahrwesen mbH , Aachen , Germany.
b Institut für Kraftfahrzeuge (ika), RWTH Aachen University , Germany.
Traffic Inj Prev. 2017 May 29;18(sup1):S37-S43. doi: 10.1080/15389588.2017.1310380. Epub 2017 Apr 3.
State-of-the-art collision avoidance and collision mitigation systems predict the behavior of pedestrians based on trivial models that assume a constant acceleration or velocity. New sources of sensor information-for example, smart devices such as smartphones, tablets, smartwatches, etc.-can support enhanced pedestrian behavior models. The objective of this article is the development and implementation of a V2Xpedestrian collision avoidance system that uses new information sources.
A literature review of existing state-of-the-art pedestrian collision avoidance systems, pedestrian behavior models in advanced driver assistance systems (ADAS), and traffic simulations is conducted together with an analysis of existing studies on typical pedestrian patterns in traffic. Based on this analysis, possible parameters for predicting pedestrian behavior were investigated. The results led to new requirements from which a concept was developed and implemented.
The analysis of typical pedestrian behavior patterns in traffic situations showed the complexity of predicting pedestrian behavior. Requirements for an improved behavior prediction were derived. A concept for a V2X collision avoidance system, based on a cost function that predicts pedestrian near future presence, and its implementation is presented. The concept presented considers several challenges such as information privacy, inaccuracies of the localization, and inaccuracies of the prediction.
A concept for an enhanced V2X pedestrian collision avoidance system was developed and introduced. The concept uses new information sources such as smart devices to improve the prediction of the pedestrian's presence in the near future and considers challenges that come along with the usage of these information sources.
先进的防撞和碰撞缓解系统基于假设恒定加速度或速度的简单模型来预测行人行为。新的传感器信息源,例如智能手机、平板电脑、智能手表等智能设备,能够支持改进的行人行为模型。本文的目的是开发并实现一种利用新信息源的车对一切(V2X)行人防撞系统。
对现有的先进行人防撞系统、高级驾驶辅助系统(ADAS)中的行人行为模型以及交通模拟进行文献综述,并对有关交通中典型行人模式的现有研究进行分析。基于此分析,研究了预测行人行为的可能参数。这些结果产生了新的要求,并据此开发并实现了一个概念。
对交通场景中典型行人行为模式的分析显示了预测行人行为的复杂性。得出了改进行为预测的要求。提出了一种基于预测行人近期出现的成本函数的V2X防撞系统概念及其实现方法。所提出的概念考虑了诸如信息隐私、定位不准确和预测不准确等若干挑战。
开发并引入了一种增强型V2X行人防撞系统的概念。该概念利用智能设备等新信息源来改进对行人近期出现情况的预测,并考虑了使用这些信息源所带来的挑战。