针对多车道路复杂的车辆行驶状况,文章借助无线传感网络的相关技术来设计车辆运行中的物联网络(The Internet of Things,IOT)方案,并分析了运行中车辆间产生的威胁关系,提出一种利用改进边缘势场函数来描述车辆行驶中动态产生的威胁关...针对多车道路复杂的车辆行驶状况,文章借助无线传感网络的相关技术来设计车辆运行中的物联网络(The Internet of Things,IOT)方案,并分析了运行中车辆间产生的威胁关系,提出一种利用改进边缘势场函数来描述车辆行驶中动态产生的威胁关系的方法。并在预判威胁发生的估计区域的基础上,引入微分进化算法,给出了规避路径的规划算法。实验表明,相对于传统势场法,改进的边缘势场函数更适用于描述道路车辆间相互威胁的动态关系;微分进化算法在路径规划过程中,相对传统群算法,具有更好的全局优化能力及更短的收敛时间。展开更多
In the near future, active safety systems will take more control over the vehicle driving, even up to introducing fully autonomous vehicles. Nowadays, it is expected that the active safety systems will aid avoiding co...In the near future, active safety systems will take more control over the vehicle driving, even up to introducing fully autonomous vehicles. Nowadays, it is expected that the active safety systems will aid avoiding collisions much more efficiently than human drivers. These systems can protect not only the passengers, but also other road users. To mitigate collision, certain maneuvers (e.g., sudden braking, lane change, etc.) need to be done in a reasonably quick time. However, this may lead to low-g energy pulses. The latter fact, may cause unexpected and, in some cases, unwanted occupant body motion resulting even in OOP (out of position) postures. New patterns of occupant reactions in such cases are, to some extent, confirmed experimentally [1-3]. This paper evaluates the limits of standard ATDs (anthropometric test devices) and chosen human models in well established maneuver scenarios. Obtained results are compared with experimental data available in the literature. Drawbacks identify new challenges for the near future simulation based safety engineering. One scenario with combined conditions of emergency braking during lane change has been used as an example of OOP posture after maneuver.展开更多
文摘针对多车道路复杂的车辆行驶状况,文章借助无线传感网络的相关技术来设计车辆运行中的物联网络(The Internet of Things,IOT)方案,并分析了运行中车辆间产生的威胁关系,提出一种利用改进边缘势场函数来描述车辆行驶中动态产生的威胁关系的方法。并在预判威胁发生的估计区域的基础上,引入微分进化算法,给出了规避路径的规划算法。实验表明,相对于传统势场法,改进的边缘势场函数更适用于描述道路车辆间相互威胁的动态关系;微分进化算法在路径规划过程中,相对传统群算法,具有更好的全局优化能力及更短的收敛时间。
文摘In the near future, active safety systems will take more control over the vehicle driving, even up to introducing fully autonomous vehicles. Nowadays, it is expected that the active safety systems will aid avoiding collisions much more efficiently than human drivers. These systems can protect not only the passengers, but also other road users. To mitigate collision, certain maneuvers (e.g., sudden braking, lane change, etc.) need to be done in a reasonably quick time. However, this may lead to low-g energy pulses. The latter fact, may cause unexpected and, in some cases, unwanted occupant body motion resulting even in OOP (out of position) postures. New patterns of occupant reactions in such cases are, to some extent, confirmed experimentally [1-3]. This paper evaluates the limits of standard ATDs (anthropometric test devices) and chosen human models in well established maneuver scenarios. Obtained results are compared with experimental data available in the literature. Drawbacks identify new challenges for the near future simulation based safety engineering. One scenario with combined conditions of emergency braking during lane change has been used as an example of OOP posture after maneuver.