The complexity of signal controlled traffic largely stems from the various driving behaviors developed in response to the traffic signal. However, the existing models take a few driving behaviors into account and cons...The complexity of signal controlled traffic largely stems from the various driving behaviors developed in response to the traffic signal. However, the existing models take a few driving behaviors into account and consequently the traffic dynamics has not been completely explored. Therefore, a new cellular automaton model, which incorporates the driving behaviors typically manifesting during the different stages when the vehicles are moving toward a traffic light, is proposed in this paper. Numerical simulations have demonstrated that the proposed model can produce the spontaneous traffic breakdown and the dissolution of the over-saturated traffic phenomena. Furthermore, the simulation results indicate that the slow-to-start behavior and the inch-forward behavior can foster the traffic breakdown. Particularly, it has been discovered that the over-saturated traffic can be revised to be an under-saturated state when the slow-down behavior is activated after the spontaneous breakdown. Finally, the contributions of the driving behaviors on the traffic breakdown have been examined.展开更多
针对智能交通系统的开发和交通流特性,应用小波多分辨分析理论的M a llat分解算法建立交通流状态辨识方法,利用多种小波系数与交通流参数之间的相应变化规律进行交通突变状态的辨识.交通流状态的突变多与交通事件直接相关,故采用事件和...针对智能交通系统的开发和交通流特性,应用小波多分辨分析理论的M a llat分解算法建立交通流状态辨识方法,利用多种小波系数与交通流参数之间的相应变化规律进行交通突变状态的辨识.交通流状态的突变多与交通事件直接相关,故采用事件和非事件条件下的模拟数据对算法参数进行了标定及离线测试.将算法与几种传统算法分别进行了性能比较,结果表明M a llat分解算法在交通流突变状态实时辨识方面具有很好的性能.展开更多
基金supported by the National Basic Research Program of China(Grand No.2012CB723303)the Beijing Committee of Science and Technology,China(Grand No.Z1211000003120100)
文摘The complexity of signal controlled traffic largely stems from the various driving behaviors developed in response to the traffic signal. However, the existing models take a few driving behaviors into account and consequently the traffic dynamics has not been completely explored. Therefore, a new cellular automaton model, which incorporates the driving behaviors typically manifesting during the different stages when the vehicles are moving toward a traffic light, is proposed in this paper. Numerical simulations have demonstrated that the proposed model can produce the spontaneous traffic breakdown and the dissolution of the over-saturated traffic phenomena. Furthermore, the simulation results indicate that the slow-to-start behavior and the inch-forward behavior can foster the traffic breakdown. Particularly, it has been discovered that the over-saturated traffic can be revised to be an under-saturated state when the slow-down behavior is activated after the spontaneous breakdown. Finally, the contributions of the driving behaviors on the traffic breakdown have been examined.
文摘针对智能交通系统的开发和交通流特性,应用小波多分辨分析理论的M a llat分解算法建立交通流状态辨识方法,利用多种小波系数与交通流参数之间的相应变化规律进行交通突变状态的辨识.交通流状态的突变多与交通事件直接相关,故采用事件和非事件条件下的模拟数据对算法参数进行了标定及离线测试.将算法与几种传统算法分别进行了性能比较,结果表明M a llat分解算法在交通流突变状态实时辨识方面具有很好的性能.
