This paper proposes an improved cellular automaton model to describe the urban traffic flow with the consideration of traffic light and driving behaviour effects. Based on the model, the characteristics of the urban t...This paper proposes an improved cellular automaton model to describe the urban traffic flow with the consideration of traffic light and driving behaviour effects. Based on the model, the characteristics of the urban traffic flow on a single- lane road are investigated under three different control strategies, i.e., the synchronized, the green wave and the random strategies. The fundamental diagrams and time-space patterns of the traffic flows are provided for these strategies respectively. It finds that the dynamical transition to the congested flow appears when the vehicle density is higher than a critical level. The saturated flow is less dependent on the cycle time and the strategies of the traffic light control, while the critical vehicle density varies with the cycle time and the strategies. Simulated results indicate that the green wave strategy is proven to be the most effective one among the above three control strategies.展开更多
针对无人车在现实交通流中的驾驶行为以及车辆间相互影响机制还不明确的现状,提出逼近最优换道策略的无人车驾驶模型.结合无人车周围的交通环境,引入驾驶行为指标体系,利用层次分析法测算指标权值.基于欧氏距离与灰色关联分析的Topsis(T...针对无人车在现实交通流中的驾驶行为以及车辆间相互影响机制还不明确的现状,提出逼近最优换道策略的无人车驾驶模型.结合无人车周围的交通环境,引入驾驶行为指标体系,利用层次分析法测算指标权值.基于欧氏距离与灰色关联分析的Topsis(Technique for Order Preference by similarity to an Ideal Solution)法建立驾驶行为决策模型来计算换道最优逼近值,代替随机换道策略驾驶模型中的随机概率值;建立逼近最优换道策略的无人车驾驶模型,利用美国洲际5号公路的实际交通数据对新模型进行数值仿真.结果表明:逼近最优换道策略的无人车驾驶模型明显优于随机换道的无人车驾驶模型,能够改善交通拥堵状况,提高整个道路车辆的行驶速度.展开更多
基金supported by the Strategic Research Grants from City University of Hong Kong [Project No. CityU-SRG 7002370]the National Natural Science Foundation of China (Grant No. 10972135)+1 种基金Science Foundation of Shanghai Maritime University(Grant No. 20110046)the Science Foundation of Shanghai Science Commission (Grant Nos. 09DZ2250400 and 09530708200)
文摘This paper proposes an improved cellular automaton model to describe the urban traffic flow with the consideration of traffic light and driving behaviour effects. Based on the model, the characteristics of the urban traffic flow on a single- lane road are investigated under three different control strategies, i.e., the synchronized, the green wave and the random strategies. The fundamental diagrams and time-space patterns of the traffic flows are provided for these strategies respectively. It finds that the dynamical transition to the congested flow appears when the vehicle density is higher than a critical level. The saturated flow is less dependent on the cycle time and the strategies of the traffic light control, while the critical vehicle density varies with the cycle time and the strategies. Simulated results indicate that the green wave strategy is proven to be the most effective one among the above three control strategies.
文摘针对无人车在现实交通流中的驾驶行为以及车辆间相互影响机制还不明确的现状,提出逼近最优换道策略的无人车驾驶模型.结合无人车周围的交通环境,引入驾驶行为指标体系,利用层次分析法测算指标权值.基于欧氏距离与灰色关联分析的Topsis(Technique for Order Preference by similarity to an Ideal Solution)法建立驾驶行为决策模型来计算换道最优逼近值,代替随机换道策略驾驶模型中的随机概率值;建立逼近最优换道策略的无人车驾驶模型,利用美国洲际5号公路的实际交通数据对新模型进行数值仿真.结果表明:逼近最优换道策略的无人车驾驶模型明显优于随机换道的无人车驾驶模型,能够改善交通拥堵状况,提高整个道路车辆的行驶速度.
