Rolling horizon control framework for driver assistance systems. Part II: Cooperative sensing and cooperative control

This contribution furthers the control framework for driver assistance systems in Part I to cooperative systems, where equipped vehicles can exchange relevant information via vehicle-to-vehicle communication to improve the awareness of the ambient situation (cooperative sensing) and to manoeuvre together under a common goal (cooperative control). To operationalize the cooperative sensing strategy, the framework is applied to the development of a multi-anticipative controller, where an equipped vehicle uses information from its direct predecessor to predict the behaviour of its pre-predecessor. To operationalize the cooperative control strategy, we design cooperative controllers for sequential equipped vehicles in a platoon, where they collaborate to optimise a joint objective. The cooperative control strategy is not restricted to cooperation between equipped vehicles. When followed by a human-driven vehicle, equipped vehicles can still exhibit cooperative behaviour by predicting the behaviour of the human-driven follower, even if the prediction is not perfect.The performance of the proposed controllers are assessed by simulating a platoon of 11 vehicles with reference to the non-cooperative controller proposed in Part I. Evaluations show that the multi-anticipative controller generates smoother behaviour in accelerating phase. By a careful choice of the running cost specification, cooperative controllers lead to smoother decelerating behaviour and more responsive and agile accelerating behaviour compared to the non-cooperative controller. The dynamic characteristics of the proposed controllers provide new insights into the potential impact of cooperative systems on traffic flow operations, particularly at the congestion head and tail.     

物流网络优化中路径问题的研究

在深入分析物流系统化和网络化的基础上,对物流网络优化中物流路径问题进行研究,通过分析物流结构模型和数学模型,提出了最短路径和关键路径物流策略的分析方法,给出了具体的计算方法,并举实例加以说明,为解决现代物流结构中存在的系统设计和运作等问题提供了理论依据和技术方法。     

Adapt-Traf: An adaptive multiagent road traffic management system based on hybrid ant-hierarchical fuzzy model

Usually, road networks are characterized by their great dynamics including different entities in interactions. This leads to more complex road traffic management. This paper proposes an adaptive multiagent system based on the ant colony behavior and the hierarchical fuzzy model. This system allows adjusting efficiently the road traffic according to the real-time changes in road networks by the integration of an adaptive vehicle route guidance system. The proposed system is implemented and simulated under a multiagent platform in order to discuss the improvement of the global road traffic quality in terms of time, fluidity and adaptivity.     

The performance of route modification and demand stabilization strategies in stochastic vehicle routing

A key concern in managing vehicle routing operations under stochastic demands is whether, on the basis of travel distance, route modification yields materially greater logistical efficiency than fixed routes. This research uses statistical calibration as the primary technique to develop a robust and tractable model for estimating this difference in logistical efficiency. Based on features such as the models predictive accuracy and generalizability, it constitutes a substantive improvement over existing models. The present study also expands the range of predictive models relevant to vehicle routing under stochastic demands with models to estimate the transportation and inventory effects of persuading customers to stabilize their ordering patterns.     

光纤网中可变波长光交换机的优化设计

为了解决光波转换器成本昂贵与其在光纤网络中的重要性之间的矛盾，提出了新的可变波长光交换机结构和相应的优化路由及波长分配算法．为了验证该可变波长光交换机的优越性，基于NSF网络进行了仿真，并给出了最有效的光波转换器的使用方法及其配置．该光交换机设计结构和仿真工具，可以方便地应用到其它骨干光网络中各个交换节点的最优化设计中．     

Real-time freeway traffic state estimation based on extended Kalman filter: Adaptive capabilities and real data testing

This paper reports on real data testing of a real-time freeway traffic state estimator, with a particular focus on its adaptive capabilities. The pursued general approach to the real-time adaptive estimation of complete traffic state in freeway stretches or networks is based on stochastic macroscopic traffic flow modeling and extended Kalman filtering. One major innovative feature of the traffic state estimator is the online joint estimation of important model parameters (free speed, critical density, and capacity) and traffic flow variables (flows, mean speeds, and densities), which leads to three significant advantages of the estimator: (1) avoidance of prior model calibration; (2) automatic adaptation to changing external conditions (e.g. weather and lighting conditions, traffic composition, control measures); (3) enabling of incident alarms. These three advantages are demonstrated via suitable real data testing. The achieved testing results are satisfactory and promising for subsequent applications.     

Energy-aware load-balaning fault-tolerant routing scheme for ad hoc sensor networks

Most routing protocols for sensor networks try to extend network lifetime by minimizing the energy consumption, but have not taken the network reliability into account. An energy-aware, load-balancing and fault-tolerant routing scheme, termed as ELFR was propsed to adapt to the harsh environment. First a network robustness model was presented. Based on this model, the route discovery phase was designed to make the sensors to construct into a hop-leveled network which is mesh structure. A cross-layer design was adopted to measure the transmission delay so as to detect the failed nodes. The routing scheme works with acknowledge （ACK） feedback mechanism to transfer control messages to avoid producing extra control overhead messages. When nodes fail, the new healthy paths will be selected locally without rerouting. Simulation results show that our scheme is much robust, and it achieves better energy efficiency, load balancing and maintains good end-to-end delay.     

方格路网车辆路径在线选择模型及竞争分析

为分析城市方格路网遭遇突发性堵塞下的车辆路径选择问题,应用在线问题与竞争策略的方法建模,设计了2种在线路径选择竞争策略,即方向贪婪策略和多选择移动策略,计算了2种策略的竞争性能比。通过策略竞争分析得出:在发生突发性堵塞的情形下,方向贪婪策略下的费用为最优费用的3倍;利用多选择移动策略在对网络具有实际意义约束条件下的部分情形能够得到最优费用,且在最坏情形下的费用为最优费用的2倍;2种策略的竞争性能比优于以往研究给出的堵塞不可恢复问题竞争比的下界。     

基于空间特性的行李跟随系统的车辆调度方法

为了提高车辆配送初始解获得的效率,在不确定条件下,研究了上海世博会行李跟随系统需求点的空间特性,提出了基于空间特性的车辆调度方法,建立了需求点的空间特性SLINK聚类分析方法和聚类分析结果评估方法。计算结果表明:在需求点群聚状态下,采用基于空间特性的聚类分析法的调度初始解总距离为583,而传统SWEEP扫描法的调度初始解总距离为595,因此,在对车辆调度问题进行求解时,对需求点的空间分布特性进行分析有助于不确定环境下车辆调度问题的最终求解。