基于效率-安全评价的近距离错位交叉口信控优化

在城市中2个近距离错位交叉口之间的交织路段,来自不同方向的车流相互干扰严重,尤其是在交织长度限制下的连续换道操作,对交通效率和安全水平造成不良影响。因此,基于效率-安全综合考虑,研究了一种安全协调信号控制方案。即在上游交叉口的支路处设置右转信号灯,将交织路段内主、次路的车流冲突点进行时间和空间上的分离,并对近距离错位交叉口进行系统的相位和配时优化设计,从而达到降低车辆运行延误、提高行车安全性的目的。以福州市浦上大道-金州南路-金港路交叉口为例,运用Vissim微观仿真软件和SSAM替代安全评价模型,从效率-安全2个方面综合比较安全协调信控方案与信控现状、单点优化方案的优劣。实验结果表明,相对于信控现状,单点优化方案和安全协调信控方案的效率-安全水平分别提升了36.17%和57.17%,验证了安全协调信控方案的优越性。此外,通过Vissim调整2个交叉口之间的距离,比较安全协调信控方案和单点优化方案相对于信控现状的效率-安全综合优化程度。研究表明,近距离错位交叉口的间距越小,安全协调信控方案的优越性越明显。

相邻近距桥头交叉口信控协调优化

为提高相邻近距桥头的通行能力,减少桥面车辆排队和排队车辆的制动等影响,以泉州市德化县龙津桥两端交叉口为例,以排队长度、路段平均行程速度等为目标评价指标,借助Synchro仿真软件进行分析评价。在单点信控优化的基础上,根据高峰时段的交通量和交通管理措施,采取“双向绿波”的信号协调控制优化策略,建立优化的信号协调控制系统。

基于时空不均匀的交叉口信号控制自主优化

针对交叉口信号控制自主化程度不足的问题,基于交通流的时空不均匀特性,分别在时间维度引入双环相位方案和在空间维度设置左转待行区,以有效绿灯时间和信号周期为变量,构建以交叉口平均延误最小和通行能力最大为目标的信控自主优化模型,采用差分进化算法(DE)求解模型得到最优配时方案。选择潮州市一交叉口作为实际案例对象应用优化模型,研究结果表明:基于时空不均匀的交叉口信控自主优化模型对交叉口的优化结果更好,相比于对称相位方案,本模型在交叉口的通行能力上提升了7.84%,车辆平均延误降低了30.78%。

NSGA-Ⅱ based traffic signal control optimization algorithm for over-saturated intersection group

In order to improve the efficiency of traffic signal control for an over-saturated intersection group, a nondominated sorting genetic algorithm Ⅱ（NSGA-Ⅱ） based traffic signal control optimization algorithm is proposed. The throughput maximum and average queue ratio minimum for the critical route of the intersection group are selected as the optimization objectives of the traffic signal control for the over-saturated condition. The consequences of the efficiency between traffic signal timing plans generated by the proposed algorithm and a commonly utilized signal timing optimization software Synchro are compared in a VISSIM signal control application programming interfaces （SCAPI） simulation environment by using real filed observed traffic data. The simulation results indicate that the signal timing plan generated by the proposed algorithm is more efficient in managing oversaturated flows at intersection groups, and, thus, it has the capability of optimizing signal timing under the over-saturated conditions.

OPTIMAL CONTRACTS IN TWO-ECHELON SUPPLY CHAIN UNDER ASYMMETRIC INFORMATION AND NONLINEAR DEMAND

The challenge for supply chain management is to create appropriate supply chain contracts so as to optimize the system performance. To examine the role of asymmetric information in a two-echelon supply chain system and derive supply chain contracts to deal with existing asymmetric information, a two level supply chain model including one Supplier and one retailer under the demand of price elasticity is developed. By using the principalagent principle and the optimal control theory, three types of supply chain contract, i. e. , a wholesale pricing contract, a two-parameter linear and a two-parameter nonlinear contracts are obtained. In these contracts, the Supplier has asymmetric information about the retailer cost structure. Simulation results show that the two-parameter contracts are more effective strategies to achieve supply chain coordination.

Perimeter traffic control strategy based on macroscopic fundamental diagrams

A perimeter traffic signal control strategy is proposed based on the macroscopic fundamental diagram theory(MFD)to solve the signal control problem in oversaturated states.First,the MFD of a specific regional network can be derived using VSS IM simulation software.Secondly,the maximum number of cumulative vehicles that the network can accommodate is determined based on the MFD.Then,through monitoring the influx flow,the number of vehicles existing in and exiting from the network,a perimeter traffic control model is proposed to optimize the signal timing of the boundary intersections.Finally,a virtual network simulation model is established and three different kinds o f traffic demand are loaded into the network.Simulation results show that a fer the strategy implementation,the number o f vehicles accumulating in the network can be kept near the optimal value,while the number o f both entering and exiting vehicles increases significantly and the road network can be maintained at a large capacity.Simultaneously,the queue length at the approach of the border intersections is reasonably controlled and vehicles entering and exiting the network can maintain a more efficient and stable speed.The network performance indices such as the average traffic delay and average number of stops can be improved to a certain degree,thus verifying the effectiveness and feasibility of the perimeter control strategy.

Optimal distributed resource allocation in a wireless sensor network for control systems

Wireless technology is applied increasingly in networked control systems. A new form of wireless network called wireless sensor network can bring control systems some advantages, such as flexibility and feasibility of network deployment at low costs, while it also raises some new challenges. First, the communication resources shared by all the control loops are limited. Second, the wireless and multi-hop character of sensor network makes the resources scheduling more difficult. Thus, how to effectively allocate the limited communication resources for those control loops is an important problem. In this paper, this problem is formulated as an optimal sampling frequency assignment problem, where the objective function is to maximize the utility of control systems, subject to channel capacity constraints. Then an iterative distributed algorithm based on local buffer information is proposed. Finally, the simulation results show that the proposed algorithm can effectively allocate the limited communication resource in a distributed way. It can achieve the optimal quality of the control system and adapt to the network load changes.

Joint Optimization of Channel Allocation,Link Assignment and Power Control for Device-to-Device Communication Underlaying Cellular Network

Device-to-Device(D2D) communication has been proposed to facilitate cellular network with system capacity(SC) and quality of service(QoS).We consider the design of link assignment(LA),channel allocation(CA)and power control(PC) in D2D-aided content delivery scenario for both user fairness(UF)and system throughput(ST) under QoS requirement.Due to the complexity of the problem,we decompose it into two components:CA is formulated from graph perspective to mitigate severe co-channel interference,which turns out to be the Max K-cut problem;LA and PC are jointly optimized to utilize the gain achieved from CA for supreme performance,and specifically,genetic algorithm(GA) is adopted to optimize LA,but when deriving the fitness of each chromosome,PC optimization will be involved.Thanks to numerical results,we elucidate the efficacy of our scheme.

Adaptive Optimal Capacity Perception and Control for Wireless Multi-Hop Networks

In wireless multimedia communications, it is extremely difficult to derive general end-to-end capacity results because of decentralized packet scheduling and the interference between communicating nodes. In this paper, we present a state-based channel capacity perception scheme to provide statistical Quality-of-Service (QoS) guarantees under a medium or high traffic load for IEEE 802.11 wireless multi-hop networks. The proposed scheme first perceives the state of the wireless link from the MAC retransmission information and extends this information to calculate the wireless channel capacity, particularly under a saturated traffic load, on the basis of the interference among flows and the link state in the wireless multi-hop networks. Finally, the adaptive optimal control algorithm allocates a network resource and forwards the data packet by taking into consideration the channel capacity deployments in multi-terminal or multi-hop mesh networks. Extensive computer simulations demonstrate that the proposed scheme can achieve better performance in terms of packet delivery ratio and network throughput compared to the existing capacity prediction schemes.

PSO-based Control Algorithm for Polarization Mode Dispersion Self-adaptive Compensation

Polarization mode dispersion(PMD) is considered to be the ultimate limitation in high-speed optical fiber communication systems. Establishing an effective control algorithm for adaptive PMD compensation is a challenging task, because PMD possesses the time-varying and statistical properties. The particle swarm optimization(PSO) algorithm is introduced into self-adaptive PMD compensation as feedback control algorithm. The experiment results show that PSO-based control algorithm has some unique features of rapid convergence to the global optimum without being trapped in local sub-optima and good robustness to noise in the optical fiber transmission line that has never been achieved in PMD compensation before.

Researches On The Optimal Design Of Intersection Signal Lights Fuzzy Control

Fuzzy control is an important branch of intelligent control, and this paper describes the application of fuzzy pattern study in intelligent control, begins with a brief overview introduction for development of intelligent control, and then describes the main components of the fuzzy model and its characteristics and fuzzy pattern control system.Fuzzy pattern applications in the intersection signal intelligent control showed fuzzy mode control can effectively reduce the single intersection average vehicle delay time, making the intersection more unobstructed to pass.

Control-Relevant Identification Test Design for Open-Loop Experiment

An optimal experiment design (DED) with respect to the use of designing model-base controller was studied. The mean squared error at the setpoint is chosen as the performance criterion. Simple design formulas are derived based on the asymptotic theory. The signal is used for the open loop experiment. The design constraint is the power of the process signal or the process input signal. The results give guideline for identification application.

Effect of active control on optimal structures in wall turbulence

The effect of active control imposed at the wall on optimal structures in wall turbulence is studied by using a linear transient growth model.When the detection plane of the control is located in the buffer layer,the influence of the control on the transient growth of large scale motion becomes negligible as Reynolds number increases.However,if the control signal is detected at the plane located in the logarithm region,the transient growth at large scale can be greatly suppressed.New peak values of transient growth resulting from the strong blowing and suction on the wall exist.The study indicates that a proper selection of control imposed on the wall can suppress the large scale motion in the logarithmic region.