A real-time road pricing system: The case of a two-link parallel network

A real-time road pricing system in the case of a two-link parallel network is proposed in this paper. The system that is based on a combination of Dynamic Programming and Neural Networks makes “on-line” decisions about road toll values. In the first phase of the proposed model, the best road toll sequences during certain time period are calculated off-line for many different patterns of vehicle arrivals. These toll sequences are computed using Dynamic Programming approach. In the second phase, learning from vehicle arrival patterns and the corresponding optimal toll sequences, neural network is trained. The results obtained during on-line tests are close to the best solution obtained off-line assuming that the arrival pattern is known.     

基于中台技术的取消省界收费站系统设计与实现

取消高速公路省界收费站是深化收费公路制度改革的重要举措,文章以湖南高速为例,对取消省界收费站系统设计与实现进行探讨,提出了基于中台技术的取消省界站系统的建设方案,分别从技术架构、业务架构、数据架构等方面详细介绍了取消省界站系统的架构设计与实现,并在此基础上重点提出了技术中台的架构设计与实现.系统上线后的运营状况表明,该...     

引导电动汽车用户驾驶行为的充电导航策略

电动汽车充电导航便于用户合理选择充电站,降低用户自身的时间成本和经济成本,缓解配电网端的负荷压力.在电网分时电价的基础上,考虑电动汽车充电路径的选择与车主的驾驶行为密切相关,通过对电动汽车的负荷设备分类建模,根据不同设备类型的重要程度及用户的电动汽车实际工况和地形因素,利用遗传算法分析最佳出行路径,提出以时间成本与经济成本之和最优为目标,引导用户驾驶行为的充电导航策略.在20kmtimes10km含3个充电站的区域内,通过3种不同充电导航策略仿真结果对比,验证所提出的导航策略的可行性和有效性.     

Special Issue on Transport Infrastructure: A Route Choice Experiment with an Efficient Toll

Traffic congestion is a substantial time cost for many urban commuters. This paper studies the response of subjects in an experimental setting in which subjects choose between a short direct route that becomes increasingly congested as more people travel on it and a more indirect route that does not become congested. More specifically, I investigate how subjects respond to the use of a toll that theory predicts will minimize travel time costs. The experimental results reported in this paper show that this toll comes very close to achieving efficient use of the travel network.     

基于DEB-ABC算法的电动汽车充电优化调度模型

随着电动汽车保有量不断上升, 其相关配套设施也面临巨大挑战, 不合理的充电资源分配在充电高峰期会造成部分充电站过度拥挤, 并且影响电网稳定运行. 提出一种考虑多目标优化的调度模型, 通过分析充电站内不同充电选项的排队时间, 并根据排队率和分时电价提出一种动态定价模型, 影响车主充电行为, 结合动态定价模型与充电需求计算充电成本, 考虑基于起讫点的充电总路径行驶时间, 以总成本最少为优化目标, 基于DEB-ABC算法进行求解. 在某区域内对1 500辆电动汽车进行仿真验证, 结果表明提出的优化调度模型可减少充电等待时间、充电成本和总行驶时间, 提高区域内充电站利用率.     

Optimal completed work dependent loading of components in cold standby systems

This paper considers the modelling and optimization of 1-out-of-N: G cold standby (CS) systems with non-repairable components functioning at different levels of productivity or load. The productivity heterogeneity leads to difference in component failure behaviour as well as in operational and replacement costs. Thus, the choice of load or productivity of components can greatly affect the system reliability and mission cost. To make the optimal choice of component loading, we first suggest a method for analysing the reliability and expected mission cost of 1-out-of-N: G non-repairable CS systems with heterogeneous components. The optimal dynamic load distribution problem is then formulated and solved, in which the component loading is chosen depending on the amount of work completed prior to the component activation. The optimal loading is aimed at minimizing the expected mission cost, while meeting a certain system reliability constraint. Examples are given to demonstrate the proposed methodology and the improvement in the optimal design solution through introducing the component productivity’s dependence on the completed work.     

高速公路串行收费站通行能力仿真研究

针对基于车流到达服从标准泊松分布的并行收费站排队服务模型在交通流的时空复杂性、成本、可靠性等方面存在的不足,提出基于元胞自动机建模与仿真的串行收费站布设方式的通行能力、延误及布设个数的分析方法。研究结论表明：串行收费站的通行能力随布设个数的增加而增大,但增大幅度缓慢降低;串行收费站的车均延误以80%通行能力的流量水平为分界点,随着流量继续增大,车均延误急剧上升。给出了不同的流量水平所对应的串行收费站最佳布设个数。     

A distributed charging strategy based on day ahead price model for PV-powered electric vehicle charging station

This paper studies a distributed charging model based on day-ahead optimal internal price for PV-powered Electric Vehicle (EV) Charging Station (PVCS). Considering the feed-in-tariff of PV energy, the price of utility grid and the forecast model of PV based on back-propagation neural network (BPNN), a system operation model of PVCS is introduced, which consists of the profit model of PVCS operator (PO) and the cost model of EV users. The model proposed in this paper can be designed as a Stackelberg game model, where the PO acts as the leader and all EV users participated are regarded as the followers. An optimization strategy based on heuristic algorithm and nonlinear constrained programming are adopted by the PO and each EV user, respectively. Moreover, a real-time billing strategy is proposed to deal with the errors from the forecasted PV energy and the expected charging arrangements. Finally, through a practical case, the validity of the model is verified in terms of increasing operation profit and reducing charging cost.     

Optimal control of an electric vehicle’s charging schedule under electricity markets

As increasing numbers of electric vehicles (EVs) enter into the society, the charging behavior of EVs has got lots of attention due to its economical difference within the electricity market. The charging cost for EVs generally differ from each other in choosing the charging time interval (hourly), since the hourly electricity prices are different in the market. In this paper, the problem is formulated into an optimal control one and solved by dynamic programming. Optimization aims to find the economically optimal charging solution for each vehicle. In this paper, a nonlinear battery model is characterized and presented, and a given future electricity prices is assumed and utilized. Simulation results indicate that daily charing cost is reduced by smart charing.     

Fine-Grained Scalable Video Caching for Heterogeneous Clients

Much research has focused on caching adaptive videos to improve system performance for heterogeneous clients with diverse access bandwidths. However, existing rate-adaptive caching systems, which are based on layered coding or transcoding, often suffer from a coarse adaptation and/or a high computation overhead. In this paper, we propose an innovative rate-adaptive caching framework that enables low-cost and fine-grained adaptation by using MPEG-4 fine-grained scalable videos. The proposed framework is both network-aware and media-adaptive; i.e., the clients can be of heterogeneous streaming rates, and the backbone bandwidth consumption can be adaptively controlled. We develop efficient cache management schemes to determine the best contents to cache and the optimal streaming rate to each client under the framework. We demonstrate via simulations that, compared to nonadaptive caching, the proposed framework with the optimal cache management not only achieves a significant reduction in the data transmission cost, but also enables a flexible utility assignment for the heterogeneous clients. Our results also show that the framework maintains a low computational overhead, which implies that it is practically deployable.     

Cost optimization model following extended renewing two-phase warranty

In this paper, we study an extended warranty model under which the customer is offered an additional warranty period after the original two-phase warranty expires. Under the original two-phase warranty, the warranty period is divided into two non-overlapping subintervals, one of which is for replacement warranty, and the other is for minimal repair warranty. If the system failure occurs during the original warranty period, the failed system is either replaced or minimally repaired by the manufacturer, and if the failure occurs during the extended warranty period, only the minimal repair is conducted. For the system failure during the replacement warranty period, the failed system is replaced by a new one, and the warranty term is renewed anew. Following the expiration of extended warranty, the customer is solely responsible for maintaining the system for a fixed length of time period and replaces the system at the end of such a maintenance period. During the maintenance period, only the minimal repair is given for each system failure. Such a maintenance model can be considered as a generalization of several existing maintenance models which can be obtained as special cases. The main purpose of this article is to determine, from the customer’s perspective, the optimal length of maintenance period after the extended warranty expires. As the criterion to determine the optimal replacement strategy, we adopt the expected cost rate per unit time during the life cycle of the system. Given the cost structures incurred during the life cycle of the system, we formulate the expected cost and the expected length of life cycle to obtain the expected cost rate. The uniqueness of optimal solution for the decision variable is verified when the life distribution of the system shows an increasing failure rate. Numerical examples are provided to illustrate the proposed optimal replacement strategy.     

基于云管边端架构的高速AI稽查系统设计与实现

高速省界收费站撤站收费的推出,对高速收费现有模式提出了新的挑战,如何运用大数据和AI等最新信息技术进行一体化的稽核是目前高速收费稽查的重要研究课题.文章以湖南高速为例,对高速AI稽查系统的设计与实现进行研究,在对系统建设现状进行分析的基础上,给出了系统设计思路和原则,提出了基于云管边端的技术架构,并重点介绍了边缘AI一...     

Sequencing Optimization in k-out-of-n Cold-Standby Systems Considering Mission Cost

The k-out-of-n: G heterogeneous cold-standby system structure is a widely used fault-tolerant system design method, where the sequence in which the different system elements are initiated can greatly affect the system reliability and mission cost. This paper considers the optimal standby element sequencing problem (SESP) for such systems. Given the desired cold-standby redundancy level and fixed set of element choices, the objective of the optimal system design is to select the initiation sequence of the system elements so as to minimize the expected system mission cost while meeting a certain level of system reliability constraint. Based on a discrete approximation of time-to-failure distributions of the system elements, the system reliability and expected mission cost are evaluated simultaneously using a numerical method. A genetic algorithm is used as an optimization tool for solving the formulated SESP problem for k-out-of-n: G heterogeneous cold-standby systems. Examples are given to illustrate the considered problem and the proposed solution methodology.     

Optimal control of admission to a queueing system

Congestion in a queueing system can sometimes be controlled by restricting arrivals, either by "closing a gate" or by charging an entrance fee or toll. We review both static (open-loop) and dynamic (closed-loop) models for control of admission to a queueing system. The main emphases are on the difference between socially optimal and individually optimal (equilibrium) controls and on the use of dynamic-programming inductive analysis to show that an optimal control is monotonic or characterized by one or more "critical numbers." We discuss the potential for use of these models in the analysis of computer/ communication systems and compare the results to certain others in the literature.     

基于Q-Learning算法用户最优充电站运营研究

充电站运营系统是为电动汽车提供充电服务,并与电网、充电站与电力网、交通网数据中心相连接,通过数据库的信息共享、互动和数据挖掘,达到充电站高效运营管理。本文就智能充电站的运营系统的整体结构与数据分析进行探讨。运用Q-Learning算法从用户实现总成本的最优(小),作出最佳的充电服务选择角度分析用户充电决策,可在运营数据挖掘中预测用户的充电行为规律,进而预测运营的充电站设备利用状况,能够对不同充电设施规划方案下的充电负荷进行更加真实准确的计算,从而获得更加准确的充电站运行成本,最终为充电站制定的充电服务运营策略提供依据帮助,进而帮助充电站提高设备利用,提升充电站运营效益。也为日后扩建、新建充电站设备数量、类型、地点等信息提供决策依据。     

基于粗集理论的交通事故死亡人数时间分布分析

利用粗集理论,以事故死亡人数为指标,分别以月、周、日和小时为时间粒度,以吉林省某高速公路1999年至2004年发生的交通事故统计数据为例,对道路交通事故死亡人数的时间分布规律进行分析。结果表明,道路交通事故死亡人数的分布与时间有密切的关系,并且不同时间粒度对死亡人数分布影响的重要程度又存在显著差别。     

A Credit-Based Congestion Management Scheme in General Two-Mode Networks with Multiclass Users

This paper examines the design of the credit-based congestion management schemes that achieve Pareto-improving outcome in general two-mode networks. It is assumed that transit is a slower but cheaper alternative to driving alone. The distributional welfare effects of congestion pricing on users with the different value of time (VOT) in Liu and Nie (Trans Res Board 2283:34–43, 2012) are used in developing Pareto-improving credit schemes. We show that, similar to the single-mode model, the sufficient and necessary condition for the existence of a discriminatory Pareto-improving credit scheme is the reduction in the total system cost. A sufficient condition for the existence of an anonymous Pareto-improving credit scheme is also derived. A cross-OD subsidization scheme is proposed when the sufficient condition is not satisfied for each origin-destination (O-D) pair. Numerical experiments on the expanded Sioux Falls networks with a log-normal VOT distribution demonstrate that the proposed Pareto-improving scheme can generate positive net revenue in the presence of good transit coverage.     

Design of Sustainable Cordon Toll Pricing Schemes in a Monocentric City

This paper addresses the design issue of sustainable cordon toll pricing schemes in a monocentric city. An analytical model that maximizes the total social welfare of urban system is first proposed for simultaneous optimization of the cordon toll location and charge level. The solution properties of the model with/without considering traffic congestion and/or environmental effects are explored and compared analytically. The proposed model is then extended to explicitly incorporate the effects of subsidizing the retrofit of old vehicles on reduction in average vehicle emissions. The optimal subsidy scheme for maximizing the social welfare of the system is also determined. Finally, a numerical example is given to illustrate the model applications. Insightful findings are reported on the interrelationships among cordon toll scheme, traffic congestion and environmental effects, urban population distribution, and subsidy scheme as well as their implications in practice.     

Optimum block replacement policy over a random time horizon

In this paper we consider the block replacement policy (BRP) for a system operating over a random time horizon. Under such a policy, a system is replaced by a new one either at failure or at a given time interval. The optimality criterion is the expected total replacements cost. Conditions under which an optimal replacement period exits are given. It is shown that BRP over an infinite time horizon is obtained as a particular case of the present work. A numerical example is given to illustrate the proposed replacement model.     

Joint location,inventory, and preservation decisions for non-instantaneous deterioration items under delay in payments

This study models a joint location, inventory and preservation decision-making problem for non-instantaneous deteriorating items under delay in payments. An outside supplier provides a credit period to the wholesaler which has a distribution system with distribution centres (DCs). The non-instantaneous deteriorating means no deterioration occurs in the earlier stage, which is very useful for items such as fresh food and fruits. This paper also considers that the deteriorating rate will decrease and the reservation cost will increase as the preservation effort increases. Therefore, how much preservation effort should be made is a crucial decision. The objective of this paper is to determine the optimal locations and number of DCs, the optimal replenishment cycle time at DCs, and the optimal preservation effort simultaneously such that the total network profit is maximised. The problem is formulated as piecewise nonlinear functions and has three different cases. Algorithms based on piecewise nonlinear optimisation are provided to solve the joint location and inventory problem for all cases. Computational analysis illustrates the solution procedures and the impacts of the related parameters on decisions and profits. The results of this study can serve as references for business managers or administrators.