排序方式： 共有105条查询结果，搜索用时 15 毫秒
51.
依据铁路运输生产实际,充分考虑集装箱货物与集装箱班列在时间和数量方面的匹配关系,以集装箱货物在集装箱办理站的总停留时间最小为优化目标,以集装箱货物装车唯一性、班列编成箱数、作业时间和发车间隔为约束条件,构建铁路集装箱班列始发时刻优化的非线性混合整数规划模型。根据模型的特点,设计基于遗传算法的求解方法。由随机产生和先到先服务方案结合的方法生成初始种群,并运用启发式策略修复进化过程中出现的不可行解。以胶州-黄岛之间的铁路集装箱班列为例进行仿真计算。结果表明:模型和算法具有较高的计算效率;利用模型及算法得到的集装箱班列始发时刻与集装箱货物的数量、到达时间分布之间具有较好的匹配性,使集装箱在办理站停留时间最短,制定的班列开行计划响应了用户需求。 相似文献
52.
中国目前的交通情况与过去的欧洲有很多相似之处,可借鉴其相关经验教训.以匈牙利布达佩斯为例,探讨其如何利用交通需求管理措施进行城市停车管理.首先指出停车管理的目标应为降低小汽车的使用需求、强化公共交通相对于私人交通的竞争力.然后,在路内停车管理层面,剖析中国停车管理存在的问题,分别从政策及标准、运营管理模式、技术应用三方... 相似文献
53.
依托辽宁省交通工程质量监督综合信息系统的开发实际,介绍了质量监督管理信息系统的业务流程和基本功能,利用UML对部分功能进行需求分析,为同类系统的需求分析工作提供了参考实例。 相似文献
54.
随着城市发展,任何交通问题都可归到质和量的统一,针对交通出行需求,定量分析交通活动相互联系的数量关系。结合案例分析,根据地块的开发强度和不同用地的出行特征预测交通需求,通过预测方案比较,从定性转化为定量,为决策方确定项目规模提供充分的依据。 相似文献
55.
Gonçalo Homem De Almeida Correia Diana Ramos Jorge David Marques Antunes 《智能交通系统杂志
》2014,18(3):299-308
》2014,18(3):299-308
Car-sharing systems are an alternative to private transportation whereby a person may use an automobile without having to own the vehicle. The classical systems in Europe are organized in stations scattered around the city where a person may pick up a vehicle and afterward return it to the same station (round trip). Allowing a person to drop off the vehicle at any station, called one-way system, poses a significant logistics problem because it creates a significant stock imbalance at the stations, which means that there will be times when users will not have a vehicle available for their trip. Previous mathematical programming formulations have tried to overcome this limitation by optimizing trip selection and station location in a city in order to capture the best trips for balancing the system. But there was one main limitation: The users were assumed to be inflexible with respect to their choice of a station, and held to use only the one closest to their origin and destination. If the user is willing to use the second or even the third closest station the user could benefit from using real-time information on vehicle stocks at each station and be able to select the one with available capacity. In this article we extend a previous model for trip selection and station location that takes that aspect into account by considering more vehicle pick-up and drop-off station options and then apply it to a trip origin–destination matrix from the Lisbon region in Portugal. Through the extended formulation we were able to conclude that user flexibility allied with having information on vehicle stocks increases the profit of the company, as people will go directly to a station with a vehicle available, thus making the use of the fleet more efficient. Observing the size of the stations resulting from the model, we also concluded that the effect of information is enhanced by large car-sharing systems consisting of many small stations. 相似文献
56.
In this paper, we will first review literature of the land use and transportation interaction and then develop a new land use allocation methodology called Three Stages-Two-Feedback Method (Integration Method) for both land use allocation and the transportation policy options with a practical implementation. Then we apply this method in an urban general planning project in China with more than 1.2 million populations. In this project, we evaluated three land use allocation strategies and three transportation policy options using two application tools (with and without feedbacks) using this method implemented in a land use planning system UPlan and a transportation planning system Emme. The results show that the use of the feedback method (Application Two) results in a vehicle distance reduction and the increase in the service coverage area of transit bus stops at the same time. Due to the use of transportation accessibility and the congestion measures with a MSA implementation, the accessibility measure shows a convergent process over iterations. This nice feature can be used for alternative comparisons. Future research subjects are also discussed. 相似文献
57.
58.
The emergence of electric unmanned aerial vehicle (E-UAV) technologies, albeit somewhat futuristic, is anticipated to pose similar challenges to the system operation as those of electric vehicles (EVs). Notably, the charging of EVs en-route at charging stations has been recognized as a significant type of flexible load for power systems, which often imposes non-negligible impacts on the power system operator’s decisions on electricity prices. Meanwhile, the charging cost based on charging time and price is part of the trip cost for the users, which can affect the spatio-temporal assignment of E-UAV traffic to charging stations. This paper aims at investigating joint operations of coupled power and electric aviation transportation systems that are associated with en-route charging of E-UAVs in a centrally controlled and yet dynamic setting, i.e., with time-varying travel demand and power system base load. Dynamic E-UAV charging assignment is used as a tool to smooth the power system load. A joint pricing scheme is proposed and a cost minimization problem is formulated to achieve system optimality for such coupled systems. Numerical experiments are performed to test the proposed pricing scheme and demonstrate the benefits of the framework for joint operations. 相似文献
59.
The lack of a proper integration of strategic Air Traffic Management decision support tools with tactical Air Traffic Control interventions usually generates a negative impact on the Reference Business Trajectory adherence, and in consequence affects the potential of the Trajectory-Based Operations framework. In this paper, a new mechanism relaying on Reference Business Trajectories as a source of data to reduce the amount of Air Traffic Controller interventions at the tactical level while preserving Air Traffic Flow Management planned operations is presented. Artificial Intelligence can enable Constraint Programming as it is a powerful paradigm for solving complex, combinatorial search problems. The proposed methodology takes advantage of Constraint Programming and fosters adherence of Airspace User’s trajectory preferences by identifying tight interdependencies between trajectories and introducing a new mechanism to improve the aircraft separation at concurrence events considering time uncertainty. The underlying philosophy is to capitalize present degrees of freedom between layered Air Traffic Management planning tools, when sequencing departures at the airports by considering the benefits of small time stamp changes in the assigned Calculated Take-Off Time departures and to enhance Trajectory-Based Operations concepts. 相似文献
60.
Major technological and infrastructural changes over the next decades, such as the introduction of autonomous vehicles, implementation of mileage-based fees, carsharing and ridesharing are expected to have a profound impact on lifestyles and travel behavior. Current travel demand models are unable to predict long-range trends in travel behavior as they do not entail a mechanism that projects membership and market share of new modes of transport (Uber, Lyft, etc.). We propose integrating discrete choice and technology adoption models to address the aforementioned issue. In order to do so, we build on the formulation of discrete mixture models and specifically Latent Class Choice Models (LCCMs), which were integrated with a network effect model. The network effect model quantifies the impact of the spatial/network effect of the new technology on the utility of adoption. We adopted a confirmatory approach to estimating our dynamic LCCM based on findings from the technology diffusion literature that focus on defining two distinct types of adopters: innovator/early adopters and imitators. LCCMs allow for heterogeneity in the utility of adoption for the various market segments i.e. innovators/early adopters, imitators and non-adopters. We make use of revealed preference (RP) time series data from a one-way carsharing system in a major city in the United States to estimate model parameters. The data entails a complete set of member enrollment for the carsharing service for a time period of 2.5 years after being launched. Consistent with the technology diffusion literature, our model identifies three latent classes whose utility of adoption have a well-defined set of preferences that are significant and behaviorally consistent. The technology adoption model predicts the probability that a certain individual will adopt the service at a certain time period, and is explained by social influences, network effect, socio-demographics and level-of-service attributes. Finally, the model was calibrated and then used to forecast adoption of the carsharing system for potential investment strategy scenarios. A couple of takeaways from the adoption forecasts were: (1) placing a new station/pod for the carsharing system outside a major technology firm induces the highest expected increase in the monthly number of adopters; and (2) no significant difference in the expected number of monthly adopters for the downtown region will exist between having a station or on-street parking. 相似文献