交通综合信息平台建设研究

建立一个基于GIS-T的交通综合信息平台。它能够接受、存储和处理多源异构数据．能够为各种应用子系统和公众提供良好的信息服务。同时，对平台的框架设计、功能构成以及平台实现的关键技术进行说明和分析。     

利用公交通行能力解决公交问题的探讨

分析我国公交的发展,指出在我国发展公交的道路上缺乏对公交通行能力这一重要指标的思考,提出研究公交通行能力来解决我国公交运营中存在的问题,并建立公交(包括公交车辆和公交乘客)通行能力模型。然后以北京中关村大街的公交专用道为实例,从公交通行能力方面分析该段道路公交车拥堵、混乱产生的原因,然后根据实际情况提出解决措施。     

车辆折算系数的分类及算法

提出了标准车的选择原则:车长等于约定的长度;当交通流密度很小时,以道路设计速度行驶;驾驶员遵守交通规则。定义了微观车辆折算系数:交通流全部由标准车组成时的流量与交通流全部由某种车组成时的流量之比。定义了聚类车辆折算系数:组成该类车型的所有自然车的微观折算系数与组成比例的乘积之和。定义了宏观车辆折算系数:组成混合交通流的所有自然车的微观折算系数与组成比例的乘积之和。计算了这三种车辆折算系数。     

基于WebGIS车辆定位系统的设计

探讨了如何利用WebGIS技术实现在Internet环境下车辆定位中的应用,包括系统的组成、工作原理、短消息和WebGIS架构等内容,该设计方法是在微软最新的开发环境.Net和Mapinfo公司的MapX控件基础上开发实现的,详细解释了WebGIS架构和介绍了车辆定位系统的主要功能。系统的实现使用户可以直接在Internet环境下完成查询指定车辆的位置等相关信息,为智能交通的实现奠定了基础。     

Implementation and application of a stochastic aircraft boarding model

The aircraft turnaround processes is mainly controlled by the ground handling, airport or airline staff, except the aircraft boarding, which is driven by the passengers’ experience and willingness or ability to follow the proposed boarding procedures. The paper uses a prior developed, calibrated, stochastic aircraft boarding model, which is applied to different boarding strategies (chronological order of passenger arrival, hand luggage handling), group constellations and innovative infrastructural changes (Flying Carpet, Side-Slip Seat, Foldable Passenger Seat). In this context, passenger boarding is assumed to be a stochastic, agent-based, forward-directed, one-dimensional and discrete process. The stochastic model covers individual passenger behavior as well as operational constraints and deviations. A comprehensive assessment using one model allows for efficient comparison of current research approaches and innovative operational solutions for efficient passenger boarding.     

基于多旅行商问题的应急设施服务区划分模型

基于多旅行商问题，增设集散中心需求及应急服务设施资源容量约束条件，以最小化遍历区域内全部集散中心的综合旅行时间成本为优化目标，构建一种应急设施服务区划分模型，确定各应急设施的服务区范围.设计一种复合算法求解模型，首先基于P-中值选址模型的优化理念，形成初始方案；继而加入禁忌搜索算法，结合LKH求解器对模型进行迭代优化求得最优解.基于宁波市北仑区实际拓扑网络进行案例分析，验证了模型和求解方法的有效性.     

The desulphurisation of shipping: Past,present and the future under a global cap

As from January 2020, the International Maritime Organization (IMO) is implementing a global 0.5% limit on the sulphur content of fuel, commonly known as the global sulphur cap. This limit is the latest policy in the efforts to reduce sulphur emissions from shipping, following the designation of emission control areas (ECAs) and other regional regulations. In this paper, a literature review is conducted of academic studies that have dealt with issues relating to the reduction of maritime sulphur emissions. Various recurring research themes are identified, spanning the areas of operations research, maritime economics and transport policy. The effects and implications of available compliance options are then analyzed from the perspectives of ship operators, shippers and consumers. Using lessons learned from the enforcement of ECA regulations, this is followed by an appraisal of various potential issues related to the enforcement of these new global regulations. It is found that a homogeneous enforcement regime is required to ensure a level playing field amongst ship operators and that the global sulphur cap may lead to serious market distortion, due to the potential short term rise of fuel prices. The paper concludes with a set of recommendations for future research on sulphur emissions from shipping in the aftermath of the global cap and, looking forward, to its relationship to the IMO strategy on the reduction of greenhouse gas (GHG) shipping emissions.     

Investigation of tailpipe and evaporative emissions from China IV and Tier 2 passenger vehicles with different gasolines

The limited understanding of vehicular emissions in China, especially evaporative emissions, is one obstacle to establishing tighter standards. To evaluate tailpipe and evaporative emissions, two typical China IV vehicles and one Tier 2 vehicle with an onboard refuelling vapour recovery (ORVR) system were selected and tested. One of the China IV vehicles was fuelled with gasoline, E10 and M15, respectively, to investigate the effect of fuel properties on vehicular emissions. For each vehicle, cold-start tailpipe emission tests were conducted first, followed by an evaporation test. Based on the emission factors and real-world vehicle activity data, the annual tailpipe and evaporative hydrocarbon (HC) emissions of each vehicle were calculated and compared. The results show that E10 and M15 significantly reduced the tailpipe CO and particle number (PN) emissions but seriously aggravated the NOx emissions, especially for M15. The hot soak losses (HSLs) and diurnal breathing losses (DBLs) were slightly impacted by the fuel properties. The annual evaporative emissions with E10 and M15 were higher than that with gasoline. The ORVR system effectively controlled the evaporative emissions, especially for DBLs. Evaporative emissions from the China IV vehicles were 1.1–1.4 times the tailpipe HC emissions. Additionally, the evaporative emission factors of the China IV vehicles were almost 50% lower than the standard (2.0 g/test), whereas their annual evaporative emissions were almost 1.8–2.8 times higher than those from the Tier 2 vehicle. Therefore, controlling evaporative emissions currently remains a great need in China, and the ORVR might be a recommended evaporative control technology.     

Solving the gate assignment problem through the Fuzzy Bee Colony Optimization

In the field of Swarm Intelligence, the Bee Colony Optimization (BCO) has proven to be capable of solving high-level combinatorial problems, like the Flight-Gate Assignment Problem (FGAP), with fast convergence performances. However, given that the FGAP can be often affected by uncertainty or approximation in data, in this paper we develop a new metaheuristic algorithm, based on the Fuzzy Bee Colony Optimization (FBCO), which integrates the concepts of BCO with a Fuzzy Inference System. The proposed method assigns, through the multicriteria analysis, airport gates to scheduled flights based on both passengers’ total walking distance and use of remote gates, to find an optimal flight-to-gate assignment for a given schedule. Comparison of the results with the schedules of real airports has allowed us to show the characteristics of the proposed concepts and, at the same time, it stressed the effectiveness of the proposed method.     

Locating emergency vehicles with an approximate queuing model and a meta-heuristic solution approach

In this paper, the location of emergency service (ES) vehicles is studied on fully connected networks. Queuing theory is utilized to obtain the performance metrics of the system. An approximate queuing model the (AQM) is proposed. For the AQM, different service rate formulations are constructed. These formulations are tested with a simulation study for different approximation levels. A mathematical model is proposed to minimize the mean response time of ES systems based on AQM. In the model, multiple vehicles are allowed at a single location. The objective function of the model has no closed form expression. A genetic algorithm is constructed to solve the model. With the help of the genetic algorithm, the effect of assigning multiple vehicles on the mean response time is reported.