“Comparing guideway transit implementation plans,including the impact on road traffic”

A methodology for comparing phased implementation plans for a new fixed guideway transit system in an urban area is presented. Four assumptions are made: (1) the guideway system replaces existing or planned bus service, (2) superior service on the new system results in increased ridership when compared to buses; (3) presence of the guideway facility redirects outward urban growth resulting in additional ridership, and (4) conversely, the absence of any action on the new guideway facility reinforces a diffuse urban growth pattern that creates an irreversible loss of transit ridership. The economic comparision of alternative plans includes total as well as “relative” inflation of principal cost components. A key feature of the proposed methodology is including in the comparisons the costs of private automobile mileage that could have been replaced by transit. These costs are expressed as “fuel” and “all other” automobile costs; favorable transit system implementation schedules can then be identified as a function of parametrically assumed values for these two unit costs. A hypothetical example demonstrates the proposed method.     

一种抗差型航迹关联算法研究

航迹关联是多源信息融合中的关键问题.通过选择目标数据相似度计算模型和参数,计算不同信源航迹与航迹间的关联相似度,并以之构成目标关联矩阵.引入伪行列式的概念,对目标关联矩阵进行变换,形成目标联合分配矩阵.在分配限定条件下,通过最大化目标联合分配似然度,可得到航迹与航迹间的关联匹配对,实现航迹关联.仿真实验表明,在信源具有较大的系统误差情况下,该算法能够保持较高的关联正确率,表现出了良好的抗差特性.     

满意优化在建立网络设计期模型中的应用

将多目标满意优化模型用于解决网络设计期优化问题.对同时优化链路容量与路由选择问题的CFA模型提出相应的满意优化模型.并分别为建造总费用与全网利用率这两个指标选择适合它们的满意度函数,最后得出设计优化问题的综合满意度函数.该方法在实际运用中显得更加灵活,也更有效率.     

A Two-Stage Optimization Model for Staggered Work Hours

Traditional or standard work schedules refer to the requirement that workers must be at work the same days and during the same hours each day. This requirement constrains work-related trip arrivals, and generates morning and afternoon peak hours due to the concentration of work days and/or work hours. Alternative work schedules seek to reschedule work activities away from this traditional requirement. The aim is to flatten the peak hours by spreading the demand (i.e., assigning it to the shoulders of the peak hour), lowering the peak demand. This not only would reduce societal costs but also can help to minimize the physical requirements. In this article, a two-stage optimization model is presented to quantify the effects of staggered work hours under incentive policies. In the first stage, a variation of the generalized quadratic assignment problem is used to represent the firm’s assignment of workers to different work starting times. This is the input of a nonlinear complementarity problem that captures the behavior of the users of the transportation network who are seeking to overcome the constraints imposed by working schedules (arrival times). Two examples are provided to show how the model can be used to (a) quantify the effects and response of the firm to external incentives and (b) evaluate what type of arrangements in starting times are to be made in order to achieve a social optimum.     

A new statistical method of assigning vehicles to delivery areas for CO2 emissions reduction

Transportation CO₂ emissions are expected to increase in the following decades, and thus, new and better alternatives to reduce emissions are needed. Road transport emissions are explained by different factors, such as the type of vehicle, delivery operation and driving style. Because different cities may have conditions that are characterized by diversity in landforms, congestion, driving styles, etc., the importance of assigning the proper vehicle to serve a particular region within the city provides alternatives to reduce CO₂ emissions. In this article, we propose a new methodology that results in assigning trucks to deliver in areas such that the CO₂ emissions are minimized. Our methodology clusters the delivery areas based on the performance of the vehicle fleet by using the k-means algorithm and Tukey’s method. The output is then used to define the optimal CO₂ truck-area assignment. We illustrate the proposed approach for a parcel company that operates in Mexico City and demonstrate that it is a practical alternative to reduce transportation CO₂ emissions by matching vehicle type with delivery areas.     

多业务环境下切换优先算法的改进

切换是移动通信中充分利用有限频谱的一项关键技术。本文提出了在数据业务和话音业务环境下,基于混合信道分配(HCA)方案上的双先进先出(FIFO)排队算法:系统分别为切换语音呼叫和初始语音呼叫与数据呼叫分配了大小为Nh和No的排队空间,两队列均遵从FIFO法则;同时,为切换语音呼叫预留了可根据当前业务量调整数目的Cr个信道。通过与单FIFO排队算法和基于HCA的单FIFO排队算法的比较,可以看到本算法改善了系统的性能,更能适应高业务量小区的需要。     

Optimal assignment for check-in counters based on passenger arrival behaviour at an airport

Establishing how to utilize check-in counters at airport passenger terminals efficiently is a major concern facing airport operators and airlines. Inadequate terminal capacity and the inefficient utilization of facilities such as check-in counters are major factors causing congestion and delays at airport passenger terminals. However, such delays and congestion can be reduced by increasing the efficiency of check-in counter operations, based on an understanding of passengers' airport access behaviour. This paper presents an assignment model for check-in counter operations, based on passengers' airport arrival patterns. In setting up the model, passenger surveys are used to determine when passengers arrive at the airport terminals relative to their flight departure times. The model then uses passenger arrival distribution patterns to calculate the most appropriate number of check-in counters and the duration of time that each counter should be operated. This assignment model has been applied at the Seoul Gimpo International Airport in Korea. The model provides not only a practical system for the efficient operations of time-to-time check-in counter assignments, but also a valuable means of developing effective longer-term solutions to the problem of passenger terminal congestion and delays. It also offers airlines a means of operating check-in counters with greater cost effectiveness, thus leading to enhanced customer service.     

Assessment of schedule-based and frequency-based assignment models for strategic and operational planning of high-speed rail services

Despite some substantial limitations in the simulation of low-frequency scheduled services, frequency-based (FB) assignment models are by far the most widely used in practice. They are less expensive to build and less demanding from the computational viewpoint with respect to schedule-based (SB) models, as they require neither explicit simulation of the timetable (on the supply side), nor segmentation of OD matrices by desired departure/arrival time (on the demand side).The objective of this paper is to assess to what extent the lack of modeling capabilities of FB models is acceptable, and, on the other hand, the cases in which such approximations are substantial and more detailed SB models are needed. This is a first attempt to shed light on the trade-off between (frequency-based) model inaccuracy and (scheduled-based) model development costs in the field of long-distance (e.g. High-speed Rail, HSR) service modeling.To this aim, we considered two modeling specifications estimated using mixed Revealed Preferences (RP) and Stated Preferences (SP) surveys and validated with respect to the same case study. Starting from an observed (baseline) scenario, we artificially altered the demand distributions (uniform vs. time-varying demand) and the supply configuration (i.e. train departure times), and analyzed the differences in modal split estimates and flows on individual trains, using the two different model specifications.It resulted that when the demand distribution is uniform within the period of analysis, such differences are significant only when departure times of trains are strongly unevenly spaced in time. In such cases, the difference in modal shares, using FB w.r.t. SB, is in the range of [0%, +5%] meaning that FB models tend to overestimate HSR modal shares. When the demand distribution is not uniform, the difference in modal shares, using FB w.r.t. SB, is in the range of [−10%, +10%] meaning that FB models can overestimate or underestimate HSR modal shares, depending on timetable settings with respect to travelers’ desired departure times. The differences in on-board train flow estimates are more substantial in both cases of uniform and not uniform demand distribution.     

Waiting time and the role and value of information in scheduled transport

A new logit-based model for assigning public transit passengers to transit lines or routes is proposed. The model is based on the realistic assumption that once passengers arrive at stops, they can obtain information regarding the specific departure times. Furthermore, it takes into account that passengers are heterogeneous and hence, the choice made by a ‘representative’ passenger appears to be stochastic. The model is evaluated by means of simulations.