基于改进因子评点法的公交专用道服务水平分级

通过引入因子评点法及分析其原理，提出了改进的因子评点法，拓展了理论方法 的应用范围.提出以单位公交专用道延误作为评价公交专用道的服务水平分级的指标；针对 既有的上游停靠站延误估算模型，通过实际调研确定模型中解释变量的取值，从而获取容量 为15 288 的延误样本；然后基于延误样本对单位公交专用道延误进行频次分析，得到其累积 分布，采用改进的因子评点法对公交专用道服务水平进行分级.本文研究成果为公交专用道 的运营评价和规划设计提供了指导依据.     

Closing the loop in real-time railway control: Framework design and impacts on operations

Railway traffic is heavily affected by disturbances and/or disruptions, which are often cause of delays and low performance of train services. The impact and the propagation of such delays can be mitigated by relying on automatic tools for rescheduling traffic in real-time. These tools predict future track conflict based on current train information and provide suitable control measures (e.g. reordering, retiming and/or rerouting) by using advanced mathematical models. A growing literature is available on these tools, but their effects on real operations are blurry and not yet well known, due to the very scarce implementation of such systems in practice.In this paper we widen the knowledge on how automatic real-time rescheduling tools can influence train performance when interfaced with railway operations. To this purpose we build up a novel traffic control framework that couples the state-of-the art automatic rescheduling tool ROMA, with the realistic railway traffic simulation environment EGTRAIN, used as a surrogate of the real field. At regular times ROMA is fed with current traffic information measured from the field (i.e. EGTRAIN) in order to predict possible conflicts and compute (sub) optimal control measures that minimize the max consecutive delay on the network. We test the impact of the traffic control framework based on different types of interaction (i.e. open loop, multiple open loop, closed loop) between the rescheduling tool and the simulation environment as well as different combinations of parameter values (such as the rescheduling interval and prediction horizon). The influence of different traffic prediction models (assuming e.g. aggressive versus conservative driving behaviour) is also investigated together with the effects on traffic due to control delays of the dispatcher in implementing the control measures computed by the rescheduling tool.Results obtained for the Dutch railway corridor Utrecht–Den Bosch show that a closed loop interaction outperforms both the multiple open loop and the open loop approaches, especially with large control delays and limited information on train entrance delays and dwell times. A slow rescheduling frequency and a large prediction horizon improve the quality of the control measure. A limited control delay and a conservative prediction of train speed help filtering out uncertain traffic dynamics thereby increasing the effectiveness of the implemented measures.     

An analytical model to conduct a person-based evaluation of transit preferential treatments on signalized arterials

The complexities of urban transportation networks where multiple modes with different characteristics and needs travel in combination with constraints on space and funding make the sustainable management of these systems a challenge. In order to improve transit service, space (e.g., dedicated bus lanes) and time (e.g., transit signal priority strategies) Transit Preferential Treatments (TPT) are deployed to improve transit operations. The objective of this paper is to develop an analytical model that allows for a person-based evaluation of alternative TPTs when considered individually and in combination. In particular, the analytical model is developed to assess person delay and person discharge flow at any intersection that is part of a signalized arterial, where auto arrivals are in platoons. The performance of TPTs is evaluated using both the analytical model and through microsimulation tests on two intersections of San Pablo Avenue in Berkeley, CA. Space TPTs such as dedicated bus lanes and queue jumper lanes are beneficial in reducing bus person delay when provided in addition to the existing lanes; however, the effectiveness of time TPTs such as green extension depends on the level of auto demand in combination with signal settings. Changes in person discharge flow are not significant for any of the treatments tested with the exception of the bus lane substitution with and without green extension, which led to a significant decrease in person discharge flow. Increased bus frequency increases the effectiveness of transit signal priority in reducing total and bus person delay. The analytical model results produce ranking outcomes that are comparable with the microsimulation ones and therefore, the model may be used for a quantitative evaluation of TPTs without the need for data intensive and time consuming calibration efforts required for microsimulation models. The developed model can be used to guide infrastructure and investment decisions on where such TPTs should be implemented and under what conditions space TPTs should be combined with time TPTs to improve person mobility.     

基于Q强化学习的AVB数据转发时延模型研究

为了提高音视频桥接技术(Audio/Video Bridge,AVB)数据时延分析结果的正确性,以AVB交换机处转发的数据为研究对象,在经典的AVB协议模型中融入Q强化学习理论,构造时延数学模型.在完成AVB协议模型和Q强化学习理论研究基础上,提出更加符合实际的AVB交换机数据转发策略,结合车载以太网数据转发时延影响因...     

变道约束下近邻交织区交通均衡组织方法

针对相邻较近的交织区车辆持续交织运行特点,以提高交织区通行效率及交通安全为目标,提出一种基于变道约束下近邻交织区交通均衡组织方法,旨在计算不同时段交通量所对应近邻各交织区的最佳提前变道诱导距离,以减少近邻交织区车辆相互干扰,降低平均交通延误,提高道路通行效率.对重庆市海峡路两段近邻交织区的日均交通量(4 092 pcu/h),早高峰时段交通量(5 340 pcu/h),晚高峰时段交通量(4 596 pcu/h),以及年均交通量(3 276 pcu/h)进行仿真建模分析.实验选取近邻交织区内累计平均延误作为近邻交织区的评价指标,利用仿真软件(Vissim 4.3)持续仿真 40次.结果表明,最佳提前变道约束距离为交织区长度的 60%,其相应的平均交通延误分别降低了57%、73%、63%和72%.     

车队离散模型研究

用“多点摄像法”对长春市的2个路段交通流进行了实地调查。通过数据处理,给出了车队离散过程中的多点流量图式以及多段的车速分布。用实际观测数据所得的流量图式与TRRI。的流量图式进行对比,分析异同。还对车辆行驶速度及行驶时间分布进行了拟合,分析了各离散模型的适用范围。最后对车队离散进行计算机仿真,得出了满意的结论。     

境外港口升级改造工程建设要点

随着亚非拉国家腹地经济的发展,升级改造类工程项目逐渐增多。结合案例,分析码头升级改造工程的制约因素及需要重点考虑的问题;对港口规划中码头规模确定、码头前沿线确定所需考虑的主要因素及滚装码头的布置形式,码头结构设计中结构稳定性、整体性所需考虑的要素及解决方案,以及施工过程中所需考虑的主要问题等进行系统的对比分析。     

Pre-timed control for an under-saturated and over-saturated isolated intersection: a Bee Colony Optimization approach

In this paper we study the problem of determining the optimum cycle and phase lengths for isolated signalized intersections. Calculation of the optimal cycle and green phase lengths is based on the minimization of the average control delay experienced by all vehicles that arrive at the intersection within a given time period. We consider under-saturated as well as over-saturated conditions at isolated intersections. The defined traffic signal timing problem, that belongs to the class of combinatorial optimization problems, is solved using the Bee Colony Optimization (BCO) metaheuristic approach. The BCO is a biologically inspired method that explores collective intelligence applied by honey bees during the nectar collecting process. The numerical experiments performed on some examples show that the proposed approach is competitive with other methods. The obtained results show that the proposed approach is capable of generating high-quality solutions within negligible processing times.     

A connected-vehicle-based dynamic control model for managing the bus bunching problem with capacity constraints

This paper describes a connected-vehicle-based system architecture which can provide more precise and comprehensive information on bus movements and passenger status. Then a dynamic control method is proposed using connected vehicle data. Traditionally, the bus bunching problem has been formulated into one of two types of optimization problem. The first uses total passenger time cost as the objective function and capacity, safe headway, and other factors as constraints. Due to the large number of scenarios considered, this type of framework is inefficient for real-time implementation. The other type uses headway adherence as the objective and applies a feedback control framework to minimize headway variations. Due to the simplicity in the formulation and solution algorithms, the headway-based models are more suitable for real-time transit operations. However, the headway-based feedback control framework proposed in the literature still assumes homogeneous conditions at all bus stations, and does not consider restricting passenger loads within the capacity constraints. In this paper, a dynamic control framework is proposed to improve not only headway adherence but also maintain the stability of passenger load within bus capacity in both homogenous and heterogeneous situations at bus stations. The study provides the stability conditions for optimal control with heterogeneous bus conditions and derives optimal control strategies to minimize passenger transit cost while maintaining vehicle loading within capacity constraints. The proposed model is validated with a numerical analysis and case study based on field data collected in Chengdu, China. The results show that the proposed model performs well on high-demand bus routes.     

A family of macroscopic node models

The family of macroscopic node models which comply to a set of basic requirements is presented and analysed. Such models are required in macro-, mesoscopic traffic flow models, including dynamic network loading models for dynamic traffic assignment. Based on the behaviour of drivers approaching and passing through intersections, the model family is presented. The headway and the turn delay of vehicles are key variables. Having demand and supply as input creates a natural connection to macroscopic link models. Properties like the invariance principle and the conservation of turning fractions are satisfied. The inherent non-uniqueness is analysed by providing the complete set of feasible solutions. The node models proposed by Tampère et al. (2011), Flötteröd and Rohde (2011) and Gibb (2011) are members of the family. Furthermore, two new models are added to the family. Solution methods for all family members are presented, as well as a qualitative and quantitative comparison. Finally, an outlook for the future development of empirically verified models is given.