A GIS‐based traffic analysis zone design: implementation and evaluation

The purpose of this paper is to implement an efficient method for GIS‐based traffic analysis zone (TAZ) design in order to evaluate and validate such a method. The method was developed by the authors.

Moran's I spatial autocorrelation coefficient and sample variance are used for evaluating the generated TAZs using the Champaign‐Urbana, IL region as a case study. Sensitivity analysis is also conducted to explore the fluctuations in TAZ generation outcomes. The evaluation, the validation as well as the TAZ design have been implemented with ARC/INFO GIS software on a UNIX workstation platform.     

Simple analytical models for estimating the queue lengths from probe vehicles at traffic signals

As mobile traffic sensor technology gets more attention, mathematical models are being developed that utilize this new data type in various intelligent transportation systems applications. This study introduces simple analytical estimation models for queue lengths from tracked or probe vehicles at traffic signals using stochastic modeling approach. Developed models estimate cycle-to-cycle queue lengths by using primary parameters such as arrival rate, probe vehicle proportions, and signal phase durations. Valuable probability distributions and moment generating functions for probe information types are formulated. Fully analytical closed-form expressions are given for the case ignoring the overflow queue and approximation models are presented for the overflow case. Derived models are compared with the results from VISSIM-microscopic simulation. Analytical steady-state and cycle-to-cycle estimation errors are also derived. Numerical examples are shown for the errors of these estimators that change with probe vehicle market penetration levels, arrival rates, and volume-to-capacity ratios.     

Train routing and timetabling problem for heterogeneous train traffic with switchable scheduling rules

This paper proposes a mathematical model for the train routing and timetabling problem that allows a train to occasionally switch to the opposite track when it is not occupied, which we define it as switchable scheduling rule. The layouts of stations are taken into account in the proposed mathematical model to avoid head-on and rear-end collisions in stations. In this paper, train timetable could be scheduled by three different scheduling rules, i.e., no switchable scheduling rule (No-SSR) which allows trains switching track neither at stations and segments, incomplete switchable scheduling rule (In-SSR) which allows trains switching track at stations but not at segments, and complete switchable scheduling rule (Co-SSR) which allows trains switching track both at stations and segments. Numerical experiments are carried out on a small-scale railway corridor and a large-scale railway corridor based on Beijing–Shanghai high-speed railway (HSR) corridor respectively. The results of case studies indicate that Co-SSR outperforms the other two scheduling rules. It is also found that the proposed model can improve train operational efficiency.     

Data Fusion-Based Traffic Density Estimation and Prediction

Traffic congestion has become a major challenge in recent years in many countries of the world. One way to alleviate congestion is to manage the traffic efficiently by applying intelligent transportation systems (ITS). One set of ITS technologies helps in diverting vehicles from congested parts of the network to alternate routes having less congestion. Congestion is often measured by traffic density, which is the number of vehicles per unit stretch of the roadway. Density, being a spatial characteristic, is difficult to measure in the field. Also, the general approach of estimating density from location-based measures may not capture the spatial variation in density. To capture the spatial variation better, density can be estimated using both location-based and spatial data sources using a data fusion approach. The present study uses a Kalman filter to fuse spatial and location-based data for the estimation of traffic density. Subsequently, the estimated data are utilized for predicting density to future time intervals using a time-series regression model. The models were estimated and validated using both field and simulated data. Both estimation and prediction models performed well, despite the challenges arising from heterogeneous traffic flow conditions prevalent in India.     

铁路线路技术标准与运量水平之间的耦合关系研究

为了确定铁路线路技术标准与运量水平之间的耦合关系,分析运量水平主导线路主要技术标准类项目特性和线路技术标准主导运量水平类项目特性,从供需平衡角度出发,得出运量构成机制和线路标准条件从能力供给到运量诱发的质变条件。     

美国交通运输机构及职能简介

从4个层次分别介绍美国联邦政府运输机构、美国联邦独立运输管理机构、美国地方交通运输机构及美国道路交通管理机构的职能分工，侧重于其在道路交通管理方面的职能。     

老旧散货船营运缺陷与管理探讨

针对老旧散货船在营运中安全问题,阐述了加强老旧散货船的营运管理,做好安全防范,采取正确的管理措施是确保船舶营运安全的前提。重点探讨了老旧散货船的营运缺陷,分析了缺陷可能产生的后果,提出了营运中应采取的管理措施及建议。     

Variations of the abundance and nucleic acid content of heterotrophic bacteria in Beaufort Shelf waters during winter and spring

Depth profiles of heterotrophic bacteria abundance were measured weekly over a 6-month period from December to May in Franklin Bay, a 230 m-deep coastal Arctic Ocean site of the southeastern Beaufort Sea. Total bacteria, low nucleic acid (LNA) and high nucleic acid (HNA) bacteria abundances were measured using flow cytometry after SYBR Green I staining. The HNA bacteria abundance in surface waters started to increase 5–6 weeks after phytoplankton growth resumed in spring, increasing from 1 × 10⁵ to 3 × 10⁵ cells mL^− 1 over an 8-week period, with a net growth rate of 0.018 d^− 1. LNA bacteria response was delayed by more than two months relative to the beginning of the phytoplankton biomass accumulation and had a lower net growth rate of 0.013 d^− 1. The marked increase in bacterial abundance occurred before any significant increase in organic matter input from river discharge (as indicated by the unchanged surface water salinity and DOC concentrations), and in the absence of water temperature increase. The abundance of bacteria below the halocline was relatively high until January (up to 5 × 10⁵ cells mL^− 1) but then decreased to values close to 2 × 10⁵ cells mL^− 1. The three-fold bacterial abundance increase observed in surface waters in spring was mostly due to HNA bacteria, supporting the idea that these cells are the most active.     

公路隧道交通量的预测及分析

公路隧道交通量的预测对隧道通风系统的节能以及降低隧道运营成本有很重要的意义。分别利用多元统计分析法和BP神经网络两种方法对公路隧道交通量进行了预测,并对两类预测数据进行分析比较,得出了多元统计分析法适用于车流量少而且稳定的公路隧道的预测,而BP神经网络法则适用于车流量大而且不稳定的公路隧道的预测的结论。