Train boarding and alighting rates at high passenger loads

Line capacity in metro and high‐frequency suburban railways is as much determined by station stop times as by factors such as line speed or train acceleration. This paper applies the method developed by London Underground to estimate the time that trains spend at stations, as a function of the physical characteristics of the situation (e.g. train door width) and the numbers of passengers involved. Analysis was carried out on a number of alternative designs for refurbishment of South West Trains' Class 455 inner‐suburban rolling stock. Whilst there is indeed an interaction between boarding and alighting passengers, this paper demonstrates that the LUL relationship breaks down at the highest passenger loads. Moreover, results indicate that passenger flow is not equal between different parts of the same group of boarders or alighters.     

科学技术对航海教育与培训的影响

探讨了过去30年来科学技术如何影响海运专业人员的教育与培训，并指出日益复杂、先进的技术如何使受训和工作受益。     

Quantitative analysis of passenger and baggage security screening at airports

The terrorist attacks in the United States in 2001 opened a new era in air transportation. The realization that civil aircraft can be used as powerful weapons of mass destruction by a small group of people has drastically increased the need for security screening procedures to protect civil flights. Serving as the interface between the air and land transportation modes, airports have become the main focus in the implementation of those procedures. The need to more thoroughly screen passengers and baggage, and the consequent increase in processing time, has created the need for more space for security checkpoints and baggage screening inside passenger terminal buildings—space that is costly and very difficult to find in existing buildings. This paper evaluates the impact those measures have had on the planning and operation of airport passenger terminals. Quantification of those impacts is performed with the use of discrete‐event simulation and spreadsheet models.     

Towards a seascape typology. I. Zipf versus Pareto laws

Two data analysis methods, referred to as the Zipf and Pareto methods, initially introduced in economics and linguistics two centuries ago and subsequently used in a wide range of fields (word frequency in languages and literature, human demographics, finance, city formation, genomics and physics), are described and proposed here as a potential tool to classify space–time patterns in marine ecology. The aim of this paper is, first, to present the theoretical bases of Zipf and Pareto laws, and to demonstrate that they are strictly equivalent. In that way, we provide a one-to-one correspondence between their characteristic exponents and argue that the choice of technique is a matter of convenience. Second, we argue that the appeal of this technique is that it is assumption-free for the distribution of the data and regularity of sampling interval, as well as being extremely easy to implement. Finally, in order to allow marine ecologists to identify and classify any structure in their data sets, we provide a step by step overview of the characteristic shapes expected for Zipf's law for the cases of randomness, power law behavior, power law behavior contaminated by internal and external noise, and competing power laws illustrated on the basis of typical ecological situations such as mixing processes involving non-interacting and interacting species, phytoplankton growth processes and differential grazing by zooplankton.     

Variability of river plumes off Northwest Iberia in response to wind events

The Western Iberian Buoyant Plume (WIBP) is a low-salinity lens formed by river discharge and continental run-off extending along the shelf off Northwest Iberia. The variability of this structure is evaluated with a numerical model forced by real meteorological data and climatologic river discharge during late 2002, when conditions were those of a typical autumn. The direction and intensity of the wind-induced Ekman transport, but also the previous conditions and the duration of the event are found to determine plume behavior. We have identified three characteristic situations: a) confinement of the plume to the coast during downwelling — southerly-winds, b) expansion of the plume during the declining phase of the downwelling event by relaxation of the wind, and c) expansion of the plume by upwelling — northerly-winds. The short time scale of the response of the plume (1–3 h) adds timing between wind events and the phase of the tide as an additional source of variability. In all cases the Iberian Poleward Current (IPC), a saltier and warmer poleward current flowing over the slope, responds as well to wind changes. Furthermore, our simulations illustrate how topography and differences in the river discharge induce local differences in dynamics. Comparisons to available observations show a reasonable model skill. Differences between wind measurements and wind forcing applied to the model appear to be a major source of uncertainty in model results.     

Forecast verification of a 3D model of the Mediterranean Sea. The use of discrete wavelet transforms and EOFs in the skill assessment of spatial forecasts

The quality assessment of a nested model system of the Mediterranean Sea is realised. The model has two zooms in the Provençal Basin and in the Ligurian Sea, realised with a two-way nesting approach. The experiment lasts for nine weeks, and at each week sea surface temperature (SST) and sea level anomaly are assimilated. The quality assessment of the surface temperature is done in a spatio-temporal approach, to take into account the high complexity of the SST distribution. We focus on the multi-scale nature of oceanic processes using two powerful tools for spatio-temporal analysis, wavelets and Empirical Orthogonal Functions (EOFs). We apply two-dimensional wavelets to decompose the high-resolution model and observed SST into different spatial scales. The Ligurian Sea model results are compared to observations at each of those spatial scales, with special attention on how the assimilation affects the model behaviour. We also use EOFs to assess the similarities between the Mediterranean Sea model and the observed SST. The results show that the assimilation mainly affects the model large-scale features, whereas the small scales show little or no improvement and sometimes, even a decrease in their skill. The multiresolution analysis reveals the connection between large- and small-scale errors, and how the choice of the maximum correlation length of the assimilation scheme affects the distribution of the model error among the different spatial scales.     

Development of real-world driving cycle: Case study of Pune,India

The critical component of all emission models is a driving cycle representing the traffic behaviour. Although Indian driving cycles were developed to test the compliance of Indian vehicles to the relevant emission standards, they neglects higher speed and acceleration and assume all vehicle activities to be similar irrespective of heterogeneity in the traffic mix. Therefore, this study is an attempt to develop an urban driving cycle for estimating vehicular emissions and fuel consumption. The proposed methodology develops the driving cycle using micro-trips extracted from real-world data. The uniqueness of this methodology is that the driving cycle is constructed considering five important parameters of the time–space profile namely, the percentage acceleration, deceleration, idle, cruise, and the average speed. Therefore, this approach is expected to be a better representation of heterogeneous traffic behaviour. The driving cycle for the city of Pune in India is constructed using the proposed methodology and is compared with existing driving cycles.     

Adaptive traffic signal control using approximate dynamic programming

This paper presents a study on an adaptive traffic signal controller for real-time operation. The controller aims for three operational objectives: dynamic allocation of green time, automatic adjustment to control parameters, and fast revision of signal plans. The control algorithm is built on approximate dynamic programming (ADP). This approach substantially reduces computational burden by using an approximation to the value function of the dynamic programming and reinforcement learning to update the approximation. We investigate temporal-difference learning and perturbation learning as specific learning techniques for the ADP approach. We find in computer simulation that the ADP controllers achieve substantial reduction in vehicle delays in comparison with optimised fixed-time plans. Our results show that substantial benefits can be gained by increasing the frequency at which the signal plans are revised, which can be achieved conveniently using the ADP approach.     

Residual circulation in the Ría de Muros (NW Spain): A 3D numerical model study

The residual circulation of the Ría de Muros, a large coastal embayment in NW Spain, are studied using a three-dimensional baroclinic finite-difference model. The driving forces considered by the model include the tide, winds, river inflows and density forcing at the open boundary. In situ data of current velocity and direction, water level, wind velocity and direction, river discharge, and temperature and salinity are used for model validation. Simulated and observed time series of water level and current velocity are in good agreement. Once validated, the model is applied to compute the residual circulation induced by the relevant agents of the ría hydrodynamics—the tide, an upwelling-favourable wind characteristic of spring and summer, a downwelling-favourable wind typical of winter, and freshwater inflows associated with high river runoff. The resulting residual circulation differ notably. The tide does not generate significant residual flows except in the inner ría. By contrast, winds and river discharges induce important residual flows throughout; in the middle and outer ría they generate a 3D residual circulation pattern which renders the conventional two-layer scheme of estuarine circulation too simplistic in this case. Thus, this first application of a 3D numerical model to the Ría de Muros sheds new light on its fundamental hydrodynamics.     

Development and evaluation of a knowledge-based system for traffic congestion management and control

This paper describes a real-time knowledge-based system (KBS) for decision support to Traffic Operation Center personnel in the selection of integrated traffic control plans after the occurrence of non-recurring congestion, on freeway and arterial networks. The uniqueness of the system, called TCM, lies in its ability to cooperate with the operator, by handling different sources of input data and inferred knowledge, and providing an explanation of its reasoning process. A data fusion algorithm for the analysis of congestion allows to represent and interpret different types of data, with various levels of reliability and uncertainty, to provide a clear assessment of traffic conditions. An efficient algorithm for the selection of control plans determines alternative traffic control responses. These are proposed to an operator, along with an explanation of the reasoning process that led to their development and an estimation of their expected effect on traffic. The validation of the system, which is one of only few examples of validation of a KBS in transportation, demonstrates the validity of the approach. The evaluation results, in a simulated environment demonstrate the ability of TCM to reduce congestion, through the formulation of traffic diversion and control schemes.