The traffic and behavioral effects of the I-35W Mississippi River bridge collapse

On August 1, 2007, the collapse of the I-35W bridge over the Mississippi River in Minneapolis abruptly interrupted the usual route of about 140,000 daily vehicle trips, which substantially disturbed regular traffic flow patterns on the network. It took several weeks for the network to re-equilibrate, during which period travelers continued to learn and adjust their travel decisions. A good understanding of this process is crucial for traffic management and the design of mitigation schemes. Data from loop-detectors, bus ridership statistics, and a survey are analyzed and compared, revealing the evolving traffic reactions to the bridge collapse and how individual choices could help to explain such dynamics. Findings on short-term traffic dynamics and behavioral reactions to this major network disruption have important implications for traffic management in response to future scenarios.     

Full vehicle simulation using thermomechanically coupled hybrid neural network shock absorber model

In the case of full vehicle models, the technique of multi-body simulation (MBS) is frequently used to study their highly non-linear dynamic behaviour. Many non-linearities in vehicle models are induced by force elements like springs, shock absorbers, bushings and tires. Commonly, spline functions are used to represent the force responses of these components. If the non-linear relationships are more complicated, the spline approximations are no more accurate. An alternative approach is based on empirical neural networks which are based on the mathematical approximation of measured data. It is well known that neural networks are able to represent and predict complex component responses accurately. The aim of this paper is to perform a dynamic full vehicle simulation using a thermomechanically coupled hybrid neural network shock absorber model. In this shock absorber model, the spline approach is combined with a temperature-dependent neural network. Based on a displacement-controlled excitation on a four post test rig in the ADAMS/Car MBS software, a rugged test track is simulated. In this way, the front and rear shock absorbers are dynamically loaded with comfort-relevant frequencies in the range of 0.75-30 Hz and velocity amplitudes up to 2 m/s. By the simulation, stability of the hybrid neural network model is demonstrated. Furthermore, the damping force, the vertical acceleration of the chassis and the required simulation times are compared. The standard spline approach is used as a reference.     

A hybrid model for better predicting capabilities under parallel wind conditions for NOx concentrations from highways in Ireland

Atmospheric dispersion models based on the Gaussian line source formulation tend to give poor results for low wind speed and parallel wind directions. Certain dispersion models like HIWAY-2 have an inbuilt dispersion algorithm to adjust in such situations but no correction exists for mathematical based Gaussian dispersion models. We evaluate the performance of a hybrid model a mathematical model, to assess its suitability as an alternative to the Gaussian based models.     

Optimal resource allocation among transit agencies for fleet management

Most transit agencies require government support for the replacement of their aging fleet. A procedure for equitable resource allocation among competing transit agencies for the purpose of transit fleet management is presented in this study. The proposed procedure is a 3-dimensional model that includes the choice of a fleet improvement program, agencies that may receive them, and the timing of investments. Earlier efforts to solve this problem involved the application of 1- or 2-dimensional models for each year of the planning period. These may have resulted in suboptimal solution as the models are blind to the impact of the fleet management program of the subsequent years. Therefore, a new model to address a long-term planning horizon is proposed. The model is formulated as a non-linear optimization problem of maximizing the total weighted average remaining life of the fleet subjected to improvement program and budgetary constraints. Two variants of the problem, one with an annual budget constraint and the other with a single budget constraint for the entire planning period, are formulated. Two independent approaches, namely, branch and bound algorithm and genetic algorithm are used to obtain the solution. An example problem is solved and results are discussed in details. Finally, the model is applied to a large scale real-world problem and a detailed analysis of the results is presented.     

Integrated modeling of urban hierarchy and transportation network planning

A major problem addressed during the preparation of spatial development plans relates to the accessibility to facilities where services of general interest such as education, health care, public safety, and justice are offered to the population. In this context, planners typically aim at redefining the level of hierarchy to assign to the urban centers of the region under study (with a class of facilities associated with each level of hierarchy) and redesigning the region’s transportation network. Traditionally, these two subjects – urban hierarchy and transportation network planning – have been addressed separately in the scientific literature. This paper presents an optimization model that simultaneously determines which urban centers and which network links should be promoted to a new level of hierarchy so as to maximize accessibility to all classes of facilities. The possible usefulness of the model for solving real-world problems of integrated urban hierarchy and transportation network planning is illustrated through an application to the Centro Region of Portugal.     

Assessment of diesel combustion noise overall level in transient operation

Combustion noise in passenger cars powered with direct injection (DI) diesel engines is frequently the main reason why end-users are reluctant to drive this type of vehicle. Thus, the great potential of diesel engines for environment preservation — due to their lower CO₂ emissions — could be missed. This situation worsens with the current design trends (engine downsizing) and the emerging new diesel combustion concepts (Homogeneous Charge Compression Ignition-HCCI, Premixed Charge Compression Ignition-PCCI, etc.), which are intrinsically noisy. This negative feature can be even more critical in transient operation due to the contribution of the temporal changes of both source and transmission path on engine noise. Therefore, combustion noise must be considered as an additional essential factor in engine development, together with performance, emissions and driveability. Thus, suitable evaluation procedures that can be integrated into the global engine development process in a timely and cost-effective manner are imperative. Regarding the evaluation procedures, most of the work available in the literature addressed combustion noise at steady operation. To surpass this limitation, two possible approaches — adapted from the classical and multiple regression methods — for the overall level assessment of combustion noise in transient conditions are evaluated in this paper.     

Condition monitoring of wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are to large extent based on visual analysis. In this paper a machine vision based approach has been considered to emulate the visual abilities of the human operator to enable automation of the process. Digital images from either ends (left and right) of the sleepers have been acquired. A pattern recognition approach has been adopted to classify the condition of the sleeper into classes (good or bad) and thereby achieve automation. Appropriate image analysis techniques were applied and relevant features such as the number of cracks on a sleeper, average length and width of the crack and the condition of the metal plate were determined. Feature fusion has been proposed in order to integrate the features obtained from each end for the classification task which follows. The effect of using classifiers like multi-layer perceptron and support vector machines has been tested and compared. Results obtained from the experiments show that multi-layer perceptron and support vector machines have achieved encouraging results, with a classification accuracy of 90%; thereby exhibiting a competitive performance when compared to a human operator.     

Adapting the light · biomass (BZI) models of phytoplankton primary production to shallow marine ecosystems

Several authors have reported a strong linear relationship between daily phytoplankton production and the product of chlorophyll biomass, photic depth, and incident irradiance for a variety of estuaries. This “light · biomass” (BZ_pI_o) formulation has been proposed as an alternative to traditional mechanistic approaches for computing phytoplankton production in numerical estuarine models. One limitation to their application in shallow systems is that the BZ_pI_o models have been developed in relatively deep estuaries where light does not reach the bottom. We propose a nonlinear correction factor to adapt the BZ_pI_o relationship to shallow systems where light does reach the bottom. Our function takes into account variations in incident irradiance, attenuation coefficient for light, photosynthetic efficiency, and maximum rate of photosynthesis. A series of correction polynomials are proposed for various ranges of incident irradiance, and are integrated into a single multiple polynomial which applies across all irradiance levels. Our new correction factor was tested against a ¹⁴C-based productivity dataset from shallow stations in Narragansett Bay, RI and an O₂-based dataset from shallow (1.1 m) lagoon mesocosms at the University of Rhode Island. Results showed that our polynomials accurately correct BZ_pI_o-predicted rates of production in shallow water columns. Application of our correction factor to a series of shallow water productivity datasets from the literature together with theoretical calculations show how significant the shallow water correction can be, especially in very shallow water columns with low turbidity.     

Parking policies in large cities in Germany

This article deals with highly motorized large West German cities of about 200,000 inhabitants and more, which usually provide reasonable public transport systems. Illegal parking with shares of about 40 to 50% of the total parking is widespread in the parking problem areas of those cities, especially in the inner-city residential and mixed-use areas. Parking spaces are demanded by residents, employees, customers and visitors, and by delivery and service traffic. The different characteristics of parking demands by different user groups are discussed. The total parking supply consists of public and private spaces. The share of private spaces is about 40 to 50% of the total parking spaces in German cities. The amount of car traffic generated by a parking space depends on parking duration and parking turnover, as well as on search traffic. So the change of a space from long-duration use of an employee to short-duration of customers — as often discussed in parking concepts — generates at least five-fold car traffic. The measurements and effects of parking control of public spaces as well as the parking regulations in zoning ordinances, restrictions on the construction of new private parking spaces and park-and-ride are discussed. Finally, a parking concept methodology — using the example of Frankfurt am Main — is discussed.