Influence of vehicle driving parameters on the noise caused by passenger cars in urban traffic

In this work, a sample of vehicles has been instrumented to measure of variables that influence vehicle noise emissions in Madrid. A circuit reproducing a normal travel pattern in large city is traveled by a fleet of vehicle models representing the fleets of cars in a European city. A sample of drivers covers the test track under different traffic conditions. Driving parameters and noise emitted have been recorded in each test and average values have been extracted. These data have been analyzed to define the noise emissions produced by a vehicle in real driving conditions and to identify the noisiest driving behaviors.     

To kill a real option – Incomplete contracts,real options and PPP

This paper is concerned with the implications of public–private partnership agreements for the execution of expansion options in road infrastructure. More specifically, it analyzes the expansion of an existing two-lane road in Sweden, and examines the real options created by an intermediate type of road with three lanes. Interpreting the results from real option analysis in the light of incomplete contract theory, this paper finds that external congestion costs might necessitate public ownership to ensure a social optimal outcome in public–private partnerships.     

Biogeography-based combinatorial strategy for efficient autonomous underwater vehicle motion planning and task-time management

Autonomous Underwater Vehicles (AUVs) are capable of spending long periods of time for carrying out various underwater missions and marine tasks. In this paper, a novel conflict-free motion planning framework is introduced to enhance underwater vehicle’s mission performance by completing maximum number of highest priority tasks in a limited time through a large scale waypoint cluttered operating field, and ensuring safe deployment during the mission. The proposed combinatorial route-path planner model takes the advantages of the Biogeography-Based Optimization (BBO) algorithm toward satisfying objectives of both higher-lower level motion planners and guarantees maximization of the mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios including the particular cost constraints in time-varying operating fields. To show the reliability of the proposed model, performance of each motion planner assessed separately and then statistical analysis is undertaken to evaluate the total performance of the entire model. The simulation results indicate the stability of the contributed model and its feasible application for real experiments.     

Establishment of Community Managed Fisheries’ Closures in Kenya: Early Evolution of the Tengefu Movement

Community-based management (CBM) could be an essential tool to prevent the depletion of marine resources in the Western Indian Ocean region. In Kenya, political pressure to strengthen local governance, has led to adoption of CBM as a way of reducing over-exploitation and managing the competing uses and impacts on the marine environment. Several communities in Kenya have embraced CBM and have set aside or closed previously fished areas to enhance recovery of fisheries and biodiversity. These community fisheries closures (locally called tengefu), despite being degraded, may recover to finfish abundances and biodiversity levels similar to established MPAs or above thresholds for maintaining some ecological services. Communities see their direct involvement and control of these tengefu as more likely to result in benefits flowing directly to them. Community closures are also important for articulating and resolving community values and strengthening their management capacity. Here, we describe the evolution of the tengefu movement in Kenya and combine information from focus group discussions, interviews, underwater surveys and boundary marking to evaluate the current status, opportunities and challenges facing these tengefu. We show that in some cases community closures suffer from slow and incomplete national and local legislative processes, challenges to compliance, and weak management.     

Novel Electrically Stimulated Catalytic Converter Prototype for Replacement of Conventional Auto Exhaust Emission Converters

High voltage electrostatics and corona discharge are utilized for various applications in pollution and environmental control. The traditional applications have many flaws due to improper construction of electrode design and assembly that cause system failure, in particular when electrically stimulated devices are exposed to high humidity. A new innovative-patented design by Hamade, electrically stimulated catalytic converter(ESCC),eliminates such flaws and shows the wide practical applications of the new design. The new design utilized previous patented designs and work of the same inventor but retrofitted for catalytic auto exhaust emission control. The current and previous patents include: employing electrically stimulated filtration(ESF) to replace high efficiency particulate air(HEPA) filters, treatment of biological and infectious diseases, electret fabrication, and, most notably, the invention of a new electrically stimulated catalytic converter(ESCC). The electrically stimulated catalytic converter invention includes an exhaust conduit fed from the engine exhaust port with a housed corona charger apparatus. The opposite end is opened to the atmosphere outside of the vehicle or connected to a reduced-size catalytic converter. The corona charger is intrusively or non-intrusively associated with a main flow path defined by the exhaust conduit. The corona charger includes at least one electrode, which may be recessed away from, the main flow path. A plurality of corona chargers may be used in various combinations, optimally a two dimensional grid. The electrically stimulated catalytic converter is adapted to treat and eliminate auto exhaust pollution emission to air.     

Visualisation of uncertainty in probabilistic traffic models for policy and operations

This study investigates different methods to visualise uncertainty in static representations of probabilistic traffic models predictions on road-networks. Although various graphical cues may be used to represent uncertainty it is not a priori clear which of them are most suited for this purpose, since their legibility, intelligibility and the degree to which they interfere with other graphical elements in a representation differ widely. Several graphical uncertainty representations were therefore developed and analysed in expert sessions. A selection of the initial set of uncertainty visualisations was further evaluated in a cognitive alternative task-switching experiment. The results show that graphical representations are able to convey uncertainty information relatively accurately, while some uncertainty visualisations outperform others. It depends on the model and scenario which representation is most suited for a given application. This paper presents an overview of possible graphic uncertainty representations and the considerations involved when applying them to uncertainty in traffic model visualisations.     

Step-tolling with price-sensitive demand: Why more steps in the toll make the consumer better off

Most dynamic models of congestion pricing use fully time-variant tolls. However, in practice, tolls are uniform over the day, or at most have just a few steps. Such uniform and step tolls have received surprisingly little attention from the literature. Moreover, most models that do study them assume that demand is insensitive to the price. This seems an empirically questionable assumption that, as this paper finds, strongly affects the implications of step tolling for the consumer. In the bottleneck model, first-best tolling has no effect on the generalised price, and thus consumer surplus remains the same as without tolling. Conversely, under price-sensitive demand, step tolling increases the price, making the consumer worse off. The more steps the toll has, the closer it approximates the first-best toll, thereby increasing the welfare gain and making consumers better off. This indicates the importance for real-world tolls to have as many steps as possible: this not only raises welfare, but may also increase the political acceptability of the scheme by making consumers better off.     

Lagrangian flow in the California Undercurrent, an observation and model comparison

During the period 1992–1998, 38 isobaric RAFOS floats were deployed to sample the subsurface flow of the California Undercurrent. The deployments, released over the California continental slope west of San Francisco, have sampled robust year-round poleward subsurface flow associated with the Undercurrent most seasons and the combined inshore current and Undercurrent in winter. Two other types of flow have been seen: a region of weak flow with little net displacement just west of the California Undercurrent, and an active westward propagating eddy field. This eddy field appears to be the primary mechanism for moving floats from the Undercurrent into the ocean interior. The observations and statistics from the RAFOS floats are compared with Lagrangian estimates of particles tracked in a global high resolution ocean simulation in order to evaluate the fidelity of the model along an eastern boundary. The results show that the model reproduces the general character of the flow reasonably well, but underestimates both the mean and eddy energies by a substantial amount.     

地面注汽管线表面散热损失影响因素分析

文中采用Fluent模拟与理论计算结合比较的方法,研究了不同因素对蒸汽管道散热损失的影响规律,并分析了理论计算模型的相对误差.发现增加注汽管线距地面高度,对其散热损失影响较弱;空气温度升高,注汽管道表面散热损失降低;风速和表面发射率对注汽管线表面热损失影响较大;数值模拟结果与理论计算数据相对误差较大.     

Developing an enhanced weight-based topological map-matching algorithm for intelligent transport systems

Map-matching (MM) algorithms integrate positioning data from a Global Positioning System (or a number of other positioning sensors) with a spatial road map with the aim of identifying the road segment on which a user (or a vehicle) is travelling and the location on that segment. Amongst the family of MM algorithms consisting of geometric, topological, probabilistic and advanced, topological MM (tMM) algorithms are relatively simple, easy and quick, enabling them to be implemented in real-time. Therefore, a tMM algorithm is used in many navigation devices manufactured by industry. However, existing tMM algorithms have a number of limitations which affect their performance relative to advanced MM algorithms. This paper demonstrates that it is possible by addressing these issues to significantly improve the performance of a tMM algorithm. This paper describes the development of an enhanced weight-based tMM algorithm in which the weights are determined from real-world field data using an optimisation technique. Two new weights for turn-restriction at junctions and link connectivity are introduced to improve the performance of matching, especially at junctions. A new procedure is developed for the initial map-matching process. Two consistency checks are introduced to minimise mismatches. The enhanced map-matching algorithm was tested using field data from dense urban areas and suburban areas. The algorithm identified 96.8% and 95.93% of the links correctly for positioning data collected in urban areas of central London and Washington, DC, respectively. In case of suburban area, in the west of London, the algorithm succeeded with 96.71% correct link identification with a horizontal accuracy of 9.81 m (2σ). This is superior to most existing topological MM algorithms and has the potential to support the navigation modules of many Intelligent Transport System (ITS) services.