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International audience; IAir traffic is increasing, raising concern about local pollution and its adverse health effects on the people living in the vicinity of large airports. However, the highest risk is probably occupational exposure due to proximity. Jet exhaust is one of the main concerns at an airport and may have a health impact, particularly on the respiratory tract. Current studies are neither numerous enough nor strong enough to prove this kind of association. Yet, more and more people work in airports, and occupational exposure to jet exhaust is a fact. The aim of this review was to evaluate the existing knowledge regarding the impact of airport pollution on respiratory health. We conducted systematic literature searches to examine workplace exposures.

Предложена система контроля состояния дискового тормоза пассажирского вагона, которая решает задачу достоверного определения его состояния и обеспечивает передачу необходимой информации об этом обслуживающему персоналу. The monitoring system of a condition of a disk brake of the carriage which solves a task of authentic definition of its condition is offered and provides transfer of the necessary information on it to the attendants.

Traffic congestion in the adjacent region between the highway and urban expressway is becoming more and more serious. This paper proposes a traffic speed forecast method based on the Macroscopic Fundamental Diagram (MFD) and Gated Recurrent Unit (GRU) model to provide the necessary traffic guidance information for travelers in this region. Firstly, considering that the road traffic speed is affected by the macroscopic traffic state, the adjacent region between the highway and expressway is divided into subareas based on the MFD. Secondly, the spatial-temporal correlation coefficient is proposed to measure the correlation between subareas. Then, the matrix of regional traffic speed data is constructed. Thirdly, the matrix is input into the GRU prediction model to get the predicted traffic speed. The proposed algorithm’s prediction performance is verified based on the GPS data collected from the adjacent region between Beijing Highways and Expressway.

Waiting tolerance at ramp meters and travel time on the freeway were measured using a computer administered stated preference (CASP) survey and a virtual experience stated preference (VESP) method employing a driving simulator.The selections varied in the number of minutes waiting at a ramp meter with vehicle speed once on the freeway. The subjects ranked the selections in order of preference. The results were statistically analyzed using a binary logit model controlling for demographics, socioeconomic characteristics, daily travel time, and personality scores.The results by the CASP method displayed a preference for freeway congestion to ramp delay, but opposite results were obtained by the VESP method. A number of reasons are posited to explain the difference, but the results indicate that method of stated preference data collection can significantly affect conclusions drawn.

Adverse road condition is the main cause of traffic accidents. Road surface condition recognition based on video image has become a central issue. However, hybrid road surface and road surface under different lighting environments are two crucial problems. In this paper, the road surface states are categorized into 5 types including dry, wet, snow, ice, and water. Then, according to the original image size, images are segmented; 9-dimensional color eigenvectors and 4 texture eigenvectors are extracted to construct road surface state characteristics database. Next, a recognition method of road surface state based on SVM (Support Vector Machine) is proposed. In order to improve the recognition accuracy and the universality, a grid searching algorithm and PSO (Particle Swarm Optimization) algorithm are used to optimize the kernel function factor and penalty factor of SVM. Finally, a large number of actual road surface images in different environments are tested. The results show that the method based on SVM and image segmentation is feasible. The accuracy of PSO algorithm is more than 90%, which effectively solves the problem of road surface state recognition under the condition of hybrid or different video scenes.

In the Netherlands, more than 80% of the highways are surfaced by porous asphalt (PA) mixes. The benefits of using PA mixes include, among others, the reduction of noise and the improvement of skid resistance. However, pavements with PA mixes are known to have a shorter lifetime and higher maintenance costs as compared with traditional dense asphalt mixes. Raveling is one of the most prominent distresses that occur on PA mix pavements. To analyze the raveling distress of a PA mix pavement, the stress and strain fields at the component level are required. Computational models based on finite element methods (FEM), discrete element methods (DEM), or both, can be used to compute local stress and strain fields. However, they require the development of large FEM meshes and large-scale computational facilities. As an alternative, the homogenization technique provides a way to calculate the stress and strain fields at the component level without the need for much computation power. This study aims to propose a new approach to analyze the raveling distress of a PA mix pavement by using the homogenization technique. To demonstrate the application of the proposed approach, a real field-like example was presented. In the real field-like example, the Mori–Tanaka model was used as a homogenization technique. The commonly available pavement analysis tool 3D-MOVE was used to compute the response of the analyzed pavement. In general, it was concluded that the homogenization technique could be a reliable and effective way to analyze the raveling distress of a PA mix pavement.

With the purpose of automatic detection of crowd patterns including abrupt and abnormal changes, a novel approach for extracting motion “textures” from dynamic Spatio-Temporal Volume (STV) blocks formulated by live video streams has been proposed. This paper starts from introducing the common approach for STV construction and corresponding Spatio-Temporal Texture (STT) extraction techniques. Next the crowd motion information contained within the random STT slices are evaluated based on the information entropy theory to cull the static background and noises occupying most of the STV spaces. A preprocessing step using Gabor filtering for improving the STT sampling efficiency and motion fidelity has been devised and tested. The technique has been applied on benchmarking video databases for proof-of-concept and performance evaluation. Preliminary results have shown encouraging outcomes and promising potentials for its real-world crowd monitoring and control applications.

Designing multimodal freight transport networks can facilitate the economic development of regions and countries as well as help to reduce negative environmental impacts. It is therefore crucial that such be undertaken in areas where more priority is given on road-based freight transport systems. This paper proposes a model for strategic transport planning, particularly in freight terminal development and interregional freight transport network design. The model determines a suitable set of actions from a number of possible actions, such as improving the existing infrastructure or establishing new roads, railways, sea links, and freight terminals. Modelling is undertaken within the framework of bilevel programming, where a multimodal multiclass user traffic assignment technique is incorporated within the lower-level problem, whilst the upper-level problem determines the best combination of actions such that the freight-related benefit-cost ratio is maximised. The upper-level problem involves combinatorial optimisation, and a heuristic approach based on genetic local search is applied as a solution technique. Empirical results of the model as applied to an actual large-sized interregional intermodal freight transport network show that genetic local search could provide better performance as compared to other genetic algorithm-based, as well as tabu search-based, heuristics. The model is successfully applied to transport network planning in the Philippines, where the development of a freight transport network is necessary to increase the utilisation of other modes rather than road-based vehicles.

In view of the compulsory merging behavior and complex driving environment in freeway work zones, the factors influencing drivers’ merging behavior need to be focused on the given road environment. Realizing the need to mitigate the impact of such a challenging scenario, this study aims to explore the impact of road environment on drivers’ merging location selection in freeway work zone merging areas. The survey data for modelling were collected through questionnaires survey based on the stated preference (SP) method. The logistics regression model was utilized to extract the significant factors influencing merging location selection. The results of fitting effect analysis show that the developed logistics regression models provide a good fit for the survey data. The road conditions and speed limit strategies are the significant factors affecting the drivers’ preference to merging location selection in upstream transition area. The road conditions, traffic environment conditions, speed conditions, and speed limit strategies are the prominent influencing factors to the latter part of advance warning area. It is a comprehensive analysis to consider the influence of road environment on merging location selection from the perspective of drivers, which is expected to support the merging control strategy and avoid the occurrence of traffic crash in work zones.

High early strength (HES) concrete patching materials are increasingly used to repair damaged pavements. The use of HES concrete enables the repaired pavement to be opened to traffic shortly after the repair has been installed; for example, opening pavements to traffic 4–6 h after the concrete is placed is becoming more common. HES concrete mixtures are typically designed with a low water-to-cement ratio and a high cement content; they contain accelerating admixtures and limited supplementary cementitious materials. As a result, these HES patches may be susceptible to self-desiccation, causing autogenous shrinkage and early age cracking. Self-desiccation can lead to reduced hydration, limited strength gain, and overestimation of strength development in maturity-based predictions. The objectives of this study are threefold. First, the paper will illustrate how self-desiccation can lead to the premature cessation of hydration and increased potential for shrinkage cracking. Second, the paper will illustrate how maturity-based predictions can be modified to account for self-desiccation. Third, internal curing is discussed as a way to mitigate self-desiccation and shrinkage ultimately improving the performance of HES concrete patching materials.