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Synchronized flow has been found recently in studies of empirical GPS probe-vehicle data collected in oversaturated city traffic. In this paper, results of simulations with a three-phase microscopic model from Kerner and Klenov are presented. These results show features of synchronized flow. The effect of the driver's speed adaptation was found to play the key role in understanding the emergence of synchronized flow in over-saturated city traffic. The physical meaning of the speed adaptation effect in oversaturated city traffic was explained, and the influence of the speed adaptation effect on the average speed and travel time in oversaturated city traffic was investigated.

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.

Subduction of a narrow slab of oceanic lithosphere beneath a tightly curved orogenic arc requires the presence of at least one lithospheric scale tear fault. While the Calabrian subduction beneath southern Italy is considered to be the type example of this geodynamic setting, the geometry, kinematics and surface expression of the associated lateral, slab tear fault offshore eastern Sicily remain controversial. Results from a new marine geophysical survey conducted in the Ionian Sea, using high-resolution bathymetry and seismic profiling reveal active faulting at the seafloor within a 140 km long, two-branched fault system near Alfeo Seamount. The previously unidentified 60 km long NW trending North Alfeo Fault system shows primarily strike-slip kinematics as indicated by the morphology and steep-dipping transpressional and transtensional faults. Available earthquake focal mechanisms indicate dextral strike-slip motion along this fault segment. The 80 km long SSE trending South Alfeo fault system is expressed by one or two steeply dipping normal faults, bounding the western side of a 500+ m thick, 5 km wide, elongate, syntectonic Plio-Quaternary sedimentary basin. Both branches of the fault system are mechanically capable of generating magnitude 6–7 earthquakes like those that struck eastern Sicily in 1169, 1542, and 1693. peer-reviewed

The aim of the System Dynamics Model for Economic Assessment of Sustainability Policies of Transport (ESCOT) is to describe a path towards a sustainable transport system in Germany and to assess its economic impacts. ESCOT was developed within the environmentally sustainable transport (EST) project of the Organization for Economic Co?operation and Development (OECD) that was designed to set up the ecological and technical framework of a transition towards sustainable transportation. ESCOT comprises five models: macroeconomic, transport, regional economic, environmental and policy. The economic assessment for environmentally sustainable scenarios shows that the departure from car? and road freight?oriented transport policy is far from leading to an economic breakdown. By expanding the period for the transition, even more encouraging economic results were derived. For the economic assessment, it is important that ESCOT considers not only first round effects, but also secondary effects. This ability makes ESCOT a powerful instrument for the assessment of such large system transitions.

Senior travelers (those 55 or older) are a substantial and accessible market for motorcoach operators because they represent a major portion of the motorcoach market. This study examined Pennsylvania senior travelers’ motorcoach use and their important considerations in selecting a motorcoach tour. It was found that senior travelers’ taking motorcoach tours could be predicted from their demographic, psychological, and psychographic characteristics. The study provides practical implications that could be helpful for tourist destinations and motorcoach companies to target senior travelers and to build a sound marketing planning strategy.

Abstract Computer vision technologies are at the core of different advanced driver assistance systems (ADAS) and will play a key role in oncoming autonomous vehicles too. One of the main challenges for such technologies is to perceive the driving environment, i.e. to detect and track relevant driving information in a reliable manner (e.g. pedestrians in the vehicle route, free space to drive through). Nowadays it is clear that machine learning techniques are essential for developing such a visual perception for driving. In particular, the standard working pipeline consists of collecting data (i.e. on-board images), manually annotating the data (e.g. drawing bounding boxes around pedestrians), learning a discriminative data representation taking advantage of such annotations (e.g. a deformable part-based model, a deep convolutional neural network), and then assessing the reliability of such representation with the acquired data. In the last two decades most of the research efforts focused on representation learning (first, designing descriptors and learning classifiers; later doing it end-to-end). Hence, collecting data and, especially, annotating it, is essential for learning good representations. While this has been the case from the very beginning, only after the disruptive appearance of deep convolutional neural networks that it became a serious issue due to their data hungry nature. In this context, the problem is that manual data annotation is a tiresome work prone to errors. Accordingly, in the late 00’s we initiated a research line consisting of training visual models using photo-realistic computer graphics, especially focusing on assisted and autonomous driving. In this paper, we summarize such a work and show how it has become a new tendency with increasing acceptance.

Travel time variability is determined by variations in demand and capacity. Knowledge about these demand and supply factors can help improve the reliability of travel time and hence the quality of traveling. The precise nature of the relationship between, for example, variations in inflows and travel time variation is still largely unknown. This paper uses empirical traffic data from both Regiolab-Delft in the Netherlands and the Beijing Olympic area to analyze the variability of travel times depending on inflow conditions. Preliminary analysis shows that travel time variability is a function of inflow characterized by two so-called critical inflows (critical transition inflow λ1 and critical capacity inflow λ2, which are both lower than capacity). These critical inflow levels subdivide traffic into a fluent traffic region, a transition traffic region, and a capacity traffic region. Variation of inflow has little or no effect on travel time variation below λ1. But both demand and capacity variations have a positive correlation with travel time variability in between λ1 and λ2. When volumes are above λ2, the inflow slightly affects the travel time variability. Under all inflow levels, the variation in capacity appears to have more impact on travel time variability than does the variation of traffic flow.

The necessity of work-in-process management of rail-cars production by intelligent decision support software, which is based on JIT and Kanban principles, is identified. The scheme of one type cargo-flow movement between two workshops with control by electronic and traditional kanban-card is offered. For simulation of rail-cars production cargo flows Markov chain of M/M/1/1 type was applied. Simulation shows the dependence of the work-in-process on the in-flow and out-flow intensity. To determine the high level of the optimal work-in-process the stochastic inventory management model is applied.