Analysis of Air Pollution around a CHP Plant: Real Measurements vs. Computer Simulations

This study examines the concentrations of air pollution in the vicinity of a combined heat and power plant (CHP) and a communication route, using computer modeling of pollutant dispersion and spatial analysis based on real measurements in the city of Łódź, Poland, Europe. The research takes into account the concentrations of particulate matter (PM10, PM2.5, PM1.0) and gaseous pollutants (SO2 and VOC) in winter and summer. The spatial distribution of pollutants is discussed, including the presence of areas with increased accumulations of pollutants. Because atmospheric air has no natural boundaries, when analyzing any location, not only local sources of pollution, but also background pollution, should be analyzed. A clear difference was observed between the concentrations of pollutants in the summer and winter seasons, with significantly higher concentrations in the winter (heating) period. The impacts of road transport, individual heating systems, and combined heat and power plants were also assessed. Computer calculations confirmed that road transport accounted for the largest share of both PM and SO2 emissions. The CHP plant was responsible for the smallest percentage of dust emissions and was the next largest producer of SO2 emissions. The share of the total emissions from the individual sources were compared with the results of detailed field tests. The numerical analysis of selected pollution sources in combination with the field analysis shows that the identified pollution sources included in the analysis represent only a part of the total observed pollutant concentrations (suggesting that other background sources account for the rest).

A Computational Framework for Human-centric Vehicular Crashworthiness Design and Decision-Making Under Uncertainty

Government agencies, globally, strive to minimize the likelihood and frequency of human death and severe injury on road transport systems. From an engineering design standpoint, the minimization of these road accident effects on occupants becomes a critical design goal. This necessitates the quantification and management of injury risks on the human body in response to several vehicular impact variables and their associated uncertainties for different crash scenarios. In this paper, we present a decision-based, robust design framework to quantify and manage the impact-based injury risks on occupants for different computational model-based car crash scenarios. The key functionality offered is the designer's capability to conduct robust concept exploration focused on managing the selected impact variables and associated uncertainties, such that injury risks are controlled within acceptable levels. The framework's efficacy is tested for near-side impact scenarios with impact velocity and angle of impact as the critical variables of interest. Two injury criteria, namely, Head Injury Criterion (HIC) and Lateral Neck Injury Criteria (Lateral Nij), are selected to quantitatively measure the head and neck injury risks in each crash simulation. Using the framework, a robust design problem is formulated to determine the combination of impact variables that best satisfice the injury goals defined. The framework and associated design constructs are generic and support the formulation and decision-based robust concept exploration of similar problems involving models under uncertainty. Our focus in this paper is on the framework rather than the results per se.

METHODOLOGY EXPERT STUDY OF ROAD TRANSPORT ACCIDENT WITH PEDESTRIAN RIDING

The article presents a methodology for an expert study of a road accident with a collision with a pedestrian, which is aimed at determining whether a vehicle driver has the technical ability to avoid a collision in a specific situation. In addition, an analysis of methods is presented with a description of the stages of research and patterns of movement of a vehicle and a pedestrian before the occurrence of an accident. The presented technique can be used by experts in the investigation of road accidents

Methodological Foundations of Renewal and Expansion of Car Fleet

Currently, Russian international road transport carriers do not have sufficient potential to successfully compete with their foreign partners. The main reasons for this are significant deterioration of the car fleet and its non-compliance to modern environmental requirements, lack of own funds for timely renovation and development of the motor transport fleet, as well as systemic lag in development of transportation technologies and their logistics support.The objective of the article is to substantiate the choice of rational measures to solve the problem of expanded reproduction of car fleet used in international road haulage. The methodology used in preparation of the article is based on the use of general scientific methods in combination with special methods, including the analysis of statistical data on international road haulage, a comparative analysis of the state of the car fleet of Russian carriers, considering the basic conditions and operational characteristics, classification of the fleet of trucks based on typification of their operational characteristics with subsequent subdivision of this fleet into three main groups, an overview analysis and benchmarking of foreign operating experience and future development of car fleet, an analysis of the economic and legal possibilities of raising funds for renewal of car fleet.The article examines and studies: a) urgency of solving the problem of renewal and expansion of the car fleet used by Russian carriers in international road transportation; b) foreign experience and trends in development of fleet used for international haulage; c) the main directions of providing economic opportunities for transition to expanded renewal of vehicles; d) analysis of the legal possibilities of providing public support for expanded reproduction of the motor transport fleet of Russian international road carriers including through the use of public-private partnerships.Based on the results of the study, proposals have been developed aimed at ensuring renewal and expansion of car fleet and increasing the efficiency of international road haulage operations.

STRUCTURE OF THE STREET ROAD NETWORK IN THE FREIGHT TRANSPORTATION SYSTEM

The road network constitutes the main part of the transport system for both passenger and freight traffic. Achieving a sustainable road transport system including multimodal terminals, autonomous vehicles, intelligent transport systems, infrastructure are considered to be important design areas. The efficient use of the transport system is essential in terms of economic, environmental and social sustainability. Therefore, it is necessary to develop methods for optimizing the transportation process

Mitigating Motion Sickness in Automated Vehicles with Vibration Cue System

<p>Motion sickness is very common in road transport. To guarantee ride comfort and user experience, there is an urgent need for effective solutions to motion sickness mitigation in semi- and fully-automated vehicles. Considering both effectiveness and user-friendliness, a vibration cue system is proposed to inform passengers of the upcoming vehicle movement through tactile stimulation. By integrating the motion planning results from automated driving algorithms, the vibration cueing timing and patterns are optimized with the theory of motion anticipation. Using a cushion-based prototype of vibration cue system, 20 participants were invited to evaluate this solution in two conditions of driving simulator experiments. Results show that with the proposed vibration cue system, it could also help participants to comprehend the cues and to generate motion anticipation. The participants’ motion sickness degrees were significantly lowered. This research may serve as one foundation for the detailed system development in practical applications.</p><p>(This article has been accepted for publication in <i>Ergonomics</i>, published by Taylor & Francis.)</p><br>

An Intelligent Visualisation Tool to Analyse the Sustainability of Road Transportation

Road transport is an integral part of economic activity and is therefore essential for its development. On the downside, it accounts for 30% of the world’s GHG emissions, almost a third of which correspond to the transport of freight in heavy goods vehicles by road. Additionally, means of transport are still evolving technically and are subject to ever more demanding regulations, which aim to reduce their emissions. In order to analyse the sustainability of this activity, this study proposes the application of novel Artificial Intelligence techniques (more specifically, Machine Learning). In this research, the use of Hybrid Unsupervised Exploratory Plots is broadened with new Exploratory Projection Pursuit techniques. These, together with clustering techniques, form an intelligent visualisation tool that allows knowledge to be obtained from a previously unknown dataset. The proposal is tested with a large dataset from the official survey for road transport in Spain, which was conducted over a period of 7 years. The results obtained are interesting and provide encouraging evidence for the use of this tool as a means of intelligent analysis on the subject of developments in the sustainability of road transportation.

Estimating the impact of a new bridge over the river Danube

The impact of a new bridge over the Danube was estimated using a 3-step road transport model, as at the time no multimodal model was available. Different forecasts have been considered for both scenarios without the project and with the project. Also, sensitivity tests have been carried out in order to assess the impact of various bridge tolls. At the end, time savings and emissions have been estimated.