Volume 20 (2019): Edizione 3 (June 2019)

Various methodologies and tools applied to identification of vehicle and collision impact seek to present more and more accurate solutions to reproduce, restore, recreate and investigate the casualty. Modern computer technology and software provide the tools to solve specific problems developing mathematical modelling of complex mechanical systems involving vehicles and other objects in a road accident. Scientists generally utilize the Standard Test Method for Impact Testing calculating the energy of deformation of both vehicles, however, one of its limitations is the evaluation of the kinetic energy of the vehicles in post-collision taking into consideration vehicle rotation and linear displacement. To improve the analysis, dynamic traffic simulation is used, taking into account the variations in the coefficient of friction, suspension elasticity and damping. The proposed method is based on a system of two equations derived from two principles: the Principle of Conservation of Mechanical Energy and the Principle of Conservation of Momentum in the impact phase. The new approach is conducted on mathematical modelling and computer simulation of vehicle motion after the impact, wherefrom the linear and angular velocities are analysed. This is achieved by the numerical solution of the differential equations of motion of the cars after the impact, and the given initial conditions that satisfy the solution are used to solve the system of equations. The main findings of the study can be grouped as follows: 1) The positions of the vehicles prior to the moment of first impact and the post-impact orientation of velocity vectors are more precise. 2) The variability of the tire-road friction coefficient is taken into consideration. 3) The value of coefficient of restitution according to Newton’s theory of impact is unnecessarily determined.

The estimation of traffic flow variables (flow, space mean speed and density) plays a fundamental role in highways planning and designing, as well as in traffic control strategies. Moving Observer Method (MOM) allows traffic surveys in a road, or in a road network. This paper proposes a novel automated procedure, called MOM-AP based on Moving Observer Method and Digital Image Processing (DIP) Technique able to automatically detect (without human observers) and calculate flow q, space mean speed vs and density k in case of stationary and homogeneous traffic conditions.

In order to evaluate how reliable is the MOM-AP, an experiment has been carried out in a segment of one two-lane single carriageway road, in Italy. 30 datasets for the segment have been collected (in total 30 round trips). A comparative analysis between MOM-AP and traditional MOM has been carried out. First results show that the current MOM-AP algorithms underestimate the local mean flow variable values of around 10%. Nowadays MOM-AP may be implemented in smartphone apps. Instead, in the near future, it is realistic expecting the increase in the use of automated procedures for calculating the traffic flow variables (based on the “moving observer method”), due to the amount of sensors and digital cameras employed in the new autonomous vehicles (AVs). Considering such technical advances, the MOM-AP is a feasible model for real-time traffic analyses of road networks.

The article proposes a method for determining the rational motion intensity of specific train traffic flows on railway transport corridors with account for balance of expenses on traction resources and cargo owners. A mathematical model based on stochastic optimization is developed, which allows to optimize, in the conditions of risks, the interval between trailing trains on the railway lines taking into account the limited resources of the traction rolling stock, the capacity of the stations and freight fronts at the cargo destination point. Solving this mathematical model allows to find a balance between the expenses for movement of train traffic flows from different railway lines to their terminal reference station and the expenses of a consignee, subject to the limitations of the technological logistics chain in cargo transportation. For the solution of this mathematical model, a Real-coded Genetic Algorithm (RGA) was used.

Vehicular communication is a cynosure in automotive industry these days. V2V communication is one of the types of vehicular communication which render lane change warning, emergency vehicle alert, intersection alert, congestion alert, payment at tolls etc. A simulation research on the utilization of vehicle to vehicle connectivity via different routing protocols in VANET, contemplating the instance of a city situation has been introduced in our paper in order to resolve the issue of traffic routing. A routing algorithm is proposed which firstly selects optimal path via carry and forward approach and then transmits information on that path and the proposed algorithm is then compared with contemporary routing protocols based on different QoS parameters like throughput, packet delivery ratio, delay which are measured using NETSIM simulator to evaluate the behaviour of dissimilar routing protocols. The proposed algorithm outperforms most of the simulation cases.

This paper presents and analyses an innovative integrated scheme that aims to rationalize and improve the efficiency of urban freight transport as well as to promote reduced GHG emissions and traffic flows. Emissions management has become critical concern for modern companies and public authorities seeking to reduce carbon emissions and energy consumption from private and commercial heavy vehicle fleets, in line with the political targets of COP21 to COP23. The proposed scheme aims to utilize the current technological advances for efficient transport and logistics operations that regional authorities and companies can use and afford in order to provide competitive traffic management decisions as well as improvements in terms of pollutant emissions reduction. Both public and private stakeholders could interact to monitor and evaluate the impact of traffic policies and measures over time as well as the level of success of their routing strategies. Computational results on different scenarios of an experimental simulation model illustrate the competitiveness of the proposed scheme in an effort to quantify its effect.

Inventory control problems arise in various industries, and each single real-world inventory is replete with non-standard factors and subtleties. Practical stochastic inventory control problems are often analytically intractable, because of their complexity. In this regard, simulation-optimization is becoming more and more popular tool for solving complicated business-driven problems. Unfortunately, simulation, especially detailed, is both time and memory consuming. In the light of this fact, it may be more reasonable to use an alternative cheaper-to-compute metamodel, which is specifically designed in order to approximate an original simulation. In this research we discus metamodelling of stochastic multiproduct inventory control system with perishable products using a multilayer perceptron with a rectified linear unit as an activation function.

In the late 2013 One Belt and One Road (OBOR) was announced in Chinese international political speeches. Thereafter, this significant investment program started and research works were also initiated. We found that first journal publications (in English) appeared in 2016, and thereafter their amounts have increased, especially in 2018. Most of the contributing authors are China based or Chinese scholars living in abroad. Highest citations amounts are for the works published in the first analysis year, however, some differences exist between Scopus and Web of Science citation service amounts. Ten highest cited works account most of the citations on analysed 66 articles. Literature analysis uses tag cloud and network analysis to identify and analyse what are the most used references of these OBOR works. There does not exist any clear key reference among articles, but most used references form a network among analysed research work citations. This further verifies that OBOR program is significantly sized in topics covered, and it is still difficult to define its central or key area.

Automated vehicles (AVs) are one of the emerging technologies that can perform the driving task themselves. The market penetration of AVs is expected to get growth in the close future. Therefore, it is crucial to have an overall clue on how they play the role in the road transportation sector. Automation might be assumed to have a beneficial impact on many aspects related to road transportation. The current paper attempts to investigate this rough assumption by reviewing the literature on the potential effects of automated vehicles on road transportation. A comprehensive look at the overall potential effects of automated vehicles will show the entire picture, and not just a cropped portion of that, to the researchers, decision makers, and practitioners and helps them to identify the negative and positive effects as well as challenges and uncertainties towards this new technology. In this paper, literature findings on the potential effects of automated vehicles on traffic flow, pedestrians mobility, travel demand and travel pattern, safety and security, and energy consumption and emissions are reviewed and discussed. According to the literature, it is concluded that AVs, as their market penetration increases, promisingly improve the capacity of a road network, eliminates human driver errors, and provide better mobility for groups of people who are currently facing travel-restriction conditions. However, the long-term effects of AVs especially on energy consumption, emission, pedestrian interaction, safety and security has uncertainty due to the complexity of predicting the future mobility pattern.

The Global Air Navigation Plan (GANP) is a flexible global engineering approach that allows all States to advance their Air Navigation capacities based on their specific operational requirements. Aviation professionals have an essential role in the transition to, and successful implementation of the GANP. The development of new air traffic control technology requires new competencies from operational and maintenance personnel under the circumstances. And this, in turn, requires new education curricula for initial, vocational and advanced training in this area.

The paper is focused on the creation of methodology for the partial automation of the comparison of existing and required competences of Air Traffic Management (ATM) personal and synthesis of training courses and modules, using a formal, ontology-based approach as a tool to solve these problems. One of the problems in the implementation of the GANP is that, on the one hand, there are currently no unified requirements for all categories of ATM personnel, and on the other hand, the development of ATM technologies is far ahead of the pace of training of personnel of appropriate qualifications. This problem becomes even more noticeable in countries that have just started an active modernization of ATC systems and do not have enough experience in this field.

The paper describes the general methodological approach based on the education ontology modelling for human competency gap analysis in ATM and for gap analysis between the university curricula outcomes and the ATM requirements. The ontology of key personnel competencies issues for the design and integration of large-scale future ATM programmes is proposed.