The aim of this paper is to demonstrate the possibilities of estimating the track condition using axle-boxes and car-bodies motions described by acceleration signals. In the paper, the results presented indicate the condition of tracks obtained from the preliminary investigation on the test track. Furthermore, the results from the supervised runs (on Polish Railway Lines) of Electric Multiple Unit (EMU-ED74) with the prototype of track quality monitoring system installed on-board are described. As Track Quality Indicator (TQI) algorithm, used in the mentioned prototype, a modified Karhunen-Loeve transformation is used in preliminary preparation of acceleration signals. The transformation is used to extract the principal dynamics from measurement data. Obtained results are compared to other methods of evaluating the geometrical track quality, namely methods, which apply the synthetic coefficient Jsynth and five parameters of defectiveness W-5. The results from the investigation showed that track condition estimation is possible with acceptable accuracy for in-service use and for defining cost-effective maintenance strategies.
In this paper, railway passenger flows are analyzed and a suitable modeling method proposed. Based on historical data composed from monthly passenger counts realized on Serbian railway network it is concluded that the time series has a strong autocorrelation of seasonal characteristics. In order to deal with seasonal periodicity, Seasonal AutoRegressive Integrated Moving Average (SARIMA) method is applied for fitting and forecasting the time series that spans over the January 2004 - June 2014 periods. Experimental results show good prediction performances. Therefore, developed SARIMA model can be considered for forecasting of monthly passenger flows on Serbian railways.
The main advantages of maritime transport are (1) lowest costs, (2) large-scale carriage capacity, (3) carriage of different goods over long distances and (4) the most acceptable mode of transport in the context of the environment. This mode of transport is considered more profitable and more cost-effective than all other transport modes. Modern maritime ports have become the essential nodal components of freight transport networks. This paper is focused on determining the most suitable layout of space for the loading units warehousing and handling in the maritime port using the particular method. In the paper, four types of layout and five criteria were taken into account. Layout of warehousing and handling space can affect the entire transport process and can have a great effect on the economics of enterprises.
Fleets of shared Autonomous Vehicles (AVs) could replace private cars by providing a taxi-like service but at a cost similar to driving a private car. On the one hand, large Autonomous Taxi (AT) fleets may result in increased road capacity and lower demand for parking spaces. On the other hand, an increase in vehicle trips is very likely, as travelling becomes more convenient and affordable, and additionally, ATs need to drive unoccupied between requests. This study evaluates the impact of a city-wide introduction of ATs on traffic congestion. The analysis is based on a multi-agent transport simulation (MATSim) of Berlin (Germany) and the neighbouring Brandenburg area. The central focus is on precise simulation of both real-time AT operation and mixed autonomous/conventional vehicle traffic flow Different ratios of replacing private car trips with AT trips are used to estimate the possible effects at different stages of introducing such services. The obtained results suggest that large fleets operating in cities may have a positive effect on traffic if road capacity increases according to current predictions. ATs will practically eliminate traffic congestion, even in the city centre, despite the increase in traffic volume. However, given no flow capacity improvement, such services cannot be introduced on a large scale, since the induced additional traffic volume will intensify today's congestion.
Cities' sustainability strategies seem to aim at the reduction of the negative impacts of urban freight transport. In the past decades, many public and private initiatives have struggled to gain broad stakeholder support and thus remain viable. Researchers and practitioners have only recently recognised stakeholder acceptance of urban freight solutions as a challenge. A first step in achieving convergence is to understand stakeholder needs, preferences and viewpoints. This paper proposes and applies an approach to identify the main stakeholder perspectives in the domain of urban freight transport. We use Q-methodology, which originates from social sciences and psychology, to record subjective positions and identify the dominant ones. We explain the approach, operationalise the method for the domain of urban freight transport and apply it to stakeholder groups in the Netherlands. We find four dominant perspectives, reflecting how stakeholders normally take positions in the urban freight dialogue. Important findings concern disparities between industry associations and some of their membership, divergent views about the expected role of public administration, and the observation that the behaviour of shippers and Logistics Service Providers (LSP) appears to be inconsistent with their beliefs. All these factors together can act as a barrier to the implementation of urban freight consolidation concepts. The Q-methodology is valuable for eliciting perspectives in urban freight and is a promising tool to facilitate stakeholder dialogue and, eventually, convergence.
The influence of co-solvent on transesterification of one of non-edible feedstocks, Bitter Almond Oil (BAO) with methanol was investigated. Hexane and potassium hydroxide (KOH) were chosen as the co-solvent and the catalyst, respectively. The variables included in the optimization process were concentration of KOH, methanol to oil molar ratio, hexane to methanol volume ratio, reaction temperature, reaction time, type of co-solvent and type of the alkali catalyst. BioDiesel (BD) with yield of 97.88 and 98.50 wt. % ester content were obtained using 0.60 wt. % KOH, 5:1 methanol to oil molar ratio, 1:1 hexane to methanol volume ratio, 32 degrees C reaction temperature and 45 minutes of reaction. The Fourier Transform InfraRed (FTIR) spectroscopy and Thin Layer Chromatography (TLC) were used to ensure the conversion of BAO into BD. The fuel properties of the prepared BD were determined and found within the acceptable limits prescribed by ASTM D6751-15cel and EN 14214:2017. Moreover, properties of (biodiesel + petro-diesel) blends complied with the limits prescribed in the ASTM D7467-17 standards as well. It was concluded that the presence of co-solvent reduced the concentration of the catalyst, temperature, methanol to oil molar ratio and time required to produce maximum yield of BD comparing to non-solvent process. As a result, co-solvent transesterification is recommended for further application.
The aim of this article was to analyse the correlation of emission intensity of carbon monoxide, hydrocarbons, nitrogen oxides, and carbon dioxide in various conditions of operation of the automotive internal combustion engine. The operational properties of the engine were investigated on chassis dynamometer in driving test cycles simulating various real-world conditions of the vehicle drive: street congestions, urban traffic without congestions, extra-urban traffic, and high-speed traffic. The correlational dependence of the pollutant emission intensity on the non-negative effective power of the engine and the correlational interdependence between the emission intensity of individual pollutants were investigated. The coefficients of Pearson’s linear correlation, Spearman’s rank correlation, Kruskal’s gamma correlation, and Kendall’s tau correlation were calculated. It was found that the emission intensity of pollutants in the driving test cycles strongly depends on the dynamic states of operation of the engine. The time histories of the emission intensity of pollutants were strongly correlated with the non-negative effective power of the engine. There were only a few cases where this correlation can be assessed as weak. The time histories of the emission intensity of individual pollutants were also strongly correlated with each other, with only a few exemptions.
The Origin–Destination (O–D) matrix, is an important information in transportation planning and traffic control. Rapid changes in land use, particularly in developing countries, have been and are on an increase, which makes the estimation and observation of this matrix more significant. The objective of this paper is to observe O–D matrix under two scenarios. In the first scenario, it is assumed that the traffic network is equipped with path-ID sensors. In this situation, the goal is to determine the optimal number and location of these sensors in the network, where by applying collected information through these sensors, the O–D matrix is observed. Because path-ID sensors are not available in many cities, in the second scenario the interview alternative is proposed in order to observe O–D matrix. The interview method has encountered some restrictions. Several mathematical programming models have been developed to overcome these restrictions. To illustrate these proposed methodologies, they are applied in the Nguyen–Dupuis transportation network and the results are analysed. By applying the model on the intercity road network in the Province of Isfahan (Iran), a large network, the efficiency of these proposed models is demonstrated. Finally, some conclusions and final recommendations are included.
The transmission of mechanical front-wheel drive tractors normally has a front axle lead ratio, which is equal to 1.5…2.5%. Naturally, when ballast masses are added to the tractor or when inflation pressure in the tires is reduced, distortion of the tires is inevitable, which changes the lead of the front wheels. In this paper, we present the impact of tire inflation pressures on the lead front drive wheels and movement resistance force when the tractor travelled with a front drive axle enabled and was engine braking with the fuel supply off. It was found that the variation in front and rear tires inflation pressure combination can significantly change the lead of the front drive wheels. For the tested tractor up to 6.9%. The result is that when the tractor travelled with the front axle enabled and was engine braking, the engine-braking efficiency decreases with increasing lead of the front wheels. Front (slipping) wheels create the opposite-direction torque, which is transferred to the rear wheels through the tractor’s front-rear axle drive system. Additional losses of the engine braking occur in transmission due to power circulation, and the result is that the tractor wheels receive less braking torque from the engine.
Limited-stop bus services are a highly efficient way to release more potential of the public transit system to meet travel demand, especially under constraints on vehicle fleet size and transportation infrastructure. This work first proposes a visualized fare table for the design of limited-stop bus services along a public transit corridor, along which many lines of public transit carry a heavy load of demand back and forth every working day. Based on this proposed fare table, a set of fare strategies and desired aims of fare policy, a differentiated fare structure is established to improve social equity and increase revenue. The nature of the structure can help travellers understand how to be charged between their origins and destinations (e.g. flat, time-based, stop-based or quality-based pricing) and then plan their trips efficiently. Secondly, a model is formulated to minimize the total social cost in designing a fixed demand limited-stop bus service system with a differentiated fare structure. Thirdly, numerical results are carried out with sensitivity analysis within three scenarios of differentiated fare structures. It is found that a differentiated fare structure has a great effect on passenger path choice behaviour and resulting optimal design of bus services. An attractive feature of this differentiated fare structure is that it could not only enhance the operator’s revenue and social equity but also reduce passenger transfers and social cost.
With the acceleration of globalization processes and increased international cooperation, freight transport routes are expanding, which requires new solutions for the most efficient use of various modes of transport. One of the most important factors that may improve the efficiency of the interoperability of different transport modes is information exchange allowing to plan transport flows in advance, exploiting benefits of the maritime and rail transport and minimizing its disadvantages. Precise information allows to find the most efficient mode of transport for the freight transportation chain. Precise information is necessary for effective management of information flows to ensure interoperability between the transport modes. This article analyses the specificity of railway and maritime transport modes, hence research questionnaire of Lithuanian transport companies is performed to present the results to show the most significant elements of railway and maritime transport interoperability. The completed expert evaluation enabled to prioritize the sequence of elements to ensure the efficient interoperability between rail and maritime transport.
An efficient and intelligent road traffic management system is the corner stone for every smart cities. Vehicular Ad-hoc NETworks (VANETs) applies the principles of mobile ad hoc networks in a wireless network for Vehicle-to-vehicle data exchange communication. VANETs supports in providing an efficient Intelligent Transportation System (ITS) for smart cities. Road traffic congestion is a most common problem faced by many of the metropolitan cities all over the world. Traffic on the road networks are widely increasing at a larger rate and the current traffic management systems is unable to tackle this impediment. In this paper, we propose an Efficient Intelligent Traffic Light Control and Deviation (EITLCD) system, which is based on multi-agent system. This proposed system overcomes the difficulties of the existing traffic management systems and avoids the traffic congestion problem compare to the prior scenario. The proposed system is composed of two systems: Traffic Light Controller (TLC) system and Traffic Light Deviation (TLD) system. The TLC system uses three agents to supervise and control the traffic parameters. TLD system deviate the vehicles before entering into congested road. Traffic and travel related information from several sensors are collected through a VANET environment to be processed by the proposed technique. The proposed structure comprises of TLC system and makes use of vehicle measurement, which is feed as input to the TLD system in a wireless network. For route pattern identification, any traditional city map can be converted to planar graph using Euler’s path approach. The proposed system is validated using Nagel–Schreckenberg model and the performance of the proposed system is proved to be better than the existing systems in terms of its time, cost, expense, maintenance and performance.
This paper considers a Capacitated Location-Arc Routing Problem (CLARP) with Deadlines (CLARPD) and a fleet of capacitated heterogeneous vehicles. The proposed mixed integer programming model determines a subset of potential depots to be opened, the served roads within predefined deadlines, and the vehicles assigned to each open depot. In addition, efficient routing plans are determined to minimize total establishment and traveling costs. Since the CLARP is NP-hard, a Genetic Algorithm (GA) is presented to consider proposed operators, and a constructive heuristic to generate initial solutions. In addition, a Simulated Annealing (SA) algorithm is investigated to compare the performance of the GA. Computational experiments are carried out for several test instances. The computational results show that the proposed GA is promising. Finally, sensitivity analysis confirms that the developed model can meet arc routing timing requirements more precisely compared to the classical Capacitated Arc Routing Problem (CARP).
The private sector assumes that logistics centers create cost benefits for their operations. On the other hand, the public sector also assumes that logistics sectors maintain harmony with an aim to improve the logistics network structure and efficiency. In Turkey, nineteen logistics centers are on-going to develop a system approach and integrate different transportation modes to increase logistics performance. In this study, we focused on a multi-stage methodology that combines the fuzzy analytic hierarchy process, spatial statistics and analysis approaches to evaluate the suitability degrees of the logistics centers in the study area. To reach the suitability levels, seven decision criteria were considered alongside their priority levels. These criteria were proximities to highway, railway, airports, and seaports; volume of international trade; total population; and handling capabilities of the ports. The reached suitability degrees were tested using a sensitivity analysis. Different scenarios were discussed to understand how the decision environment might illustrate differences in spatial aspect.
Identifying the optimal time to replace a passenger bus in a buses fleet has implications on the size of the reserve fleet. Such calculations rest on endogenous and exogenous economic variables: the former include operating and maintenance costs and bus depreciation; the latter include market imponderables such as the inflation and real discount rates, as well as energy costs, particularly fuel. The authors have created models for the withdrawal/replacement of buses using endogenous economic variables. The models include standard econometric models reflecting the influence of maintenance policies, especially Condition Monitoring (CM) or predictive maintenance, and the size of the reserve fleet. The paper deals with exogenous economic variables, specifically the influence of the cost of money, the inflation and real discount rates rate and the cost of fuel. Both variables fluctuate over time. The paper proposes analytical models for determining the influence of those variables on the withdrawal time and the size of the reserve fleet. It then comprehensively summarizes the variables in a global model, showing its relevance to the dimensioning of the reserve fleet and the withdrawal time.
The ridesourcing services market in China has recently experienced significant changes, which stem from its legalization and management policy. These changes impact multiple stakeholders of this market (e.g., drivers, passengers, government, competing services) and present them with new opportunities and challenges. This paper develops an evolutionary game model to analyse the Evolutionary Stable Strategy (ESS) between the Transportation Network Companies (TNCs) and drivers. The new model is explored and analysed with simulation experiments to observe the dynamic route of multiple stakeholders. The theoretical research and simulation results indicate that under the authorities’ control over the TNCs, when the net income under strict management is higher than that of the loose management for the TNCs, the final ESS is “Legal Operation, Strict Management”. When the net income under strict management is less than that of the loose management for the THCs, the strategy of “Illegal Operation, Loose Management” may gain popularity and continue to grow; in this case, the ESS may also not exist. The model indicates the strength of the government’s control plays a significant role in leading the achievement of “Legal Operation, Strict Management”. As a consequence, to achieve the perfect evolution of “Legal Operation, Strict Management”, it is necessary for the government to impose a greater penalty on illegal drivers and ensure appropriate compensation measures. The results of the study provide a useful reference for the sustainable development of the ridesourcing services market.
The European Commission initiated the process of liberalization and introducing competition in the European railway sector more than twenty-five years ago. Despite the liberalization of the railway sector, train paths are currently administratively allocated in all EU countries using the train service priority criterion, which may not treat all train operators equally. This is especially evident in those network sections where demand exceeds the available capacity. In these situations, economic theory suggests the implementation of a market-based mechanism for allocation of capacity, such as auctions. However, due to its incompatibilities with priority criteria in the process of the capacity allocation, it is necessary to develop a new procedure to support the implementation of an auction. In this paper, the proposed algorithm fills the technological gap between train timetable design and train operator requests. The new algorithm for decentralized capacity allocation is the result of a multidimensional approach, which encompasses setting new relations between train operators and the infrastructure manager, train timetable drafting and resolving the conflicting request. In addition, the algorithm provides a feasible solution ensuring equal treatment of train operators and efficient allocation, in order to foster the development of the competition in the European rail market.
The goal of the study is to develop a model that focuses on managing logistics costs at all stages of a product’s life cycle. The model includes several different cost components and provides a wider coverage of individual processes, as logistics costs are present in different areas of a company’s operations. The applicability of the proposed method was tested in a multinational company that manufactures furniture fittings on a randomly selected product. The test results provide a theoretical and practical confirmation of the necessity to manage the logistics costs for an individual product, since other models are focused exclusively on the cost optimisation of individual logistics processes. The model therefore complements the existing knowledge and represents a practical tool for logistics professionals that enables more efficient logistics costs planning at an early stage in the development of a product, which can result in the long-term reduction in the total costs of logistics and improve the quality of business processes.
The paper presents the results of the investigation of Dual Fuel (DF) diesel engines powered by high bioethanol contain fuel - E85. The object of the investigation is a three-cylinder Compression Ignition (CI) Internal Combustion Engine (ICE) powered by diesel oil and bioethanol fuel E85 injected into the intake port as a DF engine. With the increase in the share of E85 fuel the highest intensification of the combustion process takes place in the main stage of the combustion and the ignition delay increases as well. The researchers are conducted using Computational Fluid Dynamics (CFD) method; the results of the investigation are successfully verified based on the indicator diagrams, heat performance rate and emissions. Based on CFD results the cross sections investigation of the combustion chamber it can be seen that in case of the DF engine, the flame front propagates with a higher speed. The initial phase of the combustion starts in a different location of the combustion chamber than in the classic CI engine. Replacement of diesel fuel by E85 in 20% resulted in the shortening of the combustion duration more than 2-times. With the increase of energetic share in E85 the soot emission is decreased at all ranges of the analysed operations of the engine. The opposite relationship was observed in case of NO emission. With the increase of E85 in the fuel, the emission of NO increased.
A decision-making process requires a prior definition and fulfilment of certain factors, especially when it refers to complex fields such as supply chain management. One of the most important items in the initial stage of a supply chain, which strongly influences its further flow, is making a decision on the most suitable supplier. In this paper, a model for evaluation and supplier selection has been proposed, which has been considered in more than ten different production areas. The model consists of twenty quantitative and qualitative criteria, which are reduced to a total of nine by the application of the fuzzy AHP and the assessment of managers in production companies. The verification of the model has been presented throughout a selection of suppliers in a company for the production of plastic bags and foils, where the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) method has been used to determine the significance of the criteria, and the Fuzzy Evaluation based on Distance from Average Solution (Fuzzy EDAS) to evaluate and select suppliers. The obtained results have been considered throughout a sensitivity analysis in which a total of 15 different scenarios have been formed and where the stability of the model has been determined, since the supplier one is the best solution in all the cases.