Search

This paper constructs a berth-quay crane capacity planning model with the lowest average daily cost in the container terminal, and analyzes the influence of the number of berths and quay cranes on the terminal operation. The object of berth-quay crane capacity planning is to optimize the number of berths and quay cranes to maximize the benefits of the container terminal. A steady state probability transfer model based on Markov chain for container terminal is constructed by the historical time series of the queuing process. The current minimum time operation principle (MTOP) strategy is proposed to correct the state transition probability of the Markov chain due to the characteristics of the quay crane movement to change the service capacity of a single berth. The solution error is reduced from 7.03% to 0.65% compared to the queuing theory without considering the quay crane movement, which provides a basis for the accurate solution of the berth-quay crane capacity planning model. The proposed berth-quay crane capacity planning model is validated by two container terminal examples, and the results show that the model can greatly guide the container terminal berth-quay crane planning.

Route selection and distribution costs of express delivery based on the urban metro network, referred to as metro express delivery (MeD), is addressed in this study. Considering the characteristics of express delivery transportation and the complexity of the urban metro network, three distribution modes of different time periods are proposed and a strict integrated integer linear programming model is developed to minimize total distribution costs. To effectively solve the optimal problem, a standard genetic algorithm was improved and designed. Finally, the Ningbo subway network is used as an example to confirm the practicability and effectiveness of the model and algorithm. The results show that when the distribution number of express delivery packages is 1980, the three different MeD modes can reduce transportation costs by 40.5%, 62.0%, and 59.0%, respectively. The results of the case analysis will help guide express companies to collaborate with the urban metro network and choose the corresponding delivery mode according to the number of express deliveries required.

The past years brought massive changes in the transport and mobility market, accompanied by the rise of concepts such as Mobility as a Service. An enormous increase in publications on this topic documents the growing importance of multimodal mobility solutions for daily transport, but practical applications of the concept are rare. In addition to challenges in the organization of players, this is due to an unclear conception of the service offer and which particular services should be included to what extent. This paper presents the results of an empirical study in the city of Dresden, Germany, where participants could choose out of various bundles of mobility services in a conjoint analysis. The survey provides evidence for the great importance of public transport for the evaluation of mobility bundles as well as for the benefit-enhancing effect of car and bike sharing. A comparison among different user groups reveals a very homogeneous picture of mobility plans, which, however, only partly reflects actual behaviour.

Deteriorated urban areas in large cities have poor living standards, are inaccessible and small-sized, and have unstable building structures. Earthquake hazards may turn such situations into human disasters. In most cases, neither the governments nor the owners of these properties have enough budgets for renovating them. The purpose of this paper is to take advantage of Transit Oriented Development concepts to simultaneously solve two major urban area problems: (a) renovation of deteriorated urban areas and prevention of urban sprawl, and (b) design of transit network and promotion of transit-oriented development to reduce traffic congestion, pollution, and other unwanted outcomes of the extensive automobile use in large metropolitan areas. This paper proposes a bilevel multi-agent programming in which each agent maximizes the respective benefits while being subjected to the results of the decisions by others. We formulate the problem and solve it by a novel meta-heuristic algorithm. After analyzing the set of solutions to a test problem, we apply the algorithm on this rather large, real case urban area, and discuss the results. The solution results indicate that the proposed methodology: (a) reduces the total travel time in transportation networks of the city, (b) turns the deteriorated urban developments into a new and attractive environment, (c) provides a profitable investment for the construction industries in the context of Build-Operate-Transfer scheme, and (d) upgrades urban life for the city in general, and alleviates earthquake hazards for the inhabitants of the deteriorated urban areas, in particular., European Journal of Transport and Infrastructure Research, Vol 21 No 1 (2021)

Vulnerability has been a major concern in the performance evaluation of transportation networks. In the concept of vulnerability, the key step is to identify the critical link, which are the ones susceptible to severe operational degradation caused by any type of failure. Several studies have been devoted to this issue by introducing indicators that illustrate the network's operational degradation's overall impact. However, the impact of the interrupted network on users can be further evaluated using the inequity perspective. Here, we present a method to assess network vulnerability to operational degradation based on spatial inequity impacts. The importance of a link is determined by calculating the Gini-coefficient of the distribution of added travel time to the users when the link is disabled. Furthermore, the overall impact of link failure is calculated based on the total extra travel time. The final link's importance is determined by the non-dominated sorting method based on the Pareto optimality concept considering both overall and inequity objectives. Measures quantifying overall and inequity impacts of link failure allow planners to determine how this influences the disadvantaged distribution and help them make decisions associated with maintenance plans that consider link failure's equity impact., European Journal of Transport and Infrastructure Research, Vol. 21 No. 1 (2021)

The role of cross-border commuting needs is remarkable, given that large cross-border cities tend to have high traffic attractiveness. Thus, agglomeration effects are strongly prevalent in populous settlements close to the border. This is due to the fact that both Hungary and the neighboring countries are burdened by spatial inequalities; therefore, the traffic at the individual border crossing points is unbalanced. Our aim is to show the extent to which the introduction of certain public transport modes contributes to the reduction of cross-border passenger car traffic. In order to do this, we have to set up a spatial econometric model that can simultaneously handle the parallel public transport infrastructure, the cross-border attractiveness of border cities, and the impact of spatial inequalities. The results of the research shed light on how the introduction of each means of transport contributes to increasing the competitiveness of border regions. This will demonstrate the effectiveness of policy tools that can improve the competitiveness of a given macroregion.

The article describes the problem of incorrect U-turns at intersections with traffic lights. Statistical data on road incidents related to U-turns are presented. Then, the international, Polish and foreign regulations concerning u-turning at intersections with traffic lights were analysed. The situations in which U-turns are allowed or prohibit-ed are presented. The differences in design rules for junctions with U-turns in different countries have been taken into account. A literature review was also carried out that outlined various current U-turns around the world, including the design of turning places, the location of turning points, road safety when turning, and the impact of U-turns on traffic conditions. The further part of the article presents the results of field tests of the U-turn at 6 intersections located in Warsaw. The research was conducted by video observation. The results were broken down by age, gender, place of regis-tration of the vehicle, type of vehicle, and the effect of incorrect turning. Data on road incidents at the examined intersections were also analysed. Data from the database kept by the Police were compared with the measure-ment data. A regression analysis was performed between the types of recorded incorrect manoeuvres and the number of accidents at the intersection. The results of statistical analysis carried out do not indicate the existence of a relationship between the number of identified incorrect U-turns and the number of road incidents at inter-sections. Based on the research, it was found that the phenomenon of incorrect U-turns at intersections with traffic lights is common, and the use of directional (protected) signals does not eliminate this phenomenon. The conclusions indicate practical solutions to reduce the number of illegally U-turning vehicles. The recommended actions are related to the stage of shaping the road network, designing the road geometry and organizing traffic and traffic lights, and auditing road safety, as well as the stage of road operation.

Coach emergency escape research is an effective measure to reduce casualties under serious vehicle fire accidents. A novel experiment method employing a wireless transducer was implemented and the head rotation speed, rotation moment and rotation duration were collected as the input variables for the classification and regression tree (CART) model. Based on this model, the classification result explicitly pointed out that the exit searching efficiency was evolving. By ignoring the last three unimportant factors from the Analytic Hierarchy Process (AHP), the ultimate Dynamic Bayesian Network (DBN) was built with the temporal part of the CART output and the time-independent part of the vehicle characteristics. Simulation showed that the most efficient exit searching period is the middle escape stage, which is 10 seconds after the emergency signal is triggered, and the escape probability clearly increases with the efficient exit searching. Furthermore, receiving emergency escape training contributes to a significant escape probability improvement of more than 10%. Compared with different failure modes, the emergency hammer layout and door reliability have a more significant influence on the escape probability improvement than aisle condition. Based on the simulation results, the escape probability will significantly drop below 0.55 if the emergency hammers, door, and aisle are all in a failure state.

Accurate metro ridership prediction can guide passengers in efficiently selecting their departure time and simultaneously help traffic operators develop a passenger organization strategy. However, short-term passenger flow prediction needs to consider many factors, and the results of the existing models for short-term subway passenger flow forecasting are often unsatisfactory. Along this line, we propose a parallel architecture, called the seasonal and nonlinear least squares support vector machine (SN-LSSVM), to extract the periodicity and nonlinearity characteristics of passenger flow. Various forecasting models, including auto-regressive integrated moving average, long short-term memory network, and support vector machine, are employed for evaluating the performance of the proposed architecture. Moreover, we first applied the method to the Tiyu Xilu station which is the most crowded station in the Guangzhou metro. The results indicate that the proposed model can effectively make all-weather and year-round passenger flow predictions, thus contributing to the management of the station.

The research on improvement of methodical approaches to definition of the probable reasons of infringement of conditions of stability of freight cars from derailment is carried out. Using a basic computer model of the dy-namics of a freight car, the influence of the characteristics of the technical condition of their running gear and track on the indicators of empty cars stability from derailment was studied through the computational experi-ment. The article presents the main statements of the research methodology, which provides the analysis of probable causes of derailment of freight cars by conducting a series of numerical experiments with logging the progress of calculations and saving the results. Factor analysis was used to interpret the calculated data with an assessment of each of the factors influence or their combination on the probability of derailment. The developed procedure of the simulation experiment provides a step-by-step study of the freight cars derail-ment conditions, including factors structuring and ranking, development of experimental plan, calculating coef-ficients of wheel pairs resistance to derailment from rails, provided that the wheel flange rolls onto the rail head, and determining the degree of influence of relevant factors on the dynamic stability of cars from derailment. A comparative analysis of the stability of cars in rail tracks was performed using the introduced concept of the combined coefficient of stability of wheel pairs against derailment. Determining the probable causes of car derailment is based on scanning the parameter field. The results of the parametric study revealed the degree of influence on the freight cars stability of running gear technical condition characteristics. In particular, it is determined that the most dangerous in terms of stability loss of empty cars in the track is the exceeding of the wedges of the vibration dampers.

The Polish electric mobility market, presently at a relatively early development stage, cannot compete with traditional means of transport in relation to the number of locations enabling drivers to “refuel” their vehicles. Simultaneously, extension of the network of publicly available EV charging stations constitutes a vital prerequisite for electric vehicle industry development. The feeling of range anxiety connected with limited access to suitable EV charging outlets, in particular during longer trips, discourages potential buyers from purchasing electric vehicles, and, as a result, limited demand hinders development of this industry. In January 2018, the Polish Parliament (the Sejm) passed the Act on electromobility and alternative fuels which establishes a certain system and provides a number of objectives vital for electric vehicle market development. Being aware of the fact that, at least for the first few years, infrastructure devel-opment is a key factor, the legislator, in Art. 60, section 1 of the Act, establishes a minimum number of EV charging outlets to be installed in Polish communes, by 31 December 2020. However, no detailed guidelines as to their location were given. It only indicates a minimum number of them, which should be established in communes with a given demo-graphic and transport characteristics of the commune ie the number of inhabitants and motor vehicles and the number of cars per 1000 inhabitants of the commune. The purpose of this article is to indicate in which, specifically, municipal-ities, according to the act, electric vehicles charging outlets are to be located. Based on the analysis performed it was determined that publicly available EV charging outlets must be installed only in 32 of 2477 communes in Poland and and these are municipalities. Identification of such communes made it possible to determine the distances between them, which made it possible to verify whether the network of EV charging infrastructure planned on the basis of the guidelines in the Act will enable efficient route travel in the future without experiencing any range anxiety. In addition, the existing market conditions were presented and discussed, with an indication of whether they are conducive to meeting the minimum set in the Act regarding the number of charging points. The conducted analysis is an introduction to further research on determining the optimal distribution of charging outlet in Poland.

In the present work, biofuels produced from different raw fatty materials have been proposed asa dominant fuel component in biodiesel–diesel fuel blends. Biofuels were produced from pork lard and rapeseed oil by alkali transesterification usingmethyl alcohol. Blends of biofuels in volumetric proportions of 60 and 80% of the biocomponent and the remaining part of the conventional fuel were used in a compression ignition engine designed for medium-duty vehicles. The experiments were conducted attwo engine rotational speeds (1500 and 3000 rpm,respectively) and a set of load conditions (50, 100, and200 Nm,respectively). The tests focused onengine efficiency parameters (brake-specific fuel consumption and brake fuel conversion efficiency) as well as exhaust gas emissions (hydrocarbons, carbon monoxide, and carbon dioxide were determined). The obtained results indicate that blends containing biocomponents produced from pork lard were characterized by superior fuel consumption and efficiency results, compared to blends containing biocomponents produced from rapeseed oil. In terms of exhaust emissions,biocomponents produced from pork lard were also characterized by lower emission of all of the examined components compared to rapeseed methyl ester–diesel blends. This study proposes that fuel components obtained from custom (animal) raw-fatty material canbe an effective substitute for commonly used rapeseed oil methyl esters.

The problem of choosing the way to move people is often encountered both in scientific research and in everyday life. The difficulty of this process depends on the availability of many variants and the pursuit of satisfying transport needs at the minimum cost, in the shortest possible time and in the most comfortable conditions. The publication presents a decision problem of choosing the best transport option using multi-criteria methods. At the beginning authors present-ed the widely used methods of solving decision problems in the literature. Subsequently, based on the example of the Warsaw-Wroclaw connection, the MAJA multi-criteria assessment method algorithm was analysed. Both road, rail and air transport options were considered. Six possible variants of solutions were indicated, which were assessed in three sub-criteria: cost, time and comfort of travel. Then, the results of the analysis were compared with the results obtained using other multi-criteria decision-making support methods, i.e. ELECTRE I, AHP, TOPSIS, PROMETHEE, SAW, PVM. The considered methods were divided according to the way the result was presented, as a result of which the methods based on the relation of superiority (which included the MAJA method) and methods using ranking were distinguished, and then an intra-group comparison was made. On the basis of the constructed compliance matrix of the relation of superiority, it was found that domination methods exhibited convergence of the obtained results. However, in order to compare the convergence of the results of the ranking methods, the Spearman's linear correlation coefficient was used. The applied MAJA multi-criteria method has made it possible to determine non-dominated solutions considered optimal taking into account the adopted weights of criteria and compliance and non-compliance thresholds. Its unquestionable advantage is the possibility of using many partial criteria expressed in different measurement units. In the presented example, the best options were the premium express rail transport and airplane. The summary defines the direction of further research and possibilities of modification of the presented method.

Improving safety has always been the top interest in the aviation industry. The outcomes of safety and risk analyses have become much more thorough and sophisticated. They have become an industry standard of safety investigations in many airlines nowadays. In the past, airlines were much more limited in answering the questions about hazardous situations, accident probabilities, and accident rates. Airlines try hard to cope with stricter safety standards. The objective of this paper is to find out and quantify the extent of the expert judgment in helping airlines in the evaluation of the Flight Data Monitoring (FDM) events. On top of that, the paper reveals the method for a careful choice of experts, so that their estimations will maximize the potential of an accurate and useful outcome. Also, the paper provides details of implementation of the classical model into this research, then continues with the calculations and visualization of the outcomes. The outcomes are probability distributions per each aircraft type, then per IATA accident type and finally per FDM event.

Autonomous vehicles are the most advanced intelligent vehicles and will play an important role in reducing traffic accidents, saving energy and reducing emission. Motion control for trajectory tracking is one of the core issues in the field of autonomous vehicle research. According to the characteristics of strong nonlinearity, uncertainty and chang-ing longitudinal velocity for autonomous vehicles at high speed steering condition, the robust trajectory tracking control is studied. Firstly, the vehicle system models are established and the novel target longitudinal velocity planning is carried out. This velocity planning method can not only ensure that the autonomous vehicle operates in a strong nonlinear coupling state in bend, but also easy to be constructed. Then, taking the lateral location deviation minimiz-ing to zero as the lateral control objective, a robust active disturbance rejection control path tracking controller is designed along with an extended state observer which can deal with the varying velocity and uncertain lateral dis-turbance effectively. Additionally, the feedforward-feedback control method is adopted to control the total tire torque, which is distributed according to the steering characteristics of the vehicle for additional yaw moment to enhance vehicle handing stability. Finally, the robustness of the proposed controller is evaluated under velocity-varying condi-tion and sudden lateral disturbance. The single-lane change maneuver and double-lane change maneuver under vary longitudinal velocity and different road adhesions are both simulated. The simulation results based on Matlab/Simulink show that the proposed controller can accurately observe the external disturbances and have good performance in trajectory tracking and handing stability. The maximum lateral error reduces by 0.18 meters compared with a vehicle that controlled by a feedback-feedforward path tracking controller in the single-lane change maneuver. The lateral deviation is still very small even in the double lane change case of abrupt curvature. It should be noted that our proposed control algorithm is simple and robust, thus provide great potential for engineering application.

COVID-19 caused by the SARS-CoV-2 virus is a global health concern due to the quick spread of the disease. In Turkey, the first confirmed COVID-19 case and death occurred on 11 and 15 March 2020, respectively. There is a lack of research on the impact of COVID-19 on public transportation mobility and the Air Quality Index (AQI) around the world. The objective of this research is to consider the impact of COVID-19 on public transportation usage and consequently the AQI level in Turkey. Data collection for the analysis of public transportation usage and the air quality status during pre-lockdown and lockdown was carried out using the public transportation applications Moovit and World’s Air Pollution. The results demonstrated that during the lockdown in Ankara and Istanbul, public transportation usage dramatically decreased by more than 80% by the end of March and did not change significantly until the end of May. As regards air quality, the results confirmed that air quality improved significantly during the lockdown. For Ankara and Istanbul, the improvement was estimated at about 9% and 47%, respectively.

Battery electric buses(BEBs)are gaininggroundin public transport, andthe next decade is likely to witnessa further increase in the numbers of these vehicles.The core problem of the BEB deployment process in public transport lies in howto deal with the technical limitationsof this technology(primarily, a limited range of a bus). This paper outlines the model of vehicle cycle hierarchizationdedicatedtomunicipal transport planners and transit companies. The model isbased on a multicriteria decision-making methodologythatresults in a hierarchy of vehicle cycles, ordered from the most to the least suitable to be operated by electric buses.The proof-of-principle demonstration of the model has been carried out inthe Polish medium-sized city of Jaworzno.

The rapid growth of the intercity travel demand has resulted in enormous pressure on the passenger transportation network in a megaregion area. Optimally locating hubs and allocating demands to hubs influence the effectiveness of a passenger transportation network. This study develops a hierarchical passenger hub location model considering the service availability of hierarchical hubs. A mixed integer linear programming formulation was developed to minimize the total cost of hub operation and transportation for multiple travel demands and determine the proportion of passengers that access hubs at each level. This model was implemented for the Wuhan metropolitan area in four different scenarios to illustrate the applicability of the model. Then, a sensitivity analysis was performed to assess the impact of changing key parameters on the model results. The results are compared to those of traditional models, and the findings demonstrate the importance of considering hub choice behavior in demand allocation.

The number of IT systems and technologies supporting various processes, including the manufacturing, has been grow-ing in recent years. Various versions of integrated ERP-class systems are known. At the same time, we are in the fourth industrial revolution. The future is Industry 4.0 and Digital Factory. Industry 4.0 is an overall term for technical inno-vations and value change organization concepts which revolutionize the industrial production. Currently, the digital technologies change the way production is carried out by generating, transferring and processing of data, and also by analysing large amounts of datasets. There is a problem of the place and significance of logistics, transport and supply chains in the fourth industrial revolution. What is logistics engineering, what methods are suggested to solve the con-temporary problems of logistic support of production processes? To whom are the virtual systems dedicated? What rules should be applied by small and medium enterprises (SME)? Is the pressure of virtual world a threat to such com-panies? Is it possible to design and make real products without virtual manufacturing? Hence, does Logistics 4.0 exist and where is it used? The practice of logistics engineering is applied during the entire system lifecycle by means of interactive processes supporting the analyses and research (compromise) for optimization of costs, logistics and effi-ciency. Surely, it can be said that without the correctly designed and effective logistic processes the contemporary production system could not achieve the required productivity and effectiveness. The article describes the basic tasks of logistics engineering in relation to production companies, as well as relations with Industry 4.0. and digital factory. Moreover, a proposal of the author’s own algorithms for use in the quest to improve the continuity of flow and of enterprise effectiveness for SME class companies was presented.

Ticket tariff is an important factor influencing the demand for public transport. Among basic problematics re-garding ticket tariffs are designing new fare systems and optimization of current systems. The task of optimization is influenced by two main factors: ticket prices and the structure of the tariff. Both elements were researched in this article, based on eleven public transport organizers fare systems in Poland – metropolitan areas and cities of a different scale. The purpose of this article was to define basic tariff types used in urban and regional public transport with a presentation of their function models. Ticket tariffs split into two main groups: flat and differen-tial. Differential group of tariffs covers: distance (usually are encountered fares based on a number of kilometres or stops travelled), quality (e.g. different fares on basic and express lines), time (minutes, hours or days of ticket validity, but also different tariff during on-peak and off-peak hours), sections (between which passenger travel on a transit route) and zones (transport network divided into areas, e.g. designated by municipalities bounda-ries) tariffs. The concept of this study was to transform as many tariffs as possible from tabular form to the math-ematical function. Five types of functions were considered for each tariff schematic: linear, power, polynomial, logarithmic and exponential. Functions and associated with them R-squared parameters were obtained as a result of regression analysis. The paper indicates that for time, distance and flat tariffs conformity (R2) was in most cases very high and above 0,90. The results indicate that the power function best describes time tariffs. In the case of distance tariffs, different kind of functions can be used: logarithmic, power or polynomial. The pro-posed function form of tariffs may speed up the process of creating new fare systems or upgrading existing ones. With general knowledge about the structure of tariffs and their function forms, it would be easier to determine the price of different kinds of tickets. New fare integration solutions could be also proposed in the future by using Big Data analysis.

This computational and experimental work is dedicated to the development of promising designs of vehicle drive shafts made of polymer composite materials. This paper analyzes the existing models of drive shaftsof“Formula Student” class vehicles and substantiates the use of a carbon-fiber drive shaft with titanium tips. A manufacturing technology for such a product is also presented.Evaluation of structure performance under the action of ultimate loads was carried out by the finite element method. Prototypes of composite drive shafts were produced for further laboratoryand fieldtests. The author proposed a new design of composite drive shafts and a method for calculating the strength of the proposed design;the results were verified by bench laboratory and field tests. From the results ofthis work, conclusions about the performance of the developed structures and their applicability to racing cars were drawn.

Autonomous solutions for transportation are emerging worldwide, and one of the sectors that will benefit the most from these solutions is the public transport by shifting toward the new paradigm of Mobility as a Service (MaaS). Densely populated areas cannot afford an increase in individual transportation due to space limitation, congestion, and pollution. Working towards more effective and inclusive mobility in public areas, this paper compares user experiences of autonomous public transport across Baltic countries, with the final goal of gaining an increased insight into public needs. User experience was evaluated through questionnaires gathered along pilot projects implementing a public transportation line, using an automated electric minibus between 2018 and 2019. To have sufficient diversity in the data, the pilot projects were implemented in several cities in the Baltic Sea Area. The data analysed in this paper specifically refer to the cities of Helsinki (Finland), Tallinn (Estonia), Kongsberg (Norway), and Gdańsk (Poland). Across all cities, passengers provided remarkably positive feedback regarding personal security and safety onboard. The overall feedback, which was very positive in general, showed statistically significant differences across the groups of cities (Kongsberg, Helsinki, Tallinn and Gdansk), partially explicable by the differences in the route design. In addition, across all cities and feedback topics, males gave a lower score compared to females. The overall rating suggests that there is a demand for future last-mile automated services that could be integrated with the MaaS concept, although demand changes according to socio-economic and location-based conditions across different countries. Supplementary Information The online version contains supplementary material available at 10.1186/s12544-021-00477-3.

The strategic goal of development of the transport system is to meet the needs of sociallyoriented development of the economy and society in competitive high-quality transport services. The method of determining the competitiveness of freight transport services developed by the authorsis based on the system of indicators for assessing the competitiveness of freight transport services and includes natural and cost indicators that collectively reflect the competitiveness of each operator's servicesforrailway, airway and roadwaynetworks.

In complex socio-technical systems there is an influence of safe unwanted events on the occurrence of accidents. It is like domino bricks. Therefore, it is not only the recovery from major events that is important, but also the recovery from disruptions in operation. As the literature review shows, the recovery of operation processes is analysed by single criterions for small disruptions. On the other hand, resilience research is focused on the network and major events, but not on frequent small-consequence events that affect operational processes. The performance of a system is a key pa-rameter when evaluating resilience. As a result of the performed literature survey, the aim of the paper was to propose a new method for evaluating performance in terms of operational processes and resilience analysis. Moreover, it is also important to order the most important terms related to this issue, as well as to introduce new types of qualities, which are not only focused on the system, but also on the implemented operational processes. The paper consists of eight sections. The introduction section describes generally the problem, that leads to formula-tion of the aim of the paper and description of its structure. It is followed by the second section consisting of a complex literature survey. Section three orders the reliability, robustness and resilience definitions. Section four analyses the performance influencing factors using Fault and Event Tree Analysis, while section five defines the operational layer of the system and shows a formal description of operation processes. Section six presents the operation process evalua-tion model. It was elaborated using the Fuzzy Logic approach, that allows combining of incoherent system and process qualities: punctuality, probability no further delays, quantitative implementation of scheduled processes, reconfigura-tion level. Afterwards a case study is shown to present the method application. The performed case study shows the advantages of the proposed approach, which is related to the most common methods. The paper ends with conclusions and further research perspectives.

The article investigates the influence of preventive maintenance on the reliability and availability indexes of the railway means of transport, which also determine the economic aspects of their operation and maintenance. The research was done using the method based on fault tree analysis (FTA) and Monte Carlo simulation. The authors performed a cause and effect analysis of the occurrence of undesirable events during the operation of selected vehicles. They identified the weakest components of the rail vehicle that affect the downtime and mean availability most significantly. Specialized software including Weibull++, BlockSim,and MiniTabaided calculations were used to illustrate the application of the results of a modernization project involving a 6Dg diesel locomotive, carried out in cooperation with the biggest Polish rail carrier. The applicability of the proposed tools has been verified on the example of a selected sample of 75 diesel locomotives employing data on their use and maintenance acquired in the real operation process. The obtained results indicate that the proposedapproach can be particularly useful in practice when assessing the applied rail vehicle maintenance strategy,and while developing new strategies and selecting the best one to implement.

This article deals with the possibilities of adhesion force changes of a road vehicle. The authors present the possibilities of reducing the adhesion force of road vehicles and,at the same time,present their own system for changing the radial reaction of the vehicle wheels. This system removes the disadvantages of a commercially available SkidCar system. A representative road test is chosen in the article to determine the stability in a straight-linedrive. Furthermore,the authors report the courses of characteristic parameters describing the behavior of a vehicle for driving a conventional car on a sliding surface and compared to the 50% radial reaction of a vehicle driven with the SlideWheel on dryasphalt. It is clear from the measured runs that it is possible to change the adhesion force by changing the adhesion weight transmitted by the vehicle wheels. The use of the proposed SlideWheel system is possible for the purpose of verifying vehicle stability, while improving the driver's ability to operate the vehicle under reduced-adhesion conditions.The main goal of this paper is to design a system for reducing the adhesive force in an experimental car and performexperimental measurements. Tento článek se zabývá možnostmi změn adhezní síly silničního vozidla. Autoři prezentují možnosti snížení adhezní síly silničních vozidel a současně představují vlastní systém pro změnu radiální reakce kol vozidla. Tento systém odstraňuje nevýhody komerčně dostupného systému SkidCar. V článku je vybrán reprezentativní silniční test ke stanovení stability v přímém pohonu. Autoři dále referují o průběhu charakteristických parametrů popisujících chování vozidla pro řízení konvenčního automobilu na kluzkém povrchu a ve srovnání s 50% radiální reakcí vozidla poháněného SlideWheel na dryasphalt. Z naměřených jízd je zřejmé, že je možné změnit adhezní sílu změnou adhezní hmotnosti přenášené koly vozidla. Použití navrhovaného systému SlideWheel je možné za účelem ověření stability vozidla a zlepšení schopnosti řidiče provozovat vozidlo za podmínek snížené adheze. Hlavním cílem tohoto článku je navrhnout systém pro snížení adhezní síly v experimentální auto a experimentální měření.

The growing demand for private and public transport services in urban areas requires sophisticated approaches to achieve satisfactory mobility standards in urban areas. Some of the main problems in urban areas today are road congestions and consequently vehicle emissions. The aim of this paper is to propose a methodological approach for the estimation of vehicle emissions. The proposed methodology is based on two interrelated models. The first model is a microscopic simulation SUMO model which can be used to identify the most congested urban areas and roads with critical values of traffic parameters. The second model is the COPERT Street Level for estimating vehicle emissions. The proposed models were tested on the urban area of Rijeka. The results of the microscopic SUMO simulation model indicate six urban roads with the critical traffic flow parameters. On the basis of the six identified urban roads, an estimation of vehicle emissions was carried out for specific time periods: 2017, 2020, 2025, and 2030. According to the results of the second model, the urban road R20-21 was identified as the most polluted road in the urban district of Rijeka. The results indicate that over the period 2017–2030, CO emissions will be reduced on average by 57% on all observed urban roads, CO2 emissions by 20%, and PM emissions by 58%, while the largest reduction of 65% will be in NOx emissions.

The main objective of this research is to examine the influencing parameters of driver performance through the yellow phase at urban signalized intersections with and without red-light running (RLR) cameras. Data were collected to include the intersection type, vehicle type, turning movement type, whether the vehicle position is in a platoon or not, presence of RLR cameras, green light flash devices, pedestrians, and pavement markings. A total of 2168driver observations were extracted. Only 33.3% of the drivers stopped before the stop line, 59% of the drivers passed the intersection through the yellow phase, and7% of the drivers committed RLR violations. The results showed that drivers were morelikely to stop before the stop line through the yellow phase at locations with RLR cameras, green light flash devices, pavement markings, where pedestrianswere present, and at a four-leg intersection. Chi-square tests indicated that all parameters had a significant impact on driver performance, except for the type of turning movement.

BackgroundIn 2017, smaller container ports handled approximately 22% of total containerized cargo. Nowadays liner operators are calling on those ports with larger ships and demanding fast and efficient turnaround of the ships in port. This is possible only if the berth has the right capacities, is working properly and achieves a good productivity level.MethodologyProductivity level does not depend only on the quay crane capacities but also the transfer mechanisation, of which the main function is to serve quay cranes on one side and yard cranes on the other side. Choosing the correct type and number of vehicles to transfer container units from berth to yard has become a very important decision in every container terminal.ResultsIn small container terminals yard trucks represents the most common type of transfer mechanization. That is why this research is based on the allocation of the right number of yard trucks to quay cranes in order to assure better productivity levels in the berth and yard subsystems. For this purpose, a discrete-event simulation modelling approach is used. The approach is applied to a hypothetical small container terminal, which includes operations on the berth-yard-berth relation.

The Signal Phase and Timing (SPaT) message is an important input for research and applications of Connected Vehicles (CVs). However, the actuated signal controllers are not able to directly give the SPaT information since the SPaT is influenced by both signal control logic and real-time traffic demand. This study elaborates an estimation method which is proposed according to the idea that an actuated signal controller would provide similar signal timing for similar traffic states. Thus, the quantitative description of traffic states is important. The traffic flow at each approaching lane has been compared to fluids. The state of fluids can be indicated by state parameters, e.g. speed or height, and its energy, which includes kinetic energy and potential energy. Similar to the fluids, this paper has proposed an energy model for traffic flow, and it has also added the queue length as an additional state parameter. Based on that, the traffic state of intersections can be descripted. Then, a pattern recognition algorithm was developed to identify the most similar historical states and also their corresponding SPaTs, whose average is the estimated SPaT of this second. The result shows that the average error is 3.1 seconds.

The present review paper provides a systematic insight into the studies published so far when it comes to the research on the cost and performance optimisation in the parcel delivery phase. Globalisation, as well as the new trends, such as selling online, directly influences the demands for the delivery of goods. Demand for the delivery of goods proportionally affects the transport prices. A great majority of deliveries is carried out in densely populated urban areas. In terms of costs, the greatest part in the courier organisations costs is observed in the technological phase of parcel delivery, which is at the same time the least efficient. For that reason, significant improvement of performance and cost optimisation in the very delivery phase is a rather challenging field for the researchers. New algorithm-based technologies, innovations in the logistics and outsourcing of individual technological phases are ways by means of which one strives to enhance the delivery efficiency, to improve performance and quality, but also - to optimise the costs in the last phase of delivery. The aim of the present paper is to offer a systematic review into the most recent research in the field of technology, innovations and outsourcing models with the aim of reducing the cost and enhancing the productivity and quality in parcel delivery.

Roundabouts are very useful when flows are balanced but can have operational challenges when flows increase. Most roundabouts on arterial roadways in Ghana experience recurring congestion during peak traffic. The four roundabouts between Ejisu Municipality and Asokwa Municipality on the N6 highway are typical of the situation found on arterials countrywide. They experience recurring long queues and delays during the peak hours and over-representation of truck rollover accidents. In Ghana, historically, most roundabouts with capacity problems have been developed into interchanges at very high cost without consideration of other effective at-grade configurations. When roundabouts are signalized, various configurations can be explored to enhance capacity while preserving the safety benefits. Using simulation techniques, various configurations and design options were tested for their effectiveness at two of the roundabouts, located at KNUST police station and Ejisu, with similar demand and high left turning volumes. The objectives of this study were to a) evaluate the performance of the selected roundabouts on the corridor; b) explore alternative intersection configurations to improve capacity and delay. Using video data collection techniques, 2-h time stamped footages of AM and PM peak traffic flows were captured for two days. Geometric design parameters of the existing roundabouts, queue lengths, travel times, and approach flows were also captured. VISSIM models of the selected roundabouts were developed and calibrated for the baseline conditions. Signalized unconventional roundabout configuration, with a phase for major road through traffic were simulated and assessed for capacity, delay and queue length. The results showed that signalized roundabout intersections effectively increased capacity by as much as 50% in some cases, reduced delay and queue length significantly, and maintained the benefits of roundabouts including safety. The performance could be further enhanced by introducing separate left turn phases to reduce conflicts or through a right turn U-turn (RTUT) concept.

Estimating safety effectiveness of roadway improvements and countermeasures, using cross-sectional models, generally requires large amounts of data such as road geometric and traffic-related characteristics at road segment levels. These models do not consider all confounding crash contributory factors such as driving culture and environmental conditions at the segment level due to a lack of readily available data. This may result in inaccurate models representing actual conditions at road segment levels, followed by erroneous estimations of safety effectiveness. To minimize the effect of not including such variables, this study develops a new methodology to estimate safety effectiveness of roadway countermeasures, based on generalized linear mixed models, assuming zero-inflated Poisson distribution for the response, and adjusting for spatial autocorrelation using the spatial random effect. The Bayesian approach, with Integrated Nested Laplace Approximation, was used to make inference on this model with computational efficiency. Results showed that incorporating a spatial random effect into the models provided better model fit than non-spatial models; hence, estimated safety effectiveness based on such models is more accurate. The proposed approach is a methodological advancement in traffic safety, which allows evaluation of safety effectiveness or roadway improvements when data are not readily available.

Highway agencies have been using many of the elements of asset management with the support of various decision-making tools. To determine the most effective investment strategy with scarce resources, the integration, and hence better utilization, of existing tools and practices across asset classes is generally lacking. This paper applies data envelopment analysis (DEA) to benchmark different highway investment scenarios using existing data or data readily available through existing models. Three asset types, pavements, bridges, and traffic signage, are investigated. Asset investment analysis results from the Highway Economic Requirements System State Version (HERS-ST) application, the PONTIS bridge management system software, and purpose-built traffic signage spreadsheet are obtained to capture the changes of performance measures under various budget scenarios and are further used as the inputs for the DEA process to benchmark investment scenarios for each individual asset. Subsequently, the performance measures and budget levels are assembled in the Asset Manager-NT software, whose results are input into DEA to benchmark cross-assets resource allocation scenarios. Planning for the management of highway network is addressed via case studies in a systematic manner that recognizes the tradeoffs among different funding periods and objectives such as preserving existing investments, safety, roughness and user costs. This study has established a preliminary implementable framework of highway asset management by linking DEA approach and current widely used decision-making tools for more efficient investments within and cross assets, and better understand of the tradeoffs, costs and consequences of various asset management decisions.

The ownership of motorised two wheelers (MTWs) has been on the rise across various countries across the globe. The growth has been especially higher in developing countries which have typical traffic characteristics and higher populations. This steady rise has resulted in increased accident and fatalities. This abrupt increase warranted attention from the researchers to carry out specific studies for MTWs, which have a very different behaviour as compared to cars in terms of physical and dynamic parameters. Moreover, the unique traffic patterns usually found in the developing countries pose an additional challenge to the researchers, since the conventional focus of transportation safety researchers was a homogeneous car-based traffic. Many such studies have been attempted, especially in the recent decades, which have considered various risk factors related to MTW safety. However, the studies have considered different sets of risk factors and have given surprising and even conflicting results. Therefore, a comprehensive review of the diverse studies needs to be carried out which incorporates all the risk factors considered in previous research. This study reviews such research papers which have analysed various risk factors related to safety of MTWs, especially in heterogeneous, non-lane based traffic. Specifically, this paper aims to incorporate results from those studies and highlight the conclusions from state of the art. The paper also discusses about the research gaps that are crucial for MTW safety in mixed traffic conditions. The review will be useful for researchers working in the field of MTW safety and for policy implementation and analysis.

At two-way stop controlled (TWSC) intersections drivers on minor stream are generally at risk because of the difficulty in judging safe gap between major stream vehicles. Any misjudgment by the driver while choosing gap may result in a collision with major stream vehicle. This paper provides important insights for determining and analyzing spatial critical gaps of drivers at high speed and medium speed TWSC intersections. The critical gap line (CGL) fitted for the accepted and rejected gaps using parametric (binary logit model-BLM) and non-parametric (support vector machines-SVM) techniques gives critical gap values at 15th, 50th and 85th percentile speeds. The evaluation of spatial critical gap with respect to major road vehicle (conflicting vehicle) speed makes it easier to understand the impact of variation in speed on spatial gaps accepted by the drivers on the minor road. The logit models developed revealed that the probability of accepting gap decreases with increase in the speed of the conflicting vehicle and it increases with increase in the distance of conflicting vehicle. The spatial critical gaps estimated using support vector machines were found in close approximation with those estimated using binary logit model. The study results showed that SVMs have very good potential to be an alternative tool for the estimation of driver's critical gap. The spatial critical gaps corresponding to 15th, 50th and 85th percentile speeds for medium speed intersections were 32 m, 38 m and 46 m respectively and for high speed intersections these values were 64 m, 76 m and 104 m respectively. The increase in the magnitude of gap value with respect to the percentile speed clearly states the effect of speed on spatial gaps. The insights from the study can be used to suggest various measures to improve the safety of crossing drivers at uncontrolled intersections.

The Urban Street Segment Chapter of the Highway Capacity Manual (HCM) includes a methodology for evaluating the level of service urban street segments provide to automobile users. The methodology does not account for pedestrian activity at un-signalized midblock crosswalk on an urban street segment. Pedestrian activity at un-signalized midblock crosswalk on urban street segments causes friction conditions between automobiles and pedestrians. As a consequence, the average time it takes vehicles to travel along the segment is increased. Increasing segment running time decreases both the travel speed of automobiles and the level of service provided to automobile users. There is an inverse relationship between the delay incurred by interrupted vehicles and the speeds at which pedestrians walk while crossing at midblock. To account for this delay, there is a need to investigate pedestrian walking speeds at un-signalized midblock crosswalks. This study measured pedestrian walking speeds by age-group at two un-signalized midblock crosswalks on urban street segments. The first objective of this paper is to perform statistical analyses to examine the measured free-flow pedestrian walking speeds. The second objective is to demonstrate how the findings of this study can be incorporated into the Urban Street Segment Analysis Chapter of the HCM. Pedestrian walking speeds were recorded and analyzed for 2937 pedestrians. The results show teenagers walk at an average speed of 1.45 m/s, young adults walk at an average speed of 1.55 m/s, middle age pedestrians walk at a speed of 1.45 m/s, older pedestrians walk at speed of 1.09 m/s, and elderly or physically disabled pedestrians walk at a speed of 1.04 m/s.

Short-term taxi demand forecasting is of great importance to incentivize vacant cars moving from over-supply regions to over-demand regions, which can minimize the wait time for passengers and drivers. With the consideration of spatiotemporal dependences, this study proposes a multi-task deep learning (MTDL) model to predict short-term taxi demand in multi-zone level. The nonlinear Granger causality test is applied to explore the causality relationships among various traffic zones, and long short-term memory (LSTM) is used as the core neural unit to construct the framework of the multi-task deep learning model. In addition, several hyperparameter optimization methods (e.g., grid search, random search, Bayesian optimization, hyperopt) are used to tune the model. Using the taxi trip data in New York City for validation, the multi-task deep learning model considering spatiotemporal dependences (MTDL∗) is compared with the single-task deep learning model (STDL), the full-connected multi-task deep learning model (MTDL#) and other benchmark algorithms (such as LSTM, support vector machine (SVM) and k-nearest neighbors (k-NN)). The experiment results show that the proposed MTDL model is promising to predict short-term taxi demand in multi-zone level, the nonlinear Granger causality analysis is able to capture the spatiotemporal correlations among various traffic zones, and the Bayesian optimization is superior to the other three methods, which verified the feasibility and adaptability of the proposed method.

The purpose of this paper is to provide a summary of a quick overview of the latest developments and unprecedented opportunities for scholars who want to set foot in the field of traditional taxi and online car-hailing (TTOC). From the perspectives of peoples (e.g., passenger, driver, and policymaker), vehicle, road, and environment, this paper describes the current research status of TTOC's big data in six hot topics, including the ridership factor, spatio-temporal distribution and travel behavior, cruising strategy and passenger service market partition, route planning, transportation emission and new-energy, and TTOC's data extensional application. These topics were included in five mainstreams as follows: (1) abundant studies often focus only on determinant analysis on given transportation (taxi, transit, online car-hailing); the exploration of ridership patterns for a multi-modal transportation mode is rare; furthermore, multiple aspects of factors were not considered synchronously in a wide time span; (2) travel behavior research mainly concentrates on the commuting trips and distribution patterns of various travel indices (e.g., distance, displacement, time); (3) the taxi driver-searching strategy can be divided into autopsychic cruising and system dispatching; (4) the spatio-temporal distribution character of TTOC's fuel consumption (FC) and greenhouse gas (GHG) emissions has become a hotspot recently, and there has been a recommendation for electric taxi (ET) in urban cities to decrease transportation congestion is proposed; and (5) based on TTOC and point of interest (POI) multi-source data, many machine learning algorithms were used to predict travel condition indices, land use, and travel behavior. Then, the main bottlenecks and research directions that can be explored in the future are discussed. We hope this result can provide an overview of current fundamental aspects of TTOC's utilization in the urban area.

In times of ever stronger awareness of environmental protection and potentiation of a beneficial modal split, the railway sector with efficient asset utilization and proper investment planning has the highest chance of meeting customer expectations and attracting new users more effectively. Continuous increase in railway demand leads to an increase in the utilization of railway infrastructure, and the inevitable lack of capacity, a burning problem that many national railways are continually facing. To address it more effectively, this paper reviews available methodologies for railway capacity determination and techniques for its enhancement in the recent scientific literature. Particular focus is given to the possibility of increasing railway capacity through signalling systems and installing the European Train Control System (ETCS). The most important relationships with segments of existing research have been identified, and in line with this, the directions for a potential continuation of research are suggested.

Autonomous Vehicles (AVs) have been designed to make changes in the travel behaviour of travellers. These changes can be interpreted using transport models and simulation tools. In this study, the daily activity plans were used to study the possibility of increasing the utility of travellers through minimizing the travel time by using AVs. Three groups of travellers were selected based on the benefits that they can obtain when AVs are on the market. The groups are (a) long-trip travellers (b) public transport riders, and (c) travellers with specified characteristics. Each group is divided into one or more scenarios based on the definition of each group and the collected data. A total of seven scenarios were derived from the collected data and simulated twice to include the existing transport modes and the presence of AVs. The simulations were conducted using Multi-Agents Transport Simulation (MATSim) that applies the concept of a co-evolutionary algorithm. MATSim simulates the current plans and the ones where AVs replace all or part of the existing conventional transport modes in the daily activity plans. The results have shown a reduction in the trip time: 13% to 42% for group (a), 33% for group (b), and 16% to 28% for group (c) compared with the original trip times. In conclusion, it can be claimed that AVs could reduce the travel time in all cases, which provides benefits for people to increase their utilities.

With the rapid development of urbanization in China, the number of travel modes and urban passenger transportation hubs has been increasing, gradually forming multi-level and multi-attribute transport hub networks in the cities. At the same time, Super Network Theory (SNT) has advantages in displaying the multi-layer transport hubs. The aim of this paper is to provide a new perspective to study connectivity contribution of potential hubs. Urban transport hubs are ranked through topological features based on Hub Super Network (HSN). This paper proposes two indexes based on Super-Edge (SE), Zero Hub Degree of SE (ZHDoSE) and a number of shared SEes (NSSE), respectively. Then, a case study was conducted in Beijing, which considers four combinations to study the influence of transport modes and subway lines on connectivity. The results show that no-normalization strengthens the contribution of transport modes and subway lines on connectivity. Besides, the transport mode contributes a lot to the connectivity. However, elements normalization strengthens the subway lines under ZHDoSE reciprocal. In addition, various weights of ZHDoSE and NSSE have different influences on the recognition results of SEes in HSN.

Under mixed traffic conditions prevailing on Indian roads, drivers show complex response when faced with yellow signal because lane assignment gets dynamic in nature. The present study analyzes the effect of surrounding vehicles on response of the drivers while facing dilemma at intersections. Although dilemma zone definitions hold true in case of homogeneous traffic mix, a statistical analysis is performed to check the consistency across the definitions under mixed traffic condition. Present study shows a significant difference in percentage of red light running in comparison to homogeneous traffic as reported by various studies. For carrying out the research, study locations are chosen in such a way to reflect diversity in road geometry, traffic composition and signal characteristics. The results deduced in this study indicate a strong correlation between the driver's decision making choice and the effect of presence of surrounding vehicle at the onset of yellow signal. The effect of critical time analysis has been found out to be one of the parameters other than critical distance in categorizing driver's aggressiveness while facing the yellow signal. In the process of identifying the statistical significance of dilemma zone definitions, it has been found that under heterogeneous traffic condition, drivers behave differently as compared to homogenous traffic when it comes to dilemma zone. It is observed that the percentage of vehicles crossing the intersection when faced with dilemma by violating the red light is 11.6% according to dilemma zone definition I whereas the definition II has yielded about 10.8% violation covering different vehicle types. The above violation figures derived based on the above definition is somewhat higher as compared to homogeneous traffic condition which is observed to be of the order of 5%–6%.

Introduction The COVID-19 emergency and the cities lockdown have had a strong impact on transport and mobility. In particular, travel demand has registered an unprecedented overall contraction, dramatically dropping down with peaks of - 90%-95% passengers for public transport (PT). During the re-opening phase, demand is gradually resuming the levels before the crisis, although some structural changes are observed in travel behaviour, and containment measures to reduce the risk of contagion are still being applied, affecting transport supply. Objective This paper aims at assessing to what extent keeping a one-meter interpersonal distancing on-board trains is sustainable for public transport companies. Method The analysis is based on travel demand forecasting models applied to two case-studies in Italy: a suburban railway line and a High-speed Rail (HSR) line, differentiated by demand characteristics (e.g. urban vs. ex-urban) and train access system (free access vs. reservation required). Results In the suburban case, the results show the need of new urban policies, not only limited to the transport domain, in order to manage the demand peaks at the stations and on-board vehicles. In the ex-urban case, the outputs suggest the need for public subsidies in order for the railways undertakings to cope with revenue losses and, at the same time, to maintain service quality levels.

In this article, we present an incentive mechanism for Vehicular Crowdsensing in the context of autonomous vehicles (AVs). In particular, we propose a solution to the problem of sensing coverage of regions located out of the AVs’ planned trajectories. We tackle this problem by dynamically modifying the AVs’ trajectories and collecting sensing samples from regions otherwise unreachable by originally planned routes. We model this problem as a non-cooperative game in which a set of AVs equipped with sensors are the players and their trajectories are the strategies. Thus, our solution corresponds to a model in which expected individual utility drives the mobility decision of participants. Using open-street maps, SUMO vehicular traffic simulator, and extensive simulations, we show our algorithm significantly outperforms traditional approaches for trajectory generation. In particular, our performance evaluation shows a significant lift in crowdsourcer coverage, road utilization, and average participant utility.

Background An intersection is an area with more energy consumption and emissions by motor vehicles, and the energy consumption and emissionsof vehicles at intersections should be reduced in road planning and traffic control to improve the urban traffic environment. Objectives In order to analyze the influence of signal timing on CO2 emission of traffic flow under the mixed traffic environment of fuel vehicles and electric vehicles. Methods A set of CO2 incremental emission models is established to estimate the CO2 emissions of fuel vehicles and electric vehicles at signalized intersections. Then, a signal timing model with minimum CO2 emissions is established, and the influence of signal timing with minimum CO2 emissions on vehicle control delay and stop rates under different traffic conditions is analyzed. Conclusions The case study shows that optimizing of the timing parameters of intersections from the perspective of vehicle CO2 emissions is different from the perspective of control delay or stop rate; the model’s timing optimization will effectively balance the CO2 emissions generated by vehicles during the acceleration, deceleration and idling stages, essentially achieving a comprehensive consideration of vehicle control delay and stop rates. When the road section speed and the mixed proportion of electric vehicles are low, the timing results tend to reduce the vehicle delay at intersections, but when the road section speed and the mixed proportion of electric vehicles are high, the timing results tend to reduce the vehicle stop rate.

As a rule, the road traffic volume distribution in particular hours on working days showscertain patterns on specific types of roads. Public holidays during the year cause disturbances and differences in the distribution of the daily traffic volume compared to working days. The road traffic volume distribution during the day is very important in the analysis of phenomena occurring in terms of road traffic. Knowledge of the values of traffic volumes during the day and their variability allows for the determination of a number of measures and parameters assessing traffic conditions prevailing on the elements of transport networks. Knowledge and understanding of changes in the distribution of traffic volume during a day are crucial for many aspects of transport engineering, such as road traffic control, road safety, and forecasting the traffic volume. Thisarticle evaluates the differences in the road traffic volume distributions during the day between public holidays and working days. The analysis was performed for selected intersections located in the city of Gliwice. The results of the statistical test show that on public holidays, there was less traffic volume compared to working days. The greatest decrease in the value of traffic volume occurred on 3rd May,25th, and 26th December. This decrease ranged from 27.24% to 35.67%. It can be noticed that for all analyzed intersections, the smallest differences in the values of traffic volumes between a public holiday and a working day occurred on 1st November. Additionally, the natureof the impact of public holidays on the road traffic volume on days before and afterpublic holidays was examined. The nonparametric hypothesis testing method was used to investigate changes in the road traffic volume patterns caused by public holidays. The results of Friedman's test show and confirm that there are differences in traffic volumes on the day before and after apublic holiday and an average day.

Background GPS-based cycling data are increasingly available for traffic planning these days. However, the recorded data often contain more information than simply bicycle trips. GPS tracks resulting from tracking while using other modes of transport than bike or long periods at working locations while people are still tracking are only some examples. Thus, collected bicycle GPS data need to be processed adequately to use them for transportation planning. Results The article presents a multi-level approach towards bicycle-specific data processing. The data processing model contains different steps of processing (data filtering, smoothing, trip segmentation, transport mode recognition, driving mode detection) to finally obtain a correct data set that contains bicycle trips, only. The validation reveals a sound accuracy of the model at its’ current state (82–88%).

Designation of places forpublic transport stopsis a key component of research on their accessibility. However, further research is needed to solve the problem with organization of public transport stops.This paper provides the results of an priori rankinganalysis aimed at defining the mostsignificant factors affecting the accessibility of stopsand their scope.The proposed mathematical model, which uses dimensional theory, consists of two stages: pedestrians’ movement to a stop and passengers’ trip to a transit stop. It is a theoretical premise that allows to determination ofplacement of public transportstops considering the main indicators,which are the distance covered by pedestrians and the speed of public transport.

It is shown that modern geometry cars, flaw detector cars and other track test cars provide reliable control of the technical condition of all hauls of the railroad track at “certain intervals of time”. Their number is limited and therefore “continuous monitoring” of all hauls is almost impossible. At the same time, in real life, due to the impact of various factors, such as seismic processes, certain changes take place even a day after control. The authors consider one option for continuous monitoringofthe beginning of changes in the technical condition of the track using intelligent tools, which allow one, by analyzing the useful signal and the noise from the soil vibrations caused by the rolling stock, to create informative attributes for identifying the technical condition of the track. The application of traditional technologies of correlation and spectral analysis and other methods for this purpose does not allow ensuring adequacy of the control results. This paper proposes a technology for extracting and analyzing useful vibration signals, the noise of vibration signals and the relationship between them. The estimates of both correlation and spectral characteristics of the useful signal and the noise are used as the main carriersof diagnostic information. Due to the simplicity and the reliability of implementation of the proposed technical tools, they can be easily installed in one of the cars of all rolling stocks, providing control of the beginning of changes in the technical condition of the track during their movement in all hauls.