The urban mobility is affected by global trends resulting in a growing passenger and freight transport demand. In order to improve the understanding of urban mobility in general, to evaluate mobility services and to quantify the overall transport system performance, it is necessary to assess urban mobility. Urban mobility assessment requires the application of methodology integrating different metrics and explicitly applying a multi-dimensional approach. Since scientific community does not define urban mobility in an unambiguous way, part of this paper is devoted to the analysis of the definition of urban mobility. This step enables better understanding of urban mobility in general, as well as understanding of the urban mobility assessment process. Usually, a three-layered approach that includes urban mobility data, indicators and indices is used for the assessment. Therefore, the aim of this paper was to perform extensive research in order to synthesize, define and organize the elements of those layers. The existing urban mobility indicators and indices have been developed for specific urban areas, taking into account local specifications, and they are not applicable in other cities. Also, the choice of urban mobility indicators is mainly related to the existence of data sources, which limits the objective and comparable assessment of the mobility of cities where such data do not exist.
With the aim of mitigating traffic oscillations, this paper extends a car-following model for Connected Cruise Control (CCC) systems by considering electronic throttle angles of multiple cars ahead. The linear stability condition of the proposed model is derived and numerical simulations are performed. It has been found that the proposed model is prominently better than the previous model, i.e. full velocity difference model, from the perspective of mitigating traffic oscillations. Additionally, the proposed model can also reduce fuel consumption, emissions, i.e. CO, HC and NOX, safety risk, and improve driving comfort at the same time. Simulation results suggest that the CCC car-following control design should consider the effect of multiple electronic throttle angles from the preceding cars.
Bike-and-Ride (B&R) has long been considered as an effective way to deal with urbanization-related issues such as traffic congestion, emissions, equality, etc. Although there are some studies focused on the B&R demand forecast, the influencing factors from previous studies have been excluded from those forecasting methods. To fill this gap, this paper proposes a new B&R demand forecast model considering the influencing factors as dynamic rather than fixed ones to reach higher forecasting accuracy. This model is tested in a theoretical network to validate the feasibility and effectiveness and the results show that the generalised cost does have an effect on the demand for the B&R system.
This paper focuses on converting the system optimum traffic assignment problem (SO-TAP) to system optimum fuzzy traffic assignment problem (SO-FTAP). The SO-TAP aims to minimize the total system travel time on road network between the specified origin and destination points. Link travel time is taken as a linear function of fuzzy link flow; thus each link travel time is constructed as a triangular fuzzy number. The objective function is expressed in terms of link flows and link travel times in a non-linear form while satisfying the flow conservation constraints. The parameters of the problem are path lengths, number of lanes, average speed of a vehicle, vehicle length, clearance, spacing, link capacity and free flow travel time. Considering a road network, the path lengths and number of lanes are taken as crisp numbers. The average speed of a vehicle and vehicle length are imprecise in nature, so these are taken as triangular fuzzy numbers. Since the remaining parameters, that are clearance, spacing, link capacity and free flow travel time are determined by the average speed of a vehicle and vehicle length, they will be triangular fuzzy numbers. Finally, the original SO-TAP is converted to a fuzzy quadratic programming (FQP) problem, and it is solved using an existing approach from literature. A numerical experiment is illustrated.
The motivation of this research is to explore the contributing factors of driving distraction and compare the contributing factors for three typical distracted driving behaviours: drinking water, answering a phone and using mobile phone application (APP) while driving. An online survey including a driving behaviour scale and the Theory of Planned Behaviour Questionnaire (TPB Questionnaire) was conducted to obtain data related to these driving distractions. An integral structural equation model based on the Theory of Planned Behaviour (TPB) was established to explain the factors causing three typical distracted behaviours, and the causes of differences for three typical distracted behaviours were compared. The result shows that the attitudes and perceived behaviour control are the main factors causing distracted behaviours, and the subjective norm has a significant impact on answering a phone while driving. The occurrence of a distracted driving behaviour is the consequence of behaviour intention and perceived behaviour control. These conclusions provide insights for implementing behaviour modification and traffic laws education.
This paper focuses on predicting injury severity of a driver or rider by applying multi-layer perceptron (MLP), support vector machine (SVM), and a hybrid MLP-SVM method. By correlating the injury severity results and the influences that support their creation, this study was able to determine the key influences affecting the injury severity. The result indicated that the vehicle type, vehicle manoeuvre, lack of necessary crossing facilities for cyclists, 1st point of impact, and junction actions had a greater effect on the likelihood of injury severity. Following this indication, by maximising the prediction accuracies, a comparison between the models was made through exerting the most sensitive predictors in order to evaluate the models’ performance against each other. The outcomes specified that the proposed hybrid model achieved a significant improvement in terms of prediction accuracy compared with other models.
The Balkan region has an important geostrategic position in passenger and freight transport between Europe and Asia. This paper studies the development of railway transport on twelve different railway transport markets in the Balkan region. The methodology is based on multi-criteria assessment of the level of railway development. The approach presented in this paper could help railway companies to make decisions about railway transport services. The methodology includes three steps. In the first step, the quantitative and qualitative criteria for the evaluation of the social, economic, infrastructural and technological impact of the level of development of railway transport have been defined. In the second step, the weights of criteria have been determined using both objective and subjective approaches by applying the Shannon Entropy method and the Stepwise Weight Assessment Ratio Analysis (SWARA) method. The third step presents the ranking of the countries by applying three multi-criteria methods – VIse Kriterijumska Optimizacija i kompromisno Resenje (VIKOR), Weighted Aggregated Sum Product Assessment (WASPAS) and Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), which are different in their approaches. The results show that the criteria: maximum train technical speed (13%), ERTMS Level (10%), number of train kilometres per year (9%) and Ro-La intermodal service (9%) have a great importance in the ranking. It was found that the most developed railway transports in the Balkan region are Turkey, Croatia, Slovenia, and Romania.
From the regional development point of view new investments are always of great importance as they are mainly expected to boost the regional economy and thus improve the living standard of inhabitants. Also for the literature purposes a new case study on the impact of investments on regional development can be perceived as an added value to the state of the art and thus worthy to be explored. In this research the impact is measured in the following aspects: social, economic, innovation, and environmental, which stand also for the main assessment criteria. Just recently, an opportunity has appeared to explore this subject on the Pomeranian Metropolitan Railway (PMR), which started its operations on 1st September 2015, after five years of construction works and more than a 100-year long history. Thus, the paper presents the impact results of PMR on the development of the Pomeranian region, in the form of qualitative as well as quantitative assessments in the four aspects and on different levels of detail. The final conclusion states that the impact of PMR on the regional development has appeared to be negative in 33% and positive in 67%.
Pedestrian crossing speed is the key element in the design of pedestrian facilities. It depends on various attributes related to road, traffic and pedestrians. In this paper, an attempt has been made to explore the variation, examine the influencing factors and formulate a model for the pedestrian crossing speed at signalised intersection crosswalks. The data have been collected using video graphic technique at 16 signalised crosswalks of the Chandigarh city. The findings reveal that a 15th percentile crossing speed (1.11-1.31 m/s) exceeds the design crossing speed of 0.95 m/s. It is also higher than the crossing speed of 1.2 m/s, usually being prescribed and adopted in the developed countries. The statistical analysis indicates no significant difference in the percentile crossing speeds between males and females. However, the variation exists among different age groups, group sizes, and crossing patterns. The correlation analysis depicts that the pedestrian crossing speed has significant negative correlation with the crosswalk width, the crosswalk length, the width of the pedestrian island, the classification of road, average traffic flow and average pedestrian delay, whereas the availability of separate bicycle paths at intersections is positively correlated. Furthermore, the stepwise regression model with 70.1 percent accuracy reveals that the crosswalk width, the width of the pedestrian island and the average pedestrian delay play a predominant role in determining the pedestrian crossing speed. The authors propose the usage of the developed model for setting out the standards for the appropriate design crossing speed for different crosswalks having similar geometric and traffic conditions as that of the study area.
High-speed railway (HSR) network building was initiated in China in the early 2000s, and full-scale construction began several years later as a larger use phase started in 2008. Thereafter, the expansion speed has been impressive. Network investment could be considered as a success, if evaluating the amount of high-speed railway usage already during the expansion phase. The diffusion models built in this research show that expansion in the network and growth of the passengers will continue at least until the following decade. The performance is evaluated in terms of DEA efficiency model. It is shown that efficiency started from very low levels, but it has been increasing together with the expansion of HSR network. Currently, the efficiency is near the level of the leading European High-speed (HS) countries (Germany and France). However, it is projected with linear model and by Bass diffusion models that the efficiency will reach Japanese and South Korean standards in the next decade. A somewhat larger network length with smaller relative growth of passengers, but with a higher growth of passenger-km seems to be able to reach even the frontier efficiency.
Most of the microscopic traffic simulation programs used today incorporate car-following and lane-change models to simulate driving behaviour across a given area. The main goal of this study has been to develop an automatic calibration process for the parameters of driving behaviour models using metaheuristic algorithms. Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and a combination of GA and PSO (i.e. hybrid GAPSO and hybrid PSOGA) were used during the optimization stage. In order to verify our proposed methodology, a suitable study area with high bus volume on-ramp from the O-1 Highway in Istanbul has been modelled in VISSIM. Traffic data have been gathered through detectors. The calibration procedure has been coded using MATLAB and implemented via the VISSIM-MATLAB COM interface. Using the proposed methodology, the results of the calibrated model showed that hybrid GAPSO and hybrid PSOGA techniques outperformed the GA-only and PSO-only techniques during the calibration process. Thus, both are recommended for use in the calibration of microsimulation traffic models, rather than GA-only and PSO-only techniques.
More than 13.7 million people in Taiwan are scooter users, which signifies the highest density of scooter users in the world. The aim of the present study is to use the user experience (UX) evaluation methods to investigate the factors that influence the users’ satisfaction, recommendation intention, and willingness to accommodate Electric two-wheelers (E2Ws). An online survey design has been used to recruit two-wheeler owners who live in Taiwan. The results of the hierarchical multiple regression analysis, based on a sample of 315 Taiwanese, indicate that the variables of satisfaction, positive emotions, and riding experience predicted whether users intended to recommend a two-wheeler. The results also reveal that external motivation is the core factor that influences a rider’s willingness to purchase an E2W. It highlights the importance of providing opportunities for people to experience the advantages of E2Ws and services. Having good hedonic and pragmatic experiences accumulated during two-wheeler usage may further positively influence the users’ satisfaction and intrinsic motivation. It is recommended that the government and the related industries consider the above issues when formulating related policies or developing E2W or battery technologies.
In order to satisfy the requirements of International Civil Aviation Organization (ICAO) for aircraft taxi route planning in Advanced Surface Movement Guidance and Control System (A-SMGCS), an airport surface operation modelling and simulation approach based on timed and coloured Petri net is presented. According to the layout of the airport surface and the features of surface operation units, a static Petri net model of the airport surface is established. On this basis, in line with the requirements on the aircraft taxiing velocity in ICAO DOC 9830, the dynamic Petri net model of the airport surface operation is established by adding the time attribute to the static model. Additionally, the method of defining the capacity of airport operation unit place is proposed and the constraints of the airport surface operation are incorporated using Petri net elements. Unlike other papers in the field, the airport surface Petri net model established in this paper can simulate conflict-free taxiing using a Petri net simulator without relying on other model-independent algorithms. Based on the CPN Tools software, taking Toulouse Airport as an example, the validity of the model has been verified by comparing the model running data with real flight data.
Providing a satisfying delivery service is an important way to maintain the customers’ loyalty and further expand profits for manufacturers and logistics providers. Considering customers’ preferences for time windows, a bi-objective time window assignment vehicle routing problem has been introduced to maximize the total customers’ satisfaction level for assigned time windows and minimize the expected delivery cost. The paper designs a hybrid multi-objective genetic algorithm for the problem that incorporates modified stochastic nearest neighbour and insertion-based local search. Computational results show the positive effect of the hybridization and satisfactory performance of the metaheuristics. Moreover, the impacts of three characteristics are analysed including customer distribution, the number of preferred time windows per customer and customers’ preference type for time windows. Finally, one of its extended problems, the bi-objective time window assignment vehicle routing problem with time-dependent travel times has been primarily studied.
In order to improve the transfers inside an Urban Rail Transit (URT) station between different rail transit lines, this research newly develops two Ordinal Logistic Regression (OLR) models to explore effective ways for saving the Perceived Transfer Time (PTT) of URT passengers, taking into account the difficulty of improving the transfer infrastructure. It is validated that the new OLR models are able to rationally explain probabilistically the correlations between PTT and its determinants. Moreover, the modelling analyses in this work have found that PTT will be effectively decreased if the severe transfer walking congestion is released to be acceptable. Furthermore, the congestion on the platform should be completely eliminated for the evident reduction of PTT. In addition, decreasing the actual transfer waiting time of the URT passengers to less than 5 minutes will obviously decrease PTT.
As part of an overall traffic signalling system, traffic signs warn the traffic participants, give information about the restrictions, prohibitions and obligations and provide additional information needed for a safe and undisturbed traffic flow. The traffic sign quality is expressed by its retroreflection and it is particularly pronounced in conditions of reduced visibility. The aim of this paper is to analyse how traffic signs quality affects the frequency of traffic accidents in low visibility conditions. For this purpose, traffic accidents and the quality of traffic signs were analysed on 130 state roads in the Republic of Croatia between 2013 and 2015. In the analysis several variables were used: the number of traffic accidents occurred under reduced visibility conditions, length of the road, AADT (Annual Average Daily Traffic) and the number of traffic signs that do not meet the minimum prescribed values of retroreflection. Statistical analysis showed a positive correlation between the accidents and unsatisfactory traffic signs, i.e. that with the increase in the number of traffic sings that do not have a satisfactory level of retroreflection, an increase in the number of accidents in reduced visibility conditions is expected.
Choosing an optimal bunkering port that minimises the increase in the operating costs in a hub and spoke system is a multi-criteria decision-making (MCDM) problem. Furthermore, the criteria are related to the port particularities, the environment, fuel price, and some criteria are quantitative while others are qualitative. It is therefore necessary to create a model that takes such features into consideration. Firstly, in this paper a set of the most used criteria will be defined. Then, a method to choose suitable criteria for a hub and spoke system will be proposed. Secondly, using a Fuzzy AHP, weights will be defined and used in a multi-criteria goal function. The outcome is a bunkering policy MCDM model based on the aggregation of fuel consumption and price to criteria related to port characteristics, local aspects and service particularities. All these factors must be considered by a chief engineer (superintendent) in the process of defining a sustainable bunker policy. A case study based on the North Adriatic port system demonstrates the applicability of the proposed model. In addition, the case study highlights that in hub and spoke systems with short loops, feeder ships can regulate cargo capacity and stay at a port with bunkering policy planning.
The aim of the system with reservations is to reduce the time the user needs to reach the parking space as well as to rationalize the controlling of demands in the central business districts. When applying the system with reservations, it is necessary to know the user’s travel time to the parking space, as well as the time of parking. The sum of these two periods represents the parking space “occupancy”. The purpose of this paper is to suggest a model for determining the total occupancy of a parking space based on 1) the user’s travel time to the parking space; 2) the user’s duration of parking. Considering the fact that we are dealing with values which cannot be exactly estimated, the fuzzy logic system (FLS) is used. A Neural Network (NN) is trained on the basis of data about the estimated values of the input parameters and the real value of output parameters. Thus, a hybrid model of fuzzy logic and neural networks (ANFIS) is obtained. Finally, there is an example based on the real data which shows the application possibilities of this model.
The paper introduces a framework to perform the demand management and route planning tasks of a highly developed transport system managing scheme, assuming an autonomous transport system. Two types of autonomous transport system managing models have been introduced. In case of the first model, the assigned number of trips is assumed to be the modified variable related to the optimization problem. In case of the second model, the decision process is directly influenced by the travel prices defined by the optimization method. These approaches represent different demand management strategies. The first model aims to directly assign the incoming user demands to the system, while the second procedure lets the users make the decision. However, in the second case the system can strongly influence the users’ choices through the values of the travel prices. Accordingly, it seems to be a reasonable assumption that the firstly presented model has significantly higher efficiency in distributing the load on the network. On the other hand, the method of the second model would be much more tolerable and acceptable from a social point of view. Therefore, the aim of the paper is to introduce the developed models and to compare their efficiencies.
The paper presents the methodology for the risk analysis of the road transport of dangerous goods. The risk analysis includes the societal risk for communities living or staying within a radius of six kilometres from all national roads in Poland. The GIS software was employed to make this analysis. The prepared matrix has included the product of the likelihood of a road accident involving explosive dangerous goods and the consequences for communities living in the abovementioned area. The likelihood analysis was developed for explosive and toxic dangerous goods. The consequence analysis was based on the population density, according to which a respective number of people was assigned to each building, depending on the time of day (daytime, nighttime). Each stage of the analysis was presented in the form of a map. In total, two variants of the likelihood analysis, four variants of the consequence analysis and four variants of risk analysis have been developed. All analyses have been developed for the entire country.
The aim of this paper is to identify what attitudes towards safety performance indicators influence the attitudes towards successfulness of ISM Code implementation among contemporary seafarers. Secondly, the goal of the research was to obtain insight into the seafarer’s attitudes towards the current state of ISM implementation and safety performance. Consequently, a sample of N=330 seafarers was examined regarding their attitudes towards safety performance variables and ISM Code implementation. By using multiple regression analysis it was concluded that well designed and structured safety rules and procedures, positive work environment and adequate communication can make significant contributions to seafarers’ attitudes towards ISM implementation.
Ride-hailing, in addition to a common mode of daily transportation, is an attractive option for evacuating stranded passengers and supplementing bus bridging in the early stages of an urban rail transit (URT) disruption. This paper proposes a service supply chain comprised of ride-hailing vehicles, ride-hailing platforms, and stranded passengers wherein the URT and ride-hailing chain together provide emergency evacuation services. The emergency evacuation service supply chain can be coordinated under an effort-based revenue sharing contract. A URT-dominated Stackelberg game model between the URT and ride-hailing platform is then formulated to optimize compensation decisions on the part of the URT; numerical analysis reveals critical factors affecting the said decisions. The main contributions of this paper are two-fold: first, it provides new information regarding collaboration between URT operators and ride-hailing platforms for stranded passenger evacuation, including a ride-hailing platform pricing strategy; and second, the URT compensation decision process is solved via Stackelberg game model while revealing an incentive coefficient parameter for the URT decision and solver.
Air traffic complexity is usually defined as difficulty of monitoring and managing a specific air traffic situation. Since it is a psychological construct, best measure of complexity is that given by air traffic controllers. However, there is a need to make a method for complexity estimation which can be used without constant controller input. So far, mostly linear models were used. Here, the possibility of using artificial neural networks for complexity estimation is explored. Genetic algorithm has been used to search for the best artificial neural network configuration. The conclusion is that the artificial neural networks perform as well as linear models and that the remaining error in complexity estimation can only be explained as inter-rater or intra-rater unreliability. One advantage of artificial neural networks in comparison to linear models is that the data do not have to be filtered based on the concept of operations (conventional vs. trajectory-based).
This paper analyses changes of berth infrastructure and suprastructure by global container terminals (CTs) and by four eastern Adriatic ports in the last decade. The emphasis is on understanding whether CTs at Koper, Trieste, Rijeka and Bar achieved higher berth utilisation and productivity per ship-to-shore (STS) crane and if so, how and whether their development is in line with the global trend in CT berth productivity. On this basis a comparison model of twenty selected global CTs is used for productivity comparison as a first step in the process of analysing subsystem productivity. The study shows that four eastern Adriatic ports made different decisions, but with the same goals in reaction to the increased flow of containers via the Adriatic Sea transport route. Their main goal was to increase berth productivity by controlling the eventual subsystem overcapacity. According to observations, the Port of Koper is running at the subsystem’s upper level, while CTs in Trieste, Rijeka and Bar operate with certain degree of berth infrastructural, and suprastructural overcapacity.
Fuel savings are a significant aspect for evaluating the current and future technologies of civil aviation. Continuous-Descent Approach (CDA), as a representative of new concepts, requires a method for evaluating its fuel benefits. However, because of unavailability of the practical operational data, it is difficult to validate whether the previous fuel consumption mechanisms are suitable. This paper presents a unique method for quantifying potential fuel benefits. This permits an easy evaluation for the new procedures without modelling before implementing field tests. The proposed method is detailed in this paper. It derives from the inherent mechanical characteristic of aircraft engine, and utilizes historical flight data, rather than modelling, to predict fuel flow rates by matching flight conditions from Quick Access Recorder (QAR) data. The result has been shown to predict fuel consumption for conventional descent with the deviation of ±0.73%. To validate such method, a case study for our designed CDA procedure is presented. Fuel consumptions in baseline scenarios are estimated to analyse the variable impacts on fuel consumption. The estimated fuel benefits are consistent with the results in the previous field tests. This analysis helps support Air Traffic Management decisions on eventual field test by reducing the validation time and cost.
The phenomenon of affordable housing emerges in Chinese cities to meet low-income residents’ living needs in the city. Because affordable housing projects tend to be located far away from the city centre, their residents tend to face long commuting times to go to work. Although several studies have analysed commuting travel times, none have considered the commuting pattern of residents living in these affordable housing projects. This study employs a decision tree classifier to examine the commuting time patterns of affordable housing residents, fusing the data from the 2010 Nanjing Household Travel Survey and supplementary data collected through Google maps. Results show that attributes of the built environment and distance to work are the factors mostly influencing commuting time patterns of affordable housing residents in Nanjing. The availability of a subway service, job type, household car ownership, job location, travel mode choice, and departure time have logical but varying effects on commuting trip duration. These results provide a better understanding of these residents’ commuting patterns and provide urban planners insights about the effects of their affordable housing policies on travel behaviour.
Driving speed remains within the most important factors in road safety, and speed not only affects the severity of a crash but is also related to the risk of being involved in a crash. Inappropriate speed is responsible for more than a third of all fatal accidents occurring on roads. In Poland the problem of speeding drivers is widely present. Hence, effective speed management and enforcement of speed limits on existing roads plays an important role. Possible solutions for rural roads are very limited and are focused mainly on administrative speed limitations and speed cameras enforcement. However, due to their limited effectiveness new solutions are still being sought. High expectations are associated with the automatic section speed control system that has recently been introduced in Poland. The aim of this paper is to examine the efficiency of the automatic section speed control system on the basis of speed surveys collected on chosen national roads where the system for sectional speed control was first implemented. Conducted comparisons and statistical analyses included driver’s average speed, speed percentiles, the number of speeding drivers as well as speed heterogeneity. To evaluate the efficacy of the sectional speed system, speed measurements were also conducted on fourteen, similar in geometry and functional characteristics, reference national roads located in Podlaskie voivodship in Poland without any specific speed enforcement.
Design of curves and their adjacent elements presents the greatest safety problem on rural two-lane roads. The use of the existing alignment consistency safety criteria (design, operating speed, and driving dynamic consistency) could have some shortcomings, especially in countries where the project or design speed is in use instead of (higher) operating speed. The consequence is that the designer should use smaller cross fall on curves than needed, while the calculated side friction is lower than in reality. Further, the existing graphs of adjacent curve radii do not take into account that there is a maximum operating speed achieved for a certain radius or long tangent above which it does not increase. This paper presents a methodology for determination of adjacent horizontal curve radii, with and without tangent between, based on the operating speed models which include dependence of operating speeds on tangents and curves on speed of adjacent alignment elements as well as maximum tangent and curve speed. The developed graphs of adjacent radii at the same time include the limiting values of driving dynamic consistency criteria, so the road designer does not need to calculate permissible and demand side friction for every combination of adjacent alignment elements.
The availability of information and communication (IC) resources is a growing problem caused by the increase in the number of users, IC services, and the capacity constraints. IC resources need to be available to legitimate users at the required time. The availability is of crucial importance in IC environments such as smart city, autonomous vehicle, or critical infrastructure management systems. In the mentioned and similar environments the unavailability of resources can also have negative consequences on people's safety. The distributed denial of service (DDoS) attacks and traffic that such attacks generate, represent a growing problem in the last decade. Their goal is to disable access to the resources for legitimate users. This paper analyses the trends of such traffic which indicates the importance of its detection methods research. The paper also provides an overview of the currently used approaches used in detection system and model development. Based on the analysis of the previous research, the disadvantages of the used approaches have been identified which opens the space and gives the direction for future research. Besides the mentioned this paper highlights a DDoS traffic generated through Internet of things (IoT) devices as an evolving threat that needs to be taken into consideration in the future studies.
In recent years, high-speed maglev systems have received renewed attention once again. However, a systematic and transparent approach to evaluate high-speed maglev projects does not currently exist, which could be an obstacle for their application, even with technical success. In Germany, the Standardised Evaluation is applied as a basis for decision making regarding the public funding of projects. It should be implemented for all investments of urban public transport projects with a value of more than € 25 million. In this paper, the economic evaluation for the Shanghai-Hangzhou maglev project is carried out with the Standardised Evaluation. One of the most important contributions of this work is to demonstrate the applicability of Standardised Evaluation for high-speed maglev projects. With the Standardised Evaluation, the evidence of macroand microeconomic benefit can be presented in a transparent and systematic way. The result can be used to prove the project’s profitability and to rank different projects or project alternatives.
This paper considers vehicle dispatching for a flexible transit system providing doorstep services from a terminal. The problem is tackled with an easy-to-implement threshold policy, where an available vehicle is dispatched when the number of boarded passengers reaches or exceeds a certain threshold. A simulation-based approach is applied to find the threshold that minimizes the expected system-wide cost. Results show that the optimal threshold is a function of demand, which is commonly stochastic and time-varying. Consequently, the dispatching threshold should be adjusted for different times of the day. In addition, the simulation-based approach is used to simultaneously adjust dispatching threshold and fleet size. The proposed approach is the first work to analyse threshold dispatching policy. It could be used to help improve efficiency of flexible transit systems, and thereby make this sustainable travel mode more economical and appealing to users.
Bicycle is one of the main factors that affects the traffic safety and capacity on pedestrian-bicycle mixed traffic sections. It is important for implementing the warning of bicycle safety and improving the active safety to identify the cyclists’ intention in the mixed traffic environments under the condition of the “Internet of Things”. The phase-field coupling theory has been developed in this paper to comprehensively analyse the generation, spring up, increase, transfer, regression and reduction method of the traffic phase. The adaptive genetic algorithm based on the information entropy has been used to extract feature vectors of different types of cyclists for intention identification from the reduced pedestrian-bicycle traffic phase, and the theory of evidence has been provided here to build the identification model. The experimental verification shows that the extraction method of cyclists’ intention feature vector and identification model are scientific and reasonable. The theoretical basis can be applied to establishing the pedestrian-bicycle interactive security system.
This paper presents a centralized approach for establishing end-to-end communication services via management agents. The main proposal is the modular architecture of the third-party based Service Establishment Agent (SEA). The SEA manages inter-provider service negotiation process with per-domain management agents through an appropriate signaling agent. It also receives and interprets end-toend service requests, selects inter-domain paths, performs mapping of service classes among domains on the path, and evaluates conformance of the offered service level with the required one. It allows implementation of different algorithms for the aforementioned functions as well as their selection and combination according to the predefined management policies. Simulation results show that the proposed model significantly outperforms the distributed model in terms of service negotiation times. In the prototype development process, a policy-based solution for mapping of service classes was implemented. The performance evaluation shows that processing requirements for handling multiple service requests are modest, while benefit of the SEA approach is the lack of need to build long-term consensus among providers about technical choices for achieving network interconnection. The SEA architecture is completely independent of the quality of service mechanisms available in particular domains.
This paper evaluates and quantifies the adverse impact of traffic-induced vibrations on the structural systems of residential buildings and their occupants. To do this, İstanbul, one of the world’s most populous and traffic-congested cities, was selected as a case study. Firstly, a survey was conducted on 100 occupants of six neighbourhoods to understand human perception of vibrations and the physical condition of typical buildings. Then, train-induced ground vibrations were measured near a busy railway. Using the survey data and the measured train vibrations, time-history analyses were applied to five typical residential buildings. The results showed that there is a considerable contribution of higher modes to overall building response. Peak particle velocities calculated on the buildings are predominantly intolerable. Critically, 95% of the occupants would like authorities to reorganize traffic regulations to reduce the effects of this global problem. Therefore, human response to traffic-induced vibrations should be consideration of serviceability limit state and site-specific analysis should be incorporated into the codes of practice.
Fuel consumption of marine vessels plays an important role in both generating air pollution and ship operational expenses where the global environmental concerns toward air pollution and economics of shipping operation are being increased. In order to optimize ship fuel consumption, the fuel consumption prediction for her envisaged voyage is to be known. To predict fuel consumption of a ship, noon report (NR) data are available source to be analysed by different techniques. Because of the possible human error attributed to the method of NR data collection, it involves risk of possible inaccuracy. Therefore, in this study, to acquire pure valid data, the NR raw data of two very large crude carriers (VLCCs) composed with their respective Automatic Identification System (AIS) satellite data. Then, well-known models i.e. K-Mean, Self-Organizing Map (SOM), Outlier Score Base (OSB) and Histogram of Outlier Score Base (HSOB) methods are applied to the collected tankers NR during a year. The new enriched data derived are compared to the raw NR to distinguish the most fitted methodology of accruing pure valid data. Expected value and root mean square methods are applied to evaluate the accuracy of the methodologies. It is concluded that measured expected value and root mean square for HOSB are indicating high coherence with the harmony of the primary NR data.
Electric bicycles are one of the essential traffic modes in many cities in China. Due to the consideration on safety and efficiency of the urban transportation systems, it is recognized that the use of electric bicycles should be limited by shifting the demand towards public transit by imposing parking charges on electric bicycles. To plan for this, the travellers’ acceptance of parking charges must be taken into account. This paper proposes an acceptable threshold Logit model based on the non-compensation theory to calculate the threshold of the parking charge of electric bicycles. Electric bicycle trips are categorized into seven groups in terms of travel distances. The parking charges are of four discrete levels, from 0, 1, 2 to 3 yuan. Based on the survey data in the city of Handan, the traditional and acceptable threshold Nest-Logit models with the distance intervals and charges have been established and calibrated. Model calibration results show that the acceptable threshold Nest-Logit model is more accurate than the traditional Nest-Logit model, and the parking charge thresholds do exist. Specifically, within 3 km and outside 3 km the parking charge threshold is 1 yuan and 2 yuan, respectively. The parking charge thresholds can help in decision-making for parking pricing of electric bicycles.
In the paper, the public transportation line planning means planning of routes and frequencies of vehicles on them. In the world literature, different criteria are used in this context; mainly the variable costs of lines, the fixed costs of lines, the fixed plus variable costs of lines, the number of direct travellers, the total or average riding time and the total or average travelling time. The current paper adds two more: the total number of used vehicles (to be minimized when all passengers are transported) and relative excess of supply over demand (to be maximized without exceeding the number of available vehicles). Basic mathematical models for both cases are presented and the motivation of such approach is described including a brief excursion into the history of the Czech and Slovak research of line planning where the use of these objectives has arisen. Further, the basic models were modified for the cases of fourteen special practical requirements, e.g. heterogeneous vehicle fleet (= rolling stock), limitation of transfers, elastic demand, limited total number of lines, etc. The brief outline of the experience with practical use is added as well.
Railway is a critical application; hence, all systems that compose the railway infrastructure must meet two conditions: availability and safety. The availability ensures continuous operation of the system; on the other hand, safety is achieved when the device works properly regardless of the environmental or operating conditions. In addition, Wireless Sensor Networks (WSN) are used to perform tasks previously performed manually. However, it is necessary to analyse what protocol is appropriate for the railway industry, since availability and safety are the required attributes. In this work, a recently proposed routing protocol, the Multi-Parent Hierarchical (MPH), has been compared with a well-known protocol, the Ad-hoc On-Demand Distance Vector (AODV), in order to find the most suitable one for the railway applications. For this purpose, a simulator has been developed, which faithfully reifies the workings of a given protocol, considering a fixed, reconfigurable ad-hoc network given by the number and location of participants, and general network conditions.
Traffic accidents represent a social, health and political challenge in every country. Urban environments are characterized by intense traffic flows on the network, where different conditions resulting in interactions between motorised and non-motorised transport constantly occur, potentially increasing the risk of accidents. Although road accidents are considered as random events in space and time, a highly detailed analysis may establish correlations between road accidents and external factors (road infrastructure, traffic conditions, weather conditions, land use). This paper considers the impact of external factors on road accidents involving pedestrians in the City of Zagreb, which required an analysis of accident blackspots. The research conducted in this paper puts an emphasis on relations between external factors and accident blackspots involving pedestrians. The results can be used in planning pedestrian infrastructure and improving road safety.
The paper investigated the extent to which rainfall influences the quality of service delivery at multilane roundabouts using a novel quality of service approach. Quality of service is defined as how well roundabouts operate based on road users and road providers’ perception of service quality. Delay and reserve capacity were used respectively as proxies for road users and road providers’ perception of service quality. The entry and circulating traffic data were recorded continuously for eight weeks under dry, light, moderate, and heavy rainfall weather conditions at each surveyed roundabout, then collated, analysed and compared. Linear regression with dummy variable was used to model the roundabout entry capacity and a corrector factor was added to modify the regression function. The corrector factor considered different entry radii and entry angles of surveyed roundabouts. Multi-criteria quality of service table with travel time as proxy for road users and speed as proxy for road providers’ perception of service delivery was developed from peak traffic data and used to determine the extent of deterioration. The multi-criteria table introduced in the paper is a clear departure from the speed-based criteria used in many studies. The results show a significant increase in time delay and a decrease in reserve capacity relative to rainfall. The paper has concluded that rainfall has an anomalous negative effect on the quality of service at multilane roundabouts. The findings could be used in a variety of ways in traffic management to predict the travel time at roundabouts under rainy conditions and to prescribe speed limits accordingly.
Over the past decade regulatory emission control has been adopted and even stricter emission reductions are being considered. In order to comply with the present and future regulations the ship owners and engine manufacturers are facing a difficult task. The shipping industry is presently offering multiple choices such as scrubbers and Selective Catalytic Reduction (SCR), dual fuel engines, Liquefied Natural Gas / Liquefied Petroleum Gas (LNG/LPG) powered engines, and lately the introduction of methanol and ethanol as alternative fuels. This work presents a short overview of the possible use of methanol and ethanol as lternative fuels in shipping. The first part of this work deals with physical properties of methanol and ethanol, production and availability, as well as advantages and disadvantages in comparison with other fuels. In the second part the cost perspective is presented together with the cost-benefit analysis, which is the most important aspect in the ship owner’s decision whether to invest into the new alternative. Methanol and ethanol are not magical solutions, but rather another alternative which, from the cost perspective, offers a potential under certain circumstances. These circumstances are competitive prices in comparison to Marine Gas Oil (MGO) and time spent in Emission Control Area (ECA) which should be a large portion of the total sailing time. In this paper the scientific methodology was followed by using the method of compilation, the descriptive and the comparative methods.
There is a small number of empirical modelling study cases available that are related to the calculation of variant solutions efficiency from the aspect of sustainable mobility in the urban areas. In practice, it is often necessary - especially when it comes to the urban transport network - to evaluate the solutions for traffic flow organisation and routing, in order to implement the one(s) with the maximum potential to reduce the possibility of congestion during peak travelling periods i.e. during transport network peak load. The paper presents an approach to the aforementioned problem by the application of the transport system efficiency analysis. The aspect of traffic flow organisation and routing efficiency in variant solutions is clarified through the analysis model development, built on the premises of Data Envelopment Analysis (DEA) method and the principles of unnecessary traffic flow intersections (TFI) theory. The proposed model defines the efficiency limit for data attributed to variant solutions, based on the calculation of the optimal TFI model and the possibilities of DEA method that include comparison and definition of relative routing efficiency for every optional traffic flow against the efficiency limit (optimal model) in order to calculate relative efficiency in relation to other solutions.
The use of seat belts, for drivers and car occupants, results in reducing the rate of fatalities and severe road injuries. In this research, the methodology of the survey was applied through the self-reporting behaviour of the respondents who determined the subjective risk based on the attitudes of the traffic participants. To evaluate the statistical significance of the categorical variables, Pearson's chi-square test was used. For certain groups of examinees, the results of the relationship (association) between socio demographic characteristics were analysed as predictors of behaviour with the degree of seat belt use. Some other predictors of behaviour, such as the road and mood predictors were analysed as well. Interest was also focused on finding out what motivated certain groups of examinees to use the seat belt. Based on the results of this research, it is possible to classify the drivers and car occupants into certain groups with respect to the seat belt use while driving. This can help in determining the ways of eliminating problems related to the low degree of seat belt use.
The fundamental diagram links average speed to density or traffic flow. An analytic form of this diagram, with its comprehensive and predictive power, is required in a number of problems. This paper argues, however, that, in some assessment studies, such a form is an unnecessary constraint resulting in a loss of accuracy. A non-analytical fundamental diagram which best fits the empirical data and respects the relationships between traffic variables is developed in this paper. In order to obtain an unbiased fundamental diagram, separating congested and non-congested observations is necessary. When defining congestion in parallel with a safety constraint, the density separating congestion and non-congestion appears as a decreasing function of the flow and not as a single critical density value. This function is here identified and used. Two calibration techniques – a shortest path algorithm and a quadratic optimization with linear constraints – are presented, tested, compared and validated.
The transportation sector accounts for nearly 19% of total energy consumption in Turkey, where energy demand increases rapidly depending on the economic and human population growth and the increasing number of motor vehicles. Hence, the estimation of future energy demand is of great importance to design, plan and use the transportation systems more efficiently, for which a reliable quantitative estimation is of primary concern. However, the estimation of transport energy demand is a complex task, since various model parameters are interacting with each other. In this study, artificial neural networks were used to estimate the energy demand in transportation sector in Turkey. Gross domestic product, oil prices, population, vehicle-km, ton-km and passenger-km were selected as parameters by considering the data for the period from 1975 to 2016. Seven models in total were created and analyzed. The best yielding model with the parameters of oil price, population and motor vehicle-km was determined to have the lowest error and the highest R2 values. This model was selected to estimate transport energy demand for the years 2020, 2023, 2025 and 2030.
Applying cognitive radio in the railway communication systems is a cutting-edge research area. The rapid motion of the train makes the spectrum access of the railway wireless environment instable. To address the issue, first we formulate the spectrum management of railway cognitive radio as a distributed sequential decision problem. Then, based on the available environmental information, we propose a multi-cognitive-base-station cascade collaboration algorithm by using naive Bayesian learning and agent theory. Finally, our experiment results reveal that the model can improve the performance of spectrum access. This cognitive-base-station multi-agent system scheme comprehensively solves the problem of low efficiency in the dynamic access of the railway cognitive radio. The article is also a typical case of artificial intelligence applied in the field of the smart city.
The accuracy and reliability in predicting short-term traffic flow is important. The K-nearest neighbors (K-NN) approach has been widely used as a nonparametric model for traffic flow prediction. However, the reliability of the K-NN model results is unknown and the uncertainty of traffic flow point prediction needs to be quantified. To this end, we extended the K-NN approach by constructing the prediction interval associated with the point prediction. Recognizing the stochastic nature of traffic, time interval used to measure traffic flow rate is remarkably influential. In this paper, extensive tests have also been conducted after aggregating real traffic flow data into time intervals, ranging from 3 minutes to 30 minutes. The results show that the performance of traffic flow prediction can be improved when the time interval increases. More importantly, when the time interval is shorter than 10 minutes, K-NN can generate higher accuracy of the point prediction than the selected benchmark model. This finding suggests the K-NN model may be more appropriate for traffic flow point and interval prediction at a shorter time interval.
Universal service providers have an obligation to provide a minimum required set of postal services – known as universal service obligation. To ensure universal service obligation, regulatory measures (criteria) which service providers must fulfil are often set up. In this paper, a geographical analysis of these criteria is conducted using current regulatory framework in the Republic of Croatia as an example. Based on the framework of the gravity model, accessibility of postal service is presented. The goal of the proposed research is to investigate the application of the gravity model for determining postal service accessibility, with special emphasis on rural areas. To our knowledge, this method has not been used in previous studies to determine accessibility of postal services. The results of the applied model could be used in future planning of access density criteria with various transportation modes.
In road safety, the process of organizing road infrastructure
network data into homogenous entities is called segmentation.
Segmenting a road network is considered the
first and most important step in developing a safety performance
function (SPF). This article aims to study the benefit
of a newly developed network segmentation method which is based on the generation of accident groups applying K-means clustering approach. K-means algorithm has been used to identify the structure of homogeneous accident groups. According to the main assumption of the proposed clustering method, the risk of accidents is strongly influenced by the spatial interdependence and traffic attributes of the accidents. The performance of K-means clustering was compared with four other segmentation methods applying constant average annual daily traffic segments, constant length segments, related curvature characteristics and a multivariable method suggested by the Highway Safety Manual (HSM). The SPF was used to evaluate the performance of the five segmentation methods in predicting accident frequency. K-means clustering-based segmentation method has been proved to be more flexible and accurate than the other models in identifying homogeneous infrastructure segments with similar safety characteristics.
E-marketplaces have become an essential part of e-commerce. In our research, a decentralized agent-based e-marketplace platform was devised. Although there are significant agent-based supply chain models in the literature, measuring quality performance using agents is still a subject of investigation. In order to improve overall supply chain service quality by allowing companies' agents to evaluate the service quality of their partners through the history of their transactions, this article proposes a service quality agent model. The model is designed using MCDM tools to suit different approaches to supply chain management. Consequently, since more informed procurement decisions are taking place continuously and autonomously at each node of a supply chain, supply chain service quality is being improved along the whole supply chain. At the end, the service quality valuation model of the supply chain is empirically evaluated.
Operation of means of transport is one of major sources of environmental impact. The goal of this article was to analyse the greenhouse gas emissions and to assess the impact of operation of means of road transport in Poland on human health using the life cycle assessment technique based on an analysis of emission of dust and gas pollutants. Road transport was assessed by taking the following means of transport into account: passenger cars, other cars with weight of up to 3,500 kg, lorries, buses, motorcycles, mopeds and tractors. The analysis covered various dust and gas pollutants, including the emission of CO2, CO, N2O, CH4, NOx, NMVOC, PM and SO2. Using the IMPACT 2002+ life cycle impact assessment method, transport was assessed in a breakdown into the following impact categories: greenhouse gas emission and damage to human health, including damage caused by organic and inorganic compounds. It has been evidenced that the highest emissions of dust and gas pollutants are caused by passenger cars, which is mainly due to the number of vehicles of this type traversing Polish roads. The main cause of climate changes due to road transport is CO2 emission, while NOx emission is the main factor determining individual categories of damage to human health. The negative environmental impact is primarily related to the operation of combustion engine vehicles. Diesel oil and petrol are currently the main fuels used in Polish transport. In order to reduce their impact on the environment one should intensify the efforts aimed at increasing the share of alternative fuels in transport.
According to the Convention for the Safety of Life at Sea and International Convention on Maritime Search and Rescue, saving human lives at sea is the duty of all signatory states. This paper analyzes and gives an overview of previous research activities in search and rescue system at sea and how the use of unmanned aerial vehicles (UAV) can improve search and rescue actions at sea. Research activities include development of the search system and placement of resources that are used in search and rescue actions (ships, planes etc.). Previous research is mainly related to minimizing response time when accidents at sea are detected in relation to search and rescue missions. Implementation of unmanned aerial vehicles into the search and rescue system enables improvement of these actions due to earlier detection and verification of accidents at sea and prevents unnecessary search and rescue units engagement in cases when an accident did not occur. The results of previous research point to the fact that future research should aim to explore the synthesis of unmanned aerial vehicles with the existing search and rescue system at sea in Croatia.
Mileage data collected via surveys based on self-estimation, reports from garages and other sources which use estimations are rough estimates and differ greatly from the actual mileage. Vehicle mileage is a major factor in emission calculations and needs to be as accurate as possible to obtain reliable emission models. Odometer readings are collected annually at the periodic technical inspection in Croatia. Average mileage data were analyzed for vehicles up to 20 years of age in 2017. Vehicles were classified by curb weight and fuel type. Such classification proved to follow driver behavior and the intended purpose of the vehicle. For each vehicle class the model was applied using vehicle age and population size as inputs for calculating average mileage. Real data show that vehicles in Croatia considerably exceed the estimated mileage in the years following the first registration of the vehicle and that they cannot be compared to data collected in other studies based on estimations. The difference lies in the covered mileage after vehicles reach ten years of age. The outcome of this study has resulted in a model for calculating average vehicle mileage. The model is suitable for use in various analyses for Croatia or for countries with similar driving habits and economic status now and for years to come.
Despite their inherent vulnerability to structural and functional degradation, transportation networks play a vital role in the aftermath of disasters by ensuring physical access to the affected communities and providing services according to the generated needs. In this setting of operational conditions and service needs which deviate from normal, a restructuring of network functions is deemed to be beneficial for overall network serviceability. In such context, this paper explores the planning of post-disaster operations on a network following a hazardous event on one of the network’s nodes. Lane reversal, demand regulation and path activation are applied to provide an optimally reconfigured network with reallocated demand, so that the network performance is maximized. The problem is formulated as a bi-level optimization model; the upper level determines the optimal network management strategy implementation scheme while the lower level assigns traffic on the network. Three performance indices are used for that purpose: the total network travel time (TNTT), the total network flow (TNF) and the special origin-destination pair (OD pair) accessibility. A genetic algorithm coupled with a traffic assignment process is used as a solution methodology. Application of the model on a real urban network proves the computational efficiency of the algorithm; the model systematically produces robust results of enhanced network performance, indicating its value as an operation planning tool.
Traffic paradox is an important phenomenon which needs attention in transportation network design and traffic management. Previous studies on traffic paradox always examined user equilibrium (UE) or stochastic user equilibrium (SUE) conditions with a fixed traffic demand (FD) and set the travel costs of links as constants under the SUE condition. However, traffic demand is elastic, especially when there are new links added to the network that may induce new traffic demand, and the travel costs of links actually depend on the traffic flows on them. This paper comprehensively investigates the traffic paradox under different equilibrium conditions including the user equilibrium and the stochastic user equilibrium with a fixed and elastic traffic demand. Origin-destination (OD) mean unit travel cost (MUTC) has been chosen as the main index to characterize whether the traffic paradox occurs. The impacts of travelers’ perception errors and travel cost sensitivity on the occurrence of the traffic paradox are also analyzed. The conclusions show that the occurrence of the traffic paradox depends on the traffic demand and equilibrium conditions; higher perception errors of travelers may lead to a better network performance, and a higher travel cost sensitivity will create a reversed traffic paradox. Finally, several appropriate traffic management measures are proposed to avoid the traffic paradox and improve the network performance.
Design and development of systems for delivering real-time information to people with disabilities and elderly persons need to be based on defined user requirements. For this purpose, the user requirements have been defined in this paper according to the everyday needs of people who use traffic networks and move in closed spaces. The logical presentation of the functionality of the informing system operation and its subsystems includes all the information (data) important for designing a user information delivery system. The paper presents a conceptual architecture system for delivering user informing services related to the environment based on the Internet of Things concept. The aim of the user informing service is an increase in the level of mobility of persons with disabilities and the senior age groups of users. In order to check the operation of the proposed architecture, the informing system operation was monitored on Arduino Uno and Raspberry Pi platforms in laboratory conditions. A simulation confirmed the interdependence of individual data from different subsystems in order to provide real-time information to the system user. The proposed conceptual architecture can contribute to a more efficient approach to the modeling of assistive technologies (with the aim of informing the users) based on dew/fog/cloud technologies in the Internet of Things environment.
This study focuses on a distribution problem involving incompatible products which cannot be stored in a compartment of a vehicle. To satisfy different types of customer demand at minimum logistics cost, the products are stored in different compartments of fleet vehicles, which requires the problem to be modeled as a multiple-compartment vehicle routing problem (MCVRP). While there is an extensive literature on the vehicle routing problem (VRP) and its numerous variants, there are fewer research papers on the MCVRP. Firstly, a novel taxonomic framework for the VRP literature is proposed in this study. Secondly, new mathematical models are proposed for the basic MCVRP, together with its multiple-trip and split-delivery extensions, for obtaining exact solutions for small-size instances. Finally, heuristic algorithms are developed for larger instances of the three problem variants. To test the performance of our heuristics against optimum solutions for larger instances, a lower bounding scheme is also proposed. The results of the computational experiments are reported, indicating validity and a promising performance of an approach.
Bicycle traffic flow suffers from the impact of tracks at an intersection in which a modern streetcar route is laid. The primary objective of this study involves discussing the impacts of modern streetcar tracks on bicycling through an intersection and developing a quantitative approach to calculate bicycle delay. Field investigations are conducted at eight sites in Nanjing and Shenyang, China. The sites are related to five intersections. Two of the five intersections are designed with a central modern streetcar style of track. Other two intersections operate on a roadside style of track and the last intersection is without tracks. The impact of the differences in bicycle speed are tested at each site based on the observed data. The results show that modern streetcar tracks exert a significant influence on bicycle speed and bicycling behavior and lead to delay, discomfort and unsafe conditions. Furthermore, a model is proposed to predict bicycle delay caused by modern streetcar tracks. The proposed model achieved a relatively accurate prediction. The findings of this study help in adequately understanding the impacts of modern streetcar tracks on bicycling. The results also suggest that longer crossing times should be used in signal design for bicycling at an intersection in which a modern streetcar route is laid.
The performance of a traffic system tends to improve as the percentage of connected vehicles (CV) in total flow increases. However, due to low CV penetration in the current vehicle market, improving the traffic signal operation remains a challenging task. In an effort to improve the performance of CV applications at low penetration rates, the authors develop a new method to estimate the speeds and positions of non-connected vehicles (NCV) along a signalized intersection. The algorithm uses CV information and initial speeds and positions of the NCVs from loop detectors and estimates the forward movements of the NCVs using the Gipps’ car-following model. Calibration parameters of the Gipps’ model were determined using a solver optimization tool. The estimation algorithm was applied to a previously developed connected vehicle signal control (CVSC) strategy on two different isolated intersections. Simulations in VISSIM showed the estimation accuracy higher for the intersection with less lanes. Estimation error increased with the decrease in CV penetration and decreased with the decrease in traffic demand. The CVSC strategy with 40% and higher CV penetration (for Intersection 1) and with 20% and higher CV penetration (for Intersection 2) showed better performance in reducing travel time delay and number of stops than the EPICS adaptive control.
The main objective of this paper is to define the repositioning strategy of the Port of Adria, which is the leading container maritime port of Montenegro. The strategy is an integral reflection of the analysis of internal (competitive advantage and financial strength) and external (the potential of container maritime port industry and environmental stability) repositioning criteria. The case study in this paper is mainly accomplished through the definition of specific propositions that clarify the connections between these criteria and the repositioning strategy. Knowledge and attitudes of stakeholders are used with the purpose of modeling a marketing strategy, which is based on an inductive study. The paper proposes a model based on a specific maritime port case which can be applied to any other case of maritime port repositioning as well.
Intermodal transport enables energy, costs and time savings, improves the service quality and supports sustainable development. The basic element of the intermodal transport system is an intermodal terminal, whose efficiency largely depends on the subsystems’ technologies. Accordingly, the topic of this paper is the evaluation and the selection of the appropriate handling equipment within the intermodal terminal. As the decision-making on the handling equipment is influenced by different economic, technical, technological and other criteria, the appropriate multi-criteria decision-making (MCDM) methods have to be applied in order to solve the problem. In this paper, a novel hybrid model which combines the fuzzy step-wise weight assessment ratio analysis (FSWARA) and the fuzzy best-worst method (FBWM) is developed. The defined model is applied for solving the case study of selecting adequate handling equipment for the planned intermodal terminal in Belgrade. The reach stacker is selected as the most adequate handling equipment since it suits best the characteristics of the planned terminal in the given conditions and in relation to the defined criteria. Solving the case study demonstrated the justification for using the MCDM methods to solve these kinds of problems as well as the applicability of the proposed MCDM model.
The aim of this study is to find a suitable methodology for planning the locations of intermodal terminals in an urban transit context. The location planning approach, which has been developed and makes this possible, consists of three phases. The first phase is the making of the geographic information system (GIS) database which enables determining the potential locations of intermodal terminals. For every potential location of the terminal, the number of citizens gravitating to a certain terminal is calculated, which at the same time represents the output from the first phase of the model. The second phase uses an optimization algorithm in order to determine the locations of the intermodal terminals. The optimization algorithm provides several solutions for a different number of terminals, and such solutions need to be evaluated. The main contribution of this research is in upgrading the location planning approach by introducing an additional step in assessing the solutions obtained by the optimization algorithm.