The research on Bus Fleet Management (BFM) has undergone significant changes. It is unclear whether these changes are accepted as technological change or as a paradigm shift. Perhaps unintentionally, BFM is still perceived as routing and scheduling by some, and by others as maintenance and replacement strategy. Therefore, the authors conducted a Systematic Literature Review (SLR) to overview the existing concepts and school of thoughts about how stakeholders perceive the BFM. The SLR post-study exposed that BFM should be acknowledged as a multi-realm system rather than a uniform dimension of fulfilling timely service. Nonetheless, the work encapsulates BFM evolution which shows the need for the multi-realm research abstracted as "Bus Fleet Mobility Management" and "Bus Fleet Asset Management". The difficulties of transport agencies and their ability to switch from conventional to Zero-Emission Buses (ZEBs) illustrates why we propose such an agenda, by which the research is validated through needs both in academia and in practice.
Since high-speed train operation in 2004 in Korea, the revenue of conventional trains has been rapidly declining. To overcome the circumstance even a little, sightseeing trains have been introduced along ten competitive routes since 2013, which helped to reduce the loss rate from 3.0 to 2.5 compared to the existing conventional trains. Such accomplishment was based on the existing fare system fitted to conventional trains, not reflecting the value of the unique service that only the sightseeing train provides. The understanding of the Willingness To Pay (WTP) has largely remained unexplored in the railway transportation literature, and further no contributions in the sightseeing train industry. The paper aims to estimate the economic value of various types of service for sightseeing trains in the contexture of the WTP postulates using open-ended question survey data and a Tobit censored regression with four different statistical structures. The normal distribution model replicates the WTPs best fitted over entire service types, and the WTPs vary by different type of train services such as recreational activities, slow-moving operation, seating type, tourist commentary and locally connected tour service. The highest value 13.3~24.2% in room typed seats compared to observable seats has been observed. Applying the demand elasticities to price, the revenue maximizing is observed at a 6% hike for a standard seat and a 22% hike for a designated seat, and the revenue rises by 0.33% to 3.54%. This study expects that the result can be used as an appropriate guideline in determining a new fare fitted to sightseeing trains.
This study examines the correlation between road accident casualties and the age of the vehicle, assuming
that the age of vehicles and the improvements in their safety designs are related. The study evaluates the impact of the interrelationship between road segment characteristics and road accident type on vehicle age at the time of the accident (AVC). To analyse the nested relationship between these variables, a multinomial logistic regression (MML) model has been developed. The result of the analysis also duly finds that vehicle age has an emphatic role in the occurrence of accidents.
A new working mode of overloaded traffic control for rural highways is presented, and a location-routing model is built to optimize the check base distribution and the control vehicles’ routing schemes. Then, for the location-routing model with a large set of location alternatives and an unknown settable number of check bases, a multiple ant colony optimization algorithm is designed to solve the model. Furthermore, actual data from Guiyang rural highways are used to perform a numerical analysis. The results indicate that the model can be used to obtain the optimal base location-vehicle routing scheme to verify the feasibility of the model and the algorithm. The model and algorithm can help managers to make decisions on locating the check bases and routing the control vehicles.
The discourse approach for analysing various specified genres and professional discourse communities has increased in recent decades. Globalisation and synergy of disciplines opened up space for the interdisciplinary studies. The analysis of the specialized discourses enables to reveal the peculiarities and dominant concepts of the professional fields. With this in mind, this paper aims to examine the features of discourse employed in the research articles and publications about transport and logistics. The paper analyses the structural and qualitative aspect of the discourse of logistics and transportation. Based on the move/steps model, the main components of the research article in this discourse domain are found. Then, the analysis is focused on the discourse indicators that differ logistics and transportation genres from other academic genres. The changes in the scope and interest domain of logistics are worth“tracking and tracing” from a discursive aspect. The research is carried out on the material compiled of the academic research articles on logistics and transportation, referential resources in the field, and logistic dictionaries. The analysis shows that changes in logistics and transportation correlate with discourse changes. On a diachronic level, many concepts are replaced by new ones containing new approaches and dimensions in logistics. The analysis conducted in this paper brings new insight to both disciplines, logistics and linguistics.
The aim of the paper is to assess the possibility of decreasing the chosen environmental indicators like energy consumption, greenhouse gas (GHG) production and other exhaust pollutants in the selected region in Slovakia by introducing Liquefied Natural Gas (LNG) buses into bus transport. The assessment is carried out by comparing the consumption and emissions of current buses (EURO 2) in real operation, with potential buses (EURO 6) and with pilot LNG buses testing on the same lines. Comparison took place under the same conditions over the same period. The study measures the energy consumption and GHG production per bus. The research paper also compares two methodologies of calculation. The first calculation is according to the European Standard EN 16258: 2012 which specifies the general methodology for evaluation and declaration of energy consumption and GHG emissions (all services - cargo, passengers or both). The second calculation is according to the Handbook of Emission Factors for Road Transport (HBEFA). The results of the calculation are compared by both methods, and the most suitable version of the bus in terms of GHG emissions is proposed.
With the popularization of intelligent transportation system and Internet of vehicles, the traffic flow data on the urban road network can be more easily obtained in large quantities. This provides data support for shortterm traffic flow prediction based on real-time data. Of all the challenges and difficulties faced in the research of short-term traffic flow prediction, this paper intends to address two: one is the difficulty of short-term traffic flow prediction caused by spatiotemporal correlation of traffic flow changes between upstream and downstream intersections; the other is the influence of deviation of traffic flow caused by abnormal conditions on short-term traffic flow prediction. This paper proposes a Bayesian network short-term traffic flow prediction method based on quantile regression. By this method the trouble caused by spatiotemporal correlation of traffic flow prediction could be effectively and efficiently solved. At the same time, the prediction of traffic flow change under abnormal conditions has higher accuracy.
In order to improve the accuracy of short-term traffic flow prediction, a combined model composed of artificial neural network optimized by using Genetic Algorithm (GA) and Exponential Smoothing (ES) has been proposed. By using the metaheuristic optimal search ability of GA, the connection weight and threshold of the feedforward neural network trained by a backpropagation algorithm are optimized to avoid the feedforward neural network falling into local optimum, and the prediction model of Genetic Artificial Neural Network (GANN) is established. An ES prediction model is presented then. In order to take the advantages of the two models, the combined model is composed of a weighted average, while the weight of the combined model is determined according to the prediction mean square error of the single model. The road traffic flow data of Xuancheng, Anhui Province with an observation interval of 5 min are used for experimental verification. Additionally, the feedforward neural network model, GANN model, ES model and combined model are compared and analysed, respectively. The results show that the prediction accuracy of the optimized feedforward neural network is much higher than that before the optimization. The prediction accuracy of the combined model is higher than that of the two single models, which verifies the feasibility and effectiveness of the combined model.
The planning and organisation of public passenger transport in rural areas is a complex process. The transport demand in rural areas is often low, which makes it hard to establish and run a financially sustainable public transport system. A solution is integrated passenger transport that eliminates deficiencies and provides benefits for all participants in the public passenger transport process. This paper describes the impact of integrated passenger transport on mobility in rural areas and critically evaluates different literature sources. Integration of passenger transport in urban areas has been described in the context of rural areas, and the challenges of integration of public passenger transport specific to rural areas have been analysed. Through the application in urban and rural areas, the planning of integrated and non-integrated passenger transport has been functionally analysed. The analysis found an increase in the degree of mobility in the areas that use integrated passenger transport compared to the non-integrated one. This research of the literature review has identified the rural areas of mobility as under-researched. The mobility research can set up a more efficient passenger transport planning system in rural areas.
The rapid growth of CAV (Connected and Automated Vehicle) market penetration highlights the need to gain insight into the overall stability of mixed traffic flows in order to better deploy CAVs. Several studies have examined the modelling process and stability analysis of traffic flow in a mixed traffic environment without considering its inner spatial distribution. In this paper, an innovative Markov chain-based model is established for integrating the spatial distribution of mixed traffic flow in the model process of car-following behaviour. Then the linear stability analysis of the mixed traffic flow is conducted for different CAV market penetration rates, different CAV platoon strength and different cooperation efficiency between two continuous vehicles. Moreover, several simulations under open boundary conditions in multiple scenarios are performed to explicate how CAV market penetration rate, platoon strength and cooperation efficiency jointly influence the stability performance of the mixed traffic flow. The results reveal that the performance of this mixed traffic flow stability could be strengthened in these three factors. In addition to stability, an investigation of the fuel consumption and emission reduction under different market penetration rates and the platoon strength of CAVs are explored, suggesting that substantial potential fuel consumption and emission could be reduced under certain scenarios.
In the form of unattended Collection-and-Delivery Points (CDP), the fixed parcel lockers can save courier miles and improve the delivery efficiency. However, due to the fixed location and combination, the fixed parcel locker cannot accommodate the change of demands effectively. In this paper, an approach to supplementing fixed lockers by mobile parcel lockers to meet the demands of the last mile delivery has been proposed. With the goal of minimizing the operating cost, the location and route optimization problems of mobile parcel lockers are integrated into a non-linear integer programming model. An embedded GA has been developed to optimally determine the locations of distribution points, the number of mobile parcel lockers needed by each distribution point and the schedules and routes of mobile parcel lockers, simultaneously. Finally, a numerical example is given to compare the optimization results of the schemes with and without the aggregation problem. The results show that the scheme with the aggregation problem can greatly save the delivery time. However, for the scheme without the aggregation problem, time windows are more continuous, so it saves the number of vehicles.
The ongoing development of the concept ‘Mobility as a Service (MaaS)’ along with Shared Mobility contributes to the integration of transportation systems. Several MaaS or similar services are already in operation. The perceived quality of MaaS by the users varies significantly, and no general method is proposed to evaluate the service quality. This scantiness is identified as the research gap. The objective of the research is to elaborate a quantitative method to assess MaaS services. The research question is how to assess the quality of MaaS, and how to transform the qualitative description into quantitative numerical values, namely, the quality index and the level of quality. Since user expectations towards the importance of criteria are taken into consideration, the modified triangular fuzzy analytic hierarchy process method is introduced to calculate the weights of criteria. A quantitative method to calculate the quality index and to assign the quality level has been elaborated. Ten MaaS services are assessed with the method. It was found that the journey comfort is regarded with significant importance among the respondents. Furthermore, the quality index of MaaS services is not high; accordingly, the service quality requires continuous improvement. Our method facilitates decision-making when planning MaaS to identify the expected service attributes.
This paper presents an analytical framework for evaluating the performance of dedicated bus lanes. It assumes that under a designated travel demand, the traffic volume on a corridor changes with the modal shifts. The modal shift affects the operations of both bus traffic and car traffic and eventually, an equilibrium bus share ratio that maximizes the performance of the corridor will be reached. Microsimulation modelling is employed to assess the traffic operations under various demand levels and bus share ratios. The results show that converting a general lane into a bus lane significantly reduces bus delay. For car traffic, the overall trend is that delay increases after converting a general lane to a bus lane. In addition, delay decreases with the increase of bus share ratio. Nevertheless, when bus share ratio reaches 0.6 (demand less than 10,000 passengers per hour, pph; or 0.8 when demand increases up to 14,000 pph), there is no significant difference in delay between the two scenarios. The identified bus share ratios have the potential to direct the development of bus lane warrants. Finally, this research recommends that the Transportation Demand Management (TDM) strategies shall be developed to stimulate the modal shifts towards the identified optimal bus share ratio.
The research aims to identify the limitations and expectations of producers, transport companies, distributors and retailers in introducing intelligent packaging into supply chains of food products on the market of the Western Balkans. The limitations and benefits from the use of intelligent packaging have been identified in transportation, storage, operations of physical handling and display of food products at the place of their final purchase. The results have shown that there are significant differences in terms of limitations affecting the implementation of intelligent packaging into business operations of supply chains, bearing in mind the business type, number of employees, available capital and integrated standards into business operations. In contrast to this, the results point that there are no significant differences in terms of benefits that the analysed entities expect from introducing intelligent packaging into their systems. A set of measures and incentives have been defined for the competent institutions and food supply chain management to take, in order to minimize the restrictions and advance the implementation of intelligent packaging. The proposals and suggestions for further research are stated in the paper.
An integrated control strategy is considered in this paper with the aim of solving congestion in freeway merging regions during peak hours. Merging regions discussed in this paper include the mainline and on-ramp. Traditional research mainly focuses on the efficiency of traffic, ignoring the experience of on-ramp drivers and passengers. Accordingly, a dynamic competition control strategy is proposed to balance individual behaviour and traffic efficiency. First, the concept of the congestion index is introduced, which is expressed by the queue length and the speed parameter of the merging region. The congestion index is used to balance the priorities of the vehicles from the mainline and on-ramp into the merging region in order to avoid poor individual behaviour of on-ramp drivers due to the long-time waiting. Additionally, a nonlinear optimal control approach integrating variable speed limits control and ramp metering is proposed to minimize the total time spent and the maximum traffic flow. The integrated control approach proposed in this paper is tested by simulation which is calibrated using field data. The results indicate that the integrated control approach can effectively shorten the total delay and enhance the traffic service level.
Vehicles that are non-roadworthy pose a hazard for all road users and can be one of the main causes of traffic accidents. Previous studies have analysed the impact of the driving style on environmental sustainability and road safety. Starting from this, there was a need to further investigate the relationship between the driving style and vehicle roadworthiness as well. Vehicles that do not comply with the prescribed requirements should be excluded from traffic at a periodic technical inspection. However, the causes of detected vehicle defects cannot be established at a periodic technical inspection. The paper therefore, examines the factors affecting vehicle roadworthiness. First, the failure rate and mileage of vehicles at periodic technical inspection regarding the type of ownership was examined. In addition, a questionnaire was conducted to collect data about the driving style and maintenance habits of different types of car owners. The paper argues that vehicles owned by legal entities were generally in a worse condition than the vehicles owned by natural persons, due to the increased vehicle exploitation, but also due to a more aggressive driving style. Finally, it was found that by modifying their driving style, the drivers can affect the condition of their vehicles, considering the same mileage and maintenance habits.
With the increase in severe environmental problems associated with fossil fuel vehicles, the development of Alternative Fuel Vehicles (AFVs) has led to their promotion and use in Chinese provinces and cities. The comprehensive evaluation of competitiveness of the AFV industry in Chinese cities is beneficial to analyse the effects and relationships of different factors to promote the sustainable development of the AFV industry and guide the growth paths of the cities. An industrial competitiveness evaluation index system is established based on the characteristics of AFVs, and the development of the AFV industry in ten typical cities in China is comprehensively evaluated based on the Grey Relative Analysis (GRA) Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) and Principal Component Analysis (PCA) methods. To evaluate the results, the entropy weighting method is used for the weight distribution, and the industrial competitiveness rankings of ten cities are obtained by the entropy-GRA, TOPSIS, PCA (EGTP) method. The results show that Beijing is ranked first, followed by Shanghai, and Qingdao is ranked last. By analysing the correlation between the evaluation methods and indicators, it is found that EGTP has a high correlation with the other three evaluation methods, which proves the rationality of the weighted linear combination of GRA and the other three methods. Indices C5 (pure electric car proportion) and C13 (average concentration of PM2.5) were outliers due to the small number of samples.
In order to optimize the spare parts supply network, a multi-objective optimization model is established with the objectives of the shortest supply time, the lowest risk, and the minimum supply cost. A decomposition-based multi-objective evolutionary algorithm with differential evolution strategy is introduced to solve the multi-objective model. A series of non-dominated solutions, that is, representing the optimal spare parts supply schemes are obtained. In order to comprehensively measure the performance of these solutions, suitable quantitative metrics are selected, and the secondary goal-based cross-efficiency Data Envelopment Analysis (DEA) model has been used to evaluate the efficiency of the obtained optimal schemes. The improved DEA model overcomes the problems that the efficient units cannot be sorted and the optimal weight is not unique in traditional DEA model. Finally, the self-evaluation efficiency and cross-evaluation efficiency of each scheme are obtained, and the optimal supply scheme is found based on their cross-evaluation efficiency.
Given the rapid development of large cities, the residents faced with pressure both at work and in their personal lives tend to solidify their choice of transport modes and form personal travel habits, which in turn leads to higher requirements for urban traffic management. Based on the modified Theory of Planned Behaviour, the structural equation method is employed to explore people’s travel behaviour. It is found that policy attitude, perceived behaviour control, and subjective norms comprehensively affect the residents’ travel intentions under the Vehicle Restrictions in place in Beijing. The residents without private cars display a stronger intention to change their travel choices under the policies. When considering the mediating effect of travel habits between travel intention and travel choice, the impact of the restrictive policies is weakened. Compared with lower-income people, those with higher incomes demonstrate more stable travel habits in response to the effects of the restrictions. The higher the income, the greater the dependence on private cars exhibited by the residents. To summarize, people’s travel habits weaken to some extent the effects of the restrictive policies. Such policies should be created with the explicit aim of gradually changing the people’s habits.
This paper presents an overview of the applied research methodologies and developed travel demand models that take weather impact into account. The paper deals with trip generation and modal split as elements of travel demand that best describe changes in the travel behaviour in different weather conditions. The authors herein emphasize the importance of research in local conditions in all climate zones, especially in areas where climate and modal split characteristics are different from those in common research areas. This review is designed as a brief guide on how the impact of weather can be explored in order to encourage conducting research even in the countries where there is no systematic traffic and travel data collection. The stated adaptation technique followed by the panel household travel surveys may be particularly appropriate for those countries. It is concluded that small budgets should not be considered an obstacle, because it is possible to draw reliable conclusions based even on small samples. Moreover, modern research methods enable a cheaper survey process together with the possibility of obtaining higher quality of results. The increasing popularity of research in this field should contribute to the creation of more resilient transport systems all over the world. A special contribution of this paper is the review of research studies carried out in central, western and southern Europe and not mentioned in any review paper before.
Driver and pedestrian behaviour significantly affect the safety and the flow of traffic at the microscopic and macroscopic levels. The driver behaviour models describe the driver decisions made in different traffic flow conditions. Modelling the pedestrian behaviour plays an essential role in the analysis of pedestrian flows in the areas such as public transit terminals, pedestrian zones, evacuations, etc. Driver behaviour models, integrated into simulation tools, can be divided into car-following models and lane-changing models. The simulation tools are used to replicate traffic flows and infer certain regularities. Particular model parameters must be appropriately calibrated to approximate the realistic traffic flow conditions. This paper describes the existing car-following models, lane-changing models, and pedestrian behaviour models. Further, it underlines the importance of calibrating the parameters of microsimulation models to replicate realistic traffic flow conditions and sets the guidelines for future research related to the development of new models and the improvement of the existing ones.
Traffic crashes in Colombia have become a public health problem causing about 7,000 deaths and 45,000 severe injuries per year. Around 40% of these events occur on rural roads, taking note that the vulnerable users (pedestrians, motorcyclists, cyclists) account for the largest percentage of the victims. The objective of this research is to identify the factors that influence the frequency of crashes, including the singular orography of the country. For this purpose, we estimated Negative Binomial (Poisson-gamma) regression, Zero-inflated model, and generalized the linear mixed model, thus developing a comparative analysis of results in the Colombian context. The data used in the study came from the official sources regarding records about crashes with consequences; that is, with the occurrence of fatalities or injuries on the Colombian roads. For collecting the highway characteristics, an in-field inventory was conducted, gathering information about both infrastructure and operational parameters in more than three thousand kilometres of the national network. The events were geo-referenced, with registries of vehicles, involved victims, and their condition. The results suggest that highways in flat terrain have higher crash frequency than highways in rolling or mountainous terrain. Besides, the presence of pedestrians, the existence of a median and the density of intersections per kilometre also increase the probability of crashes. Meanwhile, roads with shoulders and wide lanes have lower crash frequency. Specific interventions in the infrastructure and control for reducing crashes risk attending the modelling results have been suggested.
The assessment of local air pollution due to aircraft emissions at/near the airport is an important issue from the standpoint of environment and human health, but has not received due attention in China. In this paper, the pollutant emissions (i.e. HC, CO, NOx, SOx and PM) from aircraft during landing and take-off (LTO) cycles at Nanjing Lukou Airport (NKG) in 2016 were investigated using an improved method, which considered the taxi-in and –out time calculated based on the real data from the Civil Aviation Administration of China (CAAC), instead of using the referenced time recommended by ICAO. First, the pollutant emissions and their characteristics were studied from different perspectives. Second, two various mitigation measures of emissions were proposed, and the performance of emission reduction was analysed. Our analysis shows that: (1) A320 and B738 emitted the largest emissions at NKG; (2) pollutants were mainly emitted during the taxi mode, followed by climb mode; (3) B738 had the lowest emissions per (seat•LTO) among all aircraft, while CRJ had the lowest emissions per unit LTO; (4) shortening the taxiing time and upgrading aircraft engines are both effective measures to mitigate pollutant emissions.
The characterization of complex patterns arising from electroencephalogram (EEG) is an important problem with significant applications in identifying different mental states. Based on the operational EEG of drivers, a method is proposed to characterize and distinguish different EEG patterns. The EEG measurements from seven professional taxi drivers were collected under different states. The phase characterization method was used to calculate the instantaneous phase from the EEG measurements. Then, the optimization of drivers’ EEG was realized through performing common spatial pattern analysis. The structures and scaling components of the brain networks from optimized EEG measurements are sensitive to the EEG patterns. The effectiveness of the method is demonstrated, and its applicability is articulated.
The main purpose of this paper is to research the factors that have an impact on the company profitability in the logistics industry during a five-year period (2013-2017). The sample includes 748 active companies operating in the logistics industry in the Balkan countries. Bearing in mind that logistics is an essential instrument of competitiveness and profitability of the company operations and that logistics is one of the most profitable industries, this paper used the panel data model with fixed effect in order to analyse profitability. The obtained results showed that four out of the six studied variables (company size, tangibility of assets, liquidity, and asset turnover ratio) have a statistically significant impact on profitability. The results provide guidelines for increasing profitability and improving the performance of logistics companies, given that an efficient planning system, managing and controlling the logistics system are key determinants of profitable business operations.
To improve the supply chain performance in all three aspects of sustainability (social, economic, and environmental), a comprehensive sustainable performance measurement system that captures all the supply chain partners’ efforts and commitments is required. Warehouse, as the second largest logistics source of environmental pollution in the supply chain has been almost completely overlooked and ignored in the past studies. To fill this gap, a warehouse performance metrics framework for environmental and social performance measures was proposed using a novel Fuzzy Delphi and Best-worst methodological approach. The method is less time-consuming than the Analytic Hierarchy Process or Analytic Network Process, it does not address whether criteria are dependent or independent, requires fewer comparisons of criteria, but still produces reliable and credible results. The presented framework consists of 32 equally formulated environmental and social performance indicators, including formulas and measurement units. The 14 most important indicators are ranked according to the requirements of different stakeholders.
Among the studies on the land use – travel relationship, few investigated it regarding weekend travel and destination choice. This study accordingly evaluates how the land use - destination choice relationship differs between weekdays and weekends using two multinomial logistic regression models in which the destination is classified into three types: microzone inside, microzone outside - macrozone inside, and macrozone outside. Major findings are that the choice of automobile alternatives for travel and their ownership are associated with the choice of the microzone inside while employment and income contribute to external trips. Among land use variables, nighttime population density turns out to be the only land use variable that consistently increases internal trips in all cases, regardless of the zone size and weekday - weekend difference, whereas daytime population density does not become significant in any case. Also, land use entropy and street connectivity are found to discourage a trip that moves from the microzone to the macrozone and transit system variables to facilitate a trip that goes beyond the microzone. Particularly, between two types of transit system variables, the choice of the microzone is likely to be associated with low bus stop density on weekdays and low metro station density on weekends.
Air traffic complexity is one of the main drivers of the air traffic controllers’ workload. With the forecasted increase of air traffic, the impact of complexity on the controllers' workload will be even more pronounced in the coming years. The existing models and methods for determining air traffic complexity have drawbacks and issues which are still an unsolved challenge. In this paper, an overview is given of the most relevant literature on air traffic complexity and improvements that can be done in this field. The existing issues have been tackled and new solutions have been given on how to improve the determination of air traffic complexity. A preliminary communication is given on the future development of a novel method for determining air traffic complexity with the aim of designing a new air traffic complexity model based on air traffic controller tasks. The novel method uses new solutions, such as air traffic controller tasks defined on pre-conflict resolution parameters, experiment design, static images of traffic situations and generic airspace to improve the existing air traffic complexity models.
Most of today's optimization efforts aim to reduce costs, time or the number of resources used. However, optimization efforts should consider other factors as important as these, such as facilitating the lives of the disabled, elderly and pregnant and helping them in their daily lives. In this study, the Nuh Naci Yazgan (NNY) University (Kayseri/Turkey) personnel transport problems were discussed. The NNY University provides a shuttle service to bring employees to school at the start of the work and to leave them at home after work. In order to shorten the collection / distribution time and the total distance travelled, the service vehicle does not leave / pick up all employees in front of their homes. Instead, the employees are picked up / dropped at appropriate locations on an intuitively determined route. Since only the time and cost savings are taken into account when determining the service route, some employees have a long walking distance to the service route. This creates a very important problem, especially for the disabled and pregnant workers. In this study, a new mathematical model is proposed which takes into consideration the physical disadvantages and occupational positions of the employees in order to determine the shortest vehicle route. The results show that the proposed model can significantly reduce walking distances of physically disabled people without compromising the total distance travelled by the vehicle.
Pedestrian injury in crashes at intersections often results from complex interaction among various factors. The factor identification is a critical task for understanding the causes and improving the pedestrian safety. A total of 2,614 crash records at signalized and non-signalized intersections were applied. A Partial Proportional Odds (PPO) model was developed to examine the factors influencing Pedestrian Injury Severity (PIS) because it can accommodate the ordered response nature of injury severity. An elasticity analysis was conducted to quantify the marginal effects of contributing factors on the likelihood of PIS. For signalized intersections, seven explanatory variables significantly affect the likelihood of PIS, in which five explanatory variables violate the Proportional Odds Assumption (POA). Local driver, truck, holiday, clear weather, and hit-and-run lead to higher likelihood of severer PIS. For non-signalized intersections, six explanatory variables were found significant to the PIS, in which three explanatory variables violate the POA. Young and adult drivers, senior pedestrian, bus/van, divided road, holiday, and darkness tend to increase the likelihood of severer PIS. The vehicles of large size and heavy weight (e.g. truck, bus/van) are significant factors to the PIS at both signalized and non-signalized intersections. The proposed PPO model has demonstrated its effectiveness in identifying the effects of contributing factors on the PIS.
The estimation of the saturation flow rate is of utmost importance when defining the signal plan at intersections. Because of the numerous influential factors, the values of which are hard to be determined, the subject problem is to be regarded as an extremely complex one. This research deals with the estimation of a saturation flow rate of a shared lane with permitted left turns. The suggested algorithm is based on the application of the artificial neural networks where the data for training are received by simulation. The results obtained by the neural networks are compared with multiple linear regression and the known HCM 2010 approach for determining the saturated flow of a shared lane. The testing data have shown that the approach based on the artificial neural networks foresaw statistically significantly better values than the ones obtained by multiple linear regression, with an error of 27 veh/h against 49 veh/h. The HCM 2010 approach is significantly worse than the two others included in this research. The ways of the future development of the suggested method could include additional factors, such as the grade of the traffic lane, the proximity of the bus stops, and others.
In this paper, the costs and benefits of the National Maritime Single Window (NMSW) for coastal countries that have limited human resources and infrastructure related to maritime traffic are researched. A general method for conducting a cost-benefit analysis of NMSW implementation is proposed. Using this method and the input data for Montenegro, as an example of a small-sized coastal country, the authors assess whether such an investment in NMSW implementation can be beneficial to coastal countries with limited resources.
The purpose of the study is to determine whether the presence of risk management in a warehouse requires the implementation of modern warehouse technology. On the basis of the literature analysis, it was possible to determine that there is a correlation between the presence of the highest level of risk management and the use of modern warehouse technology in individual warehousing processes. For this purpose, a statistical analysis was carried out on a sample of companies operating in the Slovenian automotive industry. The results did not reveal a tangible correlation between the presence of risk management with the use of individual modern warehouse technology, the motivation for its use and errors in its use. The results of the study therefore, highlight the problems that are present in the warehousing system of the Slovenian companies in the automotive industry, which are related to substandard technological equipment in the warehouses and to the discrepancy between the level of manufacturing automation and the level of warehousing automation. The results are important for the Slovenian automotive industry in terms of the implementation of modern warehouse technology in the high-tech automotive industry.
While rail-based public transport is clearly a more advanced and preferable alternative to driving and a way of overcoming traffic congestion and pollution problems, the rate of uptake for rail travel has remained stagnant as a result of various well-known issues such as that commuters either use a more reliable and comfortable alternative to get from A to B and/or that they are not satisfied with the quality of service provided. This study examined the factor of user satisfaction regarding rail-based public transport with the aim of discovering precisely what factors have a significant effect on the user satisfaction and uptake of rail travel. This was approached using both the Delphi approach and a thorough review of the current literature, focusing on a total of nine possible factors affecting passenger satisfaction with rail travel availability of service, accessibility of service, ticket or pass, punctuality, clarity of information, quality of customer service, comfort, safety, and image. Also discussed were 29 extra possible attributes and several measures that were implemented in various countries to increase the service quality. It was concluded that this review will provide valuable information for policymakers, researchers and service providers in terms of specifying the service factors most worth investigating if the quality of this crucial means of transport is to be raised.
The main goal of this paper is to determine the main technical and technological criteria impacting the effectiveness of the synchronization of transport flows in the East-West Transport Corridor (EWTC) in the southern part of the Baltic Sea Region (BSR) corridor using a specific questionnaire. The results were processed using the Kendall rating correlation method, and the compatibility of the expert selection was analysed using a match factor. Following Kendall’s concordance coefficient and consistency ratio values, the expert opinions were reconciled. In the course of the research using the Average Rank Transformation into Weights (ARTIW) method, the normalized subjective weights of the main technical and technological impacting synchronization of transport flows were determined. The outcomes of the research presented in the paper have shown that the main technical criteria impacting synchronization are: railway infrastructure and road transport infrastructure at the terminals. The most important technological interaction criteria are accessibility of seaports and accessibility of railway distribution stations. In the following stages of research, the main criteria of the above two factors should be used to create models and facilitate synchronization with the purpose of building an interconnected transport system spanning all modes of transport.
This paper reports on the results of subjective testing of user Quality of Experience (QoE) for omnidirectional video (ODV) streaming quality. The test was conducted among 20 test subjects who watched three ODVs using a Head Mounted Display (HMD) system. The length of the videos was between two and three minutes. The first video was used for training purposes and contained no quality degradations. The quality of the other two ODVs was degraded by manipulating the resolution or by introducing different frame drop patterns. While watching the pre-prepared videos the subjects indicated if they noticed the changes in the quality and then rated it. After watching each video, the subjects completed a separate questionnaire, which evaluated their level of enjoyment and discomfort with the video. The results showed that the degradation of both objective parameters (video resolution and frame rate) impacted the subjects’ perception of quality; however, the impact was somewhat alleviated in ODV which contained dynamic scenes and fast camera movements.
The Greek economic crisis of 2009 onwards has affected all aspects of social and economic life of the country, including transportation. The present study focuses on the impact of economic crisis on the long distance transportation between the island of Crete in Greece, the largest Greek island and one of the largest in the Mediterranean Sea, and the Greek mainland. A questionnaire survey was used to investigate the opinions of the Cretans on the way the economic crisis influenced their transportation to the Greek mainland. The results of the survey show that the frequency of the Cretans’ travels was significantly limited, owing to the increased direct or indirect associated cost, due to the economic crisis. Especially for those who struggled to make ends meet, the transportation to the mainland dropped to the bare essentials. Furthermore, the respondents deemed that the
deregulation of the Greek maritime and airline markets was also to blame for the high fares, thus they favoured a regulated public transport sector and were against privatization. Inevitably, financially vulnerable individuals were the most preoccupied with these issues. A feeling of isolation and exclusion was revealed by the sample on occasions when the scheduled trips were cancelled by the operators due to exogenous parameters.
The ongoing competition between bus and railway systems in the Hungarian regional passenger transport is a current problem, because these subsectors need to complement each other, instead of being in the government-funded competition. Long-term sustainability and efficiency in passenger transport require a balanced transport policy. The parallel bus and railway links, which are present in all regions of Hungary can result in competition. This research explores the solutions to this issue for long-term environmental and economic sustainability optimization. An objective index and interventions developed in previous studies have been applied here. This investigation is to validate the objective index and the interventions by using the Logit model.
One of the main points to be addressed when analysing vehicle-pedestrian collisions is the vehicle impact speed. If the traffic accident is not recorded on camera, and there are no skid marks nor tachograph in the vehicle, the parameter is determined on the basis of empirical models. All empirical models for ascertaining vehicle speed are based on the pedestrian throw distance, which is not always known because of an unidentified vehicle-pedestrian collision point or the final rest position of the pedestrian after collision. This paper shows a description of a vehicle damage recorded in an ordinal scale and determines the pedestrian throw distance prediction model from the vehicle damage established in such a way. If the accident scene is documented by photographs, the damage can be classified, and by applying a validated model, the pedestrian throw distance envisaged. Then, by applying an empirical model, one can determine the speed of the vehicle at the time of collision with a pedestrian. Two databases were formed during the research. The first is based on real-life traffic accidents (expert witnessing of the professors from the Faculty of Technical Sciences). The second is based on traffic accident simulations as part of PC Crash software package.
As electric bicycles (e-bikes) are becoming popular in China, concerns have been raised about their safety conditions. A traffic conflict technique is commonly used in traffic safety analysis, and there are many conflict measures designed for cars. However, e-bikes have high flexibility to change speed and trajectories, which is different from cars, so the conflict measures defined for e-bikes need to be independently explored. Based on e-bike driving characteristics, this paper proposes a new measure, the Integrated Conflict Intensity (ICI), for traffic conflicts involving e-bikes at intersections. It measures the degree of dangerousness of a conflict process, with consideration of both conflict risk and conflict severity. Time to collision is used to measure the conflict risk. Relative kinetic energy is used to measure the conflict severity. ICI can be calculated based on video analysis. The method of determining ICI thresholds for three conflict levels (serious, less serious, and slight) and two conflict types (conflicts between two e-bikes, and conflicts between an e-bike and a car) is put forward based on the questionnaires about safety perception of e-bike riders, which is regarded as the criterion of e-bike safety conditions at intersections. The video recording and a questionnaire survey about conflicts involving e-bikes at intersections have been conducted, and the unified thresholds applicable to different intersections have been determined. It is verified that ICI and its thresholds meet the criterion of e-bike safety conditions. This work is expected to be used in the selection of intersections for safety improvement of e-bike traffic.
With the rapid development of the automated metro, valid emergency procedures play a significant role for operators in metro emergency response and recovery. Also, the operators have a challenge to learn different emergency procedures under different automation grades of the metro. Hence, the paper aims to evaluate the learning performance of emergency procedures with regard to the operator. Based on the ACT-R cognitive theory, two decision patterns of the operators are proposed to predict the operator’s learning process for emergency procedures, and a cognition model including 16 production rules and 32 chunks to realize the perceptual encoding and the corresponding determining parts is built. After that, an experiment is further implemented to validate the model results.
Extensive efforts have been made in pedestrian evacuation of urban rail transit systems, since there has emerged an increasing number of congestion problems. However, few studies focus on the comprehensive urban rail transit hubs. As a comprehensive interchange hub integrating urban railway and intercity railway lines, Beijing West Railway Station was taken as a case study object. The pedestrian evacuation characteristics were analysed first. Then, a social force-based simulation model of Beijing West Railway Station was constructed in PTV Viswalk. The model was applied to visually display a real evacuation process and help identify evacuation bottlenecks. The results showed that the risk points at different facilities had various causes and features. Furthermore, the simulation model could also be used to evaluate the effectiveness of different optimization measures as long as certain model parameters were changed beforehand.
Traffic accidents leave lifelong after-effects and if the victim is disabled, they produce a production loss due to the differential in income that will be lost. This average value is very divergent in European countries, although there is consensus on cost components and valuation methods. However, many countries have legally standardised financial compensation so that it is calculated objectively and equitably for all those affected. This paper sets out the procedure for standardising the lost production cost of incapacitated road accident victims. An actuarial methodology relating to known inputs (age and salary) is used to obtain economic compensation for lost productivity. General principles and hypotheses are provided, and cases that require particular valuation are located. The standard cost thus calculated allows a homogeneous, fair and equitable compensation for all those involved in similar circumstances.
As the products of intelligent transportation systems, parking apps have become convenient platforms for implementing parking policies, which can be provided as parking app services. This paper proposes a traffic simulation model for evaluating the impacts of parking app services on the travellers’ choice behaviour and traffic dynamics. Travellers are assumed to use three types of parking app services: the provision of information on real-time parking lot occupancies, parking reservation, and the display of dynamic parking fees. The behaviour of travellers, such as travellers’ mode choices, departure time choices, and learning behaviour, are considered in this model. Numerical experiments show that providing information on real-time parking lot occupancies can be helpful in reducing the use ratio of commercial parking lots, but the effect will ultimately be smoothed during the evolution of traffic dynamics. Moreover, parking reservation is an effective way to reduce travel costs and encourage travellers to choose park-and-ride. Furthermore, dynamic parking fees usually lead to the oscillation of traffic dynamics and travellers’ choices, in addition to an increase in travel costs. This model is a useful tool for analysing the impacts of other parking management policies that can be implemented as parking app services and can be a reference for evaluating the impacts of other parking polices.
Although the four-step model is the most common method in transportation demand modelling, it is exposed to a considerable criticism in terms of representing the actual choice behaviours of travellers. For example, the four steps are presented in a fixed sequence and independently from each other. Such assumption may be correct in case of obligatory trips (e.g. work trips) where travellers’ behaviour has usually no effect on trip generation or trip distribution stages. However, in discretionary trips, they may simultaneously decide on various trip dimensions. This paper tries to overcome the limitations of traditional four-step model associated with discretionary trips by using a joint discrete choice modelling approach that represents destination, departure time and travel mode choices under a unified framework. The proposed model to be used is the Ordered Generalized Extreme Value model where potential spatial correlation among discretionary destinations can be considered as well. The research methodology has been tested by using shopping and entertainment trips data of Eskisehir city in Turkey. The proposed framework seemed to be more effective and offered an accurate alternative to the first three stages of the traditional four-step model in a setting with a limited number of discretionary destinations.
This paper compares the user experiences (UXs) while riding a scooter on the road to watching a 360° immersive scooter ride video in a laboratory using a Head-mounted Display (HMD) projection system. The aim of this study is to determine whether watching through an HMD projection system produces similar feelings of attractiveness, practicality, and enjoyment for the riding experience as riding on a real scooter. The data were collected from an experiment involving a total of 59 individual scooter commuters. The participants were asked to watch a 360° immersive video and to complete a user experience questionnaire (UEQ). The results verified that a virtual reality (VR) service with an HMD and panoramic scooter riding video content may be used as an experience tool to create reality-like scooter riding experiences for the users. Furthermore, the important factors that influence a user’s continued usage of watching 360° immersive video services were found to be attractiveness and pragmatic quality. Based on these results, a number of suggestions are proposed for the design of related VR services to strengthen the advantages of 360° immersive video in simulated two-wheeler ride experiences and providing road safety education.
Travel physical energy expenditure for travellers has impact on travel mode choice behaviour. However, quantitative study on travel physical energy expenditure is rare. In this paper, the concept of travel physical energy expenditure coefficient has been presented. A case study has been carried out of young travellers in Beijing to get the value of physical energy expenditure per unit time under three transport modes, walking, car and public transportation. A series of experiments have been designed and conducted, which consider influence factors including age, gender, travel mode, riding posture, luggage level and crowded level. By analysing the travel data of money, travel time and physical energy expenditure, we determined that the value of travel physical energy expenditure coefficient δ is 0.058 RMB/KJ, which means that travellers can pay 0.058 RMB to reduce 1 KJ physical energy expenditure. Next, a travel mode choice model has been proposed using a multinomial logit model (MNL), considering economic cost, time cost and physical energy cost. Finally, the case study based on OD from Xizhimen to Tiantongyuan in Beijing was conducted. It is verified that it will be in better agreement with the actual travel behaviour when we take the physical energy expenditure for different types of travellers into account.
Regional Traffic Signal Control (RTSC) is believed to be a promising approach to alleviate urban traffic congestion. However, the current ecology of RTSC platforms is too closed to meet the needs of urban development, which has also seriously affected their own development. Therefore, the paper proposes virtualizing the traffic signal control devices to create software-defined RTSC systems, which can provide a better innovation platform for coordinated control of urban transportation. The novel architecture for RTSC is presented in detail, and microscopic traffic simulation experiments are designed and conducted to verify the feasibility.
During the last decade, the number of vehicles on roads has been rapidly growing. Therefore, the demands for communication on the move are also increasing and the attention from many researchers is focused on the Vehicular Ad hoc NETworks (VANETs) because of their importance for Intelligent Transportation Systems (ITSs). Due to the complexity and cost of practical evaluation of VANETs, the researchers often rely on network simulation in order to evaluate their work. In this paper, we have developed a Network Simulator 3 (NS-3) based framework for VANETs that provides network performance analysis based on the key performance indicators such as throughput, packet loss ratio, overhead, end-to-end delay, jitter, etc. Since VANETs are highly dynamic networks, many researchers have proposed different routing protocols in order to improve the network performance. In this paper we have compared several topology-based routing protocols, and proposed utilization of the commonly used Expected Transmission Count (ETX) metric to improve VANET performance.
Traffic calming is the combination of mainly physical measures that reduce the negative effects of motor vehicle use, alter driver behaviour and improve conditions for non-motorized street users. Vibration measurements were performed by the authors of this paper near the roads with traffic calming devices. The measurements were taken throughout two seasons: in the winter and in the summer in order to evaluate the influence of soil freezing on traffic-induced vibrations. The only car measured was Fiat Doblo (weight 1,405 kg), and its driving speed when passing a speed bump or a speed table was controlled (20 km/h; 30 km/h; 40 km/h). The results show that the Peak Particle Acceleration (PPA) values were higher in the winter season compared with the summer. The vehicles passing over the speed tables induce lower PPA values than those passing over the speed bumps.
Policy decisions on the allocation of funds among sub-national regions for transportation infrastructure, specifically for motorways, face budgetary constraints and problems of geographical allocation. The purpose of this research is to assist the policymakers in efficiently allocating resources. The objective of this research is to test the ability of a limited model to identify regions whose freight transport capacity is constrained by lack of motorway infrastructure. This paper conducts an analysis of the relationship between freight transport volume, indicators of the demand for goods, indicators of congestion, and the availability of motorways and class one roadways across regions to determine if a model based on available data may inform the policymakers to effectively use limited funds and avoid unnecessary construction. The NUTS3 regions in the Czech Republic are used to estimate a preliminary model that may be generalized for the use across countries. The analysis finds sufficient variability across regions in the marginal effect of motorways on freight transport to assist the policymakers in determining which regions face the most economically severe constraints, and to separate the effects of population density from the lack of infrastructure. Although the Czech Republic is a developed country, there is significant emphasis, due to the increasing volumes of transportation flows, on the analysis of transportation in relation with the land use.
A variety of factors are involved in inter-city transportation route selection in the areas of complex terrain. With the help of Geographic Information System (GIS), three quantitative methods were employed to determine the transport routes between 44 cities in Northern Yunnan (China), an area with alpine valleys, Karst mountains, and plateau basins. The network analysis in GIS was used to find the routes based on the Transport Suitability Evaluation (TSE) map, which was produced from several factors, including population density, terrain slope, vertical terrain dissection, landslide and mud-flock area, land cover types, and Normalized Difference Vegetation Index (NDVI). Analytic Hierarchy Process (AHP), Grey Relational Analysis (GRA), and Delphi analysis were used to collect and calculate suitability values of these factors. Finally, all the routes connecting 44 cities of Northern Yunnan formed a network which could provide reference for route selection planning in the area.
This paper proposes a new hybrid evaluation method including Improved Analytic Hierarchy Process (IAHP), Entropy Method (EM), and Grey Comprehensive Evaluation Method (GCEM) to assess the transfer efficiency between rail transit and public bicycles. In particular, the IAHP method that replaces the nine-scale approach with three-scale approach to naturally meet the consistency requirements is applied to qualitatively calculate the weights of evaluation indices, the EM method is utilized to calculate the weights of evaluation indices with relatively high degrees of quantification, and the GCEM method is used to calculate the transfer efficiency between rail transit and public bicycles. In addition, a three-level evaluation-index system including target level, criteria level and index level is established. A numerical example is also provided to verify the feasibility of the proposed hybrid evaluation method and explore the reasons for low transfer efficiency between rail transit and public bicycles.
Electric Vehicles (EVs) are rapidly becoming the forerunners of vehicle technology. First electric vehicles were overlooked because of not having adequate battery capacity and because of low efficiency of their electric motors. Developing semiconductor and battery technologies increased the interest in the EVs. Nevertheless, current batteries still have insufficient capacity. As a result of this, vehicles must be recharged at short distances (approximately 150 km). Due to scheduled departure and arrival times EVs appear to be more suitable for city buses rather than regular automobiles. Thanks to correct charging technology and the availability of renewable energy for electric buses, the cities have less noise and CO2 emissions. The energy consumption of internal combustion engines is higher than of the electric motors. In this paper, studies on the commercial electric vehicle charging methods will be reviewed and the plug-in charging processes will be described in detail. This study strives to answer the questions of how plug-in charging process communication has performed between the EV and Electric Vehicle Supply Equipment (EVSE).
This paper proposes a region-based travel time and traffic speed prediction method using sequence prediction. Floating Car Data collected from 8,317 vehicles during 34 days are used for evaluation purposes. Twelve districts are chosen and the spatio-temporal non-linear relations are learned with Recurrent Neural Networks. Time estimation of the total trip is solved by travel time estimation of the divided sub-trips, which are constituted between two consecutive GNSS measurement data. The travel time and final speed of sub-trips are learned with Long Short-term Memory cells using sequence prediction. A sequence is defined by including the day of the week meta-information, dynamic information about vehicle route start and end positions, and average travel speed of the road segment that has been traversed by the vehicle. The final travel time is estimated for this sequence. The sequence-based prediction shows promising results, outperforms function mapping and non-parametric linear velocity change based methods in terms of root-mean-square error and mean absolute error metrics.
The daily travel patterns (DTPs) present short-term and timely characteristics of the users’ travel behaviour, and they are helpful for subway planners to better understand the travel choices and regularity of subway users (SUs) in details. While several well-known subway travel patterns have been detected, such as commuting modes and shopping modes, specific features of many patterns are still confused or omitted. Now, based on the automatic fare collection (AFC) system, a data-mining procedure to recognize DTPs of all SUs has become possible and effective. In this study, DTPs are identified by the station sequences (SSs), which are modelled from smart card transaction data of the AFC system. The data-mining procedure is applied to a large weekly sample from the Beijing Subway to understand DTPs. The results show that more than 93% SUs of the Beijing Subway travel in 7 DTPs, which are remarkably stable in share and distribution. Different DTPs have their own unique characteristics in terms of time distribution, activity duration and repeatability, which provide a wealth of information to calibrate different types of users and characterize their travel patterns.
This paper provides a framework for solving the Time Dependent Vehicle Routing Problem (TDVRP) by using historical data. The data are used to predict travel times during certain times of the day and derive zones of congestion that can be used by optimization algorithms. A combination of well-known algorithms was adapted to the time dependent setting and used to solve the real-world problems. The adapted algorithm outperforms the best-known results for TDVRP benchmarks. The proposed framework was applied to a real-world problem and results show a reduction in time delays in serving customers compared to the time independent case.
Traffic-related deaths and severe injuries may affect every person on the roads, whether driving, cycling or walking. Toronto, the largest city in Canada and the fourth largest in North America, aims to eliminate traffic-related fatalities and serious injuries on city streets. The aim of this study is to build a prediction model using data analytics and machine learning techniques that learn from past patterns, providing additional data-driven decision support for strategic planning. A detailed exploratory analysis is presented, investigating the relationship between the variables and factors affecting collisions in Toronto. A learning-based model is proposed to predict the fatalities and severe injuries in traffic collisions through a comparison of two predictive models: Lasso Regression and Random Forest. Exploratory data analysis results reveal both spatio-temporal and behavioural patterns such as the prevalence of collisions in intersections, in the spring and summer and aggressive driving and inattentive behaviours in drivers. The prediction results show that the best predictor of injury severity for drivers, cyclists and pedestrians is Random Forest with an accuracy of 0.80, 0.89, and 0.80, respectively. The proposed methods demonstrate the effectiveness of machine learning application to traffic and collision data, both for exploratory and predictive analytics.
Inadequate consideration of the elderly people crossing demand on the signalized intersections would bring great potential safety hazards, especially the speed through the crosswalk. By observing the pedestrian walking speed at three signalized crosswalks and a relatively spacious sidewalk in Chongqing, China, this paper has obtained the walking speed values of 658 elderly people and 1,176 adults at the signalized crosswalks, as well as the walking speed parameters of 868 adults and 422 elderly people on a relatively spacious sidewalk section. Comparing the walking speed of adults walking along the sidewalk section and on signalized crosswalks, the data show that there is no significant difference between these two site speeds. Similarly, when comparing the two site data of the elderly, it is found that their walking speed at the signalized crosswalk is significantly higher than that on the sidewalk section. That is to say, the speed setting for the old people crossing the crosswalk has not been fully considered. Subsequently, taking the elderly’s walking speed as input parameter, establishing the simulation models under different proportions of the elderly and different pedestrian flows, and then gain the walking speed values of the pedestrians with different quantities and different proportion of the elderly pedestrians. With the help of the unknown breakpoint Regression method, under the setting of the elderly pedestrian speed crossing the street, the proportion threshold of the elderly crossing the street at the signalized intersection is obtained. The results show that when the proportion of the elderly is more than 15% of the pedestrians crossing the street, the pedestrian crossing speed value for the signal time is suggested to be 0.97 m/s.
Forecasting short-term traffic flow using historical data is a difficult goal to achieve due to the randomness of the event. Due to the lack of a solid approach to short-term traffic prediction, the researchers are still working on novel approaches. This study aims to develop an algorithm that dynamically updates the training set of models in order to make more accurate predictions. For this purpose, an algorithm called Periodic Clustering and Prediction (PCP) has been developed for use in short-term traffic forecasting. In this study, PCP was used to improve Artificial Neural Networks (ANN) predictive performance by improving the training set of ANN to predict short-term traffic flow using selected clusters. A large amount of traffic data collected from the US and UK motorways was used to determine the PCP ability to increase the ANN performance. The robustness of the proposed approach was determined by the performance measures used in the literature and the mean prediction errors of PCP were significantly below other approaches. In addition, the studies showed that the percentage errors of PCP predictions decreased in response to increasing traffic flow values. Considering the obtained positive results, this method can be used in real-time traffic control systems and in different areas needed.
In this paper, a two-step meta-heuristic approach is proposed for vehicle assignment problem with geometric shape-based clustering and genetic algorithm. First, the geometric shape-based clustering method is used and then the solution of this method is given to the genetic algorithm as initial solution. The solution process is continued by genetic algorithm. There are 282 bus lines in İstanbul European side. Those buses should be assigned to six bus garages. The proposed method is used to determine the minimum distance between the bus lines and garages by assigning buses to garages. According to the computational results, the proposed algorithm has better clustering performance in terms of the distance from each bus-line start point to each bus garage in the cluster. The crossover rate changing method is also applied as a trial in order to improve the algorithm performance. Finally, the outputs that are generated by different crossover rates are compared with the results of the k-Nearest Neighbour algorithm to prove the effectiveness of the study.
Fuelled by the Belt and Road Initiative, Eurasia railway transport has gained rapid traction. However, China Railway Express is in the development period, information about China Railway Express lines is in chaos, and it is difficult to appraise the market situation. This paper focuses on providing an approach to estimate the market share of every China Railway Express line. In this paper, the crawled data from the website are applied to estimate the customer demands for China Railway Express services in different areas of China. The government subsidy is a factor that cannot be ignored, but its level is unclear. Thus, a dummy regression model was established to estimate the subsidy. The regression result is in line with the data released by the Guangdong Provincial Government in 2017. To identify customers’ preferred choices for particular lines, a multi-objective optimization model has been built. With the crawled demands data and this optimization model, the current and future market share of China Railway Express can be assessed. If the subsidy is cancelled, some China Railway Express lines will lose their market, and only three lines have a bright future.
Before choosing an intersection project design, an important step is to examine the justification of the construction on the basis of defined criteria. One of the key criteria is the analysis of capacity. Large numbers of roundabout capacity models are present in the world, most of them adapted to the conditions of the country they originate from and they need to be calibrated for local conditions. Key parameters for calibration are critical headway and follow-up headway. Follow-up headway can be measured directly in the field, while critical headway cannot be measured, but is estimated. Many critical headway estimation methods exist (over 30) and each of them provides different values. Different values of critical headway result in different capacity estimation values. This raises the question which method provides more realistic estimations under certain conditions. In this paper, four most frequently used critical headway estimation methods (Raff, Maximum likelihood method, Wu, Logit) were selected to be tested by comparison of theoretical capacity models and actual measured capacity at a small urban roundabout.
Public transport is a key element of sustainable transport in medium and large cities. Therefore, it is important that city residents want to use it. This paper aims to determine the criteria of the public transport infrastructure which have the most influence on passenger satisfaction with the public transport system. The criteria of public transport infrastructure of stops, vehicles, and route network were analysed. The primary attention was focused on rating these criteria from the most to the least important one. The analysis of scientific papers, specialized literature, Europe Union regulations, Lithuanian legislation, and recommendations were used to explore the necessary criteria that have a significant effect on the popularity of public transport, its functionality and gives a reference on how to raise the willingness of the citizens to use public transport. The experts (14 experts were involved) and social surveys (440 respondents were involved) were used to identify the evaluation criteria of public transport infrastructure and to investigate the state of these criteria. These criteria were grouped into three larger groups according to their nature (public transport infrastructure of stops, vehicles and route network) and were rated and prioritized by the multi-criteria analysis. The results reflect the priorities of criteria parameters of public transport infrastructure. The results show that when investing in public transport infrastructure, the main priority should be attributed to the infrastructure elements, such as public transport priority in the streets, then shelters, lighting, cleanness of bus stops and vehicles, which are physically appreciable. These parameters have the most significant impact on improving the level of service of public transport infrastructure in urban areas.
The purpose of this study was to explore outsourcing as a possible source of competitive advantage for road freight operators, with the empirical research directed towards the road freight transportation sector. Methodologically, this study drew on the data collected from a sample of Croatian road freight transporters. Because a certain number of transportation companies tend to outsource their resources, the insight into outsourcing activities was gained through analysing (1) the number of hired vehicles in the fleet (outsourced vehicles), and (2) the number of hired drivers (outsourced drivers). A variance inflation test, correlation and multiple regression analysis were conducted to test the model assumptions. The research results confirmed the connection between the externalised resources and the differentiation of services and staff. The main contribution and managerial implications included that the companies with a more significant number of hired vehicles in their fleet should differentiate their services. In contrast, the companies that own the majority of their vehicles should build their competitive advantage through staff differentiation.
Tunnels are critical areas for highway safety because the severity of crashes in tunnels tends to be more serious. Controlling vehicle speed is regarded as a feasible measure to reduce the accident rate in the tunnel entrance and exit areas. This paper aims to evaluate the effectiveness of three types of speed reduction markings (SRMs) in tunnel entrance and exit zones by conducting a driving simulation experiment. For this study, 25 drivers completed the driving tasks in the day and night scenarios. The vehicle speed and acceleration data were collected for analysing and the relative speed contrast, time mean speed and acceleration were adopted as indices to evaluate the effectiveness of SRMs. The repeated ANOVA test results revealed that SRMs have a significant effect in reducing vehicle speed, especially in the exit zone. Colour Anti-skid Markings (CASMs) produced a more obvious deceleration in the entrance zone. In the entrance zone, a similar downward trend was performed in the situation of NSRMs and SRMs, but a lower speed occurred in case of SRMs. Besides, CASMs work better and cause an obvious gap of 10 km/h in daytime and 5 km/h at night compared to the speed without SRMs. In the exit zone, the present study supports the conclusion that the drivers are prone to accelerate. Our results showed that the drivers accelerated in case of NSRMs, while they slowed down in case of SRMs. Thus, SRMs are necessarily implemented in the highway tunnel entrance and exit zones. Our study also indicates that though CASMs result in lower speed at night, the Transverse Speed Reduction Markings
(TSRMs) have a better performance than CASMs in daytime. The investigation provides essential information for developing a new marking design criterion and intelligent driver support systems in the highway tunnel zones.
Intention is the main embodiment of human cerebral conscious activities, which has an important influence on guiding the realization of human behaviour. It is a vital prerequisite for analysing the dynamic characteristics of pilots with different intentions. Considering the intention law of the generation, transfer and reduction, this paper analyses dynamic characteristics of pilots with different intentions, starting from the factors of effect on the intention. Taking airfield traffic pattern as an example for simulating flight experiments, the pilot’s multi-source dynamic data of human – aircraft – environment system under different intentions and their psycho-physiological-physical characteristics were recorded. Based on Matlab, one-way analysis of variance was used to extract variables with significant changes, and the variables under different intentions were compared and analysed. The results show that the conventional pilots are more conducive to control the aircraft to keep a stable flight attitude. This study is of great significance for perfecting the warning system of flight safety and improving the pilot’s micro-behaviour assessment system.