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, NO_x, SO_x 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.

Glavni cilj ovog rada je da istraži faktore koji utiču na profitabilnost kompanija u sektoru logistike tokom petogodišnjeg perioda (2013-2017). Uzorak obuhvata sve aktivne kompanije ili 748 kompanija koje posluju u sektoru logistike u zemljama Balkana. Imajući u vidu da je logistika bitan instrument konkurentnosti i profitabilnosti poslovanja kompanija i da je logistička industrija jedna od najprofitabilnijih, u radu je korišten panelni model podataka sa fiksnim efektom kako bi se razmotrila profitabilnost. Dobijeni rezultati su pokazali da četiri od šest posmatranih varijabli (veličina preduzeća, opipljivost imovine, likvidnost i koeficijent obrtanja aktive) imaju statistički značajan uticaj na profitabilnost. Rezultati daju smjernice za povećanje profitabilnosti i poboljšanje performansi logističkih kompanija, imajući u vidu da je efikasan sistem planiranja, upravljanja i kontrole logističkog sistema ključna odrednica profitabilnog poslovanja.

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.