JournalTOCs

European Journal of Transport and Infrastructure Research (EJTIR)
Number of Followers: 6

This is an Open Access Journal

Open Access journal
ISSN (Online) 1567-7141
Published by TU Delft

[7 journals]

Airport classification in Chinese multi-airport regions
- Authors: Yuting Chen, Kurt Fuellhart, Shengrun Zhang, Frank Witlox
  Pages: 1 - 21
  Abstract: The agglomeration of airports into multi-airport regions (MARs) has become one of the salient features of the worldwide air transport system in the last decades. Meanwhile, in China, the development of HSR is growing quickly, and is both competitive to and cooperative with the aviation network. To date some research has focused on the airport classification with aviation network properties within the specific MARs. However, little research comprehensively integrates complementary transport systems (such as civil aviation versus high-speed rail (HSR)) into the analytical framework for airport classification. The purpose of this paper is to identify the unique nature of component airports and their distribution in MARs in China from multiple perspectives by accounting for the influence of the HSR system. Airports are classified along multiple dimensions including competitive concentrations, the interaction between air transport and HSR, and airport community structure, among others. The results produce distinct partitions of the component airports in Chinese MARs, and provide insights into Chinese airport functionality and impacts of the HSR network on the distribution of different types of airports. The conclusions provide a more comprehensive assessment of airports’ spatial arrangement in the unique Chinese MAR context. Although this paper did not derive the market share allocation and co-opetition relationship between a specific airport and HSR, it proposed a basic framework for future research.
  PubDate: 2022-04-04
  DOI: 10.18757/ejtir.2022.22.2.6043
  Issue No: Vol. 22, No. 2 (2022)
Building latent segments of goods to improve shipment size modelling:
Confirmatory evidence from France
- Authors: Raphael Piendl, Martin Koning, Francois Combes, Gernot Liedtke
  Pages: 22 - 52
  Abstract: Freight transport demand models are generally based on administrative commodity type segmentation which are usually not tailored to behavioral freight transport demand modelling. Recent literature has explored new approaches to segment freight transport demand, notably based on latent class analysis, with promising results. In particular, empirical evidence from road freight transport modelling in Germany hints at the importance of conditioning and handling constraints as a sound basis for segmentation. However, this literature is currently sparse and based on small samples. Before it can be accepted that conditioning should be integrated in the state-of-the-art doctrine of freight data collection and model specification, more evidence is required. The objective of this article is to contribute to the issue. Using detailed data on shipments transported in France, a model of choice of shipment size with latent classes is estimated. The choice of shipment size is modelled as a process of total logistic cost minimization. Latent class analysis leverages the wide range of variables available in the dataset, to provide five categories of shipments which are both contrasted, internally homogenous, and directly usable to update freight collection protocols. The groups are: "‘standard temperature-controlled food products"’, "‘special transports"’, "‘bulk cargo"’, "‘miscellaneous standard cargo in bags"’, "‘palletised standard cargo"’. This segmentation is highly consistent with the empirical evidence from Germany and also leads to better estimates of shipment size choices than administrative segmentation. As a conclusion, the finding that conditioning and handling information is essential to understanding and modelling freight transport can be regarded as more robust.
  PubDate: 2022-04-11
  DOI: 10.18757/ejtir.2022.22.2.5662
  Issue No: Vol. 22, No. 2 (2022)
Modeling the impact of the River Information Services Directive on the
Performance of inland navigation in the ARA Rhine Region
- Authors: Edwin Verberght, Yasmine Rashed, Edwin van Hassel, Thierry Vanelslander
  Pages: 53 - 82
  Abstract: River Information Services (RIS) are harmonized digital services that support safety, transport and traffic management in the inland navigation. RIS refer mainly to four key technologies such as Vessel Tracking and Tracing (VTT) with onboard Inland Automatic Identification System transponders (Inland AIS), Electronic Reporting International (ERI), Notices to Skipper (NtS) and Inland Electronic Chart Display and Information System (Inland ECDIS). These key technologies were developed during the nineties and received in Europe a regulatory framework through the Directive EC/2005/44 (the RIS-Directive). In 2009, most EU Member States had implemented the Directive. One of the claimed benefits of the implementation of RIS relates to a growing performance of inland navigation. In this paper, the impact of RIS on the performance of inland navigation is analyzed via a structural break cointegration approach, followed by an Error Correction Model (ECM) estimation. The empirical analysis shows that the performance of the dry bulk market is highly dynamic, while the liquid bulk market is moderately responsive to shocks. The structural break analysis could not capture any effect of the Directive on the performance of both markets, which can be attributed to several factors, such as the difficulty to isolate the policy impact, other drivers of variation, interferences of other policies and changes at the demand side.
  PubDate: 2022-04-13
  Issue No: Vol. 22, No. 2 (2022)
Comparative mode choice analysis of university staff commuting travel
preferences
- Authors: Sarbast Moslem, Szabolcs Duleba, Domokos Esztergár-Kiss
  Pages: 83 - 107
  Abstract: Surveying citizen preferences on transportation modes when commuting is a major issue in urban transport planning. Most of the current methods approach the problem through the attributes of choices thus forecasting the demand indirectly. This paper aims to analyze a survey of commuting students and university staff by two direct preference models: the Analytic Hierarchy Process and the Best-Worst Method. Both techniques are based on pairwise comparisons; consequently, the commuting transport alternatives can be directly compared with each other, and the results are comparable, too. However, the two methods differ in the number and the nature of comparisons and in the consistency check, thus they can be regarded as competitors. A real-world case study on commuting student groups provides a better understanding of the proposed methodology. As a result, it can be stated that despite their low utilization in the transportation field, both the Analytic Hierarchy Process and the Best-Worst Method are applicable to mode choice preference surveys, and they produce comprehensive final outcomes. Therefore, the well-known tools of mode choice can be extended by Multi-Criteria-Decision-Making techniques to increase the efficiency of transport demand prediction. The extension is beneficial to avoid the bias of other methods in converting attribute evaluations to real mode choice decision, as both models, especially the Best-Worst approach, requires less cost and time than the mainstream techniques.
  PubDate: 2022-04-19
  DOI: 10.18757/ejtir.2022.22.2.5949
  Issue No: Vol. 22, No. 2 (2022)
Minimal utilization rate for railway maintenance windows: a cost-benefit
approach
- Authors: Abderrahman Ait Ali, Tomas Lidén
  Pages: 108 - 131
  Abstract: Methods for economic assessment are often used in the rail sector to evaluate large infrastructure investments such as new high-speed lines. With larger networks and ageing infrastructure, these methods can also be used for planning maintenance. In this paper, we focus on the newly introduced concept of maintenance windows in Sweden. These are pre-allocated slots in the train timetable dedicated to performing, among others, periodic/frequent maintenance activities. To justify the pre-allocation of such windows, this study presents a method to find minimal utilization rates depending on window designs and traffic situations. Using a cost-benefit approach, the windows are assessed using a total social cost including work costs, loss in traffic production and reliability gains in future traffic. Based on a case study from the Southern main line in Sweden, we study the minimal utilization rate in different test scenarios, i.e., night or day shifts, asset degradation functions and designs of maintenance windows. The results show that lower utilization rates (4-42%) can be accepted during low-volume traffic or for partial closures, while higher utilization rates (47-83%) are required for full closures during high-volume traffic. Whether the rates are measured as the share of used window time or the share of utilized windows is less important, especially when higher utilization is required. Sensitivity analyses of asset knowledge indicate that parameters such as asset degradation function and minimum asset quality (and to a lesser extent traffic volume, discount rate and failure likelihood) can have a substantial effect on the minimum required utilization rates.
  PubDate: 2022-04-22
  DOI: 10.18757/ejtir.2022.22.2.6130
  Issue No: Vol. 22, No. 2 (2022)
Using location based social media data to explain COVID-19 spread in Italy
- Authors: Evgeniia Shtele, Paolo Beria, Vardhman Lunkar
  Pages: 132 - 160
  Abstract: During crisis, social network data is valuable information for authorities and researchers. Since the COVID-19 outbreak, a significant amount of data, including mobility-related data, has been released from various agencies to support studies. This paper aims to check the suitability of mobility-related datasets in describing and predicting new cases, about the spatial dimension during the initial phase of the outbreak. We focus on rich anonymized datasets through Facebook – Data for Good program: colocation matrices, movement matrices and stay-at-home data. However, we also compare their usability with a traditional Origin-Destination matrix. Our test case is Italy, the second country hit after China, where the infection spread irregularly from a few northern provinces to rest of Italy and abroad. Our regression models explain the number of actual new cases at the provincial level (corresponding to NUTS-3) by three groups of variables: active cases proxying local infections, interprovincial mobility proxying the arrival of cases from outside, and the degree of people staying at home proxying infections from cohabitants. The variants among the models consist of different measures of interprovincial mobility, thus allowing us to confront them. The result is the inclusion of time-dependent mobility data improving the significance of model and is effective in explaining irregular rise of cases in different parts of the country. Moreover, colocation results as the best measure. From a policy perspective, results show that mobility restrictions help reduce the geographical spread of infection at the very beginning, but once the outbreak, the interprovincial mobility becomes less relevant.
  PubDate: 2022-05-26
  DOI: 10.18757/ejtir.2022.22.2.5702
  Issue No: Vol. 22, No. 2 (2022)
Modelling the relationship between covid-19 restrictive measures and
mobility patterns across Europe using time-series analysis
- Authors: Marianthi Kallidoni, Christos Katrakazas, George Yannis
  Pages: 161 - 182
  Abstract: Since early 2020, strict restrictions on non-essential movements were imposed globally as countermeasures to the rapid spread of COVID-19. The various containment and closures strategies, taken by the majority of countries, have directly affected travel behavior. This paper aims to investigate and model the relationship between covid-19 restrictive measures and mobility patterns across Europe using time-series analysis. Driving and walking data, as well as confinement policies were collected from February 2020 to February 2021 for twenty-five European countries and were implemented into Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors (SARIMAX) time-series models. Results reveal a significant number of models in order to estimate mobility during pandemic almost in every country of the study. School closing was found to be the most important exogenous factor for describing driving or walking, while “Stay at home” orders had not a significant effect on the evolution of people movements. In addition, countries which suffered the most due to the pandemic indicated a strong correlation with the restrictive measures. No time-series models were found to describe the countries which implemented weak confinement policies.
  PubDate: 2022-05-31
  DOI: 10.18757/ejtir.2022.22.2.5728
  Issue No: Vol. 22, No. 2 (2022)
Consumer preferences for parcel delivery methods
- Authors: Eric Molin, Matthijs Kosicki, Ron van Duin
  Pages: 183 - 200
  Abstract: In the Netherlands, as in many other densely populated countries, home delivery is the dominant way of delivering online ordered parcels. This is mainly because big retail companies offer this delivery option for free. Due to the expansion of e-commerce, home delivery that typically makes use of diesel vans puts increasing pressure on logistics service providers, their employees, traffic, and the environment. Increased use of service points or parcel lockers could relieve some of this pressure, but these delivery alternatives are barely used by Dutch consumers. The goal of this paper is to better understand how consumers can be stimulated to use pick-up points and in particular parcel lockers. To achieve this goal, a stated choice experiment was conducted among Dutch e-commerce consumers, in which they made choices between home delivery, service point, and parcel locker alternatives that systematically varied in costs, delivery moment, and distance. The application of the model to predict choices under a number of scenarios makes clear that even a small increase in home delivery costs together with an expansion of parcel lockers that decreases the distance to the parcel lockers, could severely reduce the choice for home delivery: home delivery is predicted to reduce from 71% to only 7%. This suggests that there is potential for breaking through the dominance of home delivery.
  PubDate: 2022-06-13
  DOI: 10.18757/ejtir.2022.22.2.6427
  Issue No: Vol. 22, No. 2 (2022)
Speed development at freeway curves based on high frequency floating car
data
- Authors: Johan Vos, Haneen Farah
  Pages: 201 - 223
  Abstract: Road designers need to have insights where deceleration and acceleration are expected related to the position of the curve, and in in which amount so that drivers are able to safely decelerate and accelerate respectively into and out of a freeway curve. For this, empirical speed data is needed. Therefore, Floating Car Data in 153 curves in The Netherlands were collected at a resolution of 1 Hz and were filtered on free-flow periods, to analyse over 800 thousand unique continuous free-flow speed observations on these curves. Regression models were developed to predict speed development, including deceleration and acceleration behaviour upon entering and exiting freeway curves. The models rely on easy to generate geometric design variables, including the start and end position of the horizontal curve, the horizontal radius and the number of lanes. Using these variables, the designer can predict the speed development based on the 85th percentile of speed and acceleration, relative to the position of the curve. The regression models reveal strong goodness-of-fit of the predicted 85th percentiles of speed in a curve, showing acceleration and deceleration inside the curve, and higher predicted 85th percentile speeds than the design speeds. The models also show satisfying results in speed development prediction in sets of consecutive curves with different characteristics, as well as deceleration when entering a first curve and acceleration when exiting a last curve. These insights are valuable in evaluating road design in relation to traffic safety based on its predicted use.
  PubDate: 2022-06-24
  DOI: 10.18757/ejtir.2022.22.2.6114
  Issue No: Vol. 22, No. 2 (2022)
The border effect in European air transport
- Authors: Zdeněk Tomeš, Vlastimil Reichel, Štěpán Veselý
  Pages: 224 - 233
  Abstract: This article deals with the analysis of the border effect in European air transport. The border effect measures how trade or transport flows are diminished when they cross a national border. This topic has attracted a great deal of attention within trade, but it is still little studied within transport. Existing studies have estimated that the border effect diminished air passenger transport flows by a factor of five to six. However, there have been many changes in the European economy and transport since those studies. Our estimate based on a new data set suggested the existence of a border effect in European passenger air traffic flows, albeit with a lower value of around two. A possible reason for the lower value is the growing integration of the European economy and the development of low-cost carriers in Europe between 2000 and 2019. Our econometric analysis also found differences in border effects among European countries. No significant border effect was detected for France, but we did find high and significant effects for Germany, Spain, and Poland. These differences can be attributed to different intensities of intermodal competition on domestic routes.
  PubDate: 2022-06-24
  DOI: 10.18757/ejtir.2022.22.2.5773
  Issue No: Vol. 22, No. 2 (2022)