Scholarly article on topic 'Development of Advanced Technologies (AT) in Green Transport Corridors'

Development of Advanced Technologies (AT) in Green Transport Corridors Academic research paper on "Civil engineering"

CC BY-NC-ND
0
0
Share paper
Academic journal
Procedia Engineering
OECD Field of science
Keywords
{transport / "advanced technologies" / "green transport corridors" / "freight transportation" / information / communication}

Abstract of research paper on Civil engineering, author of scientific article — Nijolė Batarlienė, Aldona Jarašūnienė

Abstract The paper presents tendency analysis for advanced technologies. Advanced technologies – is an area having different acceptability and local adaptation levels in different countries, thus it is particularly important to be acquainted with its application possibilities and techniques. Contributing to a more efficient use of existing transport infrastructure, AT becomes a powerful tool in improving mobility conditions and optimizing transport activities. The importance of advanced technologies application in different modes of transport is examined. The functionality of advanced technologies application in different modes of transport is indicated and all elements of the transport system are taken into account. Relational database structures are provided; aspects of information and communications, multi-stage transport chains are distinguished. The optimal functionality of road transport and port interaction is particularly important in freight transportation by green transport corridors where transport modes are combined and activities are coordinated. The carried-out analysis of advanced technologies application possibilities in freight transportation by green transport corridors indicated that issues must be explored and solutions are to be suggested. On the basis of these solutions, it is possible to make the efficient use of freight delivery (exportation) by road transport to (from) the seaport. For this purpose, efficiency analysis model of road transport and port interaction while developing freight transportation by green corridors is suggested. The developed model provides an opportunity to evaluate how efficiently road transport is employed in the green corridors, where cargo is transported to/from the seaport.

Academic research paper on topic "Development of Advanced Technologies (AT) in Green Transport Corridors"

Available online at www.sciencedirect.com

ScienceDirect

Procedía Engineering

CrossMark

ELSEVIER

Procedía Engineering 134 (2016) 481 - 489

www.elsevier.com/locate/procedia

9th International Scientific Conference Transbaltica 2015

Development of Advanced Technologies (AT) in Green Transport Corridors

Nijolè Batarlienè, Aldona Jarasunienè*

Vilnius Gediminas Technical University, Plytinés g. 27, LT-10105 Vilnius, Lithuania

Abstract

The paper presents tendency analysis for advanced technologies. Advanced technologies - is an area having different acceptability and local adaptation levels in different countries, thus it is particularly important to be acquainted with its application possibilities and techniques. Contributing to a more efficient use of existing transport infrastructure, AT becomes a powerful tool in improving mobility conditions and optimizing transport activities. The importance of advanced technologies application in different modes of transport is examined. The functionality of advanced technologies application in different modes of transport is indicated and all elements of the transport system are taken into account. Relational database structures are provided; aspects of information and communications, multi-stage transport chains are distinguished. The optimal functionality of road transport and port interaction is particularly important in freight transportation by green transport corridors where transport modes are combined and activities are coordinated. The carried-out analysis of advanced technologies application possibilities in freight transportation by green transport corridors indicated that issues must be explored and solutions are to be suggested. On the basis of these solutions, it is possible to make the efficient use of freight delivery (exportation) by road transport to (from) the seaport. For this purpose, efficiency analysis model of road transport and port interaction while developing freight transportation by green corridors is suggested. The developed model provides an opportunity to evaluate how efficiently road transport is employed in the green corridors, where cargo is transported to/from the seaport.

© 2016Publishedby ElsevierLtd. This isanopenaccess article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of the organizing committee of Transbaltica 2015

Keywords: transport; advanced technologies; green transport corridors; freight transportation; information; communication.

* Corresponding author E-mail address: aldona.jarasuniene@vgtu.lt

1877-7058 © 2016 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license

(http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of the organizing committee of Transbaltica 2015

doi:10.1016/j.proeng.2016.01.004

1. Introduction

Advanced technologies (AT) - is an area having different acceptability and local adaptation levels in different countries, thus it is particularly important to be acquainted with its application possibilities and techniques.

Contributing to a more efficient use of existing transport infrastructure, AT becomes a powerful tool in improving mobility conditions and optimizing transport activities. Currently, the majority of European countries are engaged in implementing AT - based services pursuing to increase the benefits of investments into transport infrastructure. About it was presented by Mckinnon (2009), Root (2003) and in works of Communications from the Commission ("Communications" 2006, 2007, 2009). As the European Action Plan for AT shows, currently the development of AT is one of the priorities in EU transport policy. The main aim - to ensure AT-based service continuity in order to create conditions for smooth freight mobility across Europe including green corridors (Comtois, 2010), (Panagakos, Psaraftis 2011).

As has been shown (Greiciuné, Jarasuniené 2013) green corridors can be characterized by intermodal freight transportation by environmentally-friendly mode of transport at the larger part of the road. The Green transport corridor is the concept of an integrated transport which complementary relates short - distance navigation, railway, inland waterway and road transport with the objective of securing the functioning of environmentally friendly transport system and advanced technologies application (Fozza, Recagno 2012).

The congestion of transport systems is constantly increasing. Forecasts indicate that by 2020 the flow of freight transport will increase by 55 percent. Traditional means, e.g., development of currently existing transport networks will be useless, therefore the need to find new solutions to this problem arises. Advantages of advanced technologies application are obvious since any route can be planned by including several modes of transport; all the actions can be coordinated operationally in any case of possible danger to traffic safety (Batarliené, Jarasuniené 2013; Elvik, Vss 2004; Elvik et al. 2009). Such optimization of traffic system reduces road congestion, allows planning travels efficiently and increases traffic safety, which is relevant in freight transportation by green corridors (Anciaux & Yuan, 2009).

Advanced technologies unite all the elements of a transport system - transport means, transport infrastructure, drivers and consumers - that interact dynamically. A great variety of services are being used simultaneously while applying advanced technologies, thus the architecture of these systems is particularly important in showing an agreement between consumers, service providers and transport companies, expressed in general terms and obligations. Establishment and application of AT architecture adds a significant value to entire AT development process. Its application areas and provided advantages are defined in the paper. In addition to this, the functions of advanced technologies and specific measures are provided.

Advanced technologies application in all modes of transport and increase of energy efficiency in transport sector are distinguished in the National Programme on the Development of Transport and Communications for 2014-2022. However, one fundamental issue is observed - AT are introduced in different modes of transport separately, but a unified advanced technology platform which would coordinate the entire transportation process, real-time monitoring of different modes of transport, especially intermodal freight transportation in Lithuania, is still missing. As Greiciuné and Jarasuniené (2013) demonstrated, the development and integration of this general system would enable to organize freight transportation by green corridors in Lithuania and overseas more efficiently.

2. The importance of advanced technologies (AT) application in freight transportation by green transport corridors

Advanced technologies (AT) is a new and very important concept in freight transportation process. Caris, Macharis, and Janssens (2008, 2009) found that advanced technologies can be simply described as freight transportation process managed in real-time where problems are operatively identified and solved prior customer's notice. AT application is associated with delivery time of the goods and continuity of intermodal freight transportation process as Yao-Rong, Ming, Yue (2009) demonstrated.

Advanced technologies (AT) is also defined as information and communication technology application in the area of transport. Advanced technologies - is a general term referring to integrated connections, control and

information processing technology application in transport system. The benefits it provides may save lives, time, money, energy and environment. The term AT is flexible and may be interpreted in broad or narrow definitions (Chowdhury, Sadek 2003), (Monsere 2009). AT covers all branches of transport and considers all dynamically interacting elements of transport system, i.e. transport means, infrastructure, driver and consumer. AT present a realtime information about the current situation in the roads or present it interactively, this, in turn, helps to better plan all travels for ordinary drivers, road operators, Government.

Advanced technologies are applied in freight transportation by green corridors. The aim of each project in the development process of advanced technologies is to integrate several transport business stakeholders (road and other transport network operators, police, customs, telecommunications operators, etc.) employing the following technologies: satellite navigation systems; information and communications technology (system for mobile communications, positioning, navigation and tracking algorithms, calculation distributions, etc.); radars, advanced sensor elements (vehicle-mounted road detector or distributed in road infrastructure) (Kirikova et al. 2002). Advanced technologies application requires sensible synergies between business and stakeholders. International traffic growth puts a significant pressure to ensure safe freight transportation, speed up the operations of the port terminals, cut taxes and offer additional services (Konings et al. 2008). These requirements result in increased demand for more investments in port infrastructure and its internal connections, promote technological innovations in order to increase efficiency of the existing infrastructure (Hui, Yan-Ling 2009), (Jarasuniene et al. 2012).

Satellite-based navigation system applications in transport. With the increased number in vehicle fleet, it is thus more difficult to monitor and detect real-time information on location and activities of the vehicles. Therefore, technological solutions of GPS, GSM and radio controlled communications gained its popularity among carriers. GPS devices receive signals from several different satellites and calculate the position of the transport means. This requires a direct line of sight to the satellites. Some countries, the Netherlands and Germany in particular, employ GPS devices that record distances for vehicles.

The analysis of scientific literature revealed that authors provide different definitions for GPS. GPS - is a radio navigation system that employs artificial satellites to detect geographical location (amplitude, longtitude) and the height of a fixed position above the sea level. A GPS receiver, which accepts and process radio signals is used to determine the position of an object. After having processed radio signals, GPS determines a satellites' location in space as well as the distance between them two. This allows determining locations of both stationary and mobile objects. In accordance with the changes in mobile object position, it is possible to calculate its velocity, direction and other parameters (Greiciune, Jarasuniene 2013).

Global positioning system is defined as a high-precision satellite radio navigation system that provides information on the position of objects in space, their velocity, direction, distance between the selected points on the exact time specified, the necessary geographical location parameters - sunrise/sunset times, moon phases (Greiciune, Jarasuniene 2013).

GPS navigation systems are divided into:

1. According to the method of the mounting: Stationary (consisting of separate parts - navigation computer and the screen), radio navigation system (visually resembles tape-recorder which shows directions and provides audio information);

2. According to the types of transport means: automobiles, trucks, semi-trailer trucks, buses, trailer buses.

Currently, all European business entities use one of the two military-controlled system services - GPS or

GLONASS, which means that safety of European Communities, is not appropriately ensured.

It is argued, that GALILEO system is most suitable for Europe. This satellite navigation system is designed for all modes of transport and systems to connect at the macro level (Jarasuniene 2008).

"WebFleet" - a service of the management and control of transport means, provided in the European Union countries, Belarus, Russian Federation and the Urals, where GSM communication is possible. Running on every operating system and every browser, "WebFleet" service provides an opportunity to track location of transport means, route, speed, fuel consumption, temperature control in the cargo area, hydraulics and other compatible parameters in the real-time (Greiciune, Jarasuniene 2013).

Satellite security and control system of mobile objects "MobiSafe". This system is often used for the protection of transport means as well as for ensuring security and safety during the forwarding process, e.g. of a valuable freight. Transport means are fitted with particular equipment which allows to detect the location by the means of

geostationary orbits. Information from the satellites is sent to a centralized security panel (panels). Twenty-four satellites are positioned in a way that each "MobiSafe" block would receive signals from the three satellites.

Control system "EutelTRACS" - an emergent transmission of emergency signals, monitoring of freight and transport means parameters etc. As has been shown (Ezzel 2010), (Monsere 2009) this satellite system allows the management of freight and transport means' movement.

Transport management system "NaviSat". It is crucial to know the current information about the activities of transport means in transportation business. "NaviSat" system allows operators to know the exact whereabouts of transport means.

Application of New information technologies fundamentally alters functioning and development of transport organizations.

Innovations of advanced technologies allows: detect cargo, transport means, its location and drivers; select an optimal route depending on the availability of cargo and appropriate transportation equipment, traffic and weather conditions, type of the cargo, determine the optimal route of cargo transportation and efficient use of human resources (Jarasüniené 2008).

RFIDS application possibilities have a critical advantage over currently most widespread classic barcodes in logistics.

One of the major RFID advantages is that it does not require a line-of-sight process between a transponder and a reader. This enables to read unevenly attached RFID tags or microchips fitted in the package. In addition to this, several RFID microchips can be read simultaneously.

RFID application possibilities: collection of the tolls, without having the vehicle to stop at the toll booth; identification of the trucks, located near the factories, ports or at the gates of logistics centers and the use of diverse information signs indicating the location of the cargo; identification of the containers and truck trailers in ports, railway stations and truck terminals thus avoiding "lost" containers and trailers and efficiently combaining handling equipment works and cargo; identification of the trucks at the regular stopping points (border crossings, weigh stations, checkpoints); identification of the drivers violating work/rest schedule.

In order to solve the aforementioned issues, it is thus necessary to develop an integrated model of advanced technologies on the basis of which the participants of diverse transport means would exchange information in the real-time. This would lead to implementation of a "single window system", designed for all modes of transport; it would be possible to prepare a single transport document for cargo transportation by green corridors regardless of the transport mode. Additionally, it would be possible to transfer paper-based documents into digital format.

The practical application of integrated model of advanced technologies may serve as the foundation for drawing up a plan on the basis of which the implementation of advanced technologies would increase the efficiency of transportation services (Baublys 2001), (Cekavicius, Murauskas 2002).

However, implementation of the model in Lithuania is only possible by complex coordination of scientific, economic, legal, social and other aspects.

3. Efficiency analysis model of road transport and port interaction while developing freight transportation by green corridors

Development of freight transportation by green corridors requires an important evaluation of the efficiency of road transport and port interaction, where cargo are transported to/from the seaport (Ezzel 2010). Random factors at the queue during downtime have major impact on transportation process by green corridors (depending on the number of transport means); unloading and delivering cargo to the client; time of the travel from loading to unloading points; time of the recurrence to empty-vehicle travel time. The latter two factors are random variables, which vary depending on road, weather conditions, etc. (Anciaux, Yuan 2009), (Yuchuan et al. 2010).

It is possible to claim, that one transport means carries h tons of cargo at one trip (Strauch et al. 2007). On average, one transport means performs k trips over particular period of time. Total amount of cargo in tons, carried by one transport means over particular period of time is equal to kh. The average duration of the trip can be marked by t (h), and duration of the shift - T(h).

If there is transport means N, thus the amount of cargo transported over particular period of time:

Mb = TIt . (1)

In order to calculate Mb, it is necessary to determine the t variable. Unloading process does not result in queues, thus:

t =te + ti + tn , (2)

here te - the average time spent on the road and unloading the cargo (i.e. the average time from the moment when loaded vehicle leaves the port till the moment it comes back for another cargo); tl - the average waiting time in the queue for loading; tn - the average loading time.

Therefore, if the variable t is independent from the number of transport means, the total transportation volume would be directly proportional to the number of transport means N.

The increasing number of transport means results in an increase of the queue, waiting time tn and the value t as

well. The time tn and tn (together with t) can be reduced by employing more than one handling equipment.

Possible transportation options: 1) transportation from the port to one main consumer; 2) There are many minor consumers; transportation volumes for each of them are relatively low in comparison with overall transportation volumes; 3) both options possible.

The first option can be presented as a Closed Queueing System. The second option - as an Open Queueing System, where the intensity of incoming flow practically does not depend on changes in the number of transport means allocated to a particular consumer. The third option cannot be examined by analytical methods of Queuing Theory and can only be investigated by applying simulation methods.

Random variables presented as follows: t - time taken to load one transport means, and n - the overall time spent on cargo transportation, unloading operations and return journey to the port.

Distributions of these variables are marked accordingly: S(x) and F(x), S(x) = P{t< x}, F(x) = P{n < x}. S(P) - Laplace transform of the random variable t distribution function:

~(p)= j - PxdS(x), P > 0. (3)

The average loading time tn is a mathematical hope of random variable, thus:

= J xdS (x). (4)

In order to calculate the average amount of cargo, transported over particular period of time, it is necessary to determine the variable t - the average duration of the trip, when N transport means are participating and N handling equipment is used.

Service time for vehicles includes the time required to load cargoes, waiting time in the queue, the time of the loaded-vehicle stay in the port; as well as the time up to the moment when newly arrived vehicle arrives at the loading dock and joins the queue (if all the handling equipment is occupied) or stops for loading (if the handling equipment is unoccupied).

X variable, inverse to mathematical hope of random variable:

X = 1IJ xdt (x)= 1I tv

In order to determine variable t we assume, that time taken for vehicle in n, is exponentially distributed, i.e. F(x) = 1 - . This assumption has no impact on the value of random variable t , since there are more than 5 requirements (N > 5) and it is confirmed by Limit Theorems of Probability Theory. mv - The average number of vehicles that are either loaded or waiting in the queue.

The example of one handling equipment being used:

= N--— (1 - e),

' N-1 (N -1)

1 - Nltn Y 1)! n ¿—i (

e=09n -1 - e)e! F(e)

and function F(e) fixed, when e = 0, 1, 2, ..., F (e) =

n-^fe^, when e = 1, 2,

|=}1 - s(a)

1, when e = 0.

The number of transport means N, i.e. transport means, that are loading or waiting in the queue, will be:

N = mv . (9)

The average intensity of the flow Xv:

Av = A(N - mv). (10)

The average waiting time tv = tl + tn is the ratio:

tv = mv / Av . (11)

From the formulas (10) and (11), considering that X = 1/te, we have:

tv = ^ = N - -L (1 -e), xj- (1 - e) = Ne ~te (12)

Av jtn jtn 1 - e

will be:

t = tl + tn + te = tv + te = Ntn /(1 - e) , (13)

here, the value e is determined by (12) and (13).

In the case of several handling equipment under operation, performance calculation methodology is applied when service time is exponentially distributed. We assume this particular case in S(x) = 1 - e(x(x / tn)). If the distribution function S(x) is substantially different from the exponential law, then t can only be determined by simulation methods (Hui, Yan-Ling 2009), (Jarasuniene et al. 2012). We note that p = ltn. Then:

N! _p_ I k1 (N - k)n! nk-n P° +1 (N - k)k!

here pn - possibility, that the system is empty.

It follows, that the average intensity of incoming flow is equal to 1 (N - Mv). Variable t can be found in accordance with (11):

t = fi + tn = mv / ÄN - mv ) = tlmv / N - mv ,

t = te + tt + tn = te + temv / N - mv = te (l + mv / N + mv ),

here mv is determined by (14).

We will explore the option, where cargo is being delivered to more than one consumer.

We will analyze handling equipment and queues next to it. Incoming flow intensity is X. If p(x) - time distribution function between transport means, thus:

X = 1/ J xdß (x).

Standard deviation of the length of intervals between the appearance of applications is marked by ax

J (x -1/ A )2 dß (x)

Standard deviation of service time is marked by aM:

j (x-tn )2 dF (x)

Vx - Coefficient of application variation intervals; V^ - Coefficient of service time variation: Vx = ! , VM = aM / tn .

Since the portion allocated for each client is small, we will assume, that the replacement of vehicles for analyzed consumer practically has no impact on A. If it is not so, it is thus possible to assume that A = A (N) depend on N, however, this type of dependency can be determined upon expert evaluation.

We note that p = A /M and explore the case where there is one handling equipment, thus t is determined in accordance with the following formula:

t{p 2 (v2 + VM )/[2A(1 - p)]j+tn = ¡A2 + tn2 (ajX2 + 1„2 )/2A(1 -1% j+t;

There are several requirements for the flows and these are not substantial, thus it is possible to assume, that the incoming flow - is Poisson flow. The formula for incoming Poisson flow Vx = oA = 1 and (21) is accurate. Value t can be determined in accordance with the formula:

t = te +1 , (22)

here t is determined in accordance with (21) formula.

In the case of n handling equipment and n > 1, transport mode interaction in the terminal is presented as the Queuing system along with the incoming Poisson flow. The mean of requirements in the system is calculated:

t _ 1 - o2/ tj tn (Atn )2 pp

tl _-7-^-w (23)

Z (n - Itn )2 (n - 1)

p0 - probability, that an open z - channel system with the incoming Poisson flow, which intensity A, and exponential service time distribution functions with tn mean, do not have requirements:

£ (0) + (K )"+1

k n4(n - A)

The average duration of the trip can be determined by the formula:

t =te + h + tn , (25)

here tt determined by the formulas (21) and (25).

The developed model provides an opportunity to evaluate how efficiently road transport is employed in the green corridors, where cargo is transported to/from the seaport.

4. Conclusions and recommendations

1. The carried-out analysis indicates, that one of the major issues lies in the poor integration of multimodal IT developed in different modes of transport on the basis of which it would be possible to organize freight transportation in a more safe, fast and efficient way.

2. It is thus revealed, that AT do exist at the project level, i.e. functions assigned by legislative acts within institutions can be performed by the means of AT, however, mostly it is not the case. AT application is usually implemented by separate institutions or private enterprises, thus making it difficult to combine separate AT. In the absence of clear legal regulatory basis and theoretical association between state institutions' functions and AT, it is thus difficult to distinguish separate state and local government functions and limits of liability in AT development.

3. AT application is important and related to traffic congestion and modelling of new information technologies, synergy of real-time control and communications network. One of the major issue is that so far the integration of different modes of transport into one single system is not possible. There is no single standard cargo information exchange system that covers all modes of transport (sea, road, rail) and this prevents from efficient reassurance of freight transportation organization processes in the green corridors.

4. On the basis of the carried out research on advanced technologies application in the provision of transportation services, it is possible to conclude, that the maximum interference that creates obstacles in the development process of a unified information system that covers marine, rail and road transport, road transport enterprises and state institutions, is insufficient flexibility and lack of attention paid to the relevance of the issue.

5. The proposed theoretical model would help to solve issues in the transportation process related to time, price, quality and innovation aspects. The presented transport integration would promote not only business consolidation, which respectively enhance competitiveness, but also efficiency of documentation and legal affairs. Model would exploit positive features of transport modes and its systems; additionally it would help to

develop a concept of combined transport, which would provide prerequisites for becoming the most perspective development direction in the green corridors.

References

Anciaux, D.; Yuan, K. 2009. Green Supply Chain: Intermodal Transportation modelling with environment impacts.

Batarliene, N.; Jarasüniene, A. 2009. Research on advanced technologies and their efficiency in the process of interactions between different transport modes in the terminal, Transport 24(2): 129-134. Vilnius, MA: Technika. doi:10.3846/1648-4142.2009.24.129-134

Batarliene, N.; Jarasüniene, A. 2013. Lithuanian road safety solutions based on intelligent transport systems, Transport 28(1): 97-107. Technika. doi: 10.3846/16484142.2013.782895. ISSN 1648-4142.

Baublys, A. 2001. Keli^ transporto s^veikos su uostu efektyvumo analizes modelis, Transportas 16(1) : 8-10. Vilnius: Technika. ISSN 13921533.

Caris, A.; Janssens, G. K.; Macharis, C. 2009. Modelling Complex Intermodal Freight Flows. From System Complexity to Emergent Properties, 291-300.

Caris, A.; Macharis, C.; Janssens, G. K. 2008. Planning Problems in Intermodal Freight Transport: Accomplishments and Prospects. Transportation Planning and Technology 31(3): 277-302. Taylor & Francis.

Cekavicius, V.; & Murauskas, G. 2002. Statistika ir jos taikymas. Vilnius, MA: TEV, 239 p.

Chowdhury, M. A.; Sadek, A. W. 2003. Fundamentals of intelligent transportation systems planning. Artech House, INC. Norwood, MA: 02062, 2003, 201.

Communication from the Commission. 2007. Freight Transport Logistics Action Plan (SEC 1320, SEC 1321) Luxemburg. Office of official publications of the European Communities.

Communication from the Commission. 2009. A sustainable future for transport: Towards an integrated, technology-led and user friendly system. Luxemburg: Publications office of the European Union, ISBN 978-92-79-13114-1.

Communication from the Commission to the Council and the European Parliament. 2006. Keep Europe moving - Sustainable mobility for our continent. Mid-term review of the European Commission's 2001 Transport White paper (SEC 768). Luxemburg: Office of official publications of the European Communities.

Comtois, C. 2010. Marketing Green Logistics: Environmental Strategies for Transportation Based Gateways And Corridors. Vancuver BC.: Proceeding of the 2nd international conference on gateway and corridors 2010.

Elvik, R.; Vss, T. 2004. The Handbook of Road Safety Measures. Elsevier. 1078. ISBN-10:0-08-044091-6.

Elvik, R.; Hoye, A.; Vaa, T.; Sorensen, M. 2009. The Handbook of Road Safety Measures (2nd edition). Bingley BD 16 IWA, UK. Emerald Group Publiching Limited.

Ezzel, S. 2010. Intelligent transportation systems. Washington. Retrieved from http://gigaom.files.wordp.../2010/01/its2010 report.pdf (http://gigaom.files.wordp.../2010/01/its2010 report.pdf).

Fozza, S.; Recagno, V. 2012. Sustainable technologies and innovation for green corridors: survey and application. Transport research arena-Europe 2012, 1753-1763.

Greiciüne, L.; Jarasüniene, A. 2013. Analysis on the application of intellectual technologies (IT) in Lithuanian intermodal transport. Reliability and statistics in transportation and communication (RelStat'13), Riga: Transport and Telecommunication Institute, 272-276.

Greiciüne, L.; Jarasüniene, A. 2013. Research on the efficiency of transportation services by applying information technologies. Reliability and statistics in transportation and communication (RelStat'13), Riga: Transport and Telecommunication Institute, 245-248.

Hui, L. ; Yan-Ling, X. 2009. The Traffic Flow Study Based on Fuzzy Influence Diagram Theory. Second International Conference on Intelligent Computation Technology, 845-848.

Jarasüniene, A. 2008. Intelektualiosios transporto sistemos. Vilnius: Technika. 2008.

Jarasüniene, A.; Greiciüne, L.; Sakalys, A. 2012. Research of competitive environment of Klaipeda seaport comparing to other seaports in the eastern Baltic Sea region, Transport 27(1): 5-13. Vilnius: Technika. doi: 10.3846/16484142. 2012.662911. ISSN 1648-4142.

Kirikova, M.; Grundpenkis, J.; Wojtkowski, W. 2002. Information systems development: advances in methodologies, components, and management. New York.

Konings, R.; Priemus, H.; Nijkamp, P.; Kreutzberger, E. 2008. The Future of Intermodal Transport. United Kingdom, Cheltenham. MA: Edward Elgar Publishing.

Mckinnon, A. 2009 October 2. Innovation in Road Freight Transport: Achievements and Challenges. International Transport Forum. Retrieved from IMTT Seminar on Innovation in Road Transport: Opportunities for Improving Efficiency. Lisbon.

Monsere, Ch. M. 2009. Developing corridor-level truck travel time estimates measures from archived its data. Final report SPR 304-361.

Panagakos, G. P.; Psaraftis, H. N. 2011 June 22-24. Key performance indicators for green corridors in European freight Transportation. European Conference on Shipping Intermodalism & Ports (ECONSHIP 2011). Chios, Greece.

Root, A. (2003). Delivering sustainable transport - a social science perspective. Oxford: Elsevier Science, 17-33.

Strauch, D., Moeckel, R., Wegener, M., Gräfe, J., Mühlhans, H., Rindsfüser, G., & Beckmann, K.-J. (2007). Linking Transport and Land Use Planning: The Microscopic Dynamic Simulation Model ILUMASS. 15.

Yao-Rong, Ch.; Ming, S.; Yue, Ch. 2009. The analysis and calculation of the cost of intermodal freight transport. Second International Conference on Intelligent Computation Technology and Automation. doi: 10.1109/ICICTA. 824, 451-454

Yuchuan, D.; Ziyi, Z.; Lijun, S. 2010. Novel Statistical Analysis Approach for Free-flow Speed on Real-time Traffic Data. 7h International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2010), 2844-2848.