A critical component in freight transportation is the waybill, which is a transport document that has essential information about a consignment. Actors within the supply chain handle not only the freight but also vast amounts of information,which are often unclear due to various errors. An electronic waybill (e-Waybill) solution is an electronic replacement of the paper waybill in a better way, e.g., by ensuring error free storage and flow of information. In this paper, a systematic review using the snowball method is conducted to investigate the state-of-the-art of e-Waybill solutions. After performing three iterations of the snowball process,we identified eleven studies for further evaluation and analysis due to their strong relevancy. The studies are mapped in relation to each other and a classification of the e-Waybill solutions is constructed. Most of the studies identified from our review support the benefits of electronic documents including e-Waybills. Typically, most research papers reviewed support EDI (Electronic Documents Interchange) for implementing e-Waybills. However, limitations exist due to high costs that make it less affordable for small organizations. Recent studies point to alternative technologies that we have listed in this paper. Additionally in this paper, we present from our research that most studies focus on the administrative benefits, but few studies investigate the potential of e-Waybill information for achieving services, such as estimated time of arrival and real-time tracking and tracing.

We present a study on information synergy between an electronic waybill (e-Waybill) and intelligent transportation system (ITS) services. A waybill is an important transport document, and it contains essential information about a consignment. We consider five e-Waybill solutions, which differ in where the e-Waybill information is stored, read, and written. We analyse 20 ITS services, and for each of them, the required input entities that can be provided by an e-Waybill are identified, and the synergy with each of the e-Waybill solutions is determined based on the location of the e-Waybill information. The analysis shows that e-Waybill solutions with storage at the freight-level enable the highest information synergy with ITS services. Our result may support the implementation of practical e-Waybill systems that provide high synergy with ITS services, which may lead to higher utilisation of ITS services and more sustainable transport, e.g., in terms of reduced congestion and emissions

An electronic waybill (e-Waybill) is a service whose purpose is to replace the paper waybill, which is a paper documents that traditionally follows a consignment during transport. An important purpose of the e-Waybill is to achieve a paperless flow of information during freight transport. In this paper, we investigate five e-Waybill solutions, that is, system design specifications for the e-Waybill, regarding their non-functional (technical) requirements. In addition, we discuss how well existing technologies are able to fulfil the identified requirements. We have identified that information storage, synchronization and conflict management, access control, and communication are important categories of technical requirements of the e-Waybill service. We argue that the identified technical requirements can be used to support the process of designing and implementing the e-Waybill service.

We present results from a simulation study, whichwas designed for investigating the potential positive impacts, i.e., the invoicing and processing time, and financial savings,when using an electronic waybill instead of paper waybillsfor road-based freight transportation. The simulation modelis implemented in an experiment for three different scenarios,where the processing time for waybills at the freight loadingand unloading locations in a particular scenario differs fromother scenarios. The results indicate that a saving of 65%–99%in the invoicing time can be achieved when using an electronicwaybill instead of paper waybills. Our study can be helpful todecision makers, e.g., managers and staff dealing with paperwaybills, to estimate the potential benefits when making deci-sions concerning the implementation of an electronic waybillsolution for replacing paper waybills.

In this paper, we propose a method for supporting the process of designing Intelligent Transportation System (ITS) services, which utilizes on primarily functional synergies with already existing services. Using synergies between services will enable sharing of resources, such as, information entities, functions and technical resources, which in turn may lead to reduced costs for implementing services. The method is built around an existing service description framework, which is used to describe both existing services and the service to be designed. In order to illustrate the usage of the suggested method, we have applied it for designing a new ITS service, i.e., the Liability Intelligent Transport System (LITS) service. The purpose of the LITS service is to support the process of identifying when, where and why freight has been damaged, and which actor was responsible when the freight was damaged. The LITS service may lead to better quality control of consignments and may also facilitate the identification of which actor was responsible for the freight damage, which is of particular interest in multi-modal transport. By applying our service design method we were able to identify that three out of four functions of the LITS service already exist in other existing ITS services. Therefore, the LITS service can be designed based on synergies with these services.

A waybill is a document that accompanies the freight during transportation. The document contains essential information such as, origin and destination of the freight, involved actors, and the type of freight being transported. We believe, the information from a waybill, when presented in an electronic format, can be utilized for building knowledge about the freight movement. The knowledge may be helpful for decision makers, e.g., freight transport companies and public authorities. In this paper, the results from a study of a Swedish transport company are presented using order data from a customer ordering database, which is, to a larger extent, similar to the information present in paper waybills. We have used the order data for predicting the type of freight moving between a particular origin and destination. Additionally, we have evaluated a number of different machine learning algorithms based on their prediction performances. The evaluation was based on their weighted average true-positive and false-positive rate, weighted average area under the curve, and weighted average recall values. We conclude, from the results, that the data from a waybill, when available in an electronic format, can be used to improve knowledge about freight transport. Additionally, we conclude that among the algorithms IBk, SMO, and LMT, IBk performed better by predicting the highest number of classes with higher weighted average values for true-positive and false-positive, and recall.

We present a method, which makes use of historical vehicle data and current vehicle observations in order to estimate 1) the route a vehicle has used and 2) the freight the vehicle carried along the estimated route. The method includes a learning phase and an estimation phase. In the learning phase, historical data about the movement of a vehicle and of the consignments allocated to the vehicle are used in order to build estimation models: one for route choice and one for freight allocation. In the estimation phase, the generated estimation models are used together with a sequence of observed positions for the vehicle as input in order to generate route and freight estimates. We have partly evaluated our method in an experimental study involving a medium-size Swedish transport operator. The results of the study indicate that supervised learning, in particular the algorithm Naive Bayes Multinomial Updatable, shows good route estimation performance even when significant amount of information about where the vehicle has traveled is missing. For the freight estimation, we used a method based on averaging the consignments on the historical known trips for the estimated route. We argue that the proposed method might contribute to building improved knowledge, e.g., in national road administrations, on the movement of trucks and freight.