With a focus on cargo transportation, this book addresses the development of approaches intended to secure an infrastructure of smart services to support the adaptive implementation of online multi-modal freight transport management processes. It discusses the development of multi-criteria decision-making components and their integration into the multi-layered computer-based information management of intelligent systems.
Through detailed descriptions of various components of intelligent transport management systems, the book demonstrates how to develop the services needed in the right place and at the right time, and how to properly adapt to user needs, making necessary interventions to ensure the safety of the transportation process. Further, it describes the main ways to increase the autonomy and efficiency of user-vehicle interaction and shows how Information and Communications Technology (ICT) structural support for current and past situations in AI-based systems can help to anticipate future developments in freight transportation.
Author(s): Dalė Dzemydienė, Aurelija Burinskienė, Kristina Čižiūnienė, Arūnas Miliauskas
Series: International Series in Operations Research & Management Science, 330
Publisher: Springer
Year: 2022
Language: English
Pages: 424
City: Cham
Preface
Author Contributions
Acknowledgements
Contents
Chapter 1: Introduction to Research Area
1.1 Importance of the Research
1.2 Topicality of the Research Problem
1.3 Integration of Context Recognition in Freight Transport Management
References
Chapter 2: Structure of Context Recognition in Computer-Based Systems for Transportation Management
2.1 Related Works in the Research Area of Context Analysis for Transportation
2.2 Understanding the Context of Information According to Scenario-Based Approaches
2.3 Methods for Linking of Contextual Data with Components of Information Management System
2.4 Examples of Context Data Processing Methods
2.5 Needs for Aggregation of Contextual Data and Possible Solutions
2.6 Centralized Aggregation of Context Data
2.7 Distributed Context Data Aggregation
2.8 Cluster-Based Aggregation of Context Data
2.9 Conclusions
References
Chapter 3: Wireless Communication Network Infrastructure Analysis for Smart Service System Functioning
3.1 Issues of Infrastructure Development for Delivery of Smart Services for Transportation
3.2 Possibilities of Integration of Different Services in the Changing Topology of Transportation and Communication Networks
3.3 Requirements of Smart Service Delivery System
3.4 Methods for Collection of Contextual Data in Automotive Communication Systems
3.4.1 Sensor-Based Data Collection
3.4.2 Data Collection Based on Routing Protocols
3.5 Communication Infrastructure of Vehicles and Road Site Units
3.6 Areas of Automotive Communication
3.6.1 Wireless Access in Car Communication Networks
3.6.2 Sort Review of Infrastructure of V2V Communication
3.6.3 Possibilities of Mobile Connections
3.6.4 Key Features of Automotive Communication Networks
3.7 Control of Channel Resources for the Best Bandwidth
3.8 Conclusions
References
Chapter 4: Structure of Smart Service Provision System for Operative Management of Transportation
4.1 Componential View of Smart-SDS Architecture
4.2 Classification of Heterogeneous Services Provided for Transportation
4.3 Description of Algorithms for Assessment of Importance of Transmission of Messages and Context Data
4.4 Illustration of Experimental Results
4.5 Conclusions
References
Chapter 5: Towards the Transport and Corresponding Sectors
5.1 Importance of Transport Sector
5.2 Modelling the Transport Sector
5.3 Gordon Growth Model and Technology Adoption
5.4 Development of Transport Sector Towards Synchro-Modality and ICT
5.5 The Digitalization of Documents in the Transport Sector
5.6 Analysis of TIR and CMR Statistics for the Evaluation of E-Freight Documents in European Countries
5.7 The Role of ICT in Transport for Achieving Efficiency and Sustainability
5.8 Conclusions
References
Chapter 6: Variables Important for Freight Delivery and Context Data Usage
6.1 Freight Delivery Data: Time Variable
6.2 Freight Delivery Data: Location Variable
6.3 Freight Delivery: Types of Distances
6.4 Freight Delivery: Mode Selection
6.5 Freight Delivery Data: Economic Delivery Volume
6.6 Freight Delivery Data: Service Variable
6.7 Scope of Context Data Usage
6.8 Conclusions
References
Chapter 7: Automated Freight Brokerage Based on Multi-Agent Semantic Web Service Composition
7.1 Web Services
7.2 Semantic Web Services
7.3 Web Service Composition
7.4 Development of Multi-Agent Systems
7.4.1 Communication Between Agents
7.4.2 Coordination of Services between Artificial Agents
7.4.3 Implementation of Types of Ontology
7.5 Service Composition in Freight Transport Management
7.6 Development of Ontology for System of Freight Transport Management
7.7 Proposed Solution of Service Provision System Architecture
7.8 Conclusions
References
Chapter 8: Transport Network Design Methods and Context-Aware Service Specifics
8.1 Transport Network Design Studies
8.2 Classification of Transport Networks
8.3 Service-Oriented Transportation: Revision of Research Methods
8.4 Methods Proposed for Shared Transportation Service Design
8.5 Technologies and Data Management to Support Shared Transportation
8.6 Conclusions
References
Chapter 9: Context-Aware Service Support Efficiency Improvement in the Transport System
9.1 Context-Aware Service in the Transport System
9.1.1 Onboard Applications
9.1.2 Clouding
9.1.3 Supporting ITS
9.1.4 Driver Application
9.2 Investigating Modelled Contextual Data
9.3 Characteristics of the Transport System
9.4 Routing Algorithm
9.5 Clustering Applicable in Routing
9.6 Development of Routes Using Intelligent Data Management Components
9.6.1 The Construction of the Schedule
9.6.2 Assignment of Vehicle
9.6.3 Actual Routing
9.6.4 Getting Started
9.6.5 Steps for Route Construction
9.7 Costs Metrics Used to Calculate Transportation Service Costs
9.8 Distance Metrics Used for Calculating Transportation Costs
9.8.1 Summary of Distance in Backhauling Case
9.9 Timetable Metrics for Scheduling Services
9.9.1 The Model for Optimisation
9.10 Conclusions
References
Chapter 10: Cargo Delivery Management Process: Risks, Solutions, and Optimization
10.1 Cargo Delivery Process and Risk Management in the Application of Automatic Risk Assessment Tools
10.1.1 Methods Applicable to Risk Analysis in a Service-Oriented Transport System
10.2 Application of Multi-attribute Methods of Decision Support in the Process of Cargo Delivery Management
10.2.1 Description of Attributes in Decision Models for the Selection of Alternatives in Freight Transport
10.3 Application of Metaheuristic Methods Designed for Optimizing the Performance of Process of Cargo Delivery Management
10.4 Conclusions
References
Chapter 11: Methods of Data Collection, Aggregation, and Dissemination and Their Application
11.1 Collecting Data from Data Sources
11.1.1 Information Flows in Traffic Jams
11.1.2 Data Set Reported in Cases of Traffic Accident
11.1.3 Data Set for Monitoring Vehicle and Freights
11.1.4 Tracking of Road Vehicles
11.1.5 Cargo Tracking
11.2 Methods Used to Analyse Datasets
11.2.1 Validate Data Using the Outlier Discovery Method
11.2.2 Analysing Big Data Data Sets
11.2.3 Revision of Operational Data of Cargo Delivery
11.2.4 The Resolution of Conflicts During the Planning
11.3 Validate Trust and Privacy Data in a Context-Sensitive Service Application
11.4 Conclusions
References
Chapter 12: The Concept Towards Transportation Infrastructure and Its Capacity
12.1 Transportation Infrastructure
12.2 Demand Exceeding the Capacity of Transport Infrastructure
12.3 Policy Impact on the Life Cycle of the Infrastructure for Transport
12.4 Data-Driven Modelling of Transport Infrastructure
12.5 Conclusions
References
Chapter 13: Information Systems in Freight Transportation
13.1 Areas of Activities for Transport Sector by Implementing ITS
13.2 Decision-Making and Importance of Databases
13.3 Integration of Order Management and Enterprise Logistics Management Information System
13.4 The Main Needs of Information in Logistics
13.5 Classification of Information Systems for Logistical Management
13.6 Digitization of Freight Carriage and Its Relevance to Transportation Processes
13.7 Conclusions
References
Chapter 14: Information Technology Used in the Road Transport Sector
14.1 IT for Road Transport
14.2 Freight and Transport Platforms
14.2.1 Principle of Operation of the Freight and Transport Platform
14.2.2 European Freight and Transport Platforms
14.2.3 Asian and North American Freight and Transport Platforms
14.3 Conclusions
References
Chapter 15: Information Technology Used in the Railway Transport Sector
15.1 IT for Rail Transport
15.2 System of Traffic Management of European Rail (ERTMS)
15.3 Telematics Freight Carriage Applications
15.4 Train Protection System
15.5 Conclusions
References
Chapter 16: Information Technology Used in the Water Transport Sector
16.1 Inland Water Transport
16.1.1 River Information Services
16.1.2 Transport Logistic Service of River Information Services
16.1.3 Transport Logistic Service of River Information Services Users and Stakeholders
16.2 Maritime Transport
16.2.1 SafeSeaNet system
16.2.2 Port Information Systems in Transport
16.3 Overview of Ship Routes and Scheduling
16.3.1 Scheduling and Routing of Commercial Ships
16.3.2 Ship Scheduling and Routing in Freight Delivery
16.4 Conclusions
References
Chapter 17: Information Systems in Transport and Forwarding Activities
17.1 Good Foreign Practice of IT Application in the Process of Transportation
17.2 Information Technology Used in Forwarding
17.3 IT System Compatibility in the Transport/Logistics Area
17.4 Needs for Information Systems in the Transport Chain
17.5 Conclusions
References
Chapter 18: Information Technology Used in Intermodal and Multimodal Transport
18.1 IT Services That Promote e-Freight
18.2 Interoperability of Different Modes of Transport and the Related Problems
18.3 Information Technology Systems in Multimodal Transport
18.4 Systems of Decision Support and Big Data for Intermodal Transport Management
18.5 Conclusions
References
Chapter 19: Development of Intelligent Service System for Multimodal Transport Management
19.1 Introduction to Multimodal Transport Specifics
19.2 Multilayered Architecture of Smart-SDS with Integration of MC-DSS Components for Multimodal Transportation
19.3 Representation of Subsystems with Knowledge Base Structures
19.3.1 Structure of Decision Support Processes for Multimodal Transportation
19.3.2 Agent-Based Architecture of Subsystem for Planning of Transport Corridors
19.3.3 Representation of Semantical Models in KB
19.3.4 Formal Specification of Decision Support Processes
19.4 Representation of Functional Requirements of Multimodal Transportation in Simulation Models
19.5 Possibilities of Assessment of Risks in Multimodal Transportation
19.6 Conclusions
References
Glossary
