forecasting. Packed with strategies for forecasting future demand for all transport modes, the book helps readers
assess the validity and accuracy of demand forecasts.
Forecasting and evaluating transport demand is an essential task of transport professionals and researchers
that affects the design, extension, operation, and maintenance of all transport infrastructures. Accurate demand
forecasts are necessary for companies and government entities when planning future fleet size, human resource
needs, revenues, expenses, and budgets. The operational and planning skills provided in Modeling of Transport
Demand help readers solve the problems they face on a daily basis.
Modeling of Transport Demand is written for researchers, professionals, undergraduate and graduate students
at every stage in their careers, from novice to expert. The book assists those tasked with constructing qualitative
models (based on executive judgment, Delphi, scenario writing, survey methods) or quantitative ones (based on
statistical, time series, econometric, gravity, artificial neural network, and fuzzy methods) in choosing the most
suitable solution for all types of transport applications.
- Presents the most recent and relevant findings and research - both at theoretical and practical levels - of transport demand- Provides a theoretical analysis and formulations that are clearly presented for ease of understanding- Covers analysis for all modes of transportation- Includes case studies that present the most appropriate formulas and methods for finding solutions and evaluating results
Please Note: This is an On Demand product, delivery may take up to 11 working days after payment has been received.
1. Transport demand and factors affecting it 2. Evolution and trends of transport demand 3. Methods of modeling transport demand 4. Executive judgment, Delphi, scenario writing and survey methods 5. Statistical methods for transport demand modeling 6. Trend projection and time series methods 7. Econometric, gravity and the 4-step methods 8. Artificial intelligence
Neural network methods 9. Fuzzy methods
V.A. Profillidis is Professor for the Section of Transportation at Democritus University of Thrace, Greece. He holds
the Diploma in Civil Engineering from the University of Thessaloniki, MSc and PhD in Transportation from the
Ecole Nationale des Ponts et Chaussées in Paris, and the Diploma in Law from the University of Thessaloniki. He
has acted as a consultant to many transport authorities. He has taken part in many international conferences as
well as meetings of the European Union, the World Bank, and the European Conference of Ministers of Transport.
He has carried out a number of transport studies in modeling and forecasting of demand, transport economics
and feasibility methods, traffic analysis and demand, intelligent transport systems, sustainable mobility, transport
and the environment, organization and management, airport, railway, metro, and port master plans. He has
written to this day 9 books and over 190 scientific papers that have been published in scientific journals, including
Elsevier's Journal of Air Transport Management, as well as conference proceedings.
G.N. Botzoris is Assistant Professor for the Section of Transportation at Democritus University of Thrace, Greece. He
holds the Diploma in Civil Engineering, MSc in Business Administration, and PhD in Transportation. His research
interests include travel behavior analysis and modeling, analysis and forecast of transport demand, transport
economics and feasibility methods, public transport planning and policy, traffic analysis and management,
intelligent transport systems, sustainable mobility, and effects of transport activities on the environment. He is
coauthor of one book and of five chapters in edited volumes. He has written to this day over 140 scientific papers
that have been published in scientific journals, including Elsevier's Journal of Air Transport Management, as well
as conference proceedings.