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Multimodal Transportation Model
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A Multi-Modal Transport Model for Integrated Planning

presented by Dr. Markus Friedrich, at the 8th World Conference on Transport Research, Antwerp 1998

PTV AG Stumpfstr. 1 D-76131 Karlsruhe Tel.: +49-721-9651-0 Fax: +49-721-9651-299 Email: ptv@ptv.de

A MULTI-MODAL TRANSPORT MODEL FOR INTEGRATED PLANNING

MARKUS FRIEDRICH
PTV AG D-76131 Karlsruhe, Germany

Abstract Transport models are applied to support the planner in the process of planning and decision making. Models attempt to replicate the system of interest and the system’s behaviour. The presented model considers the transportation system with its interactions between the several supply systems and the demand system. The transport model, implemented in a software product called VISUM, consists of • a network model describing the spatial and temporal structure of the supply systems, • a demand model simulating activities and generating trip chains, • routing and assignment models to determine service quality and route choice. The paper focuses on the requirements of a multi-modal transport model and • gives an overview of an activity-based demand model, • presents the structure of a network model integrating various modes and supply systems, • shows methods which support the design process and assist the planner in finding new solutions, • discusses multi-modal assignment procedures.

INTRODUCTION Understanding and solving transport problems is a process which generally starts with an analysis of the current state (Figure 1) in order to deduct deficiencies. The analysis of the current state is followed by a design process which can be partitioned into four steps (Figure 2): • development of a solution, • determination of impacts, • evaluation of impacts, • analysis of deficiencies. These four steps constitute a cyclic process which continues until a satisfactory solution meeting the planning objectives is achieved.

Current transport system

Development of a solution



References: Axhausen, K. W., Herz, R. (1989) Simulating Activity Chains: German Approach. Journal Of Transportation Engineering, Vol. 115 (3) 316-325. Günther, R. (1985) Untersuchung planerischer und betrieblicher Maßnahmen zur Verbesserung der Anschlußsicherung in städtischen Busnetzen ("Planning and operational measures to improve connections in urban bus networks"), Schriftenreihe Des Instituts Für Verkehrsplanung Und Verkehrswegebau, Heft 15, Technical University of Berlin. Fellendorf, M., Haupt, Th., Heidel, U., Scherr, W. (1997) PTV VISION: Activity-based demand forecasting in daily practice, Activity-Based Approaches To Travel Analysis, Elsevier, Oxford, 55-72. Haupt, Th., Jacobus, W., Mott, P., Sahling, B.-M., Schwerdtfeger, Th. (1990) Optimierung Der Struktur Städtischer Straßen- Und Liniennetze. Vol. I, Methoden (“Methods to optimise networks of streets and public transport”) Report for the German Federal Ministery of Transport FE-No. 70 112/85. Karlsruhe, Germany. Maziejewski, S. (1992) The Vehicle Routing And Scheduling Problem With Time Window Constraints Using Genetic Algorithms, Diploma Thesis, Institut für Logistik, Komplexität und Deduktionssysteme, Technical University of Karlsruhe. Rumbaugh, J.; Blaha, M., Premerlani, W., Eddy, F., Lorensen, W. (1991) Modelling And Design, Prentice-Hall International, New Jersey. Object-Oriented Sahling, B.-M. (1981) Linienplanung im öffentlichen Verkehr ("Planning public transport lines"), Institutsnotiz Des Instituts Für Verkehrswesen, Nr. 29, Technical University of Karlsruhe.

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