INTRANET: A new simulation tool for intermodal transportation systems

Febbraro, Angela Di; Recagno, Valerio; Sacone, Simona

doi:10.1016/0928-4869(95)00024-0

Cited by 11 publications

(3 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The network realizes the integration among urban public transport services themselves and private traffic. The proposed model can be viewed as an extension of the one presented in [8]. The system is represented as an oriented graph, in which the nodes are stations where it is possible to switch from a mode of transport to another one.…”

Section: Introductionmentioning

confidence: 99%

Modelling and Performance Analysis of Urban Transportation Networks

Febbraro

Sacone

1996

Advanced Methods in Transportation Analysis

Self Cite

View full text Add to dashboard Cite

A discrete event approach is proposed to evaluate the performance and develop control strategies for a urban intermodal transportation network. The discrete event model presented integrates public and private means of transport. Some disturbances are included to model the stochastic nature of the system. Based on such a model, a urban traffic simulator (INTRANET) has been designed on purpose. INTRANET includes two major modules. The first one, the Traffic Simulation Kernel, allows to study the dynamic behaviour of the transportation system, analyzing its performances and applying control strategies to optimize them. The second one, the Passenger Information Service, gives the system users at any time updated information about the different intermodal paths between any pair of origin/destination nodes. A case study relevant to the transportation network of an Italian city is dealt. with. Related experimental results, showing the effectiveness of the proposed control strategy, are presented and discussed.

show abstract

Section: Introductionmentioning

confidence: 99%

Modelling and Performance Analysis of Urban Transportation Networks

Febbraro

Sacone

1996

Advanced Methods in Transportation Analysis

Self Cite

View full text Add to dashboard Cite

show abstract

“…With each class of entities, static quantities (parameters) and dynamic quantities (state variables) are associated. The discrete events that describe the evolution of the considered urban transportation network, and then rule the functioning of the traffic simulation tool, are divided into two classes (Di Febbraro et al, 1995): 1. events that describe the nominal traffic conditions; 2. events that represent unpredictable conditions affecting the system. The evolution of the system is reproduced by means of discrete event simulation, which can be viewed as the modelling over time of a system in which changes in the state only occur at discrete time instants, i.e., those instants when events occur.…”

Section: The Discrete Event Model Of the Transportation Networkmentioning

confidence: 99%

“…The first objective is the validation of integrated timetables for the different transportation modes, so as to consider the various transportation services to be parts of a whole intermodal transportation system. In this sense, the traffic simulation program can evaluate the performance of the system, supporting the user in modifying adaptively a given timetable (Di Febbraro et aI., 1994, 1995.…”

Section: Introductionmentioning

confidence: 99%

Dynamic search for shortest multimodal paths in a transportation network

Febbraro

Sacone

1996

System Modelling and Optimization

View full text Add to dashboard Cite

Many transportation systems can be suitably represented as Discrete Event Systems. This is the case of the multimodal urban transportation network considered in this paper. In the simulation tool designed to reproduce its functioning, a module is included which allows to find the best multimodal paths between any pair of nodes in the network. The basic algorithm is an ad-hoc modified version of the Dijkstra algorithm to find the shortest paths in an oriented graph. Such an algorithm is complicated to include some choices left to users, regarding the number of paths required, the maximum time to travel, and the modes of transport to use. Then, a heuristic algorithm to find the best multimodal paths in a network integrating public and private modes of transport is proposed.

show abstract