Environment Oriented Transport Policies and Transit Network Design



Environment Oriented Transport Policies and Transit Network Design

Authors

B Beltran, S Carrese, E Cipriani, University ?Roma Tre?, IT; M Petrelli, University of Rome ?La Sapienza?, IT

Description

This paper introduces a new procedure to solve the transit network design problem in a multimodal, demand elastic urban context, explicitly taking into consideration the relationships among modal split, level of transit services and environment.

Abstract

INTRODUCTION
The large increase of private car utilization can be faced by supporting technology development and by introducing transport demand management policies aiming at shifting the modal split towards the public transport. This approach requires to develop design methodologies in order to explicitly consider the externalities that emerge when the actions of the users of the transport system affect the non-users.
This paper introduces a new procedure to solve the transit network design problem in a multimodal, demand elastic urban context, explicitly taking into consideration the relationships among modal split, level of transit services and environment.

TRANSIT NETWORK DESIGN PROCEDURE
The methodology adopted in this paper is the development of transit network design model that has been extended to deal with a multimodal framework and take into account the effects of supply modification on modal choice and the presence of different vehicles types. The vehicle types choice for lines involving depots is not usually considered during the design phase. An effective environmental utilization of these alternative vehicles is strictly correlated with routes and frequencies definition and different choices can generate huge negative impacts for operator?s costs and fleet management.

PROBLEM FORMULATION
The resulting transit network design problem with elastic demand and vehicle types selection is here formulated as an optimization problem consisting in the minimization of all resources and costs related to the multimodal transport system, including transport externalities and it is solved by applying a genetic algorithm.
The objective function is a combination of transit operator?s costs, car users? costs and transit user?s costs. External costs are computed by assuming that an increase of transit demand implies a proportional reduction of external costs according to a constant ratio (âTUV); this constant has been computed on the basis of the current subsidies that the public authority gives to the operator to cover the differences between the service cost and the service revenue. The constant represents the monetary value that the society relates to a user travelling on the transit mode, so reducing externalities.
The input data are the overall (private and public transport) O/D demand matrix, the road network characteristics, the operating and users unit costs. Outputs are buses routes and their frequencies as well as the vehicle types and the related depot. Route terminals are not defined as input data and are determined by the model.

SOLUTION APPROACH
The basic solving framework of the method proposed is established on the following three stages:
1) a heuristic route generation algorithm (HRGA) that generates a large and rational set of feasible routes, by applying different design criteria and practical rules;
2) a genetic algorithm (GA) that finds the optimal sub-set of routes, their frequencies and vehicle capacity;
3) final improvement of the network configuration by means of simple heuristic rules that aim at locally improving the solution.
For computing the objective function components, the performances of the network are estimated by a probabilistic modal split model, by a hyperpath transit assignment model and by a deterministic user equilibrium assignment model, which estimates the effect of the interaction between route choice behaviour of drivers and link congestion at the equilibrium.

CONCLUSION
The new features implemented in the network design problem enhance the original transit network design model and allow to develop a comprehensive decision tool to support environmental oriented transport policies.
The proposed procedure has been implemented on a real size network for a large urban area (the city of Rome in Italy) in order to test the real procedure capacity and effectiveness in producing realistic and functional transit network and to compare the resulting transit network performances to the existing ones.

Publisher

Association for European Transport