Route Choice Modelling for Freight Transport at National Level
F Russo, A Vitetta, A Quattrone, DIMET, Univeristy Mediterranea of Reggio Calabria, IT
In this paper, a specification, calibration and validation of a path choice behavioural model for road freight transport are proposed.
Freight transport plays a fundamental role in the economy of every country. The majority of goods are transported by road and the study of truck-drivers path choice behaviour is very topical. In the literature, few path choice behavioural models have been specified, calibrated and validated for road freight transport.
In this paper, a specification, calibration and validation of a path choice behavioural model are proposed. The path choice model is simulated in two phases:
1. choice set generation, that is the possible alternatives;
2. path choice among alternatives included in the choice set.
The choice set generation is realized with multi-criteria path generation, which defines for all O/D pairs a choice set of several paths, each of which is generated by optimizing a covered function between chosen and generated paths associated to a certain criterion (i.e. minimum travel time, maximum motorway use, minimum travel cost etc.). The path choice is simulated with a C-Logit model. The C-Logit overcomes the main shortcoming of Multinomial Logit, i.e. unrealistic choice probabilities for paths sharing a number of links, while keeping a closed analytical structure, allowing calibration on disaggregate data and efficient path flow computations when paths are explicitly enumerated.
Path choice models were specified and calibrated on a truck-drivers road-side survey. In all, 280 interviews were made for path generation and path choice modelling. The chosen path was indicated in the questionnaire through origin, destination and intermediate nodes. Computations of path generation and level-of service attributes were carried out using the Italian road network, which consists of all the motorways and the main roads in the country.
As regards path generation, the covered function is calibrated with the maximization of the overlapping factor of chosen and generated paths. Path choice is calibrated with the Maximum Likelihood method that supplies the values of the parameters on which the utilities of all alternatives depend, maximizing the probability of observing the choices made by the user sample. For validation formal and informal tests on parameters and statistics were performed to ascertain the model?s goodness of fit. It was verified that the model is able to reproduce user choices, all the calibrated parameters are significant and correct in sign and the model hypotheses are acceptable.
The experiment carried out on the Italian network showed that a significant degree of coverage of chosen paths could be obtained by generating paths with respect to the criteria identified. In the future, in order to obtain more information on user path choice behaviour, the vehicles of some truck-drivers will be equipped with on-board Intelligent Transportation Systems (ITS) for monitoring freight transport. The utilization of ITS supplies new real time data about path choice. The database obtained from the truck-drivers road-side survey will be updated with these new data.
Association for European Transport