Urban freight demand forecasting: A mixed quantity/delivery/vehicle-based model

TLDR: In this article, the authors present a modelling approach that tries to point out the relations existing among city logistics measures, actors and choice dimensions, and evaluate the effectiveness of the measures to be implemented.

Abstract: The research germinates from the statement that the cities have to solve the impacts due to freight transport in order to improve their sustainability implementing sets of city logistics measures. But city logistics measures involve several actors and choice dimensions. It is therefore important to have methods and models able to assess the effectiveness of the measures to be implemented. The current models were mainly developed to simulate some aspects of urban freight transport, and are not able to forecast many impacts of implementing traffic and transportation measures at an urban scale. This paper presents a modelling approach that tries to point out the relations existing among city logistics measures, actors and choice dimensions. It comprises three model sub-systems to estimate the quantity O–D matrices by transport service type (e.g. retailer on own account or wholesaler on own account or by carrier), the delivery O–D matrices by delivery time period, and the vehicle O–D matrices according to delivery tour departure time and vehicle type. This modelling system is a multi-stage model and considers a discrete choice approach for each decisional level. It was first tested using some data collected in the inner area of Rome, including traffic counts and interviews with retailers and truck-drivers. The model estimations were also compared with the experimental ones, and quite satisfactory results were obtained.