Forecasting parcel deliveries in an urban freight simulator for the province of Zuid Holland

Abstract

1. Overview and motivation
E-commerce is a rapidly developing segment within urban goods transportation. While currently making up only 5.5% of all kilometers driven by vans in the Netherlands (CBS, 2018), this segment is experiencing rapid growth. For example, in the Netherlands, the volume of parcel deliveries grew by 20% in 2018 (ACM, 2018). This growth is further accelerated by the current coronavirus pandemic. The increasing importance of this segment is not reflected yet in strategic models used in practice for transportation demand forecasting. Parcel deliveries are not modelled explicitly, which does not only prevent the model users from calculating effects of scenarios and policies related to e-commerce, but it also disregards the unique nature of this segment (e.g. specific depot locations, strong growth rates) and, therefore, leads to flawed reference forecasts of van traffic.
In the scientific literature there are some first examples of simulation models for parcel deliveries (Sakai et al, 2020; Hörl & Puchinger, 2021; Llorca & Moeckel, 2021; Mommens et al., 2021; Reiffer et al., 2021). However, each of these examples lacks an empirical disaggregate demand model, focusses on one (part of a) city rather than a whole region, or focusses on one product/service segment rather than all parcel deliveries in a region. Moreover, little experience is gathered in applying such urban freight simulators for traffic forecasting.

2. Methodology, results and main contributions
To combat these shortcomings of the state-of-practice freight models, we developed a module for last-mile parcel deliveries and used it to explore the impacts of different scenario assumptions regarding parcel demand and scheduling. The module consists of two sub-modules: the parcel demand sub-module and the parcel scheduling sub-module.
The parcel demand sub-module calculates parcel demand based on the households and businesses in each zone. For parcels to households (B2C), a logit model is estimated on the Mobility Panel Netherlands, which included several questions regarding parcel orders in 2017 (Hoogendoorn-Lanser et al., 2015). For parcels to businesses (B2B) an average factor is deduced from aggregate statistics reported by ACM (2018). Once the total number of parcels is determined, they are spread over the different courier companies, based on their respective market shares in terms of number of parcels. Finally, for each zone and courier, the nearest depot is determined; from this depot the parcels will be shipped to their end destinations.
The parcel scheduling sub-module forms round-tours to deliver all the parcels for each parcel courier in the study area. From each depot, simple heuristics (such as nearest-neighbor and 2-opt) are used to form efficient tours that respect the vehicle capacity (in terms of number of parcels) and maximum shift lengths for drivers. This, in turn, leads to trip matrices that can be assigned to the network to arrive at network statistics such as vehicle kilometers and emissions.
The conceptual architecture of this module has been applied in four modelling systems:
(1) the strategic freight model of Flanders (SVRM);
(2) the travel demand model of the Municipality of Amsterdam (VMA);
(3) the module for logistical decision-making of the national strategic freight model of the Netherlands (BasGoed);
(4) and the tactical freight simulator of the HARMONY project for the European Commission (test bed: Province of Zuid-Holland, the Netherlands).
In this research we will analyze the impacts of different scenarios and policies, for this purpose we will use the HARMONY implementation of the model in Zuid-Holland. The scenarios explore the impacts of different developments for:
• increased demand for parcels;
• horizontal collaboration between couriers, with shared use of depots;
• a zero-emission zone in Rotterdam, in combination with consolidation centers at the outskirts of the city.

3. Conclusion and future works

A disaggregate region-wide simulation model for parcel deliveries is necessary to evaluate the impacts of policies and developments in e-commerce. Using the developed model, we can show, for example, that vehicle kilometers do not increase linearly with parcel demand due to increased consolidation and that the impacts of zero-emission zones can be diffuse due to rerouting of van trips.

Future efforts may focus on modelling the whole transport chain of e-commerce, rather than only the last-mile deliveries. Furthermore, a demand model for parcels to businesses in line with the model for households is desired, this would require additional data collection.