URBANE Thessaloniki LL MASS-GT input data

These datasets are used to generate parcel demand and delivery tours in the Thessaloniki LL. The detailed description can be found below. Data name File type Description Used by Network Data   Zones Shape file Centroids representing the zonal network of the study area Parcel demand, Parcel market, Parcel scheduling Parcel nodes Shape file Point vector showing the depot locations of the courier companies in the network Parcel demand, Parcel market, Parcel scheduling Duration matrix .csv text Duration matrix (in seconds) between each combination of the zone Parcel demand, Parcel market, Parcel scheduling Distance matrix .csv text Distance matrix (in metres) between each combination of the zone Parcel demand, Parcel market, Parcel scheduling Supply Data   Locker network .csv text Locations of the lockers in the network Parcel market Departure times of parcels .csv text Cumulative probability distribution of departure times (one full day) for the parcel tours Parcel scheduling Demand Data   Sociodemographic characteristics .csv text Population characteristics in the study area Parcel demand Courier market shares .csv text Market shares of the courier companies in the network Parcel demand Network data Zones: Represent the centroids of different zones within the study area, serving as the fundamental units for modelling and analysis in parcel demand, market, and scheduling modules. Parcel nodes: Identify the locations of courier company depots within the network, essential for determining starting points for parcel deliveries in demand, market, and scheduling modules. Duration matrix: A matrix that provides the travel time in seconds between each pair of zones, crucial for determining travel times in demand generation, market analysis, and scheduling. Distance matrix: Like the duration matrix but provides the distance in metres between each pair of zones, used for the same purposes as the duration matrix. Supply data Locker network: Indicates the positions of lockers available in the network, used primarily in the parcel market module to analyse delivery locker network. Departure times of parcels: Represent the cumulative probability distribution of parcel departure times throughout a day, used in the parcel scheduling module to simulate the timing of parcel dispatches. Demand data Sociodemographic characteristics: Provide information on the population characteristics within the study area, which is used to generate parcel demand based on population distribution and behaviours. These include sociodemographic characteristics of the population such as income and household structure such as number of households and people in the study area. Courier market shares: Show the market share distribution among different courier companies, impacting the demand module by determining how parcels are allocated among various couriers.