Estimating Truck Trip Origin–Destination with Commodity-Based and Empty Trip Models

Abstract

This study estimates origin–destination (O-D) matrices of light and heavy trucks on the basis of the flow of commodities in the Tokyo metropolitan area. The truck O-D matrix is generally determined by either vehicle trip-based or commodity-based approaches, although the former cannot distinguish between loaded and empty trips and does not characterize the shipments. Three major concepts are proposed in this study. First, the truck trip O-D is estimated on the basis of the commodity approach because it can utilize the characteristics of the shipments. Second, the main contribution of the model is its ability to estimate both loaded and empty trips by modeling the truck movements as round trips and trip chains. The O-D of truck movement, particularly the movement of loaded trips in round trips or zero-order trip chains, is similar to that of the commodity flows. However, both movements have relatively different O-D when the loaded trips travel from one origin to many destinations or are part of an nth-order trip chain. Finally, the trip chain is modeled on the basis of characteristics such as average payload, adjacent zones, and the commodity O-D providing the most attractive zones traveled by trucks. The performance of the model is demonstrated by using the mean square error between the estimated and observed truck O-D matrices. The model concept is then applied to lightweight products obtained from the food industry. The proposed concept enhances the trip chain behavior and provides better results than the model without trip chain behavior.

Descriptive modeling of freight tour formation: A shipment-based approach

“…Since number of tours, vehicle types and tour purposes are chosen before the tour formation, the model cannot be classified as shipment-based, however. Raothanachonkun et al (2007) propose a similar incremental tour building algorithm to convert aggregate commodity flows to vehicle tours. However, their approach lacks an empirical foundation based on firm-level data; tour decisions are modelled deterministically based on average payloads.…”

A modelling system to simulate goods movements at an urban scale

“…3 the main outputs are given by freight vehicle flows by retailer for zones (origin and destination), and path and link freight vehicle flows for target time. In the literature, some have proposed different methods to convert the quantity flows to truck flows without considering the average payload or load factor (Raothanachonkun et al 2007; Holguin-Veras and Wang 2009). In our case, referring to freight vehicle flows by retailer for zones (origin and destination) and under the assumptions introduced previously, num(W) = 1; let be F s;tot;d;c r LGV r ; w ½ the flow of vehicle type LGV r to transport freight type s from w to attraction zone d, it can be calculated using Eqs.…”

Modeling Truck Parking Demand at Commercial and Industrial Establishments

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