Next‐Generation Commodity Flow Survey: A Pilot in Singapore

Lynette, Cheah; Zhao, Fang; Stinson, Monique; Lu, Fangfang; Ding-Mastera, Jing; Marzano, Vittorio; Ben-Akiva, and Moshe

doi:10.1002/9781119425526.ch7

Cited by 7 publications

(4 citation statements)

References 3 publications

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“…Disaggregate data for urban freight operations, such as shipment records, is scarce and challenging to obtain. Data are only collected by using costly and infrequent establishment-based surveys, implemented large scale only for a small number of cities in the past (29)(30)(31)(32)(33)(34). Therefore, freight modeling typically requires several assumptions to compensate for the lack of the disaggregated data (35).…”

Section: Demonstration: Calibration Of An Urban Freight Simulatormentioning

confidence: 99%

Screenline-Based Two-Step Calibration and its Application to an Agent-Based Urban Freight Simulator

Hara

Sakai

Alho

et al. 2022

Transportation Research Record: Journal of the Transportation R

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Calibration is an essential process in making an agent-based simulator operational. In particular, the calibration for freight demand is challenging because of the model complexity and the shortage of available freight demand data compared with passenger data. This paper proposes a novel calibration method that relies solely on screenline counts, named screenline-based two-step calibration (SLTC). SLTC consists of two parts: (1) tour-based demand adjustment; and (2) model parameter updates. The former generates screenline-based tours by cloning/removing instances of the simulated goods vehicle tours, aiming to minimize the gaps between the observed and the simulated screenline counts. The latter updates the parameters of the commodity flow model which generates inputs to simulate goods vehicle tours. To demonstrate the practicality of the proposed method, we apply it to an agent-based urban freight simulator, SimMobility Freight. The result shows that SLTC allows the simulator to replicate the observed screenline counts with reasonable computational cost for calibration.

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Section: Demonstration: Calibration Of An Urban Freight Simulatormentioning

confidence: 99%

Screenline-Based Two-Step Calibration and its Application to an Agent-Based Urban Freight Simulator

Hara

Sakai

Alho

et al. 2022

Transportation Research Record: Journal of the Transportation R

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“…Freight survey design and its applications are summarized by Allen et al (2012), covering establishment surveys, vehicle observation surveys, parking surveys, driver surveys, commodity-flow surveys, roadside-interview surveys, and other surveys. Cheah et al (2017) provided a literature review focused on commodity and establishment-based freight surveys.…”

Section: Survey Datamentioning

confidence: 99%

“…• A large-scale GPS-based vehicle tracking and driver-activity survey to a sample of season parking ticket holders of the Urban Redevelopment Authority heavy vehicle parks to understand movements and parking patterns (Alho et al 2018). • A pilot of a commodity-flow survey in Singapore (Cheah et al 2017), which is being followed by a larger deployment, to understand commodity flows and associated business characteristics. • A shipment-tracking pilot in the USA and Singapore to gain additional understanding of the supply chain structures that shipments go through.…”

Section: Applicationsmentioning

confidence: 99%

Laboratories for Research on Freight Systems and Planning

Alho¹,

Sakai²,

Zhao³

et al. 2021

Urban Informatics

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Advancements in information and communication technologies (ICT) and the advent of novel mobility solutions have brought about drastic changes in the urban mobility environment. Pervasive ICT devices acquire new sources of data that can inform detailed transportation simulation models, and are useful in analyzing new policies and technologies. In this context, we developed software laboratories that leverage the latest technological developments and enhance freight research. Future mobility sensing (FMS) is a data-collection platform that integrates tracking devices and mobile apps, a backend with machine-learning technologies and user interfaces to deliver highly accurate and detailed mobility data. The second platform, SimMobility, is an open-source, agent-based urban simulation platform which replicates urban passenger and goods movements in a fully disaggregated manner. The two platforms have been used jointly to advance the state of the art in behavioral modeling for passenger and goods movements. In this chapter, we review recent developments in freight-transportation data-collection techniques, including contributions to transportation modeling, and state-of-the-art transportation models. We then introduce FMS and SimMobility and demonstrate a coordinated application using three examples. Lastly, we highlight potential innovations and future challenges in these research domains.

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“…On the other hand, a lot of efforts and resources were spent on collecting disaggregate data until this day. Several metropolitan-scale establishment surveys, which are also called commodity flow surveys, were conducted in recent years or are currently ongoing for informing urban freight models (Hunt et al 2006;Alho and e Silva 2015;Toilier et al 2016;Cheah et al 2017;Oka et al 2018). Exploring urban freight modeling approaches that make full use of those survey data is one of the important research topics.…”

Section: Introductionmentioning

confidence: 99%

Commodity flow estimation for a metropolitan scale freight modeling system: supplier selection considering distribution channel using an error component logit mixture model

et al. 2018

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Freight forecasting models have been significantly improved in recent years, especially in the field of goods vehicle behavior modeling. On the other hand, the improvements to commodity flow modeling, which provide inputs for goods vehicle simulations, were limited. Contributing to this component in urban freight modeling systems, we propose an error component logit mixture model for matching a receiver to a supplier that considers two-layers in supplier selection: distribution channels and specific suppliers. The distribution channel is an important element in freight modeling, as the type of distribution channel is relevant to various aspects of shipments and vehicle trips. The model is estimated using the data from the Tokyo Metropolitan Freight Survey. We demonstrate how typical establishment survey data (i.e. establishment and outbound shipment records) can be used to develop the model. The model captures the correlation structure of potential suppliers defined by business function and provides insights on the differences in the supplier choice by distribution channel. The reproducibility tests confirm the validity of the proposed approach, which is currently integrated into a metropolitan-scale agent-based freight modeling system, for practical use. Keywords Freight demand model · Urban freight · Commodity flow · Error component logit mixture · Disaggregate

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Next‐Generation Commodity Flow Survey: A Pilot in Singapore

Cited by 7 publications

References 3 publications

Screenline-Based Two-Step Calibration and its Application to an Agent-Based Urban Freight Simulator

Screenline-Based Two-Step Calibration and its Application to an Agent-Based Urban Freight Simulator

Laboratories for Research on Freight Systems and Planning

Commodity flow estimation for a metropolitan scale freight modeling system: supplier selection considering distribution channel using an error component logit mixture model

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