00803786

Component

https://doi.org/10.3141/1725-03

http://scholar.google.com...Bovy&publication_year=2000

Decision makers in freight transportation need to assess new distribution systems and the impacts of changes in the freight distribution environment on infrastructure needs and usage, logistical performance, emissions, and energy use. There is a need, therefore, for behavioral models that can predict goods flows and vehicle flows in both current and future situations. This research outlines a conceptual framework consisting of the markets, actors, and supply chain elements of freight movement. Supply chains are constructed by linking distribution channels (of different logistics characteristics) between different activity types, such as consumers, supermarkets, stores, offices, distribution centers, and factories. The framework outlined in this research was used to develop the GoodTrip model--a demand-driven, commodity-based freight movement model that incorporates supply chains. Starting with consumer demand, the model estimates goods flows and simulates vehicle tours. The open architecture of the model allows mixed use of empirical data, behavioral models, and scenario-type assumptions. The behavioral models will be developed in future research. In its first application, the GoodTrip model was used to compare the logistical performance and external impacts of three types of urban distribution systems: the traditional system and two concepts using urban distribution centers (one using vans, the other using automated underground vehicles). The results show considerable differences in the performance and effects of the alternatives, especially when they are applied to different types of distribution channels, such as food retail stores or bookstores.

This paper appears in Transportation Research Record No. 1725, Freight Travel Behavior, Route Choice Behavior, and Advanced Traveler Information Systems.

English

p. 17-25

2000

Transportation Research Record

0309067286

Figures (4) ; References (13) ; Tables (4)

Behavior; Commodity flow; Consumers; Demand; Impacts; Logistics; Mathematical models; Performance; Supply chain management; Urban goods movement

Urban distribution systems; Vehicle tours

Freight Transportation; Highways; Planning and Forecasting; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Dec 4 2001 12:00AM

• AGGREGATE- AND DISAGGREGATE-BASED TRAVEL TIME ESTIMATIONS: COMPARISON OF APPLICATIONS TO SUSTAINABILITY ANALYSIS AND ADVANCED TRAVELER INFORMATION SYSTEMS
• ANALYSIS OF TIME ALLOCATION, DEPARTURE TIME, AND ROUTE CHOICE BEHAVIOR UNDER CONGESTION PRICING
• ANTICIPATED TRAVEL TIME, INFORMATION ACQUISITION, AND ACTUAL EXPERIENCE
• ANTICIPATORY OPTIMIZATION OF TRAFFIC CONTROL
• BICRITERION TRAFFIC EQUILIBRIUM: T2 MODEL, ALGORITHM, AND SOFTWARE OVERVIEW
• CONTENT OF VARIABLE MESSAGE SIGNS AND ON-LINE DRIVER BEHAVIOR
• FRAMEWORK FOR THE ANALYSIS OF GROCERY TELESHOPPING
• FREIGHT TRAVEL DEMAND MODELING: SYNTHESIS OF APPROACHES AND DEVELOPMENT OF A FRAMEWORK
• MODELING INERTIA AND COMPLIANCE MECHANISMS IN ROUTE CHOICE BEHAVIOR UNDER REAL-TIME INFORMATION
• PERCEIVED VALUE OF TIME FOR TRUCK OPERATORS
• ROUTE AND SCHEDULING CHOICE UNDER TRAVEL TIME UNCERTAINTY
• ROUTE CHOICE MODEL WITH INDUCTIVE LEARNING
• TRAVELER RESPONSES TO ADVANCED TRAVELER INFORMATION SYSTEMS FOR SHOPPING TRIPS: INTERACTIVE SURVEY APPROACH
• USING GLOBAL POSITIONING SYSTEM DATA TO UNDERSTAND VARIATIONS IN PATH CHOICE
• VALUE OF TIME IN FREIGHT TRANSPORT IN FINLAND