Business and Site Specific Trip Generation Methodology for Truck Trips

Available Documents
Quarterly Report September 2004
Quarterly Report March 2005
Quarterly Report March 2005
Paper presented at Transport Chicago 2005
Slides from Presentation
Final Report
Research Summary

Primary Investigator
Kazuya Kawamura
Assistant Professor
Urban Transportation Center
University of Illinois at Chicago
kazuya[at]uic.edu

Project Objective
The goal of the study is to develop a robust methodology for estimating freight demand that is founded on sound economic theories. Since the study will involve substantial amount of data collection for each type of business analyzed, a carefully selected group of business establishments would include large-scale retail distribution centers, warehouses, agricultural, building materials and manufacturing facilities, and freight facilities such as inter-modal and truck freight terminals will be targeted.

The objectives are to:

  1. Collect detailed truck trip generation and activity data from businesses,
  2. Analyze the data to improve the understanding of the relationship between TTG and business decisions at the firm level including the use of information technologies and various logistics and inventory management strategies, hourly/daily/seasonal fluctuations, and the influence of other businesses in the vicinity.
  3. Identify appropriate categorization of business establishments for TTG modeling based on the similarities and differences found in 2)
  4. Propose an appropriate modeling framework that captures the relationship between business activities/strategies and TTG, and
  5. Explore the policy implications of the findings.

Project Abstract
Information on the movement of trucks is vital for the effective management of
transportation infrastructure. While goods movement by trucks plays a critical role in the national and regional economy, trucks are also responsible for most of the pavement damage and a considerable portion of air pollutants from non-stationary sources and congestion1.

Recent estimates by the Federal Highway Administration predict the volume (tons) of freight transported by trucks will grow by over 75% in the next 15 years2. Thus, it is imperative that the decision makers have accurate information on the current and future movements of trucks in order to effectively manage and utilize transportation infrastructure. While considerable strides have been made in forecasting truck travel demand in the past several years, there remain several critical gaps that need to be addressed. The growth of E-commerce and logistic management concepts such as third-party logistics (3PL) as well as a group of holistic goods distribution strategies known as City Logistics3 will likely to affect the pattern of freight flow especially in urban areas. It is evident that currently available demand forecasting methods are not suited to address those changes.

As the first step toward the development of the truck demand forecasting model that can account for the logistics and operations management strategies used by today’s businesses, this study will tackle the most fundamental but often neglected component of truck travel demand forecasting process, trip generation.

Truck trip generation (TTG) analysis is a study to estimate the number of trucks coming in and out of a study area. The analysis will help transportation planners and public agencies to provide information on making transportation asset management decisions. Despite this promise, TTG analysis has not achieved its goal of providing substantial information for decision makers due to the lack of data and an appropriate methodology. Although past TTG analyses realized the importance of economic activities, only aggregate variables or
proxies of economic activities such as land use types, number of employees, and the gross floor space were used. Consequently, existing models only indicated the relative importance of trip generators at a general level and are not suited to analyze the impacts of logistics management strategies. In addition, the results diverge; indicating such aggregate approaches cannot capture the relationships between economic activities on industrial sites and the amount of freight truck trips. This problem will be exacerbated as businesses adopt even more sophisticated logistic management strategies in the future.

The proposed study presents a different perspective on the relationship between the TTG and economic activities. At an individual firm level, the number and type of freight truck trips within a given time period can be regarded as the outcome of a series of decisions about products, sales, locations, delivery times, and frequencies4. That is, for a business establishment, the TTG is directly related to a supply chain management strategies adopted whereby the firm’s goal is to maximize the profit.

Task Descriptions

  1. Task 1 Literature Review and Development of Prototype Models.
  2. Task 2 Data Collection.
  3. Task 3 Model Development.
  4. Task 4 Policy Implications.

Potential Benefits of the Project
Relating freight movement to economic activity and truck movements to that same data could be a major break through in freight planning.

Project Information

  • Milestones, Dates: Project Duration: 12 months
  • Year 1 Budget: $132,607, Matching Funds & %: $32,789 25%
  • Student Involvement: 1project assistant
  • Modal Orientation: Highway
  • Project ID: 05-03