GPS and Driver Log–Based Survey of Grocery Trucks in Chicago, Illinois

Abstract

Freight demand modeling lags in comparison with passenger demand modeling, largely because of the limited selection of available data. Commercial firms tend to approach inquiries into the operations and finances of their businesses with suspicion or at least impatience. The risk of losing company time or a competitive edge limits potential cooperation. Thus with each advance in data collection, valuable insights into the inner decision making of capitalist industry can be gained. This paper introduces a GPS freight survey conducted in the Chicago, Illinois, metropolitan area in the spring of 2012. The GPS data were augmented by driver diaries and warehouse and distribution center data records that were designed and used for minimizing respondent burden. Data collection focused on and was made possible through the cooperation of a major grocery chain in the region. In total, 108 trip days of GPS traces were obtained and allowed for the examination of lengthy tours between warehouses, distribution centers, and stores. A descriptive analysis of these tours is included with a focus on the spatial and temporal distributions of activities. From these data, approximately 89% of all activities were major work-based activities, and the number of activities per trip had a local maximum of three, by which 32% of all tours abided. The information gathered and presented will be used to supplement future disaggregate modeling exercises.