2013 Session: 410

• Identifying and Classifying Freight Trip Stops from GPS Data
  Abstract: Many previous efforts have been made to use global positioning system (GPS) data gathered from mobile units to measure freight network performance. While the majority of these previous works were instrumental in establishing the technical reliability of GPS information and using that information to measure basic network performance, there have been few if any attempts to classify stops (i.e. stops for deliveries, unscheduled stops and traffic stops). Using data from freight vehicles in the New York City metropolitan area we developed a three step process to identify and classify trip stops by purpose (i.e. rest stops, unscheduled, deliveries) and calculate the relevant tour performance measures such as average delivery stops per tour, average service time and vehicle movements per destination.
  Authors: Richardson, Eric; Ban, Xuegang (Jeff); Holguín-Veras, Jose
  Authors: Richardson, Eric; Ban, Xuegang (Jeff); Holguín-Veras, Jose
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Freight Transportation
  Session: 410
  Paper Number: 13-3737
• Decision-Making Process and Factors Affecting Truck Routing
  Abstract: This research attempts to better understand truck routing behavior in terms of the decision-making process and the factors that affect routing choices. In order to collect data on the decision-making process, a computerized survey was employed to collect exploratory background information and Stated Preferences (SP). 252 road-intercept interviews of truck drivers have been conducted at three major corridors in North America, with 1121 valid SP observations. Both market segmentation and explicit modeling techniques have been used to analyze the data. Segmentations based on carrier/driver characteristics and shipment/route attributes are used to study the identity of routing decision makers and sources of information used in pre-trip planning and en-route adjusting. A random effects logit model was estimated using the SP data. The results show that (a) the trucking industry is highly heterogeneous with many entities contributing to the decision-making process, namely, carrier characteristics, driver characteristics, shipment attributes, and route attributes; (b) drivers do not always perceive delays negatively, there are cases when delays bring about benefits and therefore are preferred by certain groups of drivers; (c) truck drivers tend to prefer a toll road if the toll cost is covered by their employer.
  Authors: Sun, Yichen; Toledo, Tomer; Rosa, Katherine; Ben-Akiva, Moshe E.; Flanagan, Kate; Sanchez, Ricardo; Spissu, Erika
  Authors: Sun, Yichen; Toledo, Tomer; Rosa, Katherine; Ben-Akiva, Moshe E.; Flanagan, Kate; Sanchez, Ricardo; Spissu, Erika
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Freight Transportation
  Session: 410
  Paper Number: 13-4404
• Decision-Making Process and Factors Affecting Truck Routing
  Authors: Sun, Yichen
  Authors: Sun, Yichen
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Freight Transportation
  Session: 410
  Paper Number: 13-4404