Network link travel time estimation for commercial vehicles is essential to freight operations and planning. This project studies link travel time estimation using sparse truck Global Positioning System (GPS) data. First, the research team presents a naive method for truck speed analysis on individual links. The naive method can compute the average travel speed and variation on each link individually as input for further travel time analysis. Second, to address the issue of ignoring those truck trips with large intervals covering multiple links, the research team presents a network mapping method that maps the link performances using the itinerary travel times. A case study is conducted using the San Antonio corridor network, a major freight corridor. In addition, the research team further tests the proposed methods with simulation data partially on I-94 and I-894, a highway corridor in the Milwaukee, Wisconsin area. The test results indicate that the proposed network mapping method appears practical for application to the link performance analysis on freight corridors for truck transport.