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Sensor Network Design for Multimodal Freight Transportation Systems

The agricultural and manufacturing industries in the US Midwest region rely heavily on the efficiency of freight transportation systems. While the growth of freight movement far outpaces that of the transportation infrastructure, ensuring the efficiency and sustainability of the transportation networks becomes a major challenge. The prominent disbenefit of delay and unreliability highlights the need for an integrated, systems-level framework that incorporates cutting-edge information technologies and advanced multimodal network modeling techniques to monitor, manage and plan complex freight transportation systems. Recent developments in sensing and information technology hold the promise to allow efficient monitoring, assessment, and management of complex systems. This project investigated the effect of existing or off-the-shelf sensors on detecting traffic and infrastructure conditions for highway and rail modes. This research project developed an analytical framework to quantify the benefits and costs of deploying sensors for the major freight transportation modes. Specifically, this project developed a new sensor deployment problem in the context of traffic O-D flow surveillance using vehicle ID inspection technologies (e.g., RFID). In addition to traditional flow coverage benefits based on individual sensors, the authors investigated the path coverage benefits from synthesizing the multiple sensors in transportation networks. The authors considered possible sensor disruptions that are very common for many sensor technologies, yet not well addressed until very recently.