Traffic demand in the U.S. has grown substantially over the past few years because of the increase in population and urbanization in large cities. This causes traffic congestion to spread out over U.S. highways and arterials, and subsequently leads to deterioration in traffic networks in terms of operation, safety, and productivity. Therefore, congestion management strategies have become essential for addressing safety and operational problems. Recently, active traffic management (ATM) strategies have been recognized as efficient methods for managing widespread congestion, provided that a proper management strategy is identified and implemented. Any ATM strategy requires a systematic process that should work in a specific sequence starting from getting information from a congested road segment to dissemination of relevant information to travellers to help relieve congestion. This process starts with collecting traffic data from the roadways, screening the collected data to remove redundancies and erroneous data, synthesizing useful traffic information, and finally disseminating such information to travellers in real time. Based on the type of delivered information, travellers may alter their trip decision in terms of departure time, mode choice, and route selection in order to avoid congestion. This report presents a review of the state-of-the-art and state-of-practice methods used to execute the steps taken to deliver accurate real time traffic information to travellers and the impact such information has on congestion management. The report sheds light on different technologies and methodologies used for data collection, screening, and dissemination in the United States. In addition, the report highlights the impact of disseminated information on drivers’ behaviour and transportation network operation and safety. More so, the report presents few case studies on different ATM strategies and shows the gained benefits from using these strategies. (Author/publisher)
Abstract