Lead Presenter:  Lawrence (Larry) Klein |  | Klein & Associates

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Presentation Description

Knowledge of modern, state-of-the-practice traffic flow sensors provides traffic managers, researchers, and students an understanding of the operation, strengths, and limitations of current sensor technologies and enables them to make an informed decision as to which is appropriate for a particular application. Accordingly, this paper describes intrusive and non-intrusive traffic flow sensor technologies in use today, their applications and selection criteria, and typical output data. Furthermore, it provides examples of representative sensor models. The technologies discussed are mature with respect to current traffic management applications, although some may not provide the data or accuracy required for a specific application or may not perform as needed under the operational conditions anticipated at the installation site. Sensors selected for a first-time application should be field tested under conditions that will be encountered in day-to-day operation before large-scale purchases of the device are made. As alternative traffic data and information sources, such as commercial data vendors, Wi-Fi and Bluetooth sensing of smart phone locations, and connected and automated vehicle data become increasingly available, they are progressively finding their way into modern traffic management systems as a complement to conventional roadside sensors.
Traffic flow data are typically gathered from three types of sources, Eulerian sensors, Lagrangian sensors, and third-party vendors. Eulerian sensors, the most widely-deployed of which is the inductive loop detector (ILD), are used to monitor traffic flow at a given location and provide data that support a variety of applications such as signalized intersection control; ramp, freeway-to-freeway, and mainline metering; wrong-way vehicle detection; queue warning; incident detection and congestion monitoring; traffic surveys; planning; and active transportation and demand management.
As the variety of sensor technologies increased and matured, additional types of Eulerian sensors became available. These include improved versions of magnetometer and magnetic sensors, which are installed in or under the roadway, and above-roadway mounted sensors such as video detection systems (VDSs), microwave radar sensors, Doppler microwave sensors, passive infrared (PIR) sensors, lidar sensors, acoustic sensors, ultrasonic sensors, and sensors that employ combinations of these technologies.
Traffic management also relies on data from Lagrangian sensors, i.e., those that flow with the traffic. These sensing methods include probe vehicles or floating cars that can provide a traffic management center emissions information in addition to the usual traffic flow parameters linked to a vehicle via global positioning system (GPS) location data or other global navigation satellite systems’ location devices, cell phone tracking through media access control address readers, automatic license plate readers, toll-tag [radio-frequency identification (RFID) transponder] readers, transit and taxi fleet sources, and trucking industry transponders.
Often third-party data are employed to supplement or supersede agency-run speed, travel time, flow rate, incident reporting, analytics, and OD programs that rely on traditional roadway point-based sensors. Among these data sources are HERE, INRIX, Miovision, StreetLight, TomTom, Waze, and Wejo.
Initiatives such as the Connected Vehicle Program in the U.S., Cooperative Intelligent Transportation Systems (C-ITS) initiatives in Europe, Intelligent Vehicle Innovation and Development Strategy in China, and similar programs elsewhere are enabling vehicle-to-vehicle, vehicle-to-infrastructure, vehicle-to-pedestrian, and pedestrian-to-infrastructure communications. These programs utilize in-car sensors to monitor the status of vehicle systems and provide a variety of data, including braking severity, hazard warning light activation, time headways to vehicles surrounding the ego vehicle, and ego vehicle velocity, acceleration, steering wheel position, traction loss, lane departure warning, windscreen wiper activation, and air bag deployment.
Notwithstanding the importance of non-Eulerian traffic monitoring modalities, they are not discussed further as part of this review of state-of-the-practice traffic flow sensors. Nevertheless, deployment and utilization of Lagrangian sensors should be considered by traffic management agencies either as an alternative or supplement to Eulerian sensors.
A more complete discussion and description of roadside sensors is found in L. A. Klein, "Roadside Sensors for Traffic Management," in IEEE Intelligent Transportation Systems Magazine, vol. 16, no. 4, pp. 21–44, July–Aug. 2024, doi: 10.1109/MITS.2023.3346842.

Speaker Biography

Lawrence A. Klein received a Bachelor of Electrical Engineering degree from the City College of New York in 1963, an M.S. in Electrical Engineering from the University of Rochester in 1966, and a Ph.D. in Electrical Engineering from New York University in 1973.
Dr. Klein is a member of the National Cooperative Highway Research Program (NCHRP) 03-145 Panel to develop guidance for the National Traffic Sensor System Evaluation Program and the 08-157 Panel to determine Best Practices for Data Fusion of Probe and Point Detector Data. He is a past member of the Transportation Research Board’s Highway Traffic Monitoring and Freeway Operations Committees, and ASTM’s E17 Group V-ITS where he developed worldwide standards for traffic flow sensors.
While at the French Institute of Science and Technology in Transportation, Planning, and Networks (IFSTTAR) in Bron, France, Dr. Klein lectured at the Federal Institute of Technology and at the EU-sponsored Real-Time Road Traffic Monitoring and Control Summer Workshop in Lausanne, Switzerland. He was a Visiting Professor at the Harbin Institute of Technology, School of Transportation Engineering and Science, Harbin, China for several years.
At Hughes Aircraft Company, he was Principal Investigator on the FHWA Detection Technology for IVHS (ITS) Program.
His books include Traffic Flow Sensors: Technologies, Operating Principles, and Archetypes (SPIE, 2020), Sensor and Data Fusion for Intelligent Transportation Systems (SPIE, 2019), ITS Sensors and Architectures for Traffic Management and Connected Vehicles (Taylor&Francis, 2018), Traffic Detector Handbook, 3rd Ed. (FHWA, 2006), and Sensor Technologies and Data Requirements for ITS (ArtechHouse, 2001). 

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