10 Transportation Research Record: Journal of the Transportation Research Board, No. 2380, Transportation Research Board of the National Academies, Washington, D.C., 2013, pp. 10–21. DOI: 10.3141/2380-02 Extensive literature in the adaptive control field uses local detection avail- able from the traffic controller as input to various control models to adjust splits, cycle lengths, and offsets. All these models have implicit control objectives, which include facilitated progression, minimized stops, mini- mized delay, and equitable allocation of green time. Enormous opportuni- ties exist to incorporate probe data into the decision process with respect to when and where adaptive control can be used and which operating objec- tives are most applicable to a corridor as well as to an outcome assessment tool to evaluate the effectiveness of adaptive control. The research reported in this paper compared how probe data sources could be used to identify appropriate adaptive control objectives and to assess the performance of adaptive systems. Four case studies demonstrated how travel time data could be used to evaluate existing conditions, to evaluate the outcome of a traditional signal retiming, and to assess the feasibility of adaptive con- trol opportunities. Currently, the richest probe data sets are provided by agency-installed equipment. Given the increasing penetration of crowd- sourced probe data devices and the onset of connected vehicle infrastruc- ture, however, these sources could provide similarly rich data. This paper recommends that commercial data providers begin to develop more detailed base maps. These maps would provide richer probe data infor- mation, such as hour-by-hour statistical distributions and approach delay for signalized arterials for which the segments did not span multiple inter- sections. This recommendation should motivate agencies to develop more detailed specifications for probe data that will better serve their needs. The National Transportation Operations Coalition has in recent years published a Traffic Signal Report Card (1). The most recent traffic signal grade of D+ was driven in large part by a lack of up- to-date system information and an F in traffic monitoring and data collection. In fact, phone calls from the public often are the primary source of feedback. Maintenance and the operation of signal systems require special- ized technical expertise, which can be difficult for agencies with resource constraints to satisfy. Deployment of advanced control technologies can reduce staff requirements, but technology upgrades must be prioritized so that such investments can be made in areas where they are needed most. Recently, FHWA established goals as a part of its Every Day Counts initiative to incorporate adaptive control to meet the transportation demands of the 21st century (2). Before an investment is made in advanced control technology, however, it is critical to assess how candidate corridors are operating. Such an assessment will help identify objectives best suited to the corridor and maximize the opportunity for success. When an operational assessment of a signalized corridor is con- ducted, the most common form of analysis traditionally has been the floating car study. In such a study, vehicles are driven up and down the corridor to directly measure the travel time through the system. This approach is a relatively costly means to obtain a small set of data points, which covers only a brief period of time. It also does not scale for the quantification of delay on minor movements and side streets. PROBE DATA In recent years, a number of technologies have emerged to enable the collection of travel time information from traffic systems (3–14). The probe data market is not yet mature enough to effectively measure minor movement or side street delay, except in cases of exceptionally high volume. The market has reached the point, how- ever, where rich data sets can be obtained for arterial operations. Because of the large number of samples that can be obtained, often considerable variation occurs in the data, which requires more sophisticated analysis techniques than floating car studies. This variability is a direct consequence of the complexity of the control system and traffic patterns along a corridor with multiple entry and exit points, as well as locations where motorists make brief detours to purchase coffee or fuel. Existing probe vehicle technologies include numerous approaches with many advantages and disadvantages. Five techniques are described below: 1. Agency-driven probe vehicles. Agency vehicles are driven through a corridor with a Global Positioning System (GPS) unit to record the expected travel times. 2. Reidentification with pavement sensors. Sensors are placed in the pavement that can detect a vehicle’s magnetic fingerprint and match it to sensors placed upstream or downstream (3). 3. Reidentification with Metropolitan Affairs Coalition address matching. Bluetooth monitoring stations (BMS) are placed along a corridor to collect Metropolitan Affairs Coalition (MAC) addresses Performance Characterization of Arterial Traffic Flow with Probe Vehicle Data Stephen M. Remias, Alexander M. Hainen, Christopher M. Day, Thomas M. Brennan, Jr., Howell Li, Erick Rivera-Hernandez, James R. Sturdevant, Stanley E. Young, and Darcy M. Bullock S. M. Remias, A. M. Hainen, H. Li, and E. Rivera-Hernandez, 550 Stadium Mall Drive, and C. M. Day, T. M. Brennan, Jr., and D. M. Bullock, Room 303, 400 Centennial Mall Drive, Purdue University, West Lafayette, IN 47907. J. R. Sturdevant, Indiana Department of Transportation, 8620 East 21st Street, Indianapolis, IN 46219. S. E. Young, University of Maryland, 2200 Technology Ventures Building, College Park, MD 20742. Corresponding author: S. M. Remias, sremias@purdue.edu.