Hassan Charara

Performance of Advance Warning for End of Green System for High-Speed Signalized Intersections

A major difficulty with traffic signal operation on high-speed approaches is the dilemma faced by approaching motorists when the downstream signal turns yellow. Should the motorists stop or proceed through the intersection? Crashes that may occur at these intersections result in excessive property damage and personal injury because of the high speeds involved. The Texas Transportation Institute has developed a new system named the Advance Warning for End of Green System (AWEGS) for application at high-speed signalized intersections. Typically, dilemma zone detection strategy is based on a certain approach speed (typically the 85th percentile). AWEGS provides protection for the majority of motorists who are not covered by the dilemma zone treatment. AWEGS provides advance warning to motorists by using signs mounted on the roadside. These signs (Be Prepared To Stop When Flashing) would flash a beacon about 5 to 6 s before the onset of the yellow signal for high-speed approaches. Similar systems have been implemented in Canada and in a few U.S. states that use the trailing-green approach, which results in loss of dilemma zone protection every cycle. AWEGS, however, is almost completely independent of the traffic signal controller, and hence the signal controller would continue to provide the dilemma zone protection for which it was designed. The system was implemented at two sites in Waco and Brenham, Texas. Results of AWEGS implementation illustrated an improvement in traffic operations. AWEGS consistently enhanced the dilemma zone protection at intersections and reduced red light running by about 40%.

Development and Field Testing of Platoon Identification and Accommodation System

This paper describes the development and initial field testing of an intelligent traffic control system for identifying and progressing platoons at isolated traffic signals on signalized arterials. This system uses advance detection to obtain real-time information about the presence and speeds of individual vehicles. Its algorithm identifies whether a platoon—of a userspecified minimum size and density—is approaching the signal and estimates platoon arrival time at the stop bar. When warranted, the system issues a low-priority preemption signal to progress the detected platoon. Duration of the initial preemption signal is based on estimated arrival and departure times for the smallest acceptable platoon and the estimated time needed to clear any queues present at the signal. Then, the system switches to an extension mode and provides progression to any additional vehicles determined to be in the platoon. It accomplishes that by increasing preemption time until no more vehicles are determined to be in the ...

New Evidence of Improvements in Dilemma Zone Protection by Detection-Control System

This research conducted a field evaluation of the detection-control system (D-CS) at eight sites located in four states. D-CS is similar to a traditional advance detector system in that it uses information from detectors located upstream of the intersection to extend the green. However, it differs from traditional advance detector systems because it monitors individual vehicles on the intersection approach on a lane-by-lane and on a vehicle length basis. It then uses this information to predict the best time to end the major-road through phase. The D-CS software continuously evaluates and updates this prediction in real time. The prediction is based on the number of vehicles currently in, or predicted to soon arrive in, the dilemma zone as well as the number of conflicting phases with a call for service. On the basis of the findings to date, D-CS is successful in improving crash surrogate measures of effectiveness. Findings from a regression analysis for 1-h periods indicated that the “after” study periods experienced 82% fewer red light violations, 73% fewer vehicles in the dilemma zone, and 51% fewer max-outs than the before-study periods. The emphasis of D-CS on trucks is a salient feature that makes it unique in comparison with other methods of dilemma zone protection. The government is urged to encourage and support a group of interested manufacturers in integrating the D-CS algorithm into their controllers.

Improving the Quality of Motorcycle Travel Data Collection

This report presents an analysis of traffic counting technologies and data collection protocols designed to help improve the reliability of motorcycle travel data. The technologies examined include infrared classifiers, inductive loops/piezoelectric sensors, magnetometers, multi-sensor technologies, and tracking video. The report describes the performance of each technology in terms of accuracy, initial cost, portability, and ease of setup and operation. The report also evaluates and validates a hypothesis that motorcycle crash locations are reasonable predictors of traffic volume. A correlation between crash sites and volume may enable a state department of transportation to select traffic counting locations that could yield more accurate data on motorcycle traffic volumes.

Pilot 05: Distributed Architecture for Robust Real-Time Progression Evaluation and Improvement

Real-time offset tuning can provide an almost optimal operation while capitalizing on the existing knowledge and familiarity of traffic engineers and personnel with the current actuated control system. The real-time offset tuning concept was introduced several years ago by one of the authors of this paper. Advantages and disadvantages of the concept were discussed in subsequent papers. The concept was taken further for implementation by other researchers within the ACS Lite tactical-level architecture development. This paper describes a parallel effort that focuses more on (a) a robust classification algorithm of progression quality and remedies and (b) vendor-independent distributed implementation architecture for the proposed algorithm. Rather than immediate implementation issues, this research establishes a flexible development framework for theoretical development and experimentation of adaptive control algorithms in the context of closed-loop systems operation.