Optimized Advance Detector Configuration for Option Zone Protection at High-Speed Signalized Intersections

Author(s):  
Zhixia Li ◽  
Heng Wei ◽  
Zhuo Yao ◽  
Hui Xiong ◽  
Xuedong Yan
Author(s):  
Fred Coleman ◽  
oung J. Moon

A design methodology for gate delay and gate interval time for at-grade crossings using four-quadrant gates is developed. The design approach is based on the concept of dilemma zones related to signal change intervals at signalized intersections. The design approach is validated based on data from six sites in Illinois on a proposed high-speed rail corridor. Gate delay and gate interval times are determined that provide an optimal safe decision point to allow a driver to stop before the crossing or to proceed through the crossing without becoming trapped by the exit gates.


Author(s):  
Srinivasa R. Sunkari ◽  
Carroll J. Messer ◽  
Hassan Charara

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%.


2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Sheng Dong ◽  
Jibiao Zhou

The stop/go decisions at signalized intersections are closely related to driving speed during signal change intervals. The speed during stop/go decision-making has a significant influence on the dilemma area, resulting in changes of stop/go decisions and high complexity of the decision-making process. Considering that traffic delays and vehicle exhaust pollution are mainly caused by queuing at intersections, the stop-line passing speed during the signal change interval will affect both vehicle operation safety and the atmospheric environment. This paper presents a comparative study on drivers’ stop/go behaviors when facing a transition signal period consisting of 3 s green flashing light (FG) and 3 s yellow light (Y) at rural high-speed intersections and urban intersections. For this study, 1,459 high-quality vehicle trajectories of five intersections in Shanghai during the transition signal period were collected. Of these five intersections, three are high-speed intersections with a speed limit of 80 km/h, and the other two are urban intersections with a speed limit of 50 km/h. Trajectory data of these vehicle samples were statistically analyzed to investigate the general characteristics of potential influencing factors, including the instantaneous speed and the distance to the intersection at the start of FG, the vehicle type, and so on. Decision Tree Classification (DTC) models are developed to reveal the relationship between the drivers’ stop/go decisions and these possible influencing factors. The results indicate that the instantaneous speed of FG onset, the distance to the intersection at the start of FG, and the vehicle type are the most important predictors for both types of intersections. Besides, a DTC model can offer a simple way of modeling drivers’ stopping decision behavior and produce good results for urban intersections.


Author(s):  
Gerald L. Ullman ◽  
Elisabeth R. Rose

This paper describes an analysis of the effectiveness of dynamic speed display signs (DSDSs) installed in several permanent locations. Sites evaluated included a school speed zone, two transition speed zones in advance of a school speed zone, two sharp horizontal curves, and two approaches to signalized intersections on high-speed roadways. Data were collected before the DSDSs were installed, about one week after installation to determine initial effects of the signs upon vehicle speeds, and again about four months after installation to determine how well the initial speed reductions were maintained. Researchers analyzed average speeds, 85th percentile speeds, and the percentage of the sample exceeding the speed limit. In addition, least-squares regression analyses between the speed of a vehicle upstream of the DSDS and that vehicle's speed measured again at the DSDS were performed to determine whether the sign affected higher-speed vehicles more substantially than lower-speed vehicles. Overall, average speeds were reduced by 9 mph at the school speed zone. Elsewhere, the effect of the DSDS was less dramatic, with average speeds reduced by 5 mph or less depending on the location tested. As expected, those motorists traveling faster than the posted speed limit did appear to reduce their speed more significantly in response to the DSDS than did motorists traveling at or below the posted speed limit. The results of this project suggest that DSDSs can be effective at reducing speeds in permanent applications if appropriate site conditions apply.


Author(s):  
David S. Hurwitz ◽  
Haizhong Wang ◽  
Michael A. Knodler ◽  
Daiheng Ni ◽  
Derek Moore

2007 ◽  
Vol 133 (10) ◽  
pp. 556-563 ◽  
Author(s):  
Kim Mueller ◽  
Shauna L. Hallmark ◽  
Huaiqing Wu ◽  
Michael Pawlovich

2013 ◽  
Vol 54 ◽  
pp. 90-98 ◽  
Author(s):  
Zifeng Wu ◽  
Anuj Sharma ◽  
Fred L. Mannering ◽  
Shefang Wang

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