Impact of road environment on drivers' behaviors in dilemma zone: Application of agent-based simulation.

At a signalized intersection, there exists an area where drivers become indecisive as to either stop their car or proceed through when the traffic signal turns yellow. This point, called a dilemma zone, has remained a safety concern for drivers due to the great possibility of a rear-end or right-angle crash occurring. In order to reduce the risk of car crashes at the dilemma zone, Institute of Transportation Engineers (ITE) recommended a dilemma zone model. The model, however, fails to provide precise calculations on the decision of drivers because it disregards the supplemental roadway information, such as whether a red light camera is present. Hence, the goal of this study was to incorporate such roadway environmental factors into a more realistic driver decision-making model for the dilemma zone. A driving simulator was used to determine the influence of roadway conditions on decision-making of real drivers. Following data collection, each driver's decision outcomes were implemented in an Agent-Based Simulation (ABS) so as to analyze behaviors under realistic road environments. The experimental results revealed that the proposed dilemma zone model was able to accurately predict the decisions of drivers. Specifically, the model confirmed the findings from the driving simulator study that the changes in the roadway environment reduced the number of red light violations at an intersection.

A Variation of Cover-Free Families and Its Applications.

A cover-free family is a family of subsets of a finite set in which no one is covered by the union of r others. We study a variation of cover-free family: A binary matrix is (r, w]-consecutive-disjunct if for any w cyclically consecutive columns [Formula: see text] and another r cyclically consecutive columns [Formula: see text], there exists one row intersecting [Formula: see text] but none of [Formula: see text]. In group testing, the goal is to determine a small subset of positive items D in a large population [Formula: see text] by group tests. By applying consecutive-disjunct matrices, we solve threshold group testing of consecutive positives in [Formula: see text] group tests nonadaptively, and the decoding complexity is [Formula: see text] where u is a threshold parameter in threshold group testing and it is assumed that |D|≤d and [Formula: see text]. Meanwhile, we obtain that for group testing of consecutive positives, all positives can be identified in [Formula: see text] group tests nonadaptively and the decoding complexity is [Formula: see text].