Optimization of adaptive traffic signal control with transit signal priority at isolated intersections using parallel genetic algorithms

Optimization of adaptive traffic signal timing is one of the most complex problems in traffic control systems. This dissertation presents a new method that applies the parallel genetic algorithm (PGA) to optimize adaptive traffic signal control in the presence of transit signal priority (TSP). The method can optimize the phase plan, cycle length, and green splits at isolated intersections with consideration for the performance of both the transit and the general vehicles. Unlike the simple genetic algorithm (GA), PGA can provide better and faster solutions needed for real-time optimization of adaptive traffic signal control. ^ An important component in the proposed method involves the development of a microscopic delay estimation model that was designed specifically to optimize adaptive traffic signal with TSP. Macroscopic delay models such as the Highway Capacity Manual (HCM) delay model are unable to accurately consider the effect of phase combination and phase sequence in delay calculations. In addition, because the number of phases and the phase sequence of adaptive traffic signal may vary from cycle to cycle, the phase splits cannot be optimized when the phase sequence is also a decision variable. A "flex-phase" concept was introduced in the proposed microscopic delay estimation model to overcome these limitations. ^ The performance of PGA was first evaluated against the simple GA. The results show that PGA achieved both faster convergence and lower delay for both under- or over-saturated traffic conditions. A VISSIM simulation testbed was then developed to evaluate the performance of the proposed PGA-based adaptive traffic signal control with TSP. The simulation results show that the PGA-based optimizer for adaptive TSP outperformed the fully actuated NEMA control in all test cases. The results also show that the PGA-based optimizer was able to produce TSP timing plans that benefit the transit vehicles while minimizing the impact of TSP on the general vehicles. The VISSIM testbed developed in this research provides a powerful tool to design and evaluate different TSP strategies under both actuated and adaptive signal control. ^

Understanding the relationship between the Talented Twenty program and college aspirations for high ranking students at a high priority school

Percentage plans such as the Talented Twenty program purport to assist and motivate high ranking students to attend college and grant access to higher education. This type of plan is particularly important to students enrolled in high priority schools who might not view themselves as potential college students. This study examined the relationship between Florida’s Talented Twenty program that begins intervention with juniors and the college aspirations for high ranking students at a high priority school. Numerous studies have established that increased levels of education lead to higher salaries, career mobility, and an increased quality of life (e.g., Bowen, 1997; Leslie & Brinkman 1988; Pascarella & Terenzini, 1991, Swail, 2000). Given the importance of students’ decisions regarding whether or not they will attend college, understanding how and when they make decisions about attending college is important for them, their parents, advisors, and educational administrators. This research examined students’ perceptions and insights via interviews. The overarching research question was: How do high ranking high school students attending a high priority school in a south Florida district perceive their college opportunities? Sixteen high ranking students, grades nine – 12 from a high priority school in Miami-Dade County participated in the study. Participants were identified by a school counselor and individual semi structured interviews were conducted at the school. Utilizing a student development theoretical framework developed by Hossler and Gallagher (1987) that centered on students’ predisposition, search strategies and choices, data were organized and emergent themes analyzed. The analysis of the data revealed that in alignment with the framework (a) parents were the strongest influence in the development of these students’ college aspirations, (b) these students formalized their higher education plans between eighth and 10th grade, (c) these students actively engaged in academic searches and learning opportunities that increased their chances to be admitted into college, and (d) there was no relationship between knowledge regarding the Talented Twenty program and their educational decisions. This study’s findings suggest that interventions and programs intended to influence the educational aspirations of students are more likely to succeed if they take place by the eighth or ninth grade.