A navigation and object location device for the blind

Gemstone Team Vision

DEVELOPMENT OF A DECISION/DEPLOYMENT SUPPORT TOOL FOR VARIABLE SPEED LIMITS IN RECURRENT CONGESTION

Traffic demand increases are pushing aging ground transportation infrastructures to their theoretical capacity. The result of this demand is traffic bottlenecks that are a major cause of delay on urban freeways. In addition, the queues associated with those bottlenecks increase the probability of a crash while adversely affecting environmental measures such as emissions and fuel consumption. With limited resources available for network expansion, traffic professionals have developed active traffic management systems (ATMS) in an attempt to mitigate the negative consequences of traffic bottlenecks. Among these ATMS strategies, variable speed limits (VSL) and ramp metering (RM) have been gaining international interests for their potential to improve safety, mobility, and environmental measures at freeway bottlenecks. Though previous studies have shown the tremendous potential of variable speed limit (VSL) and VSL paired with ramp metering (VSLRM) control, little guidance has been developed to assist decision makers in the planning phase of a congestion mitigation project that is considering VSL or VSLRM control. To address this need, this study has developed a comprehensive decision/deployment support tool for the application of VSL and VSLRM control in recurrently congested environments. The decision tool will assist practitioners in deciding the most appropriate control strategy at a candidate site, which candidate sites have the most potential to benefit from the suggested control strategy, and how to most effectively design the field deployment of the suggested control strategy at each implementation site. To do so, the tool is comprised of three key modules, (1) Decision Module, (2) Benefits Module, and (3) Deployment Guidelines Module. Each module uses commonly known traffic flow and geometric parameters as inputs to statistical models and empirically based procedures to provide guidance on the application of VSL and VSLRM at each candidate site. These models and procedures were developed from the outputs of simulated experiments, calibrated with field data. To demonstrate the application of the tool, a list of real-world candidate sites were selected from the Maryland State Highway Administration Mobility Report. Here, field data from each candidate site was input into the tool to illustrate the step-by-step process required for efficient planning of VSL or VSLRM control. The output of the tool includes the suggested control system at each site, a ranking of the sites based on the expected benefit-to-cost ratio, and guidelines on how to deploy the VSL signs, ramp meters, and detectors at the deployment site(s). This research has the potential to assist traffic engineers in the planning of VSL and VSLRM control, thus enhancing the procedure for allocating limited resources for mobility and safety improvements on highways plagued by recurrent congestion.

Exploring the Function and Regulation of Arabidopsis EIN2 in Ethylene Signaling

Ethylene is an essential plant hormone involved in nearly all stages of plant growth and development. EIN2 (ETHYLENE INSENSITIVE2) is a master positive regulator in the ethylene signaling pathway, consisting of an N-terminal domain and a C-terminal domain. The EIN2 N-terminal domain localizes to the endoplasmic reticulum (ER) membrane and shows sequence similarity to Nramp metal ion transporters. The cytosolic C-terminal domain is unique to plants and signals downstream. There have been several major gaps in our knowledge of EIN2 function. It was unknown how the ethylene signal gets relayed from the known upstream component CTR1 (CONSTITUTIVE RESPONSE1) a Ser/Thr kinase at the ER, to EIN2. How the ethylene signal was transduced from EIN2 to the next downstream component transcription factor EIN3 (ETHYLENE INSENSITIVE3) in the nucleus was also unknown. The N-terminal domain of EIN2 shows homology to Nramp metal ion transporters and whether EIN2 can also function as a metal transporter has been a question plaguing the ethylene field for almost two decades. Here, EIN2 was found to interact with the CTR1 protein kinase, leading to the discovery that CTR1 phosphorylates the C-terminal domain of EIN2 in Arabidopsis thaliana. Using tags at the termini of EIN2, it was deduced that in the presence of ethylene, the EIN2 C-terminal domain is cleaved and translocates into the nucleus, where it could somehow activate downstream ethylene responses. The EIN2 C-terminal domain interacts with nuclear proteins, RTE3 and EER5, which are components of the TREX-2 mRNA export complex, although the role of these interactions remains unclear. The EIN2 N-terminal domain was found to be capable of divalent metal transport when expressed in E. coli and S. cerevisiae leading to the hypothesis that metal transport plays a role in ethylene signaling. This hypothesis was tested using a novel missense allele, ein2 G36E, substituting a highly conserved residue that is required for metal transport in Nramp proteins. This G36E substitution did not disrupt metal ion transport of EIN2, but the ethylene insensitive phenotype of this mutant indicates that the EIN2 N-terminal domain is important for positively regulating the C-terminal domain. The defect of the ein2 G36E mutant does not prevent proper expression or subcellular localization, but might affect protein modifications. The ein2 G36E allele is partially dominant, mostly likely displaying haploinsufficiency. Overexpression of the EIN2 N-terminal domain in the ein2 G36E mutant did not rescue ethylene insensitivity, suggesting the N-terminal domain functions in cis to regulate the C-terminal domain. These findings advance our knowledge of EIN2, which is critical to understanding ethylene signaling.

Development of Planning And Evaluation Models For Superstreets

Despite the extensive implementation of Superstreets on congested arterials, reliable methodologies for such designs remain unavailable. The purpose of this research is to fill the information gap by offering reliable tools to assist traffic professionals in the design of Superstreets with and without signal control. The entire tool developed in this thesis consists of three models. The first model is used to determine the minimum U-turn offset length for an Un-signalized Superstreet, given the arterial headway distribution of the traffic flows and the distribution of critical gaps among drivers. The second model is designed to estimate the queue size and its variation on each critical link in a signalized Superstreet, based on the given signal plan and the range of observed volumes. Recognizing that the operational performance of a Superstreet cannot be achieved without an effective signal plan, the third model is developed to produce a signal optimization method that can generate progression offsets for heavy arterial flows moving into and out of such an intersection design.