Mitigating congestion by integrating time forecasting and realtime information aggregation in cellular networks

An iterative travel time forecasting scheme, named the Advanced Multilane Prediction based Real-time Fastest Path (AMPRFP) algorithm, is presented in this dissertation. This scheme is derived from the conventional kernel estimator based prediction model by the association of real-time nonlinear impacts that caused by neighboring arcs’ traffic patterns with the historical traffic behaviors. The AMPRFP algorithm is evaluated by prediction of the travel time of congested arcs in the urban area of Jacksonville City. Experiment results illustrate that the proposed scheme is able to significantly reduce both the relative mean error (RME) and the root-mean-squared error (RMSE) of the predicted travel time. To obtain high quality real-time traffic information, which is essential to the performance of the AMPRFP algorithm, a data clean scheme enhanced empirical learning (DCSEEL) algorithm is also introduced. This novel method investigates the correlation between distance and direction in the geometrical map, which is not considered in existing fingerprint localization methods. Specifically, empirical learning methods are applied to minimize the error that exists in the estimated distance. A direction filter is developed to clean joints that have negative influence to the localization accuracy. Synthetic experiments in urban, suburban and rural environments are designed to evaluate the performance of DCSEEL algorithm in determining the cellular probe’s position. The results show that the cellular probe’s localization accuracy can be notably improved by the DCSEEL algorithm. Additionally, a new fast correlation technique for overcoming the time efficiency problem of the existing correlation algorithm based floating car data (FCD) technique is developed. The matching process is transformed into a 1-dimensional (1-D) curve matching problem and the Fast Normalized Cross-Correlation (FNCC) algorithm is introduced to supersede the Pearson product Moment Correlation Co-efficient (PMCC) algorithm in order to achieve the real-time requirement of the FCD method. The fast correlation technique shows a significant improvement in reducing the computational cost without affecting the accuracy of the matching process.

Evidence of climate variability and tropical cyclone activity from diatom assemblage dynamics in coastal southwest Florida

Estuaries are dynamic on many spatial and temporal scales. Distinguishing effects of unpredictable events from cyclical patterns can be challenging but important to predict the influence of press and pulse drivers in the face of climate change. Diatom assemblages respond rapidly to changing environmental conditions and characterize change on multiple time scales. The goals of this research were to 1) characterize diatom assemblages in the Charlotte Harbor watershed, their relationships with water quality parameters, and how they change in response to climate; and 2) use assemblages in sediment cores to interpret past climate changes and tropical cyclone activity. ^ Diatom assemblages had strong relationships with salinity and nutrient concentrations, and a quantitative tool was developed to reconstruct past values of these parameters. Assemblages were stable between the wet and dry seasons, and were more similar to each other than to assemblages found following a tropical cyclone. Diatom assemblages following the storm showed a decrease in dispersion among sites, a pattern that was consistent on different spatial scales but may depend on hydrological management regimes. ^ Analysis of sediment cores from two southwest Florida estuaries showed that locally-developed diatom inference models can be applied with caution on regional scales. Large-scale climate changes were suggested by environmental reconstructions in both estuaries, but with slightly different temporal pacing. Estimates of salinity and nutrient concentrations suggested that major hydrological patterns changed at approximately 5.5 and 3 kyrs BP. A highly temporally-resolved sediment core from Charlotte Harbor provided evidence for past changes that correspond with known climate records. Diatom assemblages had significant relationships with the three-year average index values of the Atlantic Multidecadal Oscillation and the El Niño Southern Oscillation. Assemblages that predicted low salinity and high total phosphorus also had the lowest dispersion and corresponded with some major storms in the known record, which together may provide a proxy for evidence of severe storms in the paleoecological record. ^