Real-time Traffic Flow Detection and Prediction Algorithm: Data-Driven Analyses on Spatio-Temporal Traffic Dynamics

Traffic flows over time and space. This spatio-temporal dependency of traffic flow should be considered and used to enhance the performance of real-time traffic detection and prediction capabilities. This characteristic has been widely studied and various applications have been developed and enhanced. During the last decade, great attention has been paid to the increases in the number of traffic data sources, the amount of data, and the data-driven analysis methods. There is still room to improve the traffic detection and prediction capabilities through studies on the emerging resources. To this end, this dissertation presents a series of studies on real-time traffic operation for highway facilities focusing on detection and prediction.First, a spatio-temporal traffic data imputation approach was studied to exploit multi-source data. Different types of kriging methods were evaluated to utilize the spatio-temporal characteristic of traffic data with respect to two factors, including missing patterns and use of secondary data. Second, a short-term traffic speed prediction algorithm was proposed that provides accurate prediction results and is scalable for a large road network analysis in real time. The proposed algorithm consists of a data dimension reduction module and a nonparametric multivariate time-series analysis module. Third, a real-time traffic queue detection algorithm was developed based on traffic fundamentals combined with a statistical pattern recognition procedure. This algorithm was designed to detect dynamic queueing conditions in a spatio-temporal domain rather than detect a queue and congestion directly from traffic flow variables. The algorithm was evaluated by using various real congested traffic flow data. Lastly, gray areas in a decision-making process based on quantifiable measures were addressed to cope with uncertainties in modeling outputs. For intersection control type selection, the gray areas were identified and visualized

Identification of Factors Affecting Pedestrian Satisfaction toward Land Use and Street Type

Walking is an essential sustainable mode of transportation. Encouraging to increase walking trips can bring various social and economic benefits to our society. Since the policy paradigm has been shifting from car-oriented to pedestrian-oriented, interest in securing pedestrian rights and improving walking environments is increasing significantly. This study aims to examine factors affecting pedestrian satisfaction according to land use and street type. A pedestrian satisfaction survey was conducted in an industrial city with a mid-size population in the city of Changwon, South Korea. Based on the survey data from 500 respondents, factors affecting pedestrian satisfaction were analyzed by land use (commercial or residential areas) and street type (non-separated or separated sidewalks). The analysis results, using binary and ordered logit models, showed that the less illegal parking, the more pedestrian space, pedestrian guidance facility, and green space, the higher the pedestrian satisfaction. Factors positively affecting the satisfaction of pedestrian paths according to land use were physical environmental variables, such as the separated sidewalk variable. In commercial areas, pedestrian guidance facilities and street cleanliness were included as major influencing factors, implying differences in land use influencing factors. A common factor affecting the satisfaction of separated or non-separated sidewalk cases was also identified as the sufficiency of walking space. Therefore, the most urgent policy measure for improving pedestrian satisfaction for the city was to install a sidewalk or expand the pedestrian space. In the pedestrian-vehicle separation models, green space and cleanliness were included as significant variables, and in the non-separated models, variables of pedestrian guidance facilities and sidewalk conditions were included

Estimating Destination of Bus Trips Considering Trip Type Characteristics

Recently, local governments have been using transportation card data to monitor the use of public transport and improve the service. However, local governments that are applying a single-fare scheme are experiencing difficulties in using data for accurate identification of real travel patterns or policy decision support due to missing information on alighting stops of users. This policy limits its functionality of utilizing data such as accurate identification of real travel patterns, policy decision support, etc. In order to overcome these limitations, various methods for estimating alighting stops have been developed. This study classifies trips with missing alighting stop information into trip four types and then applies appropriate alighting stop estimation methodology for each trip type in stages. The proposed method is evaluated by utilizing transportation card data of the Seoul metropolitan area and checking the accuracy for each standard of allowable error for sensitivity analysis. The analysis shows that the stage-by-stage estimation methodology based on the trip type proposed in this study can estimate users’ destinations more accurately than the methodologies of previous studies. Furthermore, based on the construction of nearly 100% valid tag data, this study differs from prior studies

Modeling public acceptance of demand-responsive transportation: An integrated UTAUT and ITM framework

Demand-responsive transportation (DRT) is a flexible form of shared mobility in which service provision is shaped by the user demand. DRT has been considered a sustainable mobility solution, as it reduces CO2 emissions from fixed-route services and encourages a mode shift from private cars to shared mobility. Given that public acceptance is a key for the wider diffusion of DRT, this study explored the factors affecting usage intention for DRT in the Republic of Korea. Drawing on the unified theory of acceptance and use of technology (UTAUT) and the initial trust model (ITM), a conceptual framework was developed that linked attitudinal and psychological factors to behavioral intention for DRT usage. 1168 valid observations were collected from adults aged 19–64 years in the Republic of Korea using a structured online survey, and analyzed using structural equation modeling. The results showed that the four UTAUT constructs (performance expectancy, social influence, facilitating conditions, and environmental concerns) were directly related to intention for DRT usage. Indirect impacts of perceived safety, structural assurance, familiarity, performance expectancy, and effort expectancy on initial trust were also found. Consequently, the constructs with the greatest total effect on usage intention were (in order of relevance) initial trust, performance expectancy, social influence, and structural assurance. As one of the few attempts to examine public acceptance of DRT, it is expected that findings from this study could contribute to the literature by providing insights into potential users’ attitudes toward DRT. This study further offers guidance on designing interventions intended to promote a transition toward increased operational efficiency through policy developments for DRT, thereby achieving sustainable development

Free-Standing Nanocomposite Multilayers with Various Length Scales, Adjustable Internal Structures, and Functionalities

We introduce an innovative and robust method for the preparation of nanocomposite multilayers, which allows accurate control over the placement of functional groups as well as the composition and dimensions of individual layers/internal structure. By employing the photocross-linkable polystyrene (PS-N3, Mn ) 28.0 kg/mol) with 10 wt % azide groups (-N3) for host polymer and/or the PS-N3-SH (Mn ) 6.5 kg/mol) with azide and thiol (-SH) groups for capping ligands of inorganic nanoparticles, nanocomposite multilayers were prepared by an efficient photocross-linking layer-by-layer process, without perturbing underlying layers and nanostructures. The thickness of individual layers could be controlled from a few to hundreds of nanometers producing highly ordered internal structure, and the resulting nanocomposite multilayers, consisting of polymer and inorganic nanoparticles (CdSe@ZnS, Au, and Pt), exhibit a variety of interesting physical properties. These include prolonged photoluminescent durability, facile color tuning, and the ability to prepare functional free-standing films that can have the one-dimensional photonic band gap and furthermore be patterned by photolithography. This robust and tailored method opens a new route for the design of functional film devices based on nanocomposite multilayers.This work was supported by the KOSEF grant funded by the Korea government (MEST) (R01-2008-000-10551-0), the SystemIC2010 project of Korea Ministry of Commerce Industry and Energy (10030559), the ERC Program of KOSEF grant funded by the Korea government (MEST) (R11-2005-048-00000-0), and the Materials Research Laboratory (NSF DMR-0520415) at the University of California, Santa Barbara

Graft Architectured Rod-Coil Copolymers Based on Alternating Conjugated Backbone: Morphological and Optical Properties

Controlling the self-assembly of conjugated copolymers is of great importance in tuning their physical and optoelectronic properties, offering potential pathways to greatly enhance the performance of organic electronics. Here, we report the synthesis of rod-coil graft copolymers containing an electroactive conjugated rod-like backbone and polymer coils as grafts and demonstrate the control of their ordered nanostructures. As a model system, we synthesized light-emitting poly(fluorene-alt-phenylene) (PFP) alternating copolymers and then grafted poly(2-vinylpyridine) (P2VP) chains with different lengths via a "click" reaction to produce a series of PFP-g-P2VP graft copolymers with various P2VP volume fractions (f(P2VP)). Interestingly, PFP-g-P2VP rod coil copolymers assembled into well-ordered cylinders and lamellae depending on f(P2VP) values that resembled those of the coil coil type block copolymers, but with very different f(P2VP) values for the morphological transitions (i.e., cylinders to lamellae). The morphological behavior of these graft copolymers was investigated using self-consistent-field theory simulations. Furthermore, by fully exploiting the controlled nanostructures of PFP-g-P2VP and the strong emitting properties of the PFP backbone, we developed multicolor colloidal particles that emit a broad range color spectrum from blue, white, and orange light. Our synthetic approach paves a new method for modulating the self-assembled nanostructures of rod coil copolymers and their optoelectronic properties

Serially Ordered Magnetization of Nanoclusters via Control of Various Transition Metal Dopants for the Multifractionation of Cells in Microfluidic Magnetophoresis Devices

A novel method (i.e., continuous magnetic cell separation in a microfluidic channel) is demonstrated to be capable of inducing multifractionation of mixed cell suspensions into multiple outlet fractions. Here, multicomponent cell separation is performed with three different distinguishable magnetic nanoclusters (MnFe2O4, Fe3O4, and CoFe2O4), which are tagged on A431 cells. Because of their mass magnetizations, which can be ideally altered by doping with magnetic atom compositions (Mn, Fe, and Co), the trajectories of cells with each magnetic nanocluster in a flow are shown to be distinct when dragged under the same external magnetic field; the rest of the magnetic characteristics of the nanoclusters are identically fixed. This proof of concept study, which utilizes the magnetization-controlled nanoclusters (NCs), suggests that precise and effective multifractionation is achievable with high-throughput and systematic accuracy for dynamic cell separation.1100sciescopu

Serially Ordered Magnetization of Nanoclusters via Control of Various Transition Metal Dopants for the Multifractionation of Cells in Microfluidic Magnetophoresis Devices

A novel method (i.e., continuous magnetic cell separation in a microfluidic channel) is demonstrated to be capable of inducing multifractionation of mixed cell suspensions into multiple outlet fractions. Here, multicomponent cell separation is performed with three different distinguishable magnetic nanoclusters (MnFe₂O₄, Fe₃O₄, and CoFe₂O₄), which are tagged on A431 cells. Because of their mass magnetizations, which can be ideally altered by doping with magnetic atom compositions (Mn, Fe, and Co), the trajectories of cells with each magnetic nanocluster in a flow are shown to be distinct when dragged under the same external magnetic field; the rest of the magnetic characteristics of the nanoclusters are identically fixed. This proof of concept study, which utilizes the magnetization-controlled nanoclusters (NCs), suggests that precise and effective multifractionation is achievable with high-throughput and systematic accuracy for dynamic cell separation