Global ETD Search

11	Using Augmented Reality For Studying Left Turn Maneuver At Un-signalized Intersection And Horizontal Visibility Blockage Moussa, Ghada 01 January 2006 (has links) Augmented reality "AR" is a promising paradigm that can provide users with real-time, high-quality visualization of a wide variety of information. In AR, virtual objects are added to the real-world view in a real time. Using the AR technology can offer a very realistic environment for driving enhancement as well as driving performance testing under different scenarios. This can be achieved by adding virtual objects (people, vehicles, hazards, and other objects) to the normal view while driving in a safe controlled environment. In this dissertation, the feasibility of adapting the AR technology into traffic engineering was investigated. Two AR systems; AR Vehicle "ARV" system and Offline AR Simulator "OARSim" system were built. The systems' outcomes as well as the on-the-road driving under the AR were evaluated. In evaluating systems' outcomes, systems were successfully able to duplicate real scenes and generate new scenes without any visual inconsistency. In evaluating on-the-road driving under the AR, drivers' distance judgment, speed judgment, and level of comfort while driving were evaluated. In addition, our systems were used to conduct two traffic engineering studies; left-turn maneuver at un-signalized intersection, and horizontal visibility blockage when following a light truck vehicle. The results from this work supported the validity of our AR systems to be used as a surrogate to the field-testing for transportation research. Augmented reality Traffic engineering Left-turn maneuver Horizontal visibility blockage Civil Engineering Engineering
12	Evaluating the Effectiveness of Conversion of Traditional Five Section Head Signal to Flashing Yellow Arrow (FYA) Signal Almoshaogeh, Meshal 01 January 2014 (has links) In the United States, there are two schemes of operating traffic signal controls for permitted protected left turns (PPLT) namely the traditional five-section head system (known as Dog-House) and the flashing yellow arrow system (FYA). Past studies have agreed that these controls lead to decrease the average delay per left turn vehicle, decrease the protected green time, increase the left turn capacity, and enhance the intersection overall operation. The flashing yellow arrow (FYA) has been approved by the Federal Highway Administration as the national standard for the PPLT operations at signalized intersections. So, the Florida Department of Transportation also approved this new system and they are extensively replacing the traditional system with the new system on the area of Central Florida (Lin, et al, 2010). Both these systems have been used for a long time and there are some studies that evaluated these systems but there are limited number of projects that evaluated and/or compared between the two PPLT systems from the operational perspective. The main goal of this research is to study the characteristics of traffic operations and evaluate the effectiveness of the conversion from five-section head signal to the FYA treatments at 13 intersections located in Orlando, Florida. To reach this goal, detailed data collection efforts were conducted at 13 selected intersections in the central Florida area and appropriate statistical tests were conducted using the Minitab 17 Software. Statistical tests were attempted to fit different new regression models that correlate delay and left turn volumes as response variables against a set of independent variables that included permitted green time, opposing volume, percent of trucks, time gaps, speed, and land use type. In addition to fitting the data to regression models, these models were also analyzed for the purpose of detecting any significant differences between the five-section head treatment and FYA treatment. The statistical differences of converting the five-section head system to FYA system were discussed. The results in this thesis agreed with some of the previous studies and did not agree with others. In general, the flashing yellow arrow system was found to enhance the intersection operation, increase the number of left turn vehicles, and reduce the delay. Also, some suggestions and recommendations were made based on this study results. Flashing yellow arrow (fya) permitted/protected left turn (pplt) five section head signal Engineering Transportation Engineering
13	Analysis of gap acceptances for left turn maneuver at the two way stop-controlled intersection using a driving simulator Yan, Xuedong 01 April 2003 (has links) No description available. Civil and Environmental Engineering Engineering
14	Safety Effectiveness of Conversion of Two-Way-Left-Turn Lanes into Raised Medians Alarifi, Saif 01 January 2014 (has links) Two way left turn lanes (TWLTL) and raised medians are common median treatments on roadways. This research focused on evaluating the safety effectiveness of conversion of TWLTLs into raised medians using Before-After and Cross Sectional Studies. In the Before-After Studies, we evaluated the effect of this treatment using the Naive, Before-After with Comparison Group (CG), and Before-After with Empirical Bayes (EB) Methods. In order to apply these methods, a total of 33 segments of a treated group and 109 segments of a comparison group have been collected. Also, safety performance functions (SPFs) have been developed using the negative binomial model in order to calibrate crash modification factors (CMF) using the Before-After with Empirical Bayes Method. This research also evaluated the safety effectiveness of this treatment on four and six lane roads using Before-After with CG and Before-After with EB. The type of raised medians was further evaluated using Before-After with CG and EB. In sum, the results from this study show that applying the before-After and Cross Sectional studies have proved that the conversion from a TWLTL to a raised median helped to reduce total, fatal and injury, head on, angle, and left turn crashes. It significantly reduces crashes for head-on and left turn crashes, by restricting turning maneuvers. Also, this study has proved that the treatment is more effective on four rather than six lane roads. Furthermore, two types of raised medians, concrete and lawn curb, were evaluated after the conversion from TWLTLs. It was found that both medians have similar effects due to the conversion, and both median types helped in reducing the number of crashes. Crash modification factor before after studies Engineering Transportation Engineering
15	Safety Issues Of Red-light Running And Unprotected Left-turn At Signalized Intersections Yan, Xuedong 01 January 2005 (has links) Crashes categorized as running red light or left turning are most likely to occur at signalized intersections and resulted in substantial severe injuries and property damages. This dissertation mainly focused on these two types of vehicle crashes and the research methodology involved several perspectives. To examine the overall characteristics of red-light running and left-turning crashes, firstly, this study applied 1999-2001 Florida traffic crash data to investigate the accident propensity of three aspects of risk factors related to traffic environments, driver characteristics, and vehicle types. A quasi-induced exposure concept and statistical techniques including classification tree model and multiple logistic regression were used to perform this analysis. Secondly, the UCF driving simulator was applied to test the effect of a proposed new pavement marking countermeasure which purpose is to reduce the red-light running rate at signalized intersections. The simulation experiment results showed that the total red-light running rate with marking is significantly lower than that without marking. Moreover, deceleration rate of stopping drivers with marking for the higher speed limit are significantly less than those without marking. These findings are encouraging and suggesting that the pavement marking may result in safety enhancement as far as right-angle and rear-end traffic crashes at signalized intersections. Thirdly, geometric models to compute sight distances of unprotected left-turns were developed for different signalized intersection configurations including a straight approach leading to a straight one, a straight approach leading to a curved one, and a curved approach leading to a curved one. The models and related analyses can be used to layout intersection design or evaluate the sight distance problem of an existing intersection configuration to ensure safe left-turn maneuvers by drivers. Red-light Running Driving Simulator Unprotected Left-turn Sight Distance Signalized Intersection Traffic Safety Civil Engineering Engineering
16	An Analysis of Decision Boundaries for Left-Turn Treatments Adamson, Michael Louis 01 April 2019 (has links) The purpose of this project is to evaluate the safety and operational differences between three left-turn treatments: permitted, protected, and protected-permitted left-turn phasing. Permitted phasing allows vehicles to turn left after yielding to any opposing vehicles; protected phasing provides an exclusive phase for vehicles to turn left that does not allow opposing vehicles; and protected-permitted phasing combines the previous phasing alternatives, allowing vehicles to turn after yielding while also providing some green time for protected left-turns.As part of evaluating the differences between these left-turn treatments, crashes before and after the change at intersections that had experienced a permanent change from one phase alternative to another were compared. The crashes that took place at these intersections were compared with the number of crashes experienced at a baseline set of intersections. A general increase in total crashes was observed for most intersections, and an increase in left-turn crashes per million entering vehicles was also observed in intersections that had experienced a change from protected to protected-permitted phasing; no other clear trends were observed.The research team also gathered simulated data using VISSIM traffic modeling software and safety data were extracted from these simulations using the Surrogate Safety Assessment Model (SSAM) created by the Federal Highway Administration to identify decision boundaries between each left-turn treatment. The simulations modeled intersections with 1-, 2-, and 3-opposing-lane configurations with permitted and protected-permitted models (split into green times of 10-, 15-, and 20-seconds) for a total of 12 different simulation models. Each model was divided into 100-225 different volume scenarios, with incremental increases in left-turn vs. opposing volumes. By exporting trajectory files from VISSIM and importing these files into SSAM, crossing conflicts for each volume combination in each model were identified and extracted. These were then entered into MATLAB to create contour maps; the contours of these maps represent the number of crossing conflicts per hour associated with different combinations of left-turn and opposing volume. Basic decision boundaries were observed in the contour maps for each model. To extract an equation to estimate each boundary, JMP Pro statistical analysis software was used to perform a linear regression analysis and develop natural log-based equations estimating the decision boundaries for each configuration and phase alternative. These equations were then charted using Excel and final decision boundaries were developed for the 1-, 2-, and 3-lane configurations between permitted and protected-permitted phasing as well as between protected-permitted and protected phasing. decision boundary intersection operations intersection safety left-turn safety signal operations SSAM UDOT VISSIM warrant Civil and Environmental Engineering Engineering
17	Modeling Permissive Left-Turn Gap Acceptance Behavior at Signalized Intersections Zohdy, Ismail Hisham 04 December 2009 (has links) The research presented in this thesis, studies driver gap acceptance behavior for permissive left turn movements at signalized intersections. The thesis attempts to model the gap acceptance behavior using three different approaches, a deterministic statistical approach, a stochastic approach, and a psycho-physical approach. First, the deterministic statistical modeling approach is conducted using logistic regression to characterize the impact of a number of variables on driver gap acceptance behavior. The variables studied are the gap duration, the driver's wait time in search of an acceptable gap, the time required to travel to clear the conflict point, and the rain intensity. Considering stochastic gap acceptance, two stochastic approaches are compared, namely: a Bayesian and a Bootstrap approach. The study develops a procedure to model stochastic gap acceptance behavior while capturing model parameter correlations without the need to store all parameter combinations. The model is then implemented to estimate stochastic opposed saturation flow rates. Finally, the third approach uses a psycho-physical modeling approach. The physical component captures the vehicle constraints on gap acceptance behavior using vehicle dynamics models while the psychological component models the driver deliberation and decision process. In general, the three proposed models capture gap acceptance behavior for different vehicle types, roadway surface conditions, weather effects and types of control which could affect the driver gap acceptance behavior. These findings can be used to develop weather responsive traffic signal timings and can also be integrated into emerging IntelliDrive systems. / Master of Science Gap acceptance Permissive left turn Saturation flow rate Weather impact Logit models Bayesian approach Boot strapping Vehicle dynamics
18	PREDICTION OF PROTECTED-PERMISSIVE LEFT-TURN PHASING CRASHES BASED ON CONFLICT ANALYSIS Sagar, Shraddha 01 January 2017 (has links) Left-turning maneuvers are considered to be the highest risk movements at intersections and two-thirds of the crashes associated with left-turns are reported at signalized intersections. Left-turning vehicles typically encounter conflicts from opposing through traffic. To separate conflicting movements, transportation agencies use a protected-only phase at signalized intersections where each movement is allowed to move alone. However, this could create delays and thus the concept of a protected-permissive phase has been introduced to balance safety and delays. However, the permissive part of this phasing scheme retains the safety concerns and could increase the possibility of conflicts resulting in crashes. This research developed a model that can predict the number of crashes for protected-permissive left-turn phasing, based on traffic volumes and calculated conflicts. A total of 103 intersections with permissive-protected left-turn phasing in Kentucky were simulated and their left-turn related conflicts were obtained from post processing vehicle trajectories through the Surrogate Safety Assessment Model (SSAM). Factors that could affect crash propensity were identified through the Principal Component Analysis in Negative Binomial Regression. Nomographs were developed from the models which can be used by traffic engineers in left-turn phasing decisions with enhanced safety considerations. Left-Turn Phasing Decisions Microsimulation Surrogate Safety Measures Conflict Points Civil and Environmental Engineering Engineering Transportation Engineering
19	Pedestrian safety at signalized intersections operating the flashing yellow arrow Tuss, Halston 21 September 2012 (has links) At signalized intersections, pedestrians are considered to be amongst the most vulnerable. When in the crosswalk at intersections without protected left-turn phasing, pedestrians are particularly at risk from left-turning vehicles. Until recently, a wide variety of indications were in use across the US to indicate a permissive left-turn condition to the driver. In Oregon, the Flashing Yellow Arrow (FYA) has been used to indicate the permissive left-turn condition for approximately 10 years. With the addition of the FYA in the 2009 MUTCD, it is likely that its use will continue to increase nationally. Though many operational and safety issues have been studied about the FYA indication, this research proposes to fully investigate factors that influence driver behavior in the context of the permissive left-turn conflict with pedestrians. Specifically, the research seeks to study driver glance behavior to identify reasons why drivers are, "looking at but not seeing" pedestrians in or near the crosswalk or not searching for the presence of pedestrians at all. / Graduation date: 2013 Transportation Pedestrian crosswalks -- Safety measures Motor vehicle drivers Left-turn lanes -- Safety measures
20	GIS-based Episode Reconstruction Using GPS Data for Activity Analysis and Route Choice Modeling / GIS-based Episode Reconstruction Using GPS Data Dalumpines, Ron 26 September 2014 (has links) Most transportation problems arise from individual travel decisions. In response, transportation researchers had been studying individual travel behavior – a growing trend that requires activity data at individual level. Global positioning systems (GPS) and geographical information systems (GIS) have been used to capture and process individual activity data, from determining activity locations to mapping routes to these locations. Potential applications of GPS data seem limitless but our tools and methods to make these data usable lags behind. In response to this need, this dissertation presents a GIS-based toolkit to automatically extract activity episodes from GPS data and derive information related to these episodes from additional data (e.g., road network, land use). The major emphasis of this dissertation is the development of a toolkit for extracting information associated with movements of individuals from GPS data. To be effective, the toolkit has been developed around three design principles: transferability, modularity, and scalability. Two substantive chapters focus on selected components of the toolkit (map-matching, mode detection); another for the entire toolkit. Final substantive chapter demonstrates the toolkit’s potential by comparing route choice models of work and shop trips using inputs generated by the toolkit. There are several tools and methods that capitalize on GPS data, developed within different problem domains. This dissertation contributes to that repository of tools and methods by presenting a suite of tools that can extract all possible information that can be derived from GPS data. Unlike existing tools cited in the transportation literature, the toolkit has been designed to be complete (covers preprocessing up to extracting route attributes), and can work with GPS data alone or in combination with additional data. Moreover, this dissertation contributes to our understanding of route choice decisions for work and shop trips by looking into the combined effects of route attributes and individual characteristics. / Dissertation / Doctor of Philosophy (PhD) GPS time use diary episode extraction multinomial logit travel behavior mode detection episode reconstruction GIS map-matching route choice path size logit potential path area scale estimation Python ArcGIS activity analysis trip reconstruction smartphone global positioning system geographic information system toolkit work trip shop trip potential activity location land use activity episode travel episode stop episode transferability scalability modularity scripting big data travel survey respondent burden preprocessing multipath error tracking purpose detection segmentation data filter data smoothing fuzzy logic neural network decision tree rule-based algorithm trajectory point road network network dataset gateway shortest path horizontal dilution of precision HDOP commonality factor mode transfer point Halifax Nova Scotia Space-Time Activity Research variance inflation factor shapefile comma-separated values traveling salesman problem data mining branch-and-bound algorithm pedestrian network alternative route observed route route efficiency route attributes distance time heading bearing duration acceleration latitude longitude coordinate overlay analysis intersect shopping module data logger walk likelihood ratio test classification table path generation kappa statistic degrees data collection transportation research automate framework ArcToolbox spatio-temporal navigation positioning trace path spatial data topology horizontal accuracy SPSS Stata spatial resolution temporal resolution household survey trip reporting proximity analysis DMTI Desktop Mapping Technologies Inc. road intersection route overlap left turn right turn location analysis time geography spatial statistics buffer analysis cycling bus transit public transportation GEOIDE AGILE data need raw data urban canyon endpoint data cleaning elevation satellite outliers automatic processing nearest node classifier classification method short trip multi-point

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