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Articles 31 - 60 of 103
Full-Text Articles in Transportation Engineering
Remediation Of Roadway Runoff Nutrients: Querying Sources Delivery Mechanism, Efficacy Of Stormwater Best Management Practices, And Stormwater Routing Through Karst Geology, Mohammad Shokri
Electronic Theses and Dissertations, 2020-2023
Stormwater road runoff is a widespread non-point source of contaminants such as nutrients, which endangers water bodies, especially in vulnerable karst areas such as Florida. While roadside vegetated filter strips (VFSs) and stormwater basins are generally accepted best management practices (BMPs) for stormwater management, uncertainties about VFS nutrient removal are reported and stormwater basins are concerned of facilitating contaminant transport. In this dissertation, the application and efficacy of engineered infiltration media was tested as a subgrade for the enhanced nutrient removal from roadway runoff. Results of field-scale laboratory testing indicated that a VFS with engineered biosorption activated media (BAM) outperformed …
Modeling Of Crash Risk For Realistic Artificial Data Generation: Application To Naturalistic Driving Study Data, Lauren Hoover
Modeling Of Crash Risk For Realistic Artificial Data Generation: Application To Naturalistic Driving Study Data, Lauren Hoover
Electronic Theses and Dissertations, 2020-2023
Most safety performance analysis employs cross-sectional and time-series datasets, posing an important challenge to safety performance and crash modification analysis. The traditional safety model analysis paradigm relying on observed data only allows relative comparisons between analysis methods and is unable to establish how well the methods mimic the true underlying crash generation process. Assumptions are made about the data, but whether the assumptions truly characterize the safety data generation in the real world remains unknown. To address this issue, this thesis proposes the generation of realistic artificial data (RAD). In developing a prototype RAD generator for crash data, we mimic …
Evaluation Of Unconventional Signalized Intersections On Arterial Roads And A Proposition For A Novel Intersection Design, Ma'en Al-Omari
Evaluation Of Unconventional Signalized Intersections On Arterial Roads And A Proposition For A Novel Intersection Design, Ma'en Al-Omari
Electronic Theses and Dissertations, 2020-2023
Several unconventional intersection designs were proposed and implemented to enhance traffic safety and operation at intersections. The efficiency of these intersection designs was not sufficiently evaluated in the previous research because of the limited implementation of such designs. However, with the growing interest in the implementation of unconventional intersections by municipalities and transport agencies, it has become a need for a comprehensive evaluation of their safety and operational benefits. Therefore, this dissertation aims to evaluate the safety and operational aspects of unconventional intersection designs by employing different research approaches: crash analysis, microscopic simulation, and driving simulation. Firstly, this dissertation evaluated …
Real-Time Traffic Safety Evaluation In The Context Of Connected Vehicles And Mobile Sensing, Pei Li
Real-Time Traffic Safety Evaluation In The Context Of Connected Vehicles And Mobile Sensing, Pei Li
Electronic Theses and Dissertations, 2020-2023
Recently, with the development of connected vehicles and mobile sensing technologies, vehicle-based data become much easier to obtain. However, only few studies have investigated the application of this kind of novel data to real-time traffic safety evaluation. This dissertation aims to conduct a series of real-time traffic safety studies by integrating all kinds of available vehicle-based data sources. First, this dissertation developed a deep learning model for identifying vehicle maneuvers using data from smartphone sensors (i.e., accelerometer and gyroscope). The proposed model was robust and suitable for real-time application as it required less processing of smartphone sensor data compared with …
Safety And Operations Of Urban Arterials Incorporating The Context Classification System, Nada Mahmoud
Safety And Operations Of Urban Arterials Incorporating The Context Classification System, Nada Mahmoud
Electronic Theses and Dissertations, 2020-2023
Urban arterials connect multiple areas in the city and encourage non-motorist activities. Hence, the safety and operations on urban arterials is vital as they improve the mobility of daily commuters and road users. This research aims to facilitate traffic operations on urban arterials by proposing multiple mythological approaches to estimate and predict turning movement counts at signalized intersections using traffic data from adjacent intersections. Further, it aims to improve the safety by developing crash prediction models, identifying the hotspots for multiple crash types, and indicating the factors contributing to operating speed as well as non-motorist crashes. The analyses included tuning, …
Crash Analysis And Development Of Safety Performance Functions For Florida Roads In The Framework Of The Context Classification System, Ma'en Al-Omari
Crash Analysis And Development Of Safety Performance Functions For Florida Roads In The Framework Of The Context Classification System, Ma'en Al-Omari
Electronic Theses and Dissertations, 2020-2023
Nowadays, technology is employed in many safety applications and countermeasures that would enhance traffic safety by influencing some crash-related factors. Therefore, crash-related factors must be determined for every roadway element by the development of safety performance functions. Safety performance functions (SPF) are employed to predict crash counts at the different roadway elements. Several SPFs have been developed for the various roadway elements based on different classifications such as functional classification and area type. Since a more detailed classification of roadway elements leads to more accurate crash predictions, multiple states have developed new system to categorize roads based on a comprehensive …
Monitoring Of Microscopic Traffic Behavior For Safety Applications Using Temporal Logic, Mariam Wessam Hassan Mohamed Nour
Monitoring Of Microscopic Traffic Behavior For Safety Applications Using Temporal Logic, Mariam Wessam Hassan Mohamed Nour
Electronic Theses and Dissertations, 2020-2023
Smart cities are revolutionizing the transportation infrastructure by the integration of technology. However, ensuring that various transportation system components are operating as expected and in a safe manner is a great challenge. One of the proposed solutions is traffic monitoring systems which collect and analyze traffic data for the safe operation and management of the overall system. Even though traffic safety analysis has been tied to crash data, surrogate safety measures (SSM) have recently emerged as a replacement. SSM can provide a convenient alternative for understanding the impact of conflicts on overall road safety. Traditionally, conflicts were studied through manual …
Applying Machine Learning Techniques To Improve Safety And Mobility Of Urban Transportation Systems Using Infrastructure- And Vehicle-Based Sensors, Zubayer Islam
Electronic Theses and Dissertations, 2020-2023
The importance of sensing technologies in the field of transportation is ever increasing. Rapid improvements of cloud computing, Internet of Vehicles (IoV), and intelligent transport system (ITS) enables fast acquisition of sensor data with immediate processing. Machine learning algorithms provide a way to classify or predict outcomes in a selective and timely fashion. High accuracy and increased volatility are the main features of various learning algorithms. In this dissertation, we aim to use infrastructure- and vehicle-based sensors to improve safety and mobility of urban transportation systems. Smartphone sensors were used in the first study to estimate vehicle trajectory using lane …
Identifying The Links Between Mental Frameworks, Context Features, And Driver Attention In Complete Streets Environments, Patricia Tice
Identifying The Links Between Mental Frameworks, Context Features, And Driver Attention In Complete Streets Environments, Patricia Tice
Electronic Theses and Dissertations, 2020-2023
Complete street systems integrate a wide range of users in the same space, with unequal risks and responsibilities. This makes driver attention a critical factor in assuring the safety of vulnerable users. The Conditioned Anticipation of People psychological model of driver attention proposes that drivers reflexively reengage their metacognitive processes when they anticipate visually interacting with the human face or form due to the neurological priority that the brain places on human recognition. To test this model, an eye-tracking tabulation was generated from the SHRP2 Naturalistic Driving Study that measured midsegment percent of time on-task and multitasking behavior for 200 …
Safety Evaluation Of Innovative Intersection Designs: Diverging Diamond Interchanges And Displaced Left-Turn Intersections, Ahmed Abdelrahman
Safety Evaluation Of Innovative Intersection Designs: Diverging Diamond Interchanges And Displaced Left-Turn Intersections, Ahmed Abdelrahman
Electronic Theses and Dissertations, 2020-2023
Diverging diamond interchanges (DDIs) and Displaced left-turn intersections (DLTs) are designed to enhance the operational performance of conventional intersections that are congested due to heavy left-turn traffic volumes. Since drivers are not familiar with these types of intersections, there is a need to evaluate their safety performance to validate their effect, and to estimate reliable and representative Crash Modification Factors (CMFs). The safety evaluation was conducted based on three common safety assessment methods, which are before-and-after study with comparison group, Empirical Bayes before-and-after method, and cross-sectional analysis. Furthermore, since DLTs showed poor safety performance, the study also investigated the operational …
Traffic Speed Prediction And Mobility Behavior Analysis Using On-Demand Ride-Hailing Service Data, Jiechao Zhang
Traffic Speed Prediction And Mobility Behavior Analysis Using On-Demand Ride-Hailing Service Data, Jiechao Zhang
Electronic Theses and Dissertations, 2020-2023
Providing accurate traffic speed prediction is essential for the success of Intelligent Transportation Systems (ITS) deployments. Accurate traffic speed prediction allows traffic managers take proper countermeasures when emergent changes happen in the transportation network. In this thesis, we present a computationally less expensive machine learning approach XGBoost to predict the future travel speed of a selected sub-network in Beijing's transportation network. We perform different experiments for predicting speed in the network from future 1 min to 20 min. We compare the XGBoost approach against other well-known machine learning and statistical models such as linear regression and decision tree, gradient boosting …
Prediction Of Pedestrians' Red Light Violations Using Deep Learning, Shile Zhang
Prediction Of Pedestrians' Red Light Violations Using Deep Learning, Shile Zhang
Electronic Theses and Dissertations, 2020-2023
Pedestrians are regarded as Vulnerable Road Users (VRUs). Each year, thousands of pedestrians' deaths are caused by traffic crashes, which take up 16% of the total road fatalities and injuries in the U.S. (FHWA, 2018). Crashes can happen if there are interactions between VRUs and motorized transportation. And pedestrians' unexpected crossings, such as red-light violations at the signalized intersections, would expose them to motorized transportation and cause potential collisions. This thesis is intended to predict the pedestrians' red-light violation behaviors at the signalized crosswalks based on an LSTM (Long Short-term Memory) neural network. With video data collected from real traffic …
Modeling Of Incident Type And Incident Duration Using Data From Multiple Years, Sudipta Dey Tirtha
Modeling Of Incident Type And Incident Duration Using Data From Multiple Years, Sudipta Dey Tirtha
Electronic Theses and Dissertations, 2020-2023
We develop a model system that recognizes the distinct traffic incident duration profiles based on incident type. Specifically, a copula-based joint framework with a scaled multinomial logit model (SMNL) system for incident type and a grouped generalized ordered logit (GGOL) model system for incident duration to accommodate for the impact of observed and unobserved effects on incident type and incident duration. The model system is estimated using traffic incident data from 2012 through 2017 for the Greater Orlando region, employing a comprehensive set of exogenous variables – incident characteristics, roadway characteristics, traffic condition, weather condition, built environment and socio-demographic characteristics. …
Mobility-As-A-Service: Assessing Performance And Sustainability Effects Of An Integrated Multi-Modal Simulated Transportation Network, Mohamed El-Agroudy
Mobility-As-A-Service: Assessing Performance And Sustainability Effects Of An Integrated Multi-Modal Simulated Transportation Network, Mohamed El-Agroudy
Electronic Theses and Dissertations, 2020-2023
Advances in information technology services have seen profound impacts on the state of transport services in the urban traffic environment. Mobility-as-a-Service (MaaS) represents the digital consolidation of users, operators, and public-private managing entities to provide totally comprehensive, integrated trip-making services. Users now enjoy extra flexibility for trip-making with new modal alternatives such as micro-mobility (e.g Lime Bikes, Spin Scooters) and rideshare (e.g. Lyft, Uber). However, current knowledge on the performance and interactive effects of these newer alternative modes is vague if not inconsistent. As such, these effects were studied through micro-simulation analysis of a multi-modal urban corridor in Orlando, Florida. …
Evaluation Of Safety And Mobility Benefits Of Connected And Automated Vehicles By Considering V2x Technologies, Md Hasibur Rahman
Evaluation Of Safety And Mobility Benefits Of Connected And Automated Vehicles By Considering V2x Technologies, Md Hasibur Rahman
Electronic Theses and Dissertations, 2020-2023
The recent development in communication technologies facilitates the deployment of connected and automated vehicles (CAV) which are expected to change the future transportation system. CAV technologies enable vehicles to communicate with other vehicles through vehicle-to-vehicle (V2V) communications and the infrastructure through Vehicle-to-infrastructure (V2I) communications. Since the real-world CAV data is not currently available as of today, simulation is the most commonly used platform to evaluate the future V2X system. Although several studies evaluated the effectiveness of CAVs in a small roadway network, there is a lack of studies analyzing the impact of CAVs at the network level by considering both …
A Deep Learning Approach For Real-Time Crash Risk Prediction At Urban Arterials, Pei Li
A Deep Learning Approach For Real-Time Crash Risk Prediction At Urban Arterials, Pei Li
Electronic Theses and Dissertations, 2020-2023
Real-time crash risk prediction aims to predict the crash probabilities within a short time period, it is expected to play a crucial role in the advanced traffic management system. However, most of the existing studies only focused on freeways rather than urban arterials because of the complicated traffic environment of the arterials. This thesis proposes a long short-term memory convolutional neural network (LSTM-CNN) to predict the real-time crash risk at arterials. The advantage of this model is it can benefit from both LSTM and CNN. Specifically, LSTM captures the long-term dependency of the data while CNN extracts the time-invariant features. …
Investigation Of Recurrent Neural Network Architectures Based Deep Learning For Short-Term Traffic Speed Forecasting, Armando Fandango
Investigation Of Recurrent Neural Network Architectures Based Deep Learning For Short-Term Traffic Speed Forecasting, Armando Fandango
Electronic Theses and Dissertations, 2020-2023
The availability of large tranches of data and its influence on traffic flow, make the problem of short-term traffic speed prediction very complex in nature. For more than 40 years, various statistical time series forecasting methods have been applied for traffic speed prediction, and in the last 20 years, machine learning-based methods have gained prevalence. However, more recently, recurrent neural network (RNN) based methods have emerged to show better results for traffic speed prediction\cite{tian2015pred, zhao2017lstm,fu2017usin,chen2016long,dai2017deep,dai2019deep, kanestrom2017traf,shao2016traf,jia2017traf}. As the interest in applying RNN models to the traffic speed predictions started to grow, we found some critical and important unanswered questions with …
Improving Traffic Safety And Efficiency By Adaptive Signal Control Systems Based On Deep Reinforcement Learning, Yaobang Gong
Improving Traffic Safety And Efficiency By Adaptive Signal Control Systems Based On Deep Reinforcement Learning, Yaobang Gong
Electronic Theses and Dissertations, 2020-2023
As one of the most important Active Traffic Management strategies, Adaptive Traffic Signal Control (ATSC) helps improve traffic operation of signalized arterials and urban roads by adjusting the signal timing to accommodate real-time traffic conditions. Recently, with the rapid development of artificial intelligence, many researchers have employed deep reinforcement learning (DRL) algorithms to develop ATSCs. However, most of them are not practice-ready. The reasons are two-fold: first, they are not developed based on real-world traffic dynamics and most of them require the complete information of the entire traffic system. Second, their impact on traffic safety is always a concern by …
Smartphone Sensor-Based Pedestrian Activity Recognition For P2v Communication And Warning System, Dhrubo Hasan Chowdhury
Smartphone Sensor-Based Pedestrian Activity Recognition For P2v Communication And Warning System, Dhrubo Hasan Chowdhury
Electronic Theses and Dissertations, 2020-2023
The ubiquity of smartphones has made a remarkable influence on everyone's day to day life. Variety of useful built-in sensors provide smartphones with a convenient floor for data collection and analysis. Application development based on the user's location and movement is not a difficult task nowadays. But injuries and deaths due to smartphone-distracted movement on roadways is on the increase. This study explores the capabilities of smartphone inertial sensors for pedestrian activity recognition. Smartphone distracted movements can be predicted from the associated pedestrian's posture, thus inertial sensors can provide effective solution for this specific task. Volunteers were asked to perform …
Applications Of Deep Learning Models For Traffic Prediction Problems, Rezaur Rahman
Applications Of Deep Learning Models For Traffic Prediction Problems, Rezaur Rahman
Electronic Theses and Dissertations
Deep learning coupled with existing sensors based multiresolution traffic data and future connected technologies has immense potential to improve traffic operation and management. But to deal with complex transportation problems, we need efficient modeling frameworks for deep learning models. In this study, we propose two different modeling frameworks using Deep Long Short-Term Memory Neural Network (LSTM NN) model to predict future traffic state (speed and signal queue length). In our first problem, we present a modeling framework using deep LSTM NN model to predict traffic speeds in freeways during regular traffic condition as well as under extreme traffic demand, such …
Energy Consumption And Routing Model For First Responder Vehicles, Alex Rodriguez
Energy Consumption And Routing Model For First Responder Vehicles, Alex Rodriguez
The Pegasus Review: UCF Undergraduate Research Journal
The ongoing research and prototyping of electric vehicles (EVs) offers numerous opportunities to investigate their performance in various service contexts. As EVs are integrated into society, the reliable prediction of fuel consumption and routing time becomes particularly important in emergency response services. This project develops a preliminary stochastic model that can route and predict the energy consumption and travel time for hypothetical emergency vehicles operating on an electric battery cell. Using a Monte-Carlo framework, we constructed a routing model designed to minimize travel time and resource consumption under various simulated conditions. In doing so, we establish the foundation for balancing …
Improving Traffic Safety At School Zones By Engineering And Operational Countermeasures, Md Hasibur Rahman
Improving Traffic Safety At School Zones By Engineering And Operational Countermeasures, Md Hasibur Rahman
Electronic Theses and Dissertations
Safety issues at school zone areas have been one of the most important topics in the traffic safety field. Although many studies have evaluated the effectiveness of various traffic control devices (e.g., sign, flashing beacon, speed monitoring display), there is a lack of studies exploring different roadway countermeasures and the relationship between school-related factors and crashes. In this study, the most crash-prone school zone was identified in Orange and Seminole Counties, Florida, based on crash rate. Afterward, a microsimulation network was built in VISSIM environment to test different roadway countermeasures in the school zones. Three different countermeasures: two-step speed reduction …
Arterial-Level Real-Time Safety Evaluation In The Context Of Proactive Traffic Management, Jinghui Yuan
Arterial-Level Real-Time Safety Evaluation In The Context Of Proactive Traffic Management, Jinghui Yuan
Electronic Theses and Dissertations
In the context of pro-active traffic management, real-time safety evaluation is one of the most important components. Previous studies on real-time safety analysis mainly focused on freeways, seldom on arterials. With the advancement of sensing technologies and smart city initiative, more and more real-time traffic data sources are available on arterials, which enables us to evaluate the real-time crash risk on arterials. However, there exist substantial differences between arterials and freeways in terms of traffic flow characteristics, data availability, and even crash mechanism. Therefore, this study aims to deeply evaluate the real-time crash risk on arterials from multiple aspects by …
Assessing Pedestrian Safety Conditions On Campus, Morgan Morris
Assessing Pedestrian Safety Conditions On Campus, Morgan Morris
Electronic Theses and Dissertations
Pedestrian-related crashes are a significant safety issue in the United States and cause considerable amounts of deaths and economic cost. Pedestrian safety is an issue that must be uniquely evaluated in a college campus, where pedestrian volumes are dense. The objective of this research is to identify issues at specific locations around UCF and suggest solutions for improvement. To address this problem, a survey that identifies pedestrian safety issues and locations is distributed to UCF students and staff, and an evaluation of drivers reactions to pedestrian to vehicle (P2V) warning systems is studied through the use of a NADS MiniSim …
Assessing The Safety And Operational Benefits Of Connected And Automated Vehicles: Application On Different Roadways, Weather, And Traffic Conditions, Md Sharikur Rahman
Assessing The Safety And Operational Benefits Of Connected And Automated Vehicles: Application On Different Roadways, Weather, And Traffic Conditions, Md Sharikur Rahman
Electronic Theses and Dissertations
Connected and automated vehicle (CAV) technologies have recently drawn an increasing attention from governments, vehicle manufacturers, and researchers. Connected vehicle (CV) technologies provide real-time information about the surrounding traffic condition (i.e., position, speed, acceleration) and the traffic management center's decisions. The CV technologies improve the safety by increasing driver situational awareness and reducing crashes through vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I). Vehicle platooning with CV technologies is another key element of the future transportation systems which helps to simultaneously enhance traffic operations and safety. CV technologies can also further increase the efficiency and reliability of automated vehicles (AV) by collecting real-time …
Basic Turbo Roundabouts As An Alternative To Conventional Double-Lane Roundabouts: Operational Performance Evaluation, Zuhair Elhassy
Basic Turbo Roundabouts As An Alternative To Conventional Double-Lane Roundabouts: Operational Performance Evaluation, Zuhair Elhassy
Electronic Theses and Dissertations
Conventional roundabouts have been prevalent worldwide since the emergence of modern roundabouts in 1966. An innovative design of multilane roundabouts known as turbo roundabouts, however, has been recently introduced as an alternative to conventional multilane roundabouts. Due to several reasons, there has been no general consensus on the operational performance of turbo roundabouts throughout the world. Nationwide, turbo roundabouts have yet to be part of roadway systems, but there is an ongoing project expected to be finished in early 2020. Therefore, this dissertation aims to evaluate the operational performance of a widespread variant of turbo roundabouts, namely basic turbo roundabouts, …
Safety, Operational, And Design Analyses Of Managed Toll And Connected Vehicles' Lanes, Moatz Saad
Safety, Operational, And Design Analyses Of Managed Toll And Connected Vehicles' Lanes, Moatz Saad
Electronic Theses and Dissertations
Managed lanes (MLs) have been implemented as a vital strategy for traffic management and traffic safety improvement. The majority of previous studies involving MLs have explored a limited scope of the impact of the MLs segments as a whole, without considering the safety and operational effects of the access design. Also, there are limited studies that investigated the effect of connected vehicles (CVs) on managed lanes. Hence, this study has two main objectives: (1) the first objective is achieved by determining the optimal managed lanes access design, including accessibility level and weaving distance for an at-grade access design. (2) the …
Development Of Decision Support System For Active Traffic Management Systems Considering Travel Time Reliability, Whoibin Chung
Development Of Decision Support System For Active Traffic Management Systems Considering Travel Time Reliability, Whoibin Chung
Electronic Theses and Dissertations
As traffic problems on roadways have been increasing, active traffic management systems (ATM) using proactive traffic management concept have been deployed on freeways and arterials. The ATM aims to integrate and automate various traffic control strategies such as variable speed limits, queue warning, and ramp metering through a decision support system (DSS). Over the past decade, there have been many efforts to integrate freeways and arterials for the efficient operation of roadway networks. It has been required that these systems should prove their effectiveness in terms of travel time reliability. Therefore, this study aims to develop a new concept of …
A System Dynamics Approach On Sustainability Assessment Of The United States Urban Commuter Transportation, Tolga Ercan
A System Dynamics Approach On Sustainability Assessment Of The United States Urban Commuter Transportation, Tolga Ercan
Electronic Theses and Dissertations
Transportation sector is one of the largest emission sources and is a cause for human health concern due to the high dependency on personal vehicle in the U.S. Transportation mode choice studies are currently limited to micro- and regional-level boundaries, lacking of presenting a complete picture of the issues, and the root causes associated with urban passenger transportation choices in the U.S. Hence, system dynamics modeling approach is utilized to capture complex causal relationships among the critical system parameters affecting alternative transportation mode choices in the U.S. as well as to identify possible policy areas to improve alternative transportation mode …
Developing A Traffic Safety Diagnostics System For Unmanned Aerial Vehicles Usingdeep Learning Algorithms, Ou Zheng
Electronic Theses and Dissertations
This thesis presents an automated traffic safety diagnostics solution using deep learning techniques to process traffic videos by Unmanned Aerial Vehicle (UAV). Mask R-CNN is employed to better detect vehicles in UAV videos after video stabilization. The vehicle trajectories are generated when tracking the detected vehicle by Channel and Spatial Reliability Tracking (CSRT) algorithm. During the detection process, missing vehicles could be tracked by the process of identifying stopped vehicles and comparing Intersect of Union (IOU) between the tracking results and the detection results. In addition, rotated bounding rectangles based on the pixel-to- pixel manner masks that are generated by …