Transportation Engineering Commons^™

Spatial Data Analysis For The Development Of Expected Adverse Weather Charts For Transportation Construction Projects, S M Rahat Rashedi, Akosua Ofosua Okyere-Addo

SDSU Data Science Symposium

Problem - Seasonal and daily weather events impact construction projects across the various climate regions of South Dakota in differing fashions. Additionally, the impacts for similar weather events can impact grading, surfacing, and structural construction activities in various ways. Adverse weather conditions can cause major delays which may lead to time extensions and increase project cost.

Purpose – To address these issues, South Dakota Department of Transportation (SDDOT) developed Working Day Weather Charts in 1998. However, advances in construction practices and weather prediction as well as climatic changes have occurred over the interim 25 years. This study is focused on …

Spatial Data Analysis For Traffic Safety Network Screening, Akosua Okyere-Addo, S. M. Rahat Rashedi

SDSU Data Science Symposium

Problem - The roadway system represents a major investment, both public and private, and a valuable resource that enables mobility and accessibility to users. Due to degradation of aging infrastructure and increasing traffic, transportation agencies are seeking to effectively update or improve the system. With rising costs, tight budgets, and limited land resources, agencies are seeking effective techniques for identifying critical mobility and safety concerns. Historically, assignment of crashes to portions of the network, whether segments or intersections, has been the primary manner to link crash and road elements.

Purpose – The primary goal is to explore a potentially more …

Dlr Covid-19 Mobility Review (Phase 2a): Report On Cmr Economic Development & Business Community Feedback, Sarah Rock Dr., Robert Bradshaw Dr., David O'Connor, Odran Reid

Reports

This research reports on the findings from an area focused economic development and business community focused study of the Costal Mobility Route (CMR), which is intended to complement and extend research previously conducted in Phase 1 of Dún Laoghaire-Rathdown County Council’s (DLR’s) ‘Covid-19 Mobility & Public Realm Works’ project. This study is based on participant interviews, and is limited to businesses located directly along the CMR, as well as a number of business groups representing a wider area and a Local Enterprise Office.

While one company reported a significant decline in revenue that they attribute to the CMR, the remainder …

Evaluation, Comparison, And Improvement Recommendations For Caltrans Financial Programming Processes And Tools, Wenbin Wei, Nigel Blampied, Raajmaathangi Sreevijay

Mineta Transportation Institute

The California Transportation Improvement Program System (CTIPS) is the main tool used by Caltrans’ Division of Financial Programming to support the business of transportation programming. It is a multi-agency joint-use project programming database system applied to develop and manage various state and federal transportation programming documents. The goal of this project is to evaluate CTIPS and explore various new options that will maintain the current functionality of CTIPS, meet legislative guidelines for ADA compliance, ensure security of the system, and have sufficient scalability and capabilities for integration with other systems in the future. The research is based on the review …

Virtual Accident Curb Risk Habituation In Workers By Restoring Sensory Responses To Real-World Warning, Namgyun Kim, Laurent Grégoire, Moein Razavi, Niya Yan, Changbum R. Ahn, Brian A. Anderson

Civil and Environmental Engineering and Engineering Mechanics Faculty Publications

In high-risk work environments, workers become habituated to hazards they frequently encounter, subsequently underestimating risk and engaging in unsafe behaviors. This phenomenon has been termed "risk habituation"and identified as a vital root cause of fatalities and injuries at workplaces. Providing an effective intervention that curbs workers' risk habituation is critical in preventing occupa-tional injuries and fatalities. However, there exists no empirically supported intervention for curbing risk habituation. To this end, here we investigated how experiencing an accident in a virtual reality (VR) environment affects workers' risk habituation toward repeatedly exposed workplace hazards. We examined an underlying mechanism of risk habituation …

The Effects Of Inaccurate And Missing Highway-Rail Grade Crossing Inventory Data On Crash Model Estimation And Crash Prediction, Aemal Khattak, M. Umer Farooq

Mid-America Transportation Center: Final Reports and Technical Briefs

ABSTRACT: Most highway-rail grade crossing (HRGC) crash models in the US rely on the Federal Railroad Administration’s (FRA) highway/rail crossing inventory database. Any errors and/or incomplete information in this database affects the estimated crash model parameters and subsequent crash predictions. Using 560 HRGCs in Nebraska, this study illustrates differences in crash predictions obtained from the FRA’s new (2020) Accident Prediction and Severity (APS) model when: 1) using the unaltered, original FRA HRGC inventory dataset as input, and 2) using a field-validated inventory dataset for those 560 HRGCs as input to the new APS model. Results showed that the predictions using …

Motor Vehicle Drivers' Knowledge Of Safely Traversing Highway-Rail Grade Crossings, Aemal Khattak, M. Umer Farooq, Abdul Farhan

Mid-America Transportation Center: Final Reports and Technical Briefs

This study investigates motor vehicle drivers’ socioeconomic, personality, and attitudinal factors associated with their knowledge of safely traversing highway-rail grade crossings (HRGCs). A survey of randomly selected Nebraska households solicited responses from licensed drivers (N= 980, response rate = 39 percent). Of the total thirty-one questions on the questionnaire, nine pertained to respondents’ knowledge of safely navigating HRGCs (e.g., what does a crossbuck sign require a driver to do when approaching a rail crossing?). Correct answers to the questions provided a measure of respondents’ knowledge of safely traversing HRGCs and led to their classification in five ordered categories. A random …

A Heterogeneity-Based Temporal Stability Assessment Of Pedestrian Crash Injury Severity Using An Aggregated Crash And Hospital Data Set, M. Umer Farooq, Aemal Khattak

Mid-America Transportation Center: Final Reports and Technical Briefs

This study utilized a unique approach to crash data analysis by examining the temporal stability of pedestrian crash injury severity and its contributory factors. Police-reported crash data and EMS-related injury data from Nebraska were obtained from 2014 to 2018, and random parameter ordered probit models for injury severity were estimated for each year to account for unobserved heterogeneity. Four discrete levels of injury severity were considered for model estimation: fatality, disabling injury/suspected serious injury, visible injury/possible injury, and no injury. Data were filtered based on several important variables of interest, such as pedestrian characteristics, crash characteristics, environmental and weather characteristics, …

A Simulation Way To Investigate The Reason For Congestion In Urban——A Case Study In Hohhot China, Junqing Wang, Hong Yang, Yuan Zhu, Qingwen Pu, Shunlai Cui

College of Engineering & Technology (Batten) Posters

In the case of high density traffic flow, traditional traffic data statistical analysis methods, which not only have certain errors and lead to inaccurate data, but also have many limitations such as labor consumption, can no longer meet the demand for traffic analysis. Drones for traffic data, based on an aerial bird's-eye view, no offset, and error-free complete statistics of urban road shooting section of all data, while greatly reducing cost consumption. A multi-dimensional simulation model is established for the UAV data to the Hohhot central urban area's road simulation platform. This project will test and explore multidimensional data in …

Investigating The Impacts Of Connected Vehicles On Driving Aggressiveness And Situational Awareness In Highway Crash Scenarios: A Driving Simulator Study, Abdalziz Alruwaili

College of Engineering & Technology (Batten) Posters

Psychological factors such as aggressiveness and situational awareness can impact driving performance. Connected vehicles (CV), equipped with advanced sensors and able to communicate safety messages to drivers, have the potential to influence driving performance by altering drivers’ aggressiveness and situational awareness. This paper aims to investigate the impacts of the CVs on driving aggressiveness and situational awareness in highway crash scenarios where a primary crash has already occurred, and a second crash may occur as a result. To achieve this goal, a driving simulator experiment was conducted, and questionnaires focused on driving aggressiveness and CV effectiveness were distributed. Structural equation …

The Impact Of Precipitation As An Adverse Weather Condition On Transportation Construction In South Dakota, Akosua Ofosua Okyere-Addo

Civil and Environmental Engineering Graduate Students Plan B Capstone Projects

This research assessed the impact of precipitation as an adverse weather condition on the transportation construction in South Dakota. A statistical survey of the data from the National Oceanic and Atmospheric Administration was conducted on 554 original stations, which was reduced to 433 stations of them were in South Dakota, then reduced to 170 stations with 30-year data coverage higher than 70 %. Eventually, the data were reduced further for pilot study purposes to a final 10 stations used for analysis in this study. The objective of this study is to examine potential precipitation thresholds towards determination of related adverse …

Developing A Physics-Informed Deep Learning Paradigm For Traffic State Estimation, Jiheng Huang

Electronic Theses and Dissertations, 2020-2023

The traffic delay due to congestion cost the U.S. economy $ 81 billion in 2022, and on average, each worker lost 97 hours each year during commute due to longer wait time. Traffic management and control strategies that serve as a potent solution to the congestion problem require accurate information on prevailing traffic conditions. However, due to the cost of sensor installation and maintenance, associated sensor noise, and outages, the key traffic metrics are often observed partially, making the task of estimating traffic states (TSE) critical. The challenge of TSE lies in the sparsity of observed traffic data and the …

Spatial Ensemble Distillation Learning Based Real-Time Crash Prediction And Management Framework, Md Rakibul Islam

Graduate Thesis and Dissertation 2023-2024

Real-time crash prediction is a complex task, since there is no existing framework to predict crash likelihood, types, and severity together along with a real-time traffic management strategy. Developing such a framework presents various challenges, including not independent and identically distributed data, imbalanced data, large model size, high computational cost, missing data, sensitivity vs. false alarm rate (FAR) trade-offs, estimation of traffic restoration time after crash occurrence, and real-world deployment strategy. A novel spatial ensemble distillation learning modeling technique is proposed to address these challenges. First, large-scale real-time data were used to develop a crash likelihood prediction model. Second, the …

Safety Considerations For Setting Variable Speed Limits On Freeways, Md Tarek Hasan

Graduate Thesis and Dissertation 2023-2024

This thesis focuses on evaluating the appropriate speed at which vehicles should travel under different traffic conditions on freeways and its impact on crash frequency. The common belief is that the lower speed results in fewer crashes as reduced speed provides drivers with more time to react effectively and avoid collisions. However, this perspective overlooks the interplay among traffic speed, average spacing between consecutive vehicles, and the distance available for stopping a vehicle. Hence, we propose a safety parameter termed ‘Safety Correlate' (SCORE), which is defined as the proportion of average spacing relative to the stopping distance. To determine the …

Modeling Individual Activity And Mobility Behavior And Assessing Ridesharing Impacts Using Emerging Data Sources, Jiechao Zhang

Electronic Theses and Dissertations, 2020-2023

Predicting individual mobility behavior is one of the major steps of transportation planning models. Accurate prediction of individual mobility behavior will be beneficial for transportation planning. Although previous studies have used different data sources to model individual mobility behaviors, they have several limitations such as the lack of complete mobility sequences and travel mode information, limiting our ability to accurately predict individual movements. In recent years, the emergence of GPS-based floating car data (FCD) and on-demand ride-hailing service platforms can provide innovative data sources to understand and model individual mobility behavior. Compared to the previously used data sources such as …

Stochastic Optimization To Reduce Aircraft Taxi-In Time At Igia, New Delhi, Rajib Das, Saileswar Ghosh, Rajendra Desai, Pijus Kanti Bhuin, Stuti Agarwal

International Journal of Aviation, Aeronautics, and Aerospace

Since there is an uncertainty in the arrival times of flights, pre-scheduled allocation of runways and stands and the subsequent first-come-first-served treatment results in a sub-optimal allocation of runways and stands, this is the prime reason for the unusual delays in taxi-in times at IGIA, New Delhi.

We simulated the arrival pattern of aircraft and utilized stochastic optimization to arrive at the best runway-stands allocation for a day. Optimization is done using a GRG Non-Linear algorithm in the Frontline Systems Analytic Solver platform. We applied this model to eight representative scenarios of two different days. Our results show that without …

Clustering States To Improve The Strategic Highway Safety Plan, Victoria Cambron

Theses and Dissertations--Civil Engineering

Each update to a Strategic Highway Safety Plan (SHSP) can require a large amount of time, resources, and funding. From the requirements in U.S.C.148(a)(13)(E-F), in the SHSP update process states must consider the results of other transportation planning processes and develop a list of strategies to reduce or eliminate fatal and serious injury crashes (United States, 2023). To fulfill these requirements more efficiently and to gain the largest amount of benefit from said research, this thesis asks the question: how do we select other state transportation plans to study for ideas on improving our own SHSP? In this thesis, a …

Nondestructive Evaluation Of Structural Defects In Concrete Slabs, Ehsanul Kabir

College of Graduate Studies: Theses & Dissertations

Nondestructive testing (NDT) is a reliable method for determining the structural integrity of new and old construction and understanding the condition of structural defects. It is widely acknowledged that the interpretation of nondestructive evaluation (NDE) has a significant impact on the reliability and consistency of this technology. However, NDT data acquisition remains subjective and heavily dependent on the operator’s knowledge and expertise. As a result, there are still issues to be resolved regarding the imaging and diagnostic procedures for NDT-based concrete inspection. NDT methods such as ground penetrating radar (GPR), and impact-echo (IE), have been extensively used to inspect concrete …

Smart Mobility Sensing Of Origin-Destination Pairs Using Computer Vision, Seyed Sina Shid Moosavi

Electronic Theses and Dissertations, 2020-2023

The measurement of the origin-destination (OD) flow of individual passengers within the public transportation system plays a vital role in understanding resident mobility and facilitating route planning. Particularly in resource-limited communities, where access to advanced technologies like smart card systems may not be available, bus transportation systems play a crucial role in daily life. Traditional methods, such as driver logs, are not only time-consuming but also difficult to provide precise measurements of individualized OD pairs. Therefore, the primary objective of this study is to propose an automatic passenger sensing system (software) capable of accurately measuring OD pairs for individual passengers …

Development,Validation, And Integration Of Ai-Driven Computer Vision System And Digital-Twin System For Traffic Safety Dignostics, Ou Zheng

Electronic Theses and Dissertations, 2020-2023

The use of data and deep learning algorithms in transportation research have become increasingly popular in recent years. Many studies rely on real-world data. Collecting accurate traffic data is crucial for analyzing traffic safety. Still, traditional traffic data collection methods that rely on loop detectors and radar sensors are limited to collect macro-level data, and it may fail to monitor complex driver behaviors like lane changing and interactions between road users. With the development of new technologies like in-vehicle cameras, Unmanned Aerial Vehicle (UAV), and surveillance cameras, vehicle trajectory data can be collected from the recorded videos for more comprehensive …