A Nested Logit analysis of the influence of distraction on types of vehicle crashes

Purpose This work aims to study factors, such as driver characteristics, environmental conditions, and vehicle characteristics, that affect different crash types with a special focus on distraction parameters. For this purpose, distraction factors are divided into five groups: cellphone usage, cognitive distractions, passengers distracting the driver, outside events attracting the driver’s attention, and in-vehicle activities. Methods Taking the crashes that occurred in the USA into account, the crash types are divided into two main groups, single-vehicle crashes and two-vehicle crashes. Since there were different crash types (alternatives) in the dataset and the probable correlation in the unobserved error term, the Nested Logit model is developed. Results The results of model illustrate that all of the aforementioned distraction-related factors increase the probability of run-off-road crashes, collision with a fixed object, and rear-end crashes. Cognitive distraction increases the probability of collision with a pedestrian. Distractions caused by passengers or out-of-vehicle events increase the probability of sideswipe crashes. Conclusion By examining how a factor affects multiple crash type outcomes, it is possible to devise countermeasures, improvements to roadway geometry, and traffic control strategies, while minimizing unintended consequences. The results should be of value in the design of educational programs and propose road safety improvement techniques. Document type: Articl

Qualitative and Quantitative Analysis to Advance Transportation

(c) 1036219Measuring equity in transportation is vitally important to ensure that the transportation network serves the entire community without introducing barriers to access. However, not all methods for assessing transportation equity produce the same results or are appropriate for all scenarios\u2014the analysis methods used should be selected to produce the highest likelihood of determining the most equitable outcomes. This research project synthesizes previous research investigating equity assessments by MnDOT, academia, and industry and leverages these findings in concert with directly collected community experience and staff expertise to achieve the following objectives: (1) establish a detailed understanding of current challenges and needs related to equity assessment in Minnesota; (2) identify or develop assessment methods and equity-focused strategic actions that will improve the likelihood that transportation equity in Minnesota is assessed in a manner that achieves context-sensitive outcomes representative of the communities served; and (3) facilitate the adoption of identified or developed equity assessment methods and complementary strategic actions, including information detailing appropriate use cases, data requirements, and considerations through a bespoke training program

Optimizing Maintenance Operations for Multimodal Transportation on the Inland Waterway System

The U.S. inland waterway system has more than 25,000 miles of the maintained navigation channel, which carries a significant percentage of the national freight total (17% of all intercity freight by volume[1]). Maintenance operations, including dredging and lock and dam maintenance & repair, are important to ensuring the effective and efficient operation of the inland marine transportation system. Each year, there is a budget [2] for the maintenance of lock/dam and navigable waterway dredging, etc. This dissertation specifically deals with maintenance fund allocation to these projects. The goal of project selection is to maximize the total network benefits, such as the network shipping capacity. In literature, there are models dealing with the maintenance project selection without considering the resulting shoaling effect. Deep dredging, although costly, brings large benefits. However, these benefits are subject to more severe shoaling effect over the years after. Selecting dredging projects by consideration of the resulting shoaling effect can cause the budget to be used in a much better-informed way and therefore more efficiently. In this dissertation, the project selection is optimized on the network by explicitly considering the stochastic nature of the shoaling. The consideration is conducted through alternative mathematical models. Those alternative models, each described in the following chapters, progress to be increasingly realistic and complex. In Chapter III, we develop a multimodal formulation that minimizes the total cost of shipping commodities in a network after the lock/dam and dredging maintenance. This formulation looks at the stochastic nature of the shoaling in a deterministic way. The findings show the difference in budget allocation towards locks and dams versus dredging operations and compare their effects on the network. In Chapter IV, we compare the results from the formulation in Chapter III with industry practices to gain managerial insights. These practices include the benefit/cost analysis and the through tonnage method. The managerial insights help managers improve their empirical decisions in light of the results from the optimization models. We also show sensitivity analysis results on the dam maintenance costs to see if the results would significantly change. In Chapter V, we analyze the shoaling data along the Ohio River to find a shoaling distribution in different reaches. The purpose of this analysis is to characterize the random shoaling distribution in order to accurately model its effect in a formal stochastic formulation next. We also run some statistical analysis to see which distributions fit better on the data. Chapter V prepares the probability distribution of shoaling for the stochastic model next. In Chapter VI, we propose a two-stage formulation that tries to allocate dredging budgets by considering two consecutive time periods (e.g. year). The budget available to allocate is the budget available in the current period, and the formulation tries to maximize the benefit realized in both the first year and the year after when shoaling has taken place as a result of the year one dredging. Multiple scenarios are developed to capture the stochasticity of the shoaling. The result shows that the dredging decisions are changed significantly by having the knowledge of shoaling rate in the future. In Chapter VII, multiple solution algorithms for the stochastic formulation are summarized. The solution algorithms decompose the formulation into multiple sub-problems and solve them. Benders and L-Shape methods are explained for general cases and for integer formulation

A Multimodal Network Approach to the Inland and Coastal Waterway System

The inland waterway system carries a significant percentage of the national"br" freight. Maintenance operations including dredging and dam repair are important"br" to maintaining the effective and efficient operation of the system. Dredging projects"br" are for recovery of the navigational channel draft from the shoaling effect while"br" lock/dam repair is about maintaining a maximum possible operational hours to"br" reduce the waiting and delay of vessels therein. The special feature in this study"br" is that the shoaling effect is random, as is subject to weather and other effects."br" This study specially deals with maintenance fund allocation to these maintenance"br" requests by first proposing a multimodal approach for formulating the waterway"br" maintenance problem in a connected network, which considers rivers, locks/dams,"br" and highways and railways

A Nested Logit analysis of the influence of distraction on types of vehicle crashes

Abstract Purpose This work aims to study factors, such as driver characteristics, environmental conditions, and vehicle characteristics, that affect different crash types with a special focus on distraction parameters. For this purpose, distraction factors are divided into five groups: cellphone usage, cognitive distractions, passengers distracting the driver, outside events attracting the driver’s attention, and in-vehicle activities. Methods Taking the crashes that occurred in the USA into account, the crash types are divided into two main groups, single-vehicle crashes and two-vehicle crashes. Since there were different crash types (alternatives) in the dataset and the probable correlation in the unobserved error term, the Nested Logit model is developed. Results The results of model illustrate that all of the aforementioned distraction-related factors increase the probability of run-off-road crashes, collision with a fixed object, and rear-end crashes. Cognitive distraction increases the probability of collision with a pedestrian. Distractions caused by passengers or out-of-vehicle events increase the probability of sideswipe crashes. Conclusion By examining how a factor affects multiple crash type outcomes, it is possible to devise countermeasures, improvements to roadway geometry, and traffic control strategies, while minimizing unintended consequences. The results should be of value in the design of educational programs and propose road safety improvement techniques

Awareness and practice of cervical cancer and Pap smear testing in a teaching hospital in Tehran

Background: Cervical cancer is known to be preventable because of long period of pre-invasive stage, availability of screening tools, and effective treatments for early invasive cervical lesions. Screening is main measures to prevent the disease and Pap smear is a screening strategy for cervical cancer. Current paper aimed to evaluate levels of awareness and practice regarding Pap smear screening among women aged between 20 to 65 years in Tehran (Iran). Methods: This was a descriptive-analytical study conducted in Tehran City of Iran in 2015 at Firoozgar Hospital. The research population included all married, widowed and divorced women aged 20-65 years. Data analysis was performed using the Pearson correlation and Student’s t-tests in SPSS, ver. 23 (Chicago, IL, USA). Results: Among 90 individuals who have fill questionnaire completely, 66.6% subjects had Pap smear tests. 40% of the individuals aged between 30 to 39 and the education level is distributed equally between Intermediate, Diploma and graduate and only 3 percent of them, continue their education to higher level. There was a significant relationship between the awareness of Pap smear and educational level (of both wives and husbands). The people who have graduate degree, have the best awareness. Working women revealed higher level of awareness about Pap smear. Shame and fear of taking the cancer were the most common reasons which lead to avoidance in doing the test by the women, while the most encouraging factors for performing the test were the information mostly provided by physicians and after that, the information provided by friends. Conclusion: The awareness of Pap smear test which was measured by weighting different questions in the questionnaire by experts, prove that the women aged above 39, have an average level of awareness of Pap smear test. Due to high prevalence of cervical cancer and prolonged pre invasive course, role of Pap smear for early diagnosis necessitate the use of proper and inexpensive instructional methods to increase awareness in women about cervical cancer and preventive strategies

3D Pavement Surface Reconstruction Using An RGB-D Sensor

Data collection plays an important role in pavement health monitoring, which is usually performed using costly devices, including point-based lasers and laser scanners. The main aim of this study measures pavement characteristics using an RGB-D sensor. By recording the depth and color images simultaneously, the sensor benefits the data fusion. By mounting the sensor on a moving cart, and fixing the vertical distance from the ground, data were collected along 100 m of the asphalt pavement using MATLAB. At each stop point, multiple frames were collected, the central region of interests was stored, and a low pass filter was subsequently applied to the data. To create a 3D surface of the pavement, sensor calibration was performed to map the RGB and depth infrared images. The SURF (speeded-up robust features) and MSAC (M-estimator sample consensus) algorithms were used to match the stitched images along the longitudinal profile. A case study of measuring roughness and rutting is applied to test the validity of the method. The result confirms that the proposed system is capable of measuring such indices with acceptable accuracy

Estimating Pavement Roughness by Fusing Color and Depth Data Obtained from an Inexpensive RGB-D Sensor

Measuring pavement roughness and detecting pavement surface defects are two of the most important tasks in pavement management. While existing pavement roughness measurement approaches are expensive, the primary aim of this paper is to use a cost-effective and sufficiently accurate RGB-D sensor to estimate the pavement roughness in the outdoor environment. An algorithm is proposed to process the RGB-D data and autonomously quantify the road roughness. To this end, the RGB-D sensor is calibrated and primary data for estimating the pavement roughness are collected. The collected depth frames and RGB images are registered to create the 3D road surfaces. We found that there is a significant correlation between the estimated International Roughness Index (IRI) using the RGB-D sensor and the manual measured IRI using rod and level. By considering the Power Spectral Density (PSD) analysis and the repeatability of measurement, the results show that the proposed solution can accurately estimate the different pavement roughness