Remediation Ranking of High Crash Fatality Locations Involving Older Drivers in Florida's Rural Counties

Raj Bridgelall is the program director for the Upper Great Plains Transportation Institute (UGPTI) Center for Surface Mobility Applications & Real-time Simulation environments (SMARTSeSM).In 2019, Florida's aging road users (65 years or older) accounted for 20% of the population but 37% of all crashes. Florida Department of Transportation has identified aging road users as one of the areas that requires attention in achieving Vision Zero--a strategy to eliminate all traffic fatalities and severe injuries, while increasing safe, healthy, equitable mobility for all. Research has documented that fatality rates in motor vehicle crashes are higher in rural than urban areas. Drivers in rural areas may be more vulnerable because they rely more on driving and consequently are reluctant to stop. This study identifies factors contributing to fatalities among aging drivers in 14 rural Florida counties experiencing high crash rates. The methodology used a multicriteria decision-making model, namely the fuzzy analytic hierarchy process (FAHP), to identify and categorize the causes of fatal crashes among drivers aged 65+, and to rank their 14 rural counties for remediation measures. FAHP methodology calculates crash factor weights and ranks the counties using pairwise comparisons of those factors to compare and quantify them. Results revealed that the top contributing factors to fatal crashes among drivers 65+ were cloudy, foggy, or rainy weather and when roadways were sandy or wet. Driving in the dark and at dawn also increased the risk of fatal crashes within this specified age group. These findings could help policy makers in each location focus on remediation measures such as older driver education and infrastructural improvements to address the most critical factors in fatal accidents.https://www.ugpti.org/about/staff/viewbio.php?id=7

Optimizing the Total Production and Maintenance Cost of an Integrated Multi-Product Process and Maintenance Planning (IPPMP) Model

Today, a competitive manufacturing environment imposes further production cost reduction on modern companies. Seeking proper recommendations in production and maintenance planning are the two essential cornerstones of effective production organizations. In the current research, we have considered the problem of integrated multi-product process and maintenance planning on a capacitated machine that is susceptible to random breakdown. Maintenance processes comprise general perfect repair (non-cyclical) as preventive maintenance (PM) in the early stages and minimal repair as corrective maintenance for the occurrence of machine breakdown. Furthermore, a rational presumption is reflected in the problem statement in which the time and cost of PM are pertinent to the interval between the prior perfect repair and current PM. The purpose served by this paper is to minimize the cost of production accompanying PM, and the expected corrective repair, consequently, a mixed-integer linear programming (MILP) model has been constructed to pave the way. The model investigated under two circumstances of the machine age effect and its absence. The outcome depicted that the presence of the machine age effect led to an accurate and lessen total cost calculation.Comment: This paper has been accepted by IEEE ISSE2020 6th IEEE International Symposium on Systems Engineerin

A Multi-Objective Meta-Heuristic Approach to Improve the Bus Transit Network: A Case Study of Fargo-Moorhead Area

In this study, the Transit Network Design Problem (TNDP) is studied to determine the set of routes and frequency on each route for public transportation systems. To ensure the important concerns of planners like route length, route configuration, demand satisfaction, and attractiveness of the transit routes, the TNDP is solved to generate a set of routes by proposing an initial route set generation (IRSG) procedure embedded into the NSGA-II algorithm. The proposed IRSG algorithm aims to produce high-quality initial route set solutions to reach better optimization procedures. Moreover, the Multi-Objective Mixed-Integer Non-Linear Programming (MOMINLP) model is proposed to formulate the frequency setting problem on each route by minimizing the total travel time of passengers (user costs) and operator costs simultaneously, while maximizing the service coverage area near all the bus stops. The MOMINLP model is solved by applying the NSGA-II algorithm to produce a Pareto front between the first and the second objective functions. The model was applied to the Fargo-Moorhead Area (FMA), a small urban area. Results were compared with the existing transit network to measure the efficiency of the NSGA-II solution methodology. The proposed algorithm was found to considerably decrease the total travel time of passengers

Extending Micromobility Deployments: A Concept and Local Case Study

Raj Bridgelall is the program director for the Upper Great Plains Transportation Institute (UGPTI) Center for Surface Mobility Applications & Real-time Simulation environments (SMARTSeSM).Micromobility is a recent phenomenon that refers to the use of small human- or electric-powered vehicles such as scooters and bikes to travel short distances, and sometimes to connect with other modes of transportation such as bus, train, or car. Deployments in major cities of the world have been both successful and challenging. This paper reviews the evolution of micromobility services from shared bicycles, dockless systems, and shared electric scooters. The authors evaluated benefits, deficiencies, and factors in adoption to inform more rigorous and extensive geospatial analysis that will examine intersections with land-use, public transit, socio-economic demographics, road networks, and traffic. This work conducted exploratory spatial data analysis and correlation of publicly available datasets on land use, trip production, traffic, and travel behavior. Data from Washington D.C. served as a case study of best practices for scaling deployments to meet the social, economic, and mobility needs of the city.https://www.ugpti.org/about/staff/viewbio.php?id=7

Optimal Placement of Battery Electric Bus Charging Stations Considering Energy Storage Technology: Queuing Modeling Approach

In recent years, there has been growing attention on the electrification of the public transit network. Battery electric buses (BEBs) are among the promising alternatives to replace diesel-powered buses. However, the possible driving range from a full charge has proved a matter of concern, as has the waiting times of BEBs returning to terminal stops after completing their journeys. This study aimed to design an efficient electric transit network considering waiting times at terminal stops and two configurations of charger to avoid BEBs running out of charge: a fast charger with energy storage (ES) technology and one without. A queuing-based mathematical model was proposed. To validate the proposed model, we tested it on two sizes of network: the Mumford0 (small) and the Mumford2 (large). By conducting a sensitivity analysis, certain model parameters, including the power of fast chargers, duration of service interval, BEB energy consumption, and maximum allowable waiting time were found to have substantial impacts on the electric public transit network. ES chargers were found to have the potential to save 15.35% of total costs. Other analyses confirmed that altering the capacity of fast- and ES chargers could affect the number of chargers required in the transit network and the total cost. Policies are suggested for transit agencies to plan to optimize their electric transit networks

Unrelated Parallel Machine Scheduling Problem Considering Job Splitting, Inventories, Shortage, and Resource: A Meta-Heuristic Approach

This research aims to study a real-world example of the unrelated parallel machine scheduling problem (UPMSP), considering job-splitting, inventories, shortage, and resource constraints. Since the nature of the studied optimization problem is NP-hard, we applied a metaheuristic algorithm named Grey Wolf Optimizer (GWO). The novelty of this study is fourfold. First, the model tackles the inventory problem along with the shortage amount to avoid the late fee. Second, due to the popularity of minimizing completion time (Makespan), each job is divided into small parts to be operated on various machines. Third, renewable resources are included to ensure the feasibility of the production process. Fourth, a mixed-integer linear programming formulation and the solution methodology are developed. To feed the metaheuristic algorithm with an initial viable solution, a heuristic algorithm is also fabricated. Also, the discrete version of the GWO algorithm for this specific problem is proposed to obtain the results. Our results confirmed that our proposed discrete GWO algorithm could efficiently solve a real case study in a timely manner. Finally, future research threads are suggested for academic and industrial communities

Literature Review of Socioeconomic and Environmental Impacts of High-Speed Rail in the World

Raj Bridgelall is the program director for the Upper Great Plains Transportation Institute (UGPTI) Center for Surface Mobility Applications & Real-time Simulation environments (SMARTSeSM).Countries considering high-speed rail (HSR) developments face enormous challenges because of their high deployment cost, environmental obstacles, political opposition, and their potentially adverse effects on society. Nevertheless, HSR services are importantly sustainable that can have positive and transformative effects on the economic growth of a nation. This paper systematically reviews and classifies impact areas of HSR deployments around the world as well as the analytical methods used to evaluate those impacts. We have utilized the scholarly scientific database to find articles in HSR systems. By defining some rules, we select 116 articles between 1997 and March 2020. The approach revealed interesting patterns and trends in space, time, and sentiment of the analyzed impacts on society, the economy, and the environment. The findings can inform decision-making about HSR developments and deployments, and the gaps identified in the literature can propose new research opportunities for future studies.https://www.ugpti.org/about/staff/viewbio.php?id=7