Browsing by Author "Gupta, Diwakar"

Now showing 1 - 8 of 8
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    Highway Cost Allocation and Determination of Heavy Freight Truck Permit Fees
    (Minnesota Department of Transportation, 2012-07) Gupta, Diwakar; Chen, Hao-Wei
    Minnesota Department of Transportation (MnDOT) and other state DOTs periodically carry out studies to assess how highway construction and maintenance (HCM) expenditures ought to be attributed to various vehicle classes. In parallel, each vehicle-class’ contribution to revenues from fuel and excise taxes and permit fees are calculated. Although, the latter are determined by the state legislature, the cost-to-revenue ratio helps inform MnDOT if changes to policy could be justified. A variety of methods have been developed to apportion HCM costs to different user classes. The purpose of this study was to evaluate pros and cons of different HCA methods and to identify/develop a methodology best suited for conditions in Minnesota. Researchers also carried out a highway cost allocation study (HCAS) using the latest data from Minnesota. In addition, the methodology developed in this project can be used to evaluate damage costs to the road system from permitting more than 80,000-lb gross vehicle weight trucks on Minnesota roads and the users’ willingness to pay for such permits.
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    Improving Capacity Planning for Demand-Responsive Paratransit Services
    (Minnesota Department of Transportation, 2008-04) Gupta, Diwakar; Chen, Hao-Wei; Miller, Lisa; Surya, Fajarrani
    This report proposes and evaluates two ideas for improving efficiency and service quality of paratransit operations. For carrying out this analysis, the authors use data from Metro Mobility, the agency responsible for providing ADA-mandated transportation services in the Twin Cities. However, the underlying principles, mathematical models, and algorithms are applicable to a variety of similar transportation operations in urban and rural areas. The first idea is to re-optimize routes developed by Metro Mobility’s route-building software (a commercial product named Trapeze) at the end of each day of booking operations to reduce the total time it takes to serve booked trips. The second idea evaluates the selective use of non-dedicated vehicles and service providers (e.g. taxi services) for lowering operational costs. Mathematical models and computer algorithms are developed for each of these approaches. These are then tested on actual operational data obtained from Metro Mobility. The report shows that a conservative estimate of savings from re-optimization would be 5% of Metro Mobility’s operating costs. Additional savings from the use of taxi service would be in the hundreds of dollars per day. The actual magnitude of these savings would depend on the proportion of customers who agree to travel by taxi.
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    Optimal Contract Mechanism Design for Performance-Based Contracts
    (Minnesota Department of Transportation Research Services Section, 2011-08) Gupta, Diwakar; Vedantam, Aditya; Azadivar, Justin
    This report explores the possibility of implementing a performance-based contract (PBC) in highway construction and maintenance. PBC allows a state transportation agency (STA) to use an incentive structure to induce the contractor to take a long-term interest in the functionality of the highway without excessive cost to the STA. First, an overview of contract mechanisms and existing PBCs in industry is provided. Then, a summary of performancebased specifications illustrates that contractors can adopt construction and maintenance policies to significantly improve pavement performance. Finally, a framework for choosing PBCs to achieve STAs’ goals is provided, with a discussion of some of the difficulties associated with implementation. It can be seen that, in a competitive bidding process, the additional cost of incentives is not larger than the additional value gained by higher-quality work.
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    Optimal Workforce Planning and Shift Scheduling for Snow and Ice Removal
    (Minnesota Department of Transportation Research Services Section, 2010-12) Gupta, Diwakar; Tokar-Erdemir, Elif; Kuchera, Dustin; Mannava, Arun Kumar; Xiong, Wei
    Shrinking budgets and high equipment, fuel, and labor costs have raised the importance of workforce planning and efficient deployment of available workforce for county-level winter maintenance operations. This project focused on developing methodologies for the estimation workforce requirements, and economic evaluation of the impact of using contract employees, split shifts and staggered shifts. In order to achieve these goals, a fundamental question that needed to be addressed was the determination of the amount of work induced by different types of storms that occur in Saint Louis County. Researchers obtained relevant storm data from a variety of weather reporting sources and extracted parameters relevant for determining plow speeds and sand/salt consumption. These parameters were used to determine optimal workforce deployment strategies that balance overtime and delay costs, which in turn provided estimates of the amount of plowing time needed for the goal of clearing roads within 24 hours after the end of snow fall. Plowing time calculations were subject to rules concerning when call outs can occur during off-shift hours. Plow time estimates were subsequently used to develop efficient algorithms to calculate workforce requirements.
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    Optimizing Automatic Traffic Recorders Network in Minnesota
    (Minnesota Department of Transportation, 2016-01) Gupta, Diwakar; Tang, Xiaoxu
    Accurate traffic counts are important for budgeting, traffic planning, and roadway design. With thousands of centerline miles of roadways, it is not possible to install continuous counters at all locations of interest (e.g., intersections). Therefore, at the vast majority of locations, MnDOT samples axle counts for short durations, called portable traffic recorder (PTR) sites, and obtains continuous counts from a small number of strategically important locations. The continuous-count data is leveraged to convert short-duration axle counts into average-annual-daily- traffic counts. This requires estimation of seasonal adjustment factors (SAFs) and axle correction factors at short- count locations. This project focused on developing a method for estimating SAFs for PTR sites. The continuous- count data was grouped into a small number of groups based on seasonal traffic-volume patterns. Traffic patterns at PTR sites were hypothesized by polling professional opinions and then verified by performing statistical tests. PTRs with matching seasonal patterns inherited SAFs from the corresponding continuous-count locations. Researchers developed a survey tool, based on the analytic hierarchy process, to elicit professional judgments. MnDOT staff tested this tool. The statistical testing approach was based on bootstrapping and computer simulation. It was tested using simulated data. The results of this analysis show that in the majority of cases, three weekly samples, one in each of the three seasons, will suffice to reliably estimate traffic patterns. Data could be collected over several years to fit MnDOT’s available resources. Sites that require many weeks of data (say, more than five) may be candidates for installation of continuous counters.
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    Statistical Analysis of Fare Compliance
    (Center for Transportation Studies, University of Minnesota, 2014-08) Gupta, Diwakar; Chen, Yibin
    Metro Transit uses a Proof of Payment (PoP) system with barrier-free stations on its Hiawatha Light Rail Line. It measures fare compliance to calculate missed revenue and to determine the effectiveness of its efforts to improve compliance. In this project, researchers employ a suite of statistical methodologies for estimating compliance from ticket sales and tagged rides' data as well as data from the Mobile Phone Validator (MPV) device used by Metro Transit police officers and Patrol Activity Logs. Researchers calculate point and interval estimates of the noncompliance rate and the minimum sample sizes needed to realize a desired degree of precision. As a first step in their analysis, researchers confirm that both ridership and noncompliance rate vary by direction, station, stratum, and day-of-week. These factors also affect the precision of noncompliance rate estimates. Researchers estimated the overall noncompliance rate to be 0.55% for weekdays and 0.7% for weekends. They also found that the noncompliance rate was relatively much higher among cardholders. One of their recommendations was that in order to realize a reasonable precision (95% confidence interval to be no more than 10% of the mean rate), Metro Transit would need to reduce weekday inspection frequency by about 30% but increase weekends' inspection frequency by 50% relative to the current practice. Researchers also found that ticket sales and tagged rides' data (currently automated) could provide reliable estimates of ridership, reducing the need to perform manual counts, and could help improve the pricing of Metro Transit's fare products.
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    Statistical Methods for Materials Testing
    (Minnesota Department of Transportation, 2009-12) Gupta, Diwakar; Peterson, Amy
    Mn/DOT provides incentives to contractors who achieve high relative density via a pay factor applied to each unit of work. To determine the pay factor, Mn/DOT divides each day of a contractor’s work into a small number of lots. Then, core samples are taken from two locations within each lot and the relative densities of the cores are calculated by performing standardized tests in materials testing laboratories. The average of these two values is used as an estimate of the lot's relative density, which determines the pay factor. This research develops two Bayesian procedures (encapsulated in computer programs) for determining the required number of samples that should be tested based on user-specified reliability metrices. The first procedure works in an offline environment where the number of tests must be known before any samples are obtained. The second procedure works in the field where the decision to continue testing is made after knowing the result of each test. The report also provides guidelines for estimating key parameters needed to implement our protocol. A comparison of the current and proposed sampling procedures showed that the recommended procedure resulted in more accurate pay factor calculations. Specifically, in an example based on historical data, the accuracy increased from 47.0% to 70.6%, where accuracy is measured by the proportion of times that the correct pay factor is identified. In monetary terms, this amounted to a change from average over and under payment of $109.60 and $287.33 per lot, to $44.50 and $90.74 per lot, respectively.
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    Weigh-in-Motion Sensor and Controller Operation and Performance Comparison
    (Minnesota Department of Transportation, 2018-01) Gupta, Diwakar; Tang, Xiaoxu; Yuan, Lu
    This research project utilized statistical inference and comparison techniques to compare the performance of different Weigh-in-Motion (WIM) sensors. First, we analyzed test-vehicle data to perform an accuracy check of the results reported by the sensor-vendor Intercomp. The results reported by Intercomp mostly matched with our own analysis, but the data were found to be insufficient to reach any conclusions about the accuracy of the sensor under different temperature and speed conditions. Second, based on the limited data from the Intercomp and IRD sensor systems, we performed tests of self-consistency and comparisons of measurements to inform the selection of a superior system. Intercomp sensor data were found to be not self-consistent but IRD data were. Given the different measurements provided by the two sensors, without additional data, we were not able to reach a conclusion regarding the relative accuracy or the duration of consistent observations before needing recalibration. Initial comparisons indicated potential problems with the Intercomp sensor. We then suggested alternate approaches that MNDOT could use to determine whether recalibration was required. Finally, we analyzed ten-month data from the IRD WIM system and four-month data from the Kistler WIM system to evaluate relative sensor accuracy. While both systems were found to be self-consistent within the data time frame, the Kistler system generated more errors than the IRD system. Conclusions regarding relative accuracy could not be reached without additional data. We identified the sorts of measurements that would need to be monitored for recalibration and the methodology needed for estimating future recalibration time.