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Browsing by Author "Davis, Gary"

Now showing 1 - 12 of 12
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    Assessing the Impact of Pedestrian-Activated Crossing Systems
    (Minnesota Department of Transportation, 2020-05) Hourdos, John; Dirks, Peter; Lehrke, Derek; Parikh, Gordon; Davis, Gary; Cheong, Christopher
    Pedestrian-Activated Crossing (PAC) systems have been shown to have a generally positive impact on driver yield rates. However, there has been insufficient research on the effect PAC treatments have on pedestrian crash rates, and there is little guidance as to when and where each treatment should be used. This study estimates the effects of PACs on pedestrian crash rates using Monte Carlo simulation and examines the relationships between driver yield rates and a variety of treatments and site designs by conducting an observational study using video data from 34 locations. The simulation outcomes suggests that while the percentage of yielding drivers might be a useful indicator of pedestrian level of service, it is less helpful as safety surrogate. This could be because a driver?s yielding to a pedestrian, as observed in field studies, might not be the same behavior as a driver attempting to stop during a vehicle/pedestrian conflict. The observational study shows that the number of lanes to cross at a crossing is positively correlated with the rate at which pedestrians activate the system, but it is not correlated with the delay. Additionally, the study showed that the effect of PAC systems is most pronounced at sites with a higher number of movements conflicting with the crossing or poor visibility from upstream without signs warning drivers of an upcoming crosswalk.
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    Developing and Validating a Model of Left-Turn Crashes to Support Safer Design and Operations
    (Center for Transportation Studies, University of Minnesota, 2018-09) Davis, Gary; Gao, Jingru; Mudgal, Abhisek
    This report documents work done to advance the state of art in crash simulation. This includes: (1) A field study to collect data on drivers’ left-turn gap acceptance and turning times, and development of statistical models that can be incorporated into a crash simulation model; (2) The use of Markov Chain Monte Carlo computational tools to quantify uncertainty in planar impact reconstruction of two-vehicle crashes; (3) A method for combing the results from planar impact reconstruction with event data recorder pre-crash data to estimate descriptive features of actual left-turn crashes. This is applied to several left-turn crashes from the National Highway Traffic Safety Administration’s NASS/CDS database; (4) A left-turn crash simulation model incorporating the above results. Initial model checking is performed using estimates from the reconstructed NASS/CDS cases as well as results from a previous study on left-turn crash risk. Also described is a method for simulating crash modification effects without having to first simulate crashes as rare outcomes in very large numbers of gap acceptances.
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    Evaluation of the Effectiveness of Stop Lines in Increasing the Safety of Stop-Controlled Intersections
    (Minnesota Department of Transportation, 2020-07) Duhn, Melissa; Dirks, Peter; Loutfi, Andrew; Hourdos, John; Davis, Gary
    Stop lines are ubiquitous, but do they really impact intersection safety? Prior to this project, no long-term studies on intersection safety with stop lines had been completed. This project was developed with two parallel research efforts: a safety study and an observational study. The safety study was developed to address stop lines’ effects over the long term and used crash data from five cities’ stop-controlled intersections to perform regression and see if stop lines actually influenced safety. The observational study was developed to determine if stop lines have an effect on driver behavior at intersections and to look at where drivers were stopping. Video was collected at 16 different intersections before and after a stop line was painted. The safety study and observational study showed that stop lines did not have a significant impact on driver behavior or intersection safety, but other factors like speed limits and sight distance did. Implications for practice include carefully examining sight distance at the intended stopping point to ensure drivers have adequate sight distance in both directions. If sight distance is not adequate, moving the intended stop location or reconsidering whether the intersection should have signage -- stop or yield -- or be uncontrolled could yield better driver compliance and safety.
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    Freeway Origin Destination Matrices: Not as Simple as They Seem
    (2004) Muthuswamy, Satya; Davis, Gary; Levinson, David M; Michalopoulos, Panos
    Travel demand can be elegantly represented using an Origin-Destination (OD) matrix. The link counts observed on the network are produced by the underlying travel demand. One could use these counts to reconstruct the OD matrix. An offline approach to estimate a static OD matrix over the peak period for freeway sections using these counts is proposed in this research. Almost all the offline methods use linear models to approximate the relationship between the on-ramp and off-ramp counts. Previous work indicates that the use of a traffic flow model embedded in a search routine performs better than these linear models. In this research that approach is enhanced using a microscopic traffic simulator, AIMSUN, and a gradient based optimization routine, MINOS, interfaced to estimate an OD matrix. This approach is an application of the Prediction Error Minimization (PEM) method. The problem is non-linear and non-smooth, and the optimization routine finds multiple local minima, but cannot guarantee a global minima. However, with a number of starting seed matrices, an OD matrix with a good fit in terms of reproducing traffic counts can be estimated. The dominance of the mainline counts in the OD estimation and an identifiability issue is indicated from the experiments. The quality of the estimates improves as the specification error, introduced due to the discrepancy between the traffic flow model and the real world process that generates the on-ramp and off-ramp counts, reduces.
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    Improving the Estimation of Travel Demand for Traffic Simulation: Part I
    (2005-03) Muthuswamy, Satya; Levinson, David; Michalopoulos, Panos; Davis, Gary
    Many current traffic management schemes are tested and implemented using traffic simulation. An Origin-Destination (OD) matrix is an ideal input for such simulations. The underlying travel demand pattern produces observed link counts. One could use these counts to reconstruct the OD matrix. An offline approach to estimate a static OD matrix over the peak period for freeway sections using these counts is proposed in this research. Almost all the offline methods use linear models to approximate the relationship between the on-ramp and off-ramp counts. Previous work indicates that the use of a traffic flow model embedded in a search routine performs better than these linear models. In this research, that approach is enhanced using a microscopic traffic simulator, AIMSUN, and a gradient-based optimization routine, MINOS, interfaced to estimate an OD matrix. The problem is highly non-linear and non-smooth, and the optimization routine finds multiple local minima, but cannot guarantee a global minima. However, with a number of starting "seed" matrices, an OD matrix with a good fit in terms of reproducing traffic counts can be estimated. The dominance of the mainline counts in the OD estimation and an identifiability issue is indicated from the experiments. The quality of the estimates improves as the pecification error, introduced due to the discrepancy between AIMSUN and the real-world process that generates the on-ramp and off-ramp counts, reduces.
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    Improving the Estimation of Travel Demand for Traffic Simulation: Part II
    (2004-12) Wu, Yao; Davis, Gary; Levinson, David
    This report examined several methods for estimating Origin- Destination (OD) matrices for freeways using loop detector data. Least squares based methods were compared in terms of both off- line and on- line estimation. Simulated data and observed data were used for evaluating the static and recursive estimators. For off- line estimation, four fully constrained least squares methods were compared. The results showed that the variations of a constrained least squares approach produced more efficient estimates. For on- line estimation, two recursive least squares algorithms were examined. The first method extends Kalman Filtering to satisfy the natural constraints of the OD split parameters. The second was developed from sequential quadratic programming. These algorithms showed different capabilities to capture an abrupt change in the split parameters. Practical recommendations of the choice of different algorithms are given.
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    Land Use and Travel Choices in the Twin Cities, 1958-1990
    (2001-07-01) Barnes, Gary; Davis, Gary
    This report examines the effects of land development patterns on travel choices by residents of the Twin Cities area. A historical analysis studies changes in travel behavior between 1958 and 1990, focusing in particular on total daily time spent traveling. The conclusion is that daily time per traveler changed only very slightly over this time, despite very significant changes in land use. The second major analysis in the report looks at travel choices in 1990 in greater detail. Again, the conclusion was that land use per se did not play a significant role in travel choices when other factors were controlled for. Dense central areas generated much less mileage per person, but this was almost entirely because of lower speeds, not because central city residents spent much less time driving. Overall, there was less than a 20% difference in average time spent driving per day between central city and outer suburbs, and this difference arose entirely from commute times. Non-work travel time showed no systematic variation by location, in contrast to expectations. The one area in which land use played a significant role was that large dense job locations attracted very high shares for non-auto modes.
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    Remaining Service Life Asset Measure, Phase 2
    (Minnesota Department of Transportation, 2022-02) Matias de Oliveira, Jhenyffer; Khani, Alireza; Davis, Gary; Marasteanu, Mihai
    The main objectives of phase 2 of this project were to obtain relevant data to calculate the percent remaining service life interval (PRSI) and two additional metrics and to perform Markov chain analysis and dynamic programming to determine how much time and funding is required to bring the system to a stable configuration, which allows for more consistent planning. First, relevant pavement management data was obtained from MnDOT and preliminary data analyses were performed. The prediction models and optimization process currently used by MnDOT were investigated and summarized. Next, two additional metrics, Asset Sustainability Ratio and Deferred Preservation Liability, were calculated for MnDOT’s network. Then details of the estimation process of state-to-state transition probabilities to be used in the Markov chain model were presented. To allow for site-specific variation, ordinal logistic regression models were incorporated in the Markov chain model. The results were used in a dynamic programming optimization methodology to obtain baseline and optimal policies for different scenarios and a user-friendly excel spreadsheet tool was developed. Finally, a summary of the work performed followed by conclusions and recommendations was presented.
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    Traffic Safety Methodologies
    (University of Minnesota, Center for Transportation Studies, 2007-09) Davis, Gary
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    Understanding Urban Travel Demand: Problems, Solutions, and the Role of Forecasting
    (1999-08-01) Barnes, Gary; Davis, Gary
    This report is a general examination and critique of transportation policy making, focusing on the role of traffic and land use forecasting. There are four major components: 1. Current, historical, and projected travel behavior in the Twin Cities. 2. The standard travel forecasting model, and some of its shortcomings. 3. The potential application of integrated land use and transportation models. 4. Specific transportation problems and proposed policies in the Twin Cities. The most important result is that the standard traffic forecasting model in its current form is not well suited for evaluating many of the policies of greatest current interest, in particular, those that seek to reduce the overall amount of travel through changes in land use or travel behavior. This model was developed to predict road capacity needs, taking the quantity of travel as more or less uninfluenced by policy. However, currently available improvements, including integrated transportation and land use models, often add little value because they are not based on a well-established theoretical and empirical understanding of travel behavior. The most urgent need in forecasting is not for more complex models, but for a better understanding of the real world processes that the models are attempting to capture.
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    Vehicle Probe Based Real-Time Traffic Monitoring on Urban Roadway Networks
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2012-10) Feng, Yiheng; Hourdos, John; Davis, Gary; Collins, Michael
    Travel time is a crucial variable both in traffic demand modeling and for measuring network performance. The objectives of this study focused on developing a methodology to characterize arterial travel time patterns by travel time distributions, proposing methods for estimating such distributions from static information and refining them with the use of historical GPS probe information, and given such time and location-based distribution, using realtime GPS probe information to produce accurate path travel times as well as monitor arterial traffic conditions. This project set the foundations for a realistic use of GPS probe travel time information and presented the proposed methodologies through two comprehensive case studies. The first study used the Next Generation SIMulation (NGSIM) Peachtree Street dataset, and the second utilized both real GPS and simulation data of Washington Avenue, in Minneapolis, MN.
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    Vehicle Speed Impacts of Occasional Hazard (Playground) Warning Signs
    (Minnesota Department of Transportation, 2012-02) Davis, Gary; Knapp, Keith K.; Hourdos, John
    The main objective of this study was to estimate the speed impact of occasional hazard (playground) warning (OHPW) signs along residential streets. Three types of data were collected at each of three study sites approximately one month before and one week to one month after the installation of a pair of OHPW signs. Vehicle speed data were collected with a pneumatic tube device. Manual observations were recorded, and focused on the magnitude and location of the on-street parking and park and/or playground activities occurring at the study sites. Linear regression analysis was used to estimate the change in mean vehicle speed associated with the presence of the OHPW signs, while controlling for the effects due to activity levels on the streets and the playgrounds. At one site the OHPW sign had no discernible effect on mean vehicle speeds, while at the other two sites mean vehicle speeds decreased by 1.5 mph and 0.9 mph following installation of the OHPW signs.