Browsing by Author "Davis, Gary A."

Now showing 1 - 20 of 38

Access to Destinations: Arterial Data Acquisition and Network-Wide Travel Time Estimation (Phase II)
(Minnesota Department of Transportation, 2010-03) Davis, Gary A.; Hourdos, John; Xiong, Hui; Morris, Ted
The objectives of this project were to (a) produce historic estimates of travel times on Twin-Cities arterials for 1995 and 2005, and (b) develop an initial architecture and database that could, in the future, produce timely estimates of arterial traffic volumes and travel times. Our Phase I field study indicated that on arterial links where both the demand traffic volume and the signal timing are known, model-based estimates of travel time that are on average within 10% of measured values can be obtained. Phase II of this project then focused on applying this approach to the entire Twin Cities arterial system. The Phase II effort divided into three main subtasks: (1) updating estimates of demand traffic volume obtained from a transportation planning model to make them consistent with available volume measurements, (2) collecting information on traffic signal locations in the Twin Cities and compiling this into a geographic database, and (3) combining the updated traffic volumes and signal information to produce link-by-link peak-period travel time estimates. The traffic volume update took as inputs the predicted volumes generated by a traffic assignment model and measured average annual daily traffic from automatic traffic recorders, and gave as output updated estimates of the traffic volumes for links lacking automatic traffic recorders. A request to state, county and municipal agencies in the seven-county metro area produced Information on approximately 2,900 traffic signals. Estimated arterial travel times for the morning and afternoon peak periods for 1995 and 2005 were then computed and sent to other components of the Access to Destinations effort.
Access to Destinations: Travel Time Estimation on Arterials
(Minnesota Department of Transportation, 2007-08) Davis, Gary A.; Xiong, Hui
The primary objective of this project was to identify and evaluate parametric models for making default estimates of travel times on arterial links. A review of the literature revealed several candidate models, including the Bureau of Public Roads (BPR) function, Spiess's conical volume delay function, the Singapore model, the Skabardonis-Dowling model, and the Highway Capacity Manual's model. A license plate method was applied to a sample of 50 arterial links located in the Twin Cities seven county metropolitan area, to obtain measurements of average travel time. Also obtained were the lengths of each link, measurements of traffic volume, and signal timing information. Default values for model parameters were obtained from the Twin Cities planning model's database. Using network default parameters, we found that the BPR and conical volume-delay models produced mean average percent errors (MAPE) of about 25%, while the Singapore and Skabardonis-Dowling models, using maximal site-specific information, produced MAPE values of around 6.5%. As site-specific information was replaced by default information the performance of the latter two models deteriorated, but even under conditions of minimal information the models produced MAPE values of around 20%. A cross-validation study of the Skabardonis-Dowling model showed essentially similar performance when predicting travel times on links not used to estimate default parameter values.
Bayesian Methods for Estimating Average Vehicle Classification Volumes
(Minnesota Department of Transportation, 1999-10) Davis, Gary A.; Yang, Shimin
This report describes the development of a data-driven methodology for estimating the mean daily traffic (MDT) for different vehicle classes from short classification-count samples. Implementation of the methodology requires that an agency maintain a small number of permanent classification counters (PCC), whose output is used to estimate parameters describing their monthly and day-of-week variation patterns and covariance characteristics. The probability of a match between a short classification count sample and each of the PCCs is computed, as well as the estimates of the short-counts site's MDTs which would arise if the short-count site had variation patterns identical to each of the PCCs. The final MDT estimates are then simply the weighted averages of these component MDTs, with the matching probabilities providing the weights. Empirical evaluation of the methods using data collected at the Long Term Pavement Performance Project sites in Minnesota indicated that a reliable match of a short-count site could be made using a sample consisting of a one-day classification count from each month of the year. An evaluation of two-day classification count samples indicated that a two-day count is not sufficient to reliably match the site to a factor group, justifying estimation of MDT using weighted averages. For estimating combination vehicle MDT, these samples should be taken between May and October, and between Tuesday and Thursday. In this case the estimated MDT differed on average by about 10% - 12% compared to estimates based on full year's worth of counts, and differed by less than 26%, 95% of the time.
Building our Way Out of Congestion? Highway Capacity for the Twin Cities
(2001-07-01) Davis, Gary A.; Sanderson, Kate
The problem of identifying a set of capacity expansions that are in some sense optimal, while accounting for traveler reaction, is known as a network design problem. A literature review reveals numerous formulations and solution algorithms over the last three decades, but the problem of implementing these for large-scale networks has remained a challenge. This project presents a solution procedure that incorporates the capacity expansion as a modified step in the Method Successive Averages, providing an efficient algorithm capable of solving realistic problems of real-world complexity. Application of this method addresses the network design problem for the freeway system of the Twin Cities by providing a lower bound on the extent to which physical expansion of highway capacity can be used to accommodate future growth. The solution estimates that adding 1,844 lane-kilometers, or 1,146 lane-miles, would be needed to accommodate the demand predicted for the year 2020.
Bus Signal Priority Based on GPS and Wireless Communications Phase I - Simulation Study
(2006-07-01) Liao, Chen-Fu; Davis, Gary A.
The Minneapolis-St. Paul metropolitan transit agency has installed Global Positioning System (GPS) equipment in transit vehicles for the purpose of monitoring vehicle locations and schedules in order to provide more reliable transit services. This research project evaluates the potential use of vehicle-mounted GPS to develop a Transit Signal Priority system that improves the efficiency of transit.
Transit Signal Priority (TSP) for transit has been proposed as an efficient way to improve transit travel & operation. Bus signal priority has been implemented in several US cities to provide more reliable travel and improve customer ride quality. Current signal priority strategies implemented in various US cities mostly utilized sensors to detect buses at a fixed or at a preset distance away from the intersection. Signal priority is usually granted after a preprogrammed time offset after detection. The proposed study would take advantage of the GPS system on the buses in Minneapolis and develop a signal priority strategy which could consider the bus' timeliness with respect to its schedule, its number of passengers, location and speed.
A Bus Signal Priority System Using Automatic Vehicle Location / Global Position Systems and Wireless Communication Systems
(University of Minnesota Center for Transportation Studies, 2008-12) Liao, Chen-Fu; Davis, Gary A.; Iyer, Priya
Current signal priority strategies implemented in various US cities mostly utilize sensors to detect buses at a fixed or preset distance away from an intersection. Traditional presence detection systems, ideally designed for emergency vehicles, usually send signal priority request after a preprogrammed time offset as soon as transit vehicles were detected without the consideration of bus readiness. The objective of this study is to integrate the already equipped Global Positioning System/Automated Vehicle Location (GPS/AVL) system on the buses in Minneapolis and develop an adaptive signal priority system that could consider the bus schedule adherence, its number of passengers, location and speed. Buses can communicate with intersection signal controllers using wireless technology to request for signal priority. Similar setup can also be utilized for other transit-related Intelligent Transportation Systems (ITS) applications. The City of Minneapolis recently deployed wireless technology to provide residents, businesses and visitors with wireless broadband access anywhere in the city. Communication with the roadside unit (e.g., traffic controller) for signal priority may be established using the readily available 802.11x WLAN or the Dedicated Short Range Communication (DSRC) 802.11p protocol currently under development for wireless access in vehicular environment. This report documents the development, verification and validation of the embedded signal priority prototype systems, field testing results and limitations of using the City of Minneapolis Wi-Fi network for Transit Signal Priority (TSP).
Capacity Expansion in the Twin Cities: The Roads-Transit Balance
(Minnesota Department of Transportation, 2006-12) Davis, Gary A.; Sanderson, Kate; Tao, HunWen
"What would it take to build our way out of congestion in the Twin Cities?" was the question posed by researchers five years ago. This previous study solved a roads-only network design problem (NDP) for the Twin Cities of Minnesota. Building on that work, another network design problem is examined for the Twin Cities metropolitan area of 3 million, to examine the tradeoff between demand side reductions and the limited access capacity expansion necessary to achieve desired levels of service. The problem is simplified by pre-determining a mode split, which allows for incorporating decreasing demand directly as an input rather than in the model formulation. The problem is solved using Sequential Linear Expansion (SLIE), a modified method of successive averages (MSA). Computation time for the large network is decreased to a reasonable length using another modification, the MSA with decreasing re-initialization (MSADR). A typical personal computer can solve this large-sized problem within 24 hours. For forecasted travel demand for 2030, it was found that if the number of trips were reduced by 20%, lanemiles needed to achieve LOS D decreases by up to 43%.
A Case Control Study of Speed and Crash Risk, Technical Report 1: Aggregation Biases in Road Safety Research and a Mechanism Approach to Accident Modeling
(2006-04-01) Davis, Gary A.
In accident reconstruction, individual road accidents are treated as essentially deterministic events, although incomplete information can leave one uncertain about how exactly an accident happened. In statistical studies, on the other hand, accidents are treated as individually random, although the parameters governing their probability distributions may be modeled deterministically. Selection of one or the other of these approaches affects how data are interpreted, and here a simple deterministic model of a vehicle/pedestrian encounter is used to illustrate how naively applying statistical methods to aggregated data could lead to an ecological fallacy and to Simpson's paradox. It is suggested that these problems occur because the statistical regularities observed in accident data have no independent status but are simply the results of aggregating particular types and frequencies of mechanisms.
A Case Control Study of Speed and Crash Risk, Technical Report 2: Bayesian Reconstruction of Traffic Accidents and the Causal Effect of Speed in Intersection and Pedestrian Accidents
(2006-04-01) Davis, Gary A.
Traffic accident reconstruction has been defined as the effort to determine, from whatever evidence is available, how an accident happened. Traffic accident reconstruction can be treated as a problem in uncertain reasoning about a particular event, and developments in modeling uncertain reasoning for artificial intelligence can be applied to this problem. Physical principles can usually be used to develop a structural model of the accident and this model, together with an expert assessment of prior uncertainty regarding the accident's initial conditions, can be represented as a Bayesian network. Posterior probabilities for the accident's initial conditions, given evidence collected at the accident scene, can then be computed by updating the Bayesian network. Using a possible worlds semantics, truth conditions for counterfactual claims about the accident can be defined and used to rigorously implement a 'but for' test of whether or not a speed limit violation could be considered a cause of an accident. The logic of this approach is illustrated for a simplified version of a vehicle/pedestrian accident, and then the approach is applied to determine the causal effect of speeding in 10 actual accidents.
A Case Control Study of Speed and Crash Risk, Technical Report 3: Speed as a Risk Factor in Run-off Road Crashes
(2006-04-01) Davis, Gary A.; Davuluri, Sujay; Pei, Jian Ping
In the U.S.A., the imposition and subsequent repeal of the 55 mph speed limit has led to an increasingly energetic debate concerning the relationship between speed and the risk of being in a (fatal) crash. In addition, research done in the 1960s and 1970s suggested that crash risk is a U-shaped function of speed, with risk increasing as one travels both faster and slower than what is average on a road. Debate continues as to the causes of this relationship, and there is reason to suspect that it may be an artifact of measurement error and/or mixing of different crash types. This report first describes two case-control analyses of run-off road crashes, one using data collected in Adelaide, Australia and the other using data from Minnesota. In both analyses the speeds of the case vehicles were estimated using accident reconstruction techniques while the speeds of the controls were measured for vehicles traveling the crash site under similar conditions. Bayesian relative risk regression was used to relate speed to crash risk, and uncertainty in the case speeds was accounted for by treating these as additional unknowns with informative priors. Neither data set supported the existence of a U-shaped relationship, although crash risk clearly tended to increase as speed increased. The resulting logit model was then used to estimate the probability that a given speed could be considered a casual factor for each of the 10 Minnesota crashes.
Criteria and Guidelines for Three-Lane Road Design and Operation
(Minnesota Department of Transportation, 2023-02) Davis, Gary A.; Hourdos, John; Gao, Jingru
A 4-3 conversion involves changing a four-lane undivided road into one with two general travel lanes separated by a two-way left turn lane. A commonly-used guideline states that a 4-3 conversion can be considering as long as the road’s average annual daily traffic (AADT) volume does not exceed 15,000 vehicles/day but opinions vary, from lowering the AADT threshold to 10,000 vehicles/day to anecdotal evidence for successful 4-3 conversions with AADTs as high as 20,000. The main objective of this project was to identify conditions where 4-3 conversions might be feasible at AADTs greater than 15,000. After reviewing the literature, we conducted simulation studies on three different roads to identify combinations of major and minor road flow where three-lane configurations provided acceptable levels of service. Eight intersections, with 16 approaches, were then selected to represent our findings. These results were presented as summary tables that practitioners could use to make initial assessments regarding 4-3 conversion feasibility.
Cross Median Crashes: Identification and Countermeasures
(Minnesota Department of Transportation, 2008-06) Davis, Gary A.
The goals of this project were to first review the state-of-art with regard to identifying highway sections where median barriers would be most effective in preventing median-crossing crashes (MCC), and if necessary, develop remedies for any identified deficiencies. A statistical technique was developed for estimating the frequency and rate of MCCs on each of a set of highway sections, which required the analyst to review only a subset of hard-copy accident reports. This technique was applied to Minnesota’s freeways and rural expressways, and highway sections were ranked with respect to estimated frequency of MCCs. A first version of a simulation model was developed for comparing the cost-effectiveness of barrier projects on different highway sections. The model uses Monte Carlo simulation to estimate the probability that an encroaching vehicle crosses a median with a specific cross-section, and collides with another vehicle traveling in the opposite direction. The model is implemented as a pair of linked Excel spreadsheets, with a companion macro written in Visual Basic for Applications.
Development and Testing of a Vehicle/Pedestrian Collision Model for Neighborhood Traffic Control
(2002-02-01) Davis, Gary A.; Sanderson, Kate; Davuluri, Sujay
This report presents an approach to assess the effect of vehicle traffic volumes and speeds on pedestrian safety. It shows that the probability of standardized pedestrian conflict resulting in a collision can be computed given data on the distribution of vehicle speeds and headways on a residential street. Researchers applied this method to data collected on a sample of 25 residential streets in the Twin Cities and found that collision rates varied between four and 64 collisions per 1,000 pedestrian conflicts, depending primarily on the street's traffic volume. Using a model that relates the impact speed of a vehicle to the severity of pedestrian injury, they computed the probabilities of a severe collision. Sensitive to both traffic volume and traffic speed, the severe collision rate varied between one and 25 collisions between 1,000 conflicts. Using the same data, researchers also computed the crash reduction factor, used to assess the potential safety effect of a 25 miles per hour speed limit on the sample of residential streets. The estimated crash reductions ranged between .2 and 45 percent, depending primarily on the degree to which the vehicle speeds currently exceeded 25 miles per hour. Researchers also showed how this computation assists with the reconstruction of actual vehicle/pedestrian collisions.
Development and Testing of Methods for Estimating the Impact of Safety Improvements
(2001-03-01) Davis, Gary A.
This report describes a Bayesian method for estimating accident rates at individual sites, which takes into account the fact that the total traffic count usually used to measure exposure is generally not known with certainty. The first step involves deriving an approximation for the probability distribution of total traffic conditioned on a short count sample. This approximation is then used to drive a Bayes estimator of a site's accident rate, conditioned on an accident count, a short count sample, and the total traffic approximation. The method then uses Gibbs sampling to compute accident rate estimates. Tests based on actual accident and traffic data revealed that accident rate estimates based on a two-week traffic sample area are almost as accurate as estimates based on full traffic counting, but that uncertainty in the estimated accident rates increase by 20 to 50 percent when using a two-day count sample.
Development of Guidelines for Permitted Left-Turn Phasing Using Flashing Yellow Arrows.
(Minnesota Department of Transportation, 2015-06) Davis, Gary A.; Hourdos, John; Moshtagh, Vahid
The objective of this project was to develop guidelines for time-of-day use of permitted left-turn phasing, which can then be implemented using flashing yellow arrows (FYA). This required determining how the risk for left-turn crashes varied as traffic-flow conditions varied during the course of a representative day. This was accomplished by developing statistical models, which expressed the risk of occurrence of a left-turn crash during a given hour as a function of the left-turn demand, the opposing traffic volume, and a classification of the approach with respect to the opposing traffic speed limit, the type of left-turn protection, and whether or not opposing left-turn traffic could obstruct sight distance. The models were embedded in a spreadsheet tool which will allow operations personnel to enter, for a candidate intersection approach, existing turning movement counts, and a classification of the approach with respect to speed limit, turn protection, and sight distance issues and receive a prediction of how the risk of left-turn crash occurrence varies throughout the day, relative to a user-specified reference condition.
Driver Comprehension of Flashing Yellow Arrows
(Minnesota Department of Transportation, 2023-12) Davis, Gary A.; Stern, Raphael; Duhn, Melissa; Gao, Jingru
In 2009, the FHWA's Manual on Uniform Traffic Control Devices (MUTCD) introduced the flashing yellow arrow (FYA) traffic signal as an alternative to circular green (CG) to indicate permitted left turns. The FYA is arguably a more intuitive indication that left turns are permitted but not protected and, in addition, the FYA signal heads can support time-of-day changes between protective and permissive left -turn phasing. In 2019, a Research Needs Statement stated that "Research is needed to examine driver comprehension of flashing yellow arrows in different light arrangements and the role of signage." Our objective in this project was to assess drivers' understanding of FYA signal indications and to see if the presence or absence of "Left Turn Yield" signs affect gap acceptance. This was accomplished by conducting an online survey of drivers regarding their understanding of FYA signals and by carrying out a field study of drivers' gap acceptance at a set of Twin Cities intersections.
Dynamic Estimation of Origin-Destination Patterns in Freeways
(Minnesota Department of Transportation, 1994-05) Davis, Gary A.
Any proposed traffic management action is essentially a forecast that the action will result in certain traffic conditions, but uncertainty concerning the amount and distribution of traffic demand will introduce random error between what is expected and what actually occurs. This report treats the problem of forecasting whether or not a given set of freeway on-ramp volumes are likely to cause over-capacity demand at some point in the freeway mainline. The main source of uncertainty in these forecasts concerns the freeway's origin-destination matrix, and four different methods for estimating this matrix from loop detector data are evaluated using Monte Carlo simulation. Only the method which explicitly modeled freeway traffic flow produced reasonably unbiased and efficient estimates, and it was concluded that successful estimation must be coupled with a good model of freeway traffic flow.
Empirical Bayes Identification of High Hazard Locations for Older Drivers
(Minnesota Department of Transportation, 1994-10) Davis, Gary A.
As part of an emphasis on improving road safety, the Minnesota Department of Transportation seeks to identify the locations where older drivers were over-represented in accident records. This research project reports on the use of three methods to help improve the accuracy of identifying locations where older drivers were at increased risk: a basic statistical model, the Empirical Bayes statistical method and a clustering method. Overall, the basic statistical model preformed the best. The clustering method and the Empirical Bayes method could both be usefully applied to the traditional task of high-hazard identification--that of automatically screening a large number of accident sites to identify potential candidates for improvement. This information can point the way to areas that may require a more detailed engineering analysis.
Estimating the Crash Reduction and Vehicle Dynamics Effects of Flashing LED Stop Signs
(Minnesota Department of Transportation, 2014-01) Davis, Gary A.; Hourdos, John; Xiong, Hui
A flashing LED stop sign is essentially a normal octagonal stop sign with light emitted diodes (LED) on the stop sign’s corners. A hierarchical Bayes observational before/after study found an estimated reduction of about 41.5% in right-angle crashes, but with 95% confidence this reduction could be anywhere between 0% and 70.8%. In a field study, portable video equipment was used to record vehicle approaches at an intersection before and after installation of flashing LED stop signs. After installing the flashing stop signs, there was no change in the relative proportion of clear stops to clear non-stops when minor approach drivers did not face opposing traffic, but the relative proportion of clear stops increased for drivers who did encounter opposing traffic. Random samples of 60 minor approach vehicles were selected before and after installation of flashing LED stop signs and speeds for these vehicles when about 500 feet from the intersection, and average deceleration rates over the final 500 feet, were estimated using trajectory-based methods. Average approach speeds tended to be highest in June, somewhat lower in July, and lower yet in September and November, with September and November having roughly equal average speeds. The average deceleration rates showed a similar pattern.
Estimation of Crossing Conflict at Signalized Intersection Using High-Resolution Traffic Data
(Minnesota Department of Transportation, 2017-03) Liu, Henry X.; Davis, Gary A.; Shen, Shengyin; Di, Xuan; Chatterjee, Indrajit
This project explores the possibility of using high-resolution traffic signal data to evaluate intersection safety. Traditional methods using historical crash data collected from infrequently and randomly occurring vehicle collisions can require several years to identify potentially risky situations. By contrast, the proposed method estimates potential traffic conflicts using high-resolution traffic signal data collected from the SMART-Signal system. The potential conflicts estimated in this research include both red-light running events, when stop-bar detectors are available, and crossing (i.e. right-angle) conflicts. Preliminary testing based on limited data showed that estimated conflict frequencies were better than AADT for predicting frequencies of angle crashes. With additional validation this could provide a low-cost and easy-to-use tool for traffic engineers to evaluate traffic safety performance at signalized intersections.

University Digital Conservancy

Browse by Author

Browsing by Author "Davis, Gary A."