In the last decades, population growth has been outpacing transportation infrastructure growth, and today's transportation professionals are challenged to meet the mobility needs of an increasing population. The effectiveness of the transportation system is an essential constituent of people's daily lives as they commute between different points of interest. Studies show that at many highway junctions, congestion continues to worsen, and drivers are experiencing greater delays and higher risk exposures. Engineers have very little resources to handle this increase in population. One solution to resolve and alleviate congestion due to increasing traffic volumes and travel demands relies in implementing alternative designs. This approach will help traffic engineers determine which design will be the most appropriate for a particular location. This study compares and evaluates the Diverging Diamond Interchange (DDI), which is an unconventional design, to Partial Cloverleaf (ParClo) types A4 and B4 interchange designs by evaluating different Measure of Effectiveness (MOEs). Using microsimulation platform AIMSUN, each interchange type was evaluated for low, medium and high traffic flows. The analysis revealed that the DDI with four through lanes performed better than the ParClo A4 for unbalanced conditions, the DDI with six though lanes had similar results as the ParClo B4 for very high volumes. In terms of queue, the DDI design had a much better performance. The results from the analysis help in providing guidelines to the decision makers for selecting the best alternative in terms of performance. / by Borja Galletebeitia. / Thesis (M.S.C.S.)--Florida Atlantic University, 2011. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.

This effort seeks to answer the question; can a transferable model be developed from easily obtainable, publicly available land-use, census, roadway, and network data for the use in safety performance functions? 474 stop-controlled minor legs were used as the training data set using ordinary least squares regression. A best-fit model of maximum independent variables, n=12 was chosen using an exhaustive approach using Mallow's Cp to select the model with least bias in the predictors. The results of the analysis revealed that the combination of variables from Washington, Ohio, and North Carolina did not have a strong relationship. The best-fit model incorporated functional class information of the major-leg, minor leg functional class information, longitudinal markings, access to a parking lot, and population density of census tract. Validation of the model demonstrated an average 59 percent error between the model estimated and actual AADT values for validation data set (n=54). Furthermore, separate models for each state revealed a lack of uniformity in the dependent variables, and more variance description of the state specific AADT.

At signalized intersections, pedestrians are considered to be amongst the most vulnerable. When in the crosswalk at intersections without protected left-turn phasing, pedestrians are particularly at risk from left-turning vehicles. Until recently, a wide variety of indications were in use across the US to indicate a permissive left-turn condition to the driver. In Oregon, the Flashing Yellow Arrow (FYA) has been used to indicate the permissive left-turn condition for approximately 10 years. With the addition of the FYA in the 2009 MUTCD, it is likely that its use will continue to increase nationally. Though many operational and safety issues have been studied about the FYA indication, this research proposes to fully investigate factors that influence driver behavior in the context of the permissive left-turn conflict with pedestrians. Specifically, the research seeks to study driver glance behavior to identify reasons why drivers are, "looking at but not seeing" pedestrians in or near the crosswalk or not searching for the presence of pedestrians at all. / Graduation date: 2013

This thesis discusses the effect of sequential conflict resolution maneuvers of a continuous flow of agents through a finite control volume. Video analysis of real world traffic flows that exhibit self-organized capabilities is conducted to extract characteristics of those agents. A tool is created which stabilizes the input video and extracts motion from it using the background subtraction method. I discuss the tool in detail as I created it to be user friendly and easily modifiable for other uses. The aim of the video analysis I conduct is to determine characteristics of agents in self-organized traffic flow. Comparisons are made with agents under sequential conflict resolution schemes and those that exhibit these self-organized capabilities to determine if agents under sequential control can approach the behaviors of those in self-organized environment. Flow geometries are studied and generalized with the goal of determining stability characteristics of arbitrary flow geometries. Stability analysis includes analytical proof of bounds on the conflict resolution maneuvers.

The safety at half-signalized intersections in Portland, Oregon is analyzed in this thesis using 10 years of crash history and analysis of video that was collected at a subset of intersections. A half-signalized intersection has a standard red-yellow-green traffic signal for automobiles on the major road, a stop sign for motorists on the minor road, and a pedestrian signal with actuation for pedestrians and/or bicyclists on the minor road. Although prevalent in Canada, this type of intersection control is not typically found in the United States because the MUTCD explicitly prohibits its use. Half-signal use is limited mostly to two cities in the Pacific Northwest. In Portland, Oregon there are forty-seven intersections where half-signals are used but the last installation was in 1986; Seattle has over 100 intersections with half-signals and installs these in new locations where warranted. To explore the safety records of these intersections in Portland, crash data from 2002-2011 was analyzed. A total of 442 crashes over the ten-year period at half-signals were observed. Sixteen of these 442 crashes involved pedestrians. In the crashes involving pedestrians, significant differences were found between the approach street of the vehicle and whether the pedestrian or driver was at fault. In the crash error reports, it was found that significantly more of the crashes involving pedestrians were the fault of motorists departing from the minor road who collided with pedestrians crossing the major street. Further crash analysis at half-signals was performed by developing matched comparison groups of minor stop controlled and fully signalized intersections. Crash rates were 0.158 and 0.178 crashes per million entering vehicles for 3-leg and 4-leg half-signals and these rates did not differ significantly from the minor street stop controlled and signalized comparison groups. Results from the matched comparison showed that the half-signalized group had more rear-end crashes when compared with the minor stop controlled group. This was the only result that held significance when crash rates were considered. It was also observed that the minor stop controlled group had a higher proportion of angle crashes when compared with the half-signal group but this did not influence the crash severity. Pedestrian crashes were more prevalent in the half-signal group when compared with the fully-signalized group. Pedestrian volumes were not available which would be used to determine if this significant measure is a result of higher pedestrian use at half-signals. In addition to crash analysis, video was captured at five half-signalized intersections totaling 180 hours. Traffic volumes, pedestrian and bicycle volumes, and signal actuations were collected over a twenty-four hour period. Over this twenty-four hour period the five intersections averaged daily counts of 18613 vehicles on the major street, 591 vehicles on the minor street, 263 pedestrians crossing the major street, 285 pedestrians crossing the minor street, 52 bicycles on the major street, 37 bicycles on the minor street, and 126 signal actuations. Twenty-four hour observations from each of the intersections were used to study conflicts and compliance. No conflicts were observed that reflect the left-turning from the minor street pedestrian crashes that were identified in the crash history. Compliance of the half-signal by vehicles and pedestrians was comparable to compliance at fully-signalized intersections found in other studies with one exception. Across the intersections where video was collected, consisting of four 4-leg intersections and one 3-leg intersection, seven left turn on red violations were observed which had a significant impact on the time after red that red light violations were made. It is hypothesized that at half-signals vehicles on the major street make a left turn on the red signal very late into the red phase because there is not a risk of colliding with a vehicle traveling on the minor street since traffic volumes on the minor street are comparably low. The observed left turn on red violations did not put pedestrians at risk since by that point into the signal pedestrians were already clear of the intersection. Finally, a stop compliance logistic regression model was developed at four four-leg intersections to see what factors had an effect on minor street vehicle stop compliance. All 166 hours of video were used to observe vehicles that arrived at the half-signal during the pedestrian phase. The dependent variable collected was whether a vehicle came to an acceptable stop. Independent variables collected included the vehicle's queue position, if it was the peak school period, if there was a vehicle across the street on the minor road, if a vehicle was stopped at the signal on the major street, if a pedestrian was present when the vehicle arrived, and the movement that the vehicle made from the minor street. Independent variables used in the model included the vehicle's queue position, if a vehicle was stopped at the signal on the major street, if a pedestrian was present, and if the vehicle made a right turn at the signal. Pedestrian presence and right turning vehicles had a positive impact on stop compliance. Vehicles being further back in the queue and cars stopped at the signal on the major street had a negative impact on stop sign compliance. In the model, pedestrian presence had the largest positive impact on stop compliance. When pedestrians were present, a motorist on the minor street was four times more likely to stop at the sign.

The Type-II dilemma zone refers to the segment of roadway approaching an intersection where drivers have difficulty deciding to stop or proceed through at the onset of the circular yellow (CY) indication. Signalized intersection safety can be improved when the dilemma zone is correctly identified and steps are taken to reduce the likelihood that vehicles are caught in it. This research employs driving simulation as a means to collect driver response data at the onset of the CY indication to better understand and describe the dilemma zone. The data obtained was compared against that from previous experiments documented in the literature and the evidence suggests that driving simulator data is valid for describing driver behavior under the given conditions. Fuzzy logic was proposed as a tool to model driver behavior in the dilemma zone, and three such models were developed to describe driver behavior as it relates to the speed and position of the vehicle. These models were shown to be consistent with previous research on this subject and were able to predict driver behavior with up to 90% accuracy. / Graduation date: 2013

Indiana University-Purdue University Indianapolis (IUPUI) / In recent decades, Petri nets (PNs) have been used to model traffic networks for different purposes, such as signal phase control, routing, and traffic flow estimation, etc. Because of the complex nature of traffic networks where both discrete and continuous dynamics come into play, the Hybrid Petri net (HPN) model becomes an important tool for the modeling and analysis of traffic networks. In Chapter 1 a brief historical summery about traffic systems control and then related work is mentioned followed by the major contributions in this research. Chapter 2 provides a theoretical background on Petri nets. In Chapter 3, we develop a HPN model for a single signalized intersection first, then we extend this model to study a simple traffic network that consists of two successive intersections. Time delays between different points of network are also considered in order to make the model suitable for analysis and simulation. In addition to HPN models, we also consider discrete Petri nets where their modeling simplicity enables the characterization of the occurrences of all events in the system. This discrete PN is particularly useful to give a higher-level representation of the traffic network and study its event occurrences and correlations. In Chapter 4, we build a discrete PN model to represent a traffic network with two successive intersections. However, we find that the model leads to unbounded places which cannot accurately reflect the dynamics of the traffic in terms of event occurrences. Hence, we introduce the Modified Binary Petri nets (MBPN) to overcome the limitation and resolve the confliction problem when we design our controllers. This MBPN model is a powerful tool and can be useful for the modeling and analysis of many other applications in traffic networks. Chapter 5 gives a summary for each chapter, provides conclusion and discusses future work for both discrete and hybrid Petri nets.