<p dir="ltr">This research proposes a methodology by which to identify signalized intersections that cannot be improved by retiming and must instead be addressed with capacity improvement via capital investments. For these intersections, a ranking metric is developed to rank based on capital investment necessity.</p>

Traffic signals are one of the vital control elements of traffic management and control systems under purview of Departments of Transportation (DOTs) nationwide. They directly affect mobility, safety, and environmental parameters of the transportation networks. Traffic engineers in DOTs often face pressure for extracting additional benefits from existing signal control equipment, influenced by evident increase in demand and changing traffic patterns. However, they often face difficulties, usually from the maturity of the field equipment, lack of understanding of currently available equipment capabilities, and multitude of market available equipment. Besides issues in everyday operation, the need for improved decision-making process appears during selection and implementation of the future signal-control subsystems. This thesis is focusing on the issues related with the need for extracting additional benefits and improved planning of signal-control equipment deployment. Presented are several methodologies and techniques for modeling and assessing traffic signal controllers and supporting communication infrastructure. Techniques presented in this thesis include Petri Net modeling language, Software-in-the-loop simulation, and Geographical Information Systems. Specific capabilities of listed techniques are coordinated for maximizing their benefits in addressing specific issues. The intended positive effects reflect in enhanced comprehension, numerical representation, and analysis of state-of-the-art signal control subsystems in focus. Frameworks, methodologies, and example cases are presented for each of the specific issues in identified traffic signal subsystems, along with recommendations for further research. / Master of Science

Traffic signal cycle lengths are traditionally optimized to minimize vehicle delay at intersections using the Webster formulation. This thesis includes two studies that develop new formulations to compute the optimum cycle length of isolated intersections, considering measures of effectiveness such as vehicle delay, fuel consumption and tailpipe emissions. Additionally, both studies validate the Webster model against simulated data. The microscopic simulation software, INTEGRATION, was used to simulate two-phase and four-phase isolated intersections over a range of cycle lengths, traffic demand levels, and signal timing lost times. Intersection delay, fuel consumption levels, and emissions of hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NOx), and carbon dioxide (CO2) were derived from the simulation software. The cycle lengths that minimized the various measures of effectiveness were then used to develop the proposed formulations. The first research effort entailed recalibrating the Webster model to the simulated data to develop a new delay, fuel consumption, and emissions formulation. However, an additional intercept was incorporated to the new formulations to enhance the Webster model. The second research effort entailed updating the proposed model against four study intersections. To account for the stochastic and random nature of traffic, the simulations were then run with twenty random seeds per scenario. Both efforts noted its estimated cycle lengths to minimize fuel consumption and emissions were longer than cycle lengths optimized for vehicle delay only. Secondly, the simulation results manifested an overestimation in optimum cycle lengths derived from the Webster model for high vehicle demands. / Master of Science / Traffic signal timings are traditionally designed to reduce vehicle congestion at an intersection. This thesis is based on two studies that develop new formulations to compute the most efficient signal cycle lengths of intersections, considering vehicle fuel consumption and tailpipe emissions. Additionally, both studies validate the Webster model, a model that is traditionally used in traffic signal design. Simulations were run to determine the intersection delay, fuel consumption levels, and emissions of hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NO_x), and carbon dioxide (CO₂) of the study intersections. To account for the random nature of traffic, each simulation scenario was run twenty different times. The cycle lengths that minimized the noted simulation outputs were then used to develop the proposed formulations. The new formulations demonstrated its estimated cycle lengths to minimize fuel consumption and emissions were longer than cycle lengths designed to minimize vehicle congestion. Secondly, the simulation results manifested an overestimation in optimum cycle lengths derived from the Webster model for high vehicle traffic.

Light Emitting Diode (LED) is used in traffic signals and highway illumination in the Texas Department of Transportation, Houston District (TxDOT). The thesis focuses on the cost of maintenance of the LED for signals on the highway system in the Houston District. This LED cost includes human and capital resources which are compared against the cost associated with the incandescent bulb used in traffic signals at a similar location in Houston. The analysis leads to actionable decisions to see if total migration of the LED is advisable or not, amidst budgetary constraints and the benefits thereof. / text

Transit Signal Priority (TSP) is an operational strategy that can speed the movement of in-service transit vehicles (typically bus, light rail, or streetcar) through traffic signals. By reducing control delay at signalized intersections, TSP can improve schedule adherence and travel time efficiency while minimizing impacts to normal traffic operations. These benefits improve the quality of service thereby making it more attractive to choice riders. A TSP system can also allow for fewer buses on the same due to travel time reductions and increased reliability, thus reducing transit operating costs. Much of the previous research on TSP has focused on signal control strategies and bus stop placement with little of it analyzing the effectiveness of the system using actual data. This study aims to evaluate the effectiveness of the system using a bus route corridor in Portland, Oregon through real-time Automatic Vehicle Locator data. Key measures that TSP is promoted to improve are evaluated, including travel time, schedule adherence and variability. The TSP system on data was collected for two weeks and is compared to an adjacent two weeks of bus data with the TSP system turned off such that there is no skewing of data due to changes in traffic volumes or transit ridership. This research has shown, that on certain corridors there may be little to no benefit towards TSP implementation and may possibly provide some disbenefit. The direct comparison for TSP on and off scenarios completed for this research yielded no significant differences in reduction in travel time or schedule adherence performance. An additional interesting result was that the standard deviation of the results did not have any specific tendencies with the TSP on or off. Based on these findings, recommendations are made to increase the effectiveness of the system.

New dynamic signal control methods such as fuzzy logic and artificial intelligence developed recently mainly focused on isolated intersection. In this study, a Fuzzy Logic Control for a Diamond Interchange incorporating with Fuzzy Ramp System (FLDI) has been developed. The signalization of two closely spaced intersections in a diamond interchange is a complicated problem that includes both increasing the diamond interchange capacity and reduce delays at the same time. The model comprises of three main modules. The Fuzzy Phase Timing module controls the current phase green time extension, the Phase Selection module select the next phase based on the pre-defined phase sequence or phase logics and the Fuzzy Ramp module determines the cycle time of the ramp meter bases on current traffic volumes and conditions of the interchanges and the motorways. The developed FLDI model has been compared with the traffic actuated simulation with respects to flow rates and the average delays of the vehicles. The model of an actual diamond interchange is described and simulated by using AIMSUN (Advanced Interactive Microscopic Simulator for Urban and Non-Urban Network) software. Simulation results show the FLDI model outperformed the traffic actuated models with lower system total travel time, average delay and improvements in downstream average speed and average delay.

Neue Methoden zur Verkehrsdatenerfassung wie die Fahrzeug-Infrastruktur-Kommunikation, der Floating Car-Ansatz und die Videodetektion eröffnen die Möglichkeit, neue Verfahren zur verkehrsabhängigen Lichtsignalanlagensteuerung zu realisieren. In dem Beitrag wird ein Verfahren beschrieben, das aus diesen Quellen Daten in Form von Fahrzeugverlustzeiten direkt zur Steuerung eines Einzelknotens verwendet. Die robuste Ausgestaltung des Verfahrens sorgt dabei dafür, dass auch mit einer lückenhaften Datenlage, wie z. B. aufgrund geringer Ausstattungsraten kommunikationsfähiger Fahrzeuge, angemessen umgegangen werden kann. Mit Hilfe einer mikroskopischen Simulationsstudie wird nachgewiesen, dass das neue Verfahren bei der Qualität des Verkehrsablaufs das gleiche Niveau wie eine traditionelle Zeitlückensteuerung erreicht oder dieses unter bestimmten Bedingungen sogar übersteigt. Mit abnehmender Ausstattungsrate ergibt sich dabei allerdings ein Qualitätsverlust, der ebenfalls mit Hilfe der mikroskopischen Simulation quantifiziert wird und wichtige Erkenntnisse für einen möglichen Praxistest liefert. / State-of-the-art traffic data sources like Car-to-Infrastructure communication, Floating Car Data and video detection offer great new prospects for vehicle-actuated traffic signal control. Due to this, the article deals with a recent approach which uses vehicles’ delay times for real-time control of traffic signals at an isolated intersection. One of the strengths of the new approach is that it can handle also incomplete data sets, e.g. caused by low penetration rates of vehicles equipped with Car-to-Infrastructure communication technology, in an appropriate manner. Based on a microscopic simulation study the high quality of this innovative approach is demonstrated, which is equal or even outperforms the well-known headway-based control. However, a decreasing penetration rate of equipped vehicles means a reduced quality of signals’ control, which is quantified in the microscopic simulation study, too, and provides useful information for tests in the field.

No description available.

As a result of high crash frequencies on roadways, transportation safety has become a high priority for the United States Department of Transportation and the Utah Department of Transportation. A large percentage of fatal and injury crashes on roadways occur at intersections and traffic signals have been implemented to reduce these severe crashes. There is a need to evaluate the effectiveness of the traffic signal improvements through the development of Crash Modification Factors (CMFs). Recent research has shown that traditional safety evaluation methods have been inadequate in developing CMFs. In recent years, Bayesian statistical methods have been utilized in traffic safety studies to more accurately analyze the effectiveness of safety improvements. The hierarchical Bayesian method is an advanced statistical technique that has the capability to account for the shortcomings of traditional methods and to more fully reflect the effectiveness of safety improvements. This report uses a hierarchical Bayesian model to analyze the effectiveness of new traffic signal installations and modified traffic signals. CMFs were developed for multiple scenarios for both new and modified traffic signals. A benefit-to-cost (B/C) analysis was also performed for each improvement to determine how long it would take to recover the cost of installation. The results showed that there was an increase in overall crashes for both new signal installations and modifications to existing signals. The severe crash analysis revealed that there was an increase in non-severe crashes and a reduction in severe crashes; the improvements are effectively reducing severe crashes and improving safety at intersections. The B/C analyses indicate that there is a safety benefit to both improvements and that new signal installation costs can be recovered in approximately 5 years while the installation of a left-turn signal modification can be recovered in approximately 9 weeks.

Dedicated short-range communication (DSRC) systems, a form of vehicle-to-everything (V2X) systems, were placed on Utah Department of Transportation (UDOT) snowplows to request signal preemption. The study took place along five state routes in the Salt Lake City metropolitan area. Snowplows and intersections were equipped with the technology to communicate and process requests for signal preemption. Signal performance and vehicle performance analysis were performed to understand the impacts that snowplows requesting signal preemption had. Signal performance analysis was done to determine how snowplows with V2X systems using DSRC affected signals. Vehicle performance analysis was done to see if plowing and traffic efficiency and performance were improved, as well as evaluating safety implications of signal preemption. To perform the signal performance analysis, V2X data were collected to understand how often signal preemption was requested by snowplows, how often it was granted by signal controllers, and how long preemption requests affected signal controller timing. Snowplows requested preemption over 50 percent of the time they approached a signalized intersection. Of messages that requested signal preemption, over 80 percent were granted. On average, signal controllers are affected by preemption processing for less than 5 minutes. This shows that the system works as designed, is used often, and does not have adverse effects on signal controller. Data for vehicle performance analysis included analysis of snowplow speed data, general travel speed data, and crash data. These were collected to analyze the effects of snowplows requesting signal preemption on vehicle performance. The analysis showed that snowplow speeds are not changed due to the signal preemption system, but the number of times snowplows stopped was reduced. General travel speeds on equipped routes were more consistently closer to the speed limits than not equipped routes. Crash data showed a greater negative decrease on equipped routes than on not equipped routes. These findings showed minimal changes or impacts to vehicle performance, but anecdotal evidence from snowplow drivers indicates benefits from the system overall. There were various limitations in the analysis. Data granularity differed among datasets, making comparison between the different datasets difficult without reducing data integrity. Some datasets did not have much data, making statistical significance unclear. With these data limitations, conclusions were drawn, but do not fully describe all the potential benefits and impacts of snowplows with V2X systems that use DSRC to request signal preemption. Additional research is needed to better understand the impacts that snowplows requesting signal preemption has on different maintenance metrics, such as fuel usage and time spent plowing. It is also recommended that data used is explored for ways to improve the granularity.