Transit signal priority (TSP) is a popular strategy used to enhance the performance of transit systems by modifying the signal control logic to give transit vehicles priority at signalized intersections. Conventional TSP strategies used in most cities have been shown to offer significant benefits by reducing delay of transit vehicles. However, concerns about shortcomings of conventional TSP strategies have limited their application. The main concern is a potential negative impact on cross street traffic. Another concern is the static nature of conventional TSP strategies and the lack of responsiveness to real-time traffic and transit conditions. A dynamic TSP control system has been developed that can provide signal priority in response to real-time traffic and transit conditions. The dynamic TSP system consists of three main components: a virtual detection system, a dynamic arrival prediction model, and a dynamic TSP algorithm. Two case studies are presented to test and compare the dynamic and the conventional TSP systems. A hypothetical intersection is simulated in the first case study, and a proposed light rail transit line is simulated in the second. For both case studies, a virtual detection system was developed in VISSIM, along with a linear travel time arrival prediction model. Finally, a dynamic TSP algorithm was developed to determine what TSP strategy to use and when to apply it. The results show that the dynamic TSP system reduced the total delay of transit vehicles and outperformed the conventional TSP system for reducing transit trip travel time.
Several unconventional intersection designs have been proposed as an innovative approach to mitigate congestion at heavily congested at-grade signalized intersections. Many of these unconventional designs were shown to outperform conventional intersections in terms of the average control delay and the overall intersection capacity. Little research has been conducted to compare the performance of these unconventional intersections to each other under different volume conditions. This study evaluated and compared the operational performance of four unconventional intersection schemes: the crossover displaced left-turn (XDL), the upstream signalized crossover (USC), the double crossover intersection (DXI) (i.e., half USC), and the median U-turn (MUT). The micro-simulation software VISSIM (PTV Planung Transport Verkehr AG, Karlsruhe, Germany) was used to model and analyze the four unconventional intersections as well as a counterpart conventional one. The results showed that the XDL intersection constantly exhibited the lowest delays at nearly all tested balanced and unbalanced volume levels. The operational performance of both the USC and the DXI was similar in most volume conditions. The MUT design, on the other hand, was unable to accommodate high approach volumes and heavy leftturn traffic. The capacity of the XDL intersection was found to be 99% higher than that of the conventional intersection, whereas the capacity of the USC and the DXI intersections was about 50% higher than that of the conventional intersection. The results of this study can provide guidance on choosing among alternative unconventional designs according to the prevailing traffic conditions at an intersection.
Travel time is a simple and robust network performance measure that is well understood by the public. However, travel time data collection can be costly especially if the analysis area is large. This research proposes a solution to the problem of limited network sensor coverage caused by insufficient sample size of probe vehicles or inadequate numbers of fixed sensors. Within a homogeneous road network, nearby links of similar character are exposed to comparable traffic conditions, and therefore, their travel times are likely to be positively correlated. This correlation can be useful in developing travel time relationships between nearby links so that if data becomes available on a subset of these links, travel times of their neighbours can be estimated. A methodology is proposed to estimate link travel times using available data from neighbouring links. To test the proposed methodology, a case study was undertaken using a VISSIM micro-simulation model of downtown Vancouver. The simulation model was calibrated and validated using field traffic volumes and travel time data. Neighbour links travel time estimation accuracy was assessed using different error measurements and the results were satisfactory. Overall, the results of this research demonstrate the feasibility of using neighbour links data as an additional source of information to estimate travel time, especially in case of limited coverage.Résumé : Le temps de trajet est une mesure simple et robuste du comportement d'un réseau qui est bien comprise par le public. Toutefois, la collecte de données de temps de trajet pour être dispendieuse, particulièrement si la zone à analyser est grande. La présente recherche propose une solution au problème de couverture limitée du capteur de réseau causée par un trop petit nombre de capteurs de véhicules ou un nombre inadéquat de capteurs fixes. Dans un réseau routier homogène, des sections adjacentes ayant des caractéristiques similaires sont exposées à des conditions de circulation comparables et, ainsi, leurs temps de trajet seront probablement corrélés de manière positive. Cette corrélation peut être utile pour établir des relations de temps de trajet entre des sections adjacentes dans le but d'estimer les temps de trajet de leurs voisins si ces données deviennent disponibles pour un sous-ensemble de ces sections. Une méthode est proposée pour estimer les temps de trajet des sections en utilisant les données disponibles à partir de sections avoisinantes. Pour mettre à l'épreuve cette méthode, une étude de cas a été entreprise en utilisant un modèle de micro-simulation VISSIM du centreville de Vancouver. Le modèle de simulation a été étalonné et validé en utilisant des débits de circulation sur le terrain et des données sur les temps de trajet. La précision des estimations des temps de trajet des sections avoisinantes a été évaluée en utilisant différentes mesures d'erreur; les résultats ont été satisfaisants. En général, les résultats de cette recherche dé-montrent la faisabilité d'utiliser des données de sections ...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.