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1
Lee, Jinwoo, Amer Shalaby, John Greenough, Mike Bowie, and Stanley Hung. "Advanced Transit Signal Priority Control with Online Microsimulation-Based Transit Prediction Model." Transportation Research Record: Journal of the Transportation Research Board 1925, no. 1 (2005): 185–94. http://dx.doi.org/10.1177/0361198105192500119.
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An advanced transit signal priority (TSP) control method is presented: it provides priority operation in response to real-time traffic and transit conditions. A high-performance online microscopic simulation model was developed for the purpose of predicting transit travel time along an intersection approach. The proposed method was evaluated through application to a hypothetical intersection with a nearside bus stop. The performance of the proposed method was compared with that of normal signal operation without TSP and a conventional signal priority method. The experimental results indicated that the developed method provided efficient and effective priority operation for both transit vehicles and automobiles. The proposed method significantly reduced transit vehicle delays as well as side-street traffic delay compared with conventional active priority control.
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Lin, Ciyun, and Bowen Gong. "Transit-Based Emergency Evacuation with Transit Signal Priority in Sudden-Onset Disaster." Discrete Dynamics in Nature and Society 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/3625342.
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This study presents methods of transit signal priority without transit-only lanes for a transit-based emergency evacuation in a sudden-onset disaster. Arterial priority signal coordination is optimized when a traffic signal control system provides priority signals for transit vehicles along an evacuation route. Transit signal priority is determined by “transit vehicle arrival time estimation,” “queuing vehicle dissipation time estimation,” “traffic signal status estimation,” “transit signal optimization,” and “arterial traffic signal coordination for transit vehicle in evacuation route.” It takes advantage of the large capacities of transit vehicles, reduces the evacuation time, and evacuates as many evacuees as possible. The proposed methods were tested on a simulation platform with Paramics V6.0. To evaluate and compare the performance of transit signal priority, three scenarios were simulated in the simulator. The results indicate that the methods of this study can reduce the travel times of transit vehicles along an evacuation route by 13% and 10%, improve the standard deviation of travel time by 16% and 46%, and decrease the average person delay at a signalized intersection by 22% and 17% when the traffic flow saturation along an evacuation route is0.8<V/C≤1.0andV/C>1.0, respectively.
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Isukapati, Isaac K., Hana Rudová, Gregory J. Barlow, and Stephen F. Smith. "Analysis of Trends in Data on Transit Bus Dwell Times." Transportation Research Record: Journal of the Transportation Research Board 2619, no. 1 (2017): 64–74. http://dx.doi.org/10.3141/2619-07.
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Transit vehicles create special challenges for urban traffic signal control. Signal timing plans are typically designed for the flow of passenger vehicles, but transit vehicles—with frequent stops and uncertain dwell times—may have different flow patterns that fail to match those plans. Transit vehicles stopping on urban streets can also restrict or block other traffic on the road. This situation results in increased overall wait times and delays throughout the system for transit vehicles and other traffic. Transit signal priority (TSP) systems are often used to mitigate some of these issues, primarily by addressing delay to the transit vehicles. However, existing TSP strategies give unconditional priority to transit vehicles, exacerbating quality of service for other modes. In networks for which transit vehicles have significant effects on traffic congestion, particularly urban areas, the use of more-realistic models of transit behavior in adaptive traffic signal control could reduce delay for all modes. Estimating the arrival time of a transit vehicle at an intersection requires an accurate model of dwell times at transit stops. As a first step toward developing a model for predicting bus arrival times, this paper analyzes trends in automatic vehicle location data collected over 2 years and allows several inferences to be drawn about the statistical nature of dwell times, particularly for use in real-time control and TSP. On the basis of this trend analysis, the authors argue that an effective predictive dwell time distribution model must treat independent variables as random or stochastic regressors.
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Wang, Ding, Wenxin Qiao, and Chunfu Shao. "Relieving the Impact of Transit Signal Priority on Passenger Cars through a Bilevel Model." Journal of Advanced Transportation 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/7696094.
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Transit signal priority (TSP) is an effective control strategy to improve transit operations on the urban network. However, the TSP may sacrifice the right-of-way of vehicles from side streets which have only few transit vehicles; therefore, how to minimize the negative impact of TSP strategy on the side streets is an important issue to be addressed. Concerning the typical mixed-traffic flow pattern and heavy transit volume in China, a bilevel model is proposed in this paper: the upper-level model focused on minimizing the vehicle delay in the nonpriority direction while ensuring acceptable delay variation in transit priority direction, and the lower-level model aimed at minimizing the average passenger delay in the entire intersection. The parameters which will affect the efficiency of the bilevel model have been analyzed based on a hypothetical intersection. Finally, a real-world intersection has been studied, and the average vehicle delay in the nonpriority direction decreased 11.28 s and 22.54 s (under different delay variation constraint) compared to the models that only minimize average passenger delay, while the vehicle delay in the priority direction increased only 1.37 s and 2.87 s; the results proved the practical applicability and efficiency of the proposed bilevel model.
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Zhou, Guangwei, and Albert Gan. "Performance of Transit Signal Priority with Queue Jumper Lanes." Transportation Research Record: Journal of the Transportation Research Board 1925, no. 1 (2005): 265–71. http://dx.doi.org/10.1177/0361198105192500127.
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Queue jumper lanes are a special type of bus preferential treatment that allows buses to bypass a waiting queue through a right-turn bay and then cut out in front of the queue by getting an early green signal. The performance of queue jumper lanes is evaluated under different transit signal priority (TSP) strategies, traffic volumes, bus volumes, dwell times, and bus stop and detector locations. Four TSP strategies are considered: green extension, red truncation, phase skip, and phase insertion. It was found that queue jumper lanes without TSP were ineffective in reducing bus delay. Queue jumper lanes with TSP strategies that include a phase insertion were found to be more effective in reducing bus delay while also improving general vehicle operations than those strategies that do not include this treatment. Nearside bus stops upstream of check-in detectors were preferred for jumper TSP over farside bus stops and nearside bus stops downstream of check-in detectors. Through vehicles on the bus approach were found to have only a slight impact on bus delay when the volume-to-capacity (v/c) ratio was below 0.9. However, when v/c exceeded 0.9, bus delay increased quickly. Right-turn volumes were found to have an insignificant impact on average bus delay, and an optimal detector location that minimizes bus delay under local conditions was shown to exist.
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Duerr, Peter A. "Dynamic Right-of-Way for Transit Vehicles: Integrated Modeling Approach for Optimizing Signal Control on Mixed Traffic Arterials." Transportation Research Record: Journal of the Transportation Research Board 1731, no. 1 (2000): 31–39. http://dx.doi.org/10.3141/1731-05.
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Public transit and general traffic on many urban arterials are controlled by the same set of signals and must compete for shared road space. In these situations, transit vehicles typically face considerable delays because their dwell times at transit stops remove them from the coordinated green wave for general traffic flow. Although existing control systems allow for local adjustments of signal timings to provide transit priority, these short-term actions often contradict the network control scheme and may preclude a priority scheme or significantly disrupt traffic flow. A new concept for a corridor control system is introduced—the dynamic right-of-way, which serves the demands of public transit and general traffic using an integrated model for evaluation and optimization. The control system is intended to ( a) reduce critical interferences between both modes of transport by dynamically controlling inflow and outflow for all network links, ( b) provide a green signal whenever a transit vehicle approaches an intersection, and ( c) minimize general traffic disruption by maintaining overall signal coordination. Through linking an event-based simulator with a genetic algorithm-based optimization routine, delay-minimizing multicycle signal control schemes are calculated. In offline experiments, the potential for achieving substantial reductions in delays is demonstrated. Finally, a method is presented by which these control schemes are implemented and adjusted dynamically, based on online measurements and a control modification function derived from a neural network model.
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Shu, Shijie, Jing Zhao, and Yin Han. "Signal Timing Optimization for Transit Priority at Near-Saturated Intersections." Journal of Advanced Transportation 2018 (July 11, 2018): 1–14. http://dx.doi.org/10.1155/2018/8502804.
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Transit signal priority is a useful way to improve transit operations in urban networks. Most of the existing studies have been conducted in conditions with low saturation to avoid the detrimental effects of vehicles without priority. However, from the public transit point of view, it is more meaningful to assign transit signal priority when the degree of the saturation intersections is high. This study proposes a signal control model for transit signal priority to minimize the overall delay at near-saturated intersection. The delay increment is calculated in three scenarios for buses and private vehicles according to the dissipation time of the vehicular queue. A set of constrains are set up to avoid queue overflows and to ensure the rationalization of the signal timing. The proposed control model is tested based on a case study and numerical experiments. The results show that the proposed model can reduce the total person delay at near-saturated intersections. The length of priority time, degree of saturation, and number of lanes are the three main influencing factors. More than 6% reductions in person delay can be obtained for undersaturated intersections when the priority time is less than 5 s. Moreover, even when the intersection saturation is 0.95, the bus signal priority can be applied if only the priority time is less than 5 s.
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Gao, Liu Yi, Xiao Jian Hu, Wei Wang, and Shan Shan Yu. "Development and Evaluation of a Green Wave Control Algorithm Based on Two-Way Bandwidth Maximization for Transit Signal Priority." Applied Mechanics and Materials 505-506 (January 2014): 1046–54. http://dx.doi.org/10.4028/www.scientific.net/amm.505-506.1046.
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A good traffic signal design is one of the key solutions to many transportation problems. A two-way green wave control strategy for transit signal priority is reviewed and evaluated in this paper. Considering the traffic tidal phenomenon along the arterial roads during rush hours, a directional transit signal priority algorithm depend on the passenger flow has been developed for the coordination in signalized intersections. The algorithm provides signal timing plans for each intersection and the optimal bus speed along each section based on two-way bandwidth maximization. The strategy was designed to provide sectional control on transits, using electric signs and existing traffic control devices. In this paper, the strategys efficiency was evaluated using VISSIM micro-simulation along an arterial road which contains five intersections and serves more than ten bus lines. Actual data was used in the simulation. The simulation results show that the presented algorithm can effectively improve the operation efficiency of the transit system. This green wave control strategy reduced the number of stops by 34 % to 47 % and travel delay time by 27 % to 30% of the transit, while restricting the impact on vehicular traffic to the minimum. Moreover, the number of stops and travel delay time of vehicular traffic actually got a slight decrease. The algorithm shows promising results, and with minor upgrades, it can be applied to any type of intersection.
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Li, Rui, Changjiang Zheng, and Wenquan Li. "Optimization Model of Transit Signal Priority Control for Intersection and Downstream Bus Stop." Mathematical Problems in Engineering 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/9487190.
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Transit signal priority has a positive effect on improving traffic condition and level of transit service in the urban area. In this paper, a passenger-based transit signal priority (TSP) optimization model is formulated to optimize intersection signal phasing based on minimizing accessibility-based passenger delay at the intersection and increased waiting-delay at the downstream bus stop simultaneously. Genetic Algorithm is utilized to calculate passenger-based optimization model that is calibrated by evening rush hour actual traffic data (17:30–18:30, October 13th–October 15th, 2015) along Shuiximen Boulevard in Nanjing, China. The performance of the proposed optimization model in decreasing delay and improving system reliability is simulated and evaluated by VISSIM-based simulation platform, and the results illustrate that the proposed optimization model presents promising outcomes in decreasing accessibility-based passenger delay at intersection (average reduction of 12%) and passenger waiting-delay at downstream bus service stop (average reduction of 18%) compared with traditional vehicle-based TSP optimization method in rush hour.
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Ghanim, Mohammad S., Francois Dion, and Ghassan Abu-Lebdeh. "The impact of dwell time variability on transit signal priority performance." Canadian Journal of Civil Engineering 41, no. 2 (2014): 154–63. http://dx.doi.org/10.1139/cjce-2012-0306.
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Transit signal priority (TSP) is an operational control strategy that provides preferential treatments for transit vehicles at signalized intersections. Many transit agencies are currently considering the implementation of priority systems providing buses with preferential treatments at signalized intersections. While studies have demonstrated potential bus delay reductions, none has attempted to identify the problems posed by variable dwell times at bus stops. This study identifies the impacts of variable dwell times on the efficiency of transit signal priority systems. Results also show that, in general, variable dwell times negatively affect the TSP performance. However, and contrary to expectations, a number of scenarios with variable dwell times resulted in lower average bus delays than scenarios with fixed dwell times. These results are attributed to changes in progression and bus arrival patterns under variable dwell times resulting in an increasing number of buses arriving close enough to benefit from preferential treatments.
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Ji, Yanjie, Bo Hu, Jing Han, and Dounan Tang. "An Improved Algebraic Method for Transit Signal Priority Scheme and Its Impact on Traffic Emission." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/412132.
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Transit signal priority has a positive effect on improving traffic congestion and reducing transit delay and also has an influence on traffic emission. In this paper, an optimal transit signal priority scheme based on an improved algebraic method was developed and its impact on vehicle emission was evaluated as well. The improved algebraic method was proposed on the basis of classical algebraic method and has improvements in three aspects. First, the calculation rules of split loss are more reasonable. Second, the delay caused by transit stations and queued vehicles can be considered. Third, measures for finding optimal ideal intersection interval are improved. By establishing a microscopic traffic emission simulation platform based on microscopic traffic simulation model VISSIM and the comprehensive modal emission model (CMEM), the traffic emissions can be evaluated. Then, an optimal transit signal priority scheme based on the traffic data collected in Changzhou city was developed and its impact on emission was simulated in the VISSIM-CMEM platform. Comparative analysis results showed that proposed scheme can outperform original scheme in the aspects of reducing emission and passenger delay and an average reduction of 25.0% on transit emission and relative decrease in overall traffic emission can be achieved.
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Bin, Lv. "Modeling of Signal Plans for Transit Signal Priority at Isolated Intersections under Stochastic Condition." Mathematical Problems in Engineering 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/650242.
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Transit signal priority (TSP) is recognized as having the potential to improve transit service reliability at small cost to general traffic. The popular preference for TSP encounters the challenges of various and challenging test scenarios. According to the stochastic characteristics of traffic flow, the signal timing model was established for TSP at an isolated signal intersection, where the passenger average delay was used as the optimization objective, and the weights of all phases were considered. The priority logic that is considered in the study provides cycle length and green time within a fixed-time traffic signal control environment. Using the Gauss elimination, the quantitative relationships were determined between phase clearance reliability (PCR), cycle length, and green time. Simulation experiments conducted by the particle swarm optimization (PSO) algorithm indicated that (1) the random variation of arrival rate has an obvious effect on traffic signal settings; (2) the proposed TSP model can reduce passenger delays, especially under stochastic traffic flow.
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Delgado, Felipe, Juan Carlos Muñoz, Ricardo Giesen, and Nigel H. M. Wilson. "Integrated Real-Time Transit Signal Priority Control for High-Frequency Segregated Transit Services." Transportation Research Record: Journal of the Transportation Research Board 2533, no. 1 (2015): 28–38. http://dx.doi.org/10.3141/2533-04.
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Bus bunching affects transit operations by increasing passenger waiting time and variability. To tackle this phenomenon, a wide range of control strategies has been proposed. However, none of them have considered station and interstation control together. In this study station and interstation control were tackled to determine the optimal vehicle control strategy for various stops and traffic lights in a single service transit corridor. The strategy minimized the total time that users must devote to making a trip, taking into account delays for transit and general traffic users. Based on a high-frequency, capacity-constrained, and unscheduled service (no timetable) for which real-time information about bus position (GPS) and bus load (automated passenger counter) is available, this study focused on strategies for traffic signal priority in the form of green extension considered together with holding buses at stops and limiting passenger boarding at stops. The decisions on transit signal priority were made according to a rolling horizon scheme in which effects over the whole corridor were considered in every single decision. The proposed strategy was evaluated in a simulated environment under different operational conditions. Results showed that the proposed control strategy achieves reductions in the excess delay for transit users close to 61.4% compared with no control, while general traffic increases only by 1.5%.
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Han, Xu, Pengfei Li, Rajib Sikder, Zhijun (Tony) Qiu, and Amy Kim. "Development and Evaluation of Adaptive Transit Signal Priority Control with Updated Transit Delay Model." Transportation Research Record: Journal of the Transportation Research Board 2438, no. 1 (2014): 45–54. http://dx.doi.org/10.3141/2438-05.
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Lai, Xiongfei, Jing Teng, Paul Schonfeld, and Lu Ling. "Resilient Schedule Coordination for a Bus Transit Corridor." Journal of Advanced Transportation 2020 (June 15, 2020): 1–12. http://dx.doi.org/10.1155/2020/5398298.
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Providing convenient transit services at reasonable cost is important for transit agencies. Timed transfers that schedule vehicles from various routes to arrive at some transfer stations simultaneously (or nearly so) can significantly reduce wait times in transit networks, while stochastic passenger flows and complex operating environments may reduce this improvement. Although transit priority methods have been applied in some high-density cities, operating delays may cause priority failures. This paper proposes a resilient schedule coordination method for a bus transit corridor, which analyzes link travel time, passenger loading delay, and priority signal intersection delay. It maximizes resilience based on realistic passenger flow volume, whether or not transit priority is provided. The data accuracy and result validity are improved with automatically collected data from multiple bus routes in a corridor. The Yan’an Road transit corridor in Shanghai is used as a case study. The results show that the proposed method can increase the system resilience by balancing operation cost and passenger-based cost. It also provides a guideline for realistic bus schedule coordination.
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Hao, Yanxi, Jing Teng, Yinsong Wang, and Xiaoguang Yang. "Increasing Capacity of Intersections with Transit Priority." PROMET - Traffic&Transportation 28, no. 6 (2016): 627–37. http://dx.doi.org/10.7307/ptt.v28i6.1999.
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Dedicated bus lane (DBL) and transit signal priority (TSP) are two effective and low-cost ways of improving the reliability of transits. However, these strategies reduce the capacity of general traffic. This paper presents an integrated optimization (IO) model to improve the performance of intersections with dedicated bus lanes. The IO model integrated geometry layout, main-signal timing, pre-signal timing and transit priority. The optimization problem is formulated as a Mix-Integer-Non-Linear-Program (MINLP) that can be transformed into a Mix-Integer-Linear-Program (MILP) and then solved by the standard branch-and-bound technique. The applicability of the IO model is tested through numerical experiment under different intersection layouts and traffic demands. A VISSIM micro simulation model was developed and used to evaluate the performance of the proposed IO model. The test results indicate that the proposed model can increase the capacity and reduce the delay of general traffic when providing priority to buses.
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Wu, Kan, and S. Ilgin Guler. "Optimizing Transit Signal Priority Implementation along an Arterial." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 20 (2018): 215–27. http://dx.doi.org/10.1177/0361198118790324.
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Transit signal priority (TSP) is a common method of providing priority to buses at signalized intersections. The implementation of TSP can affect travel time of cars traveling in the same, opposite, and cross directions. The bus delay savings and car travel-time impacts are not expected to increase linearly when considering multiple intersections along an arterial. This paper quantifies the influence of TSP on arterials with dedicated bus lanes considering an arterial-wide approach utilizing variational theory. Existing tools were modified to quantify the change in capacity along an arterial where TSP was implemented and it was shown that this effect was negligible. In addition, the bus delay savings and cross-street capacity losses were determined. Case studies provided insights into the influence of TSP among different network homogeneities and bus frequencies. Using these tools, an optimization framework was developed to determine where to implement TSP along an arterial to maximize the marginal benefits, or minimize marginal costs. In addition, a comparison of evaluating an arterial as a sum of isolated intersections as opposed to evaluating an arterial as a whole is presented. This analysis indicates the necessity of the arterial-based method in considering TSP impacts along corridors.
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Marnell, Patrick, Paul Zebell, Peter Koonce, and Shaun Quayle. "Evaluating Transit Priority Signal Phasing at Most Multimodal Intersection in Portland, Oregon." Transportation Research Record: Journal of the Transportation Research Board 2619, no. 1 (2017): 44–54. http://dx.doi.org/10.3141/2619-05.
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This research documents the operational benefits of additional phases, barrier bars, and a call-based transit priority signal-phasing strategy over a more traditional eight-phase, two-barrier preemption-based transit signal–phasing strategy. The call-based timing strategy, with a more flexible ring-and-barrier structure, takes advantage of additional phases to run less-impactful transit prioritization for light-rail trains. These two strategies have been field implemented in Portland, Oregon, at the signalized intersection of Southwest Porter Street and Southwest Moody Avenue, an intersection that has distinct signalized movements for the private-automobile, streetcar, light-rail train, bus, pedestrian, and bicycle modes. The operations of the two-intersection signal-phasing strategies were evaluated and tested by using hardware and software-in-the-loop microsimulation (in Vissim) to isolate the expected change in operational efficiency in modal delay. The two-barrier preemption-based transit signal-phasing strategy showed high variability in delay for certain movements, in particular, pedestrians. The call-based phasing strategy with flexible ring-and-barrier structure reduced total and average intersection delay. This research shows that the call-based phasing strategy with flexible ring-and-barrier structure can provide a less disruptive transit prioritization. Agencies should consider the call-phased transit priority strategy over the more traditional preemption-based strategy at a signalized intersection when ( a) delaying potential preemptive movements mode will not have large safety effects, ( b) pedestrian demand is high, ( c) preemption service will be frequent, or ( d) the intersection is operating at or over capacity.
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Li, Rui, Peter J. Jin, and Bin Ran. "Biobjective Optimization and Evaluation for Transit Signal Priority Strategies at Bus Stop-to-Stop Segment." Mathematical Problems in Engineering 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/1054570.
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This paper proposes a new optimization framework for the transit signal priority strategies in terms of green extension, red truncation, and phase insertion at the stop-to-stop segment of bus lines. The optimization objective is to minimize both passenger delay and the deviation from bus schedule simultaneously. The objective functions are defined with respect to the segment between bus stops, which can include the adjacent signalized intersections and downstream bus stops. The transit priority signal timing is optimized by using a biobjective optimization framework considering both the total delay at a segment and the delay deviation from the arrival schedules at bus stops. The proposed framework is evaluated using a VISSIM model calibrated with field traffic volume and traffic signal data of Caochangmen Boulevard in Nanjing, China. The optimized TSP-based phasing plans result in the reduced delay and improved reliability, compared with the non-TSP scenario under the different traffic flow conditions in the morning peak hour. The evaluation results indicate the promising performance of the proposed optimization framework in reducing the passenger delay and improving the bus schedule adherence for the urban transit system.
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Kwong, Ivan, Mehdi Nourinejad, and Amer Shalaby. "Existing Problems of Transit Signal Priority on Streetcar Routes." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 10 (2020): 861–73. http://dx.doi.org/10.1177/0361198120937310.
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Transit signal priority (TSP) is a traffic control strategy that gives priority to transit vehicles by adjusting intersection signals in real time. The technology is implemented in many major cities and has proved to benefit transit routes in reducing the overall passenger travel time. Unfortunately, there are several problems with TSP that are commonly ignored. These problems are predominantly operational, such as misjudgment of the arrival time at the intersection and insensitivity to the TSP activation time. It is worsened with streetcars, which have shorter headways and thus are more prone to bunching delays. In this paper, five delay problems that streetcars experience are identified. Data are collected from a TSP-equipped intersection in the City of Toronto to provide a statistical analysis of the issues. It was found that 25.8% of times, TSP is inadequate at prioritizing public transit. From the problems raised, the most frequent one is the late arrival of a streetcar during a green interval, representing 72.5% of TSP issue cases. It was also found that TSP has a bias toward different failure cases, and favors early arrivals to the intersection. Several remedies for the defined issues are recommended. The suggestions include implementing green truncations, avoiding late TSP activation in each cycle, and introducing a prediction-based TSP system.
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Shu, Shijie, Jing Zhao, and Yin Han. "Novel Design Method for Bus Approach Lanes with Bus Guidance and Priority Controls for Prioritizing Through and Left-Turn Buses." Journal of Advanced Transportation 2019 (March 6, 2019): 1–15. http://dx.doi.org/10.1155/2019/2327876.
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Transit priority is a useful way of improving transit operations in urban networks. However, the through and left-turn buses are rarely prioritized simultaneously at isolated intersections in the existing studies. This paper presents a variable bus approach lane design with a bus guidance and priority control model, which can reduce the delay of both the through and left-turn buses. The variable bus approach lanes can be dynamically used for the through and left-turn buses during the various periods of a signal cycle by the integrated design of geometric layouts and signal timing. A detailed bus guidance and priority control optimization model is formulated to guide the buses entering the appropriate bus approach lanes, and it provides optimal signal priorities for buses. The effectiveness of the proposed method is validated by a case study and numerical experiments. The results show that, on average, the total passenger delay can be reduced by 5% for every 30 veh/h and 40 veh/h increase in the volume of through buses and left-turn buses, respectively. Moreover, a comparison between the proposed method and the conventional transit priority method reveals that significant improvements can be made in reducing delays using the proposed method even at intersections with high degree of the saturation.
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Cesme, Burak, Selman Z. Altun, and Barrett Lane. "Queue Jump Lane, Transit Signal Priority, and Stop Location Evaluation of Transit Preferential Treatments Using Microsimulation." Transportation Research Record: Journal of the Transportation Research Board 2533, no. 1 (2015): 39–49. http://dx.doi.org/10.3141/2533-05.
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Transit preferential treatments offer the potential to improve transit travel time and reliability. However, the benefits of these treatments vary greatly depending on the specific characteristics of the study area, including turning movement and pedestrian volumes, signal timing parameters, and transit stop location. To evaluate the performance of preferential treatments, practitioners typically rely on microscopic simulation models, which require a considerable amount of effort, or a review of previous studies, which may reflect a bias toward the area characteristics. This paper develops a test bed and a planning-level framework to help practitioners determine benefits offered by various preferential treatments without developing a detailed simulation model. To evaluate preferential treatment benefits, the authors performed extensive simulation runs under various scenarios at an isolated intersection with VISSIM. The analyses show that the greatest benefit comes from relocating a nearside stop to a farside stop, in which farside stops can reduce delay up to 30 s per intersection. The highest saving that could be obtained with a queue jump lane is approximately 9 s per intersection. As the number of right turns increases along with the number of conflicting pedestrians, the benefit of a queue jump lane disappears. Transit signal priority with 15 s of green extension and red truncation can offer up to 19 s of reduction in delay; the benefits become more pronounced with a high volume-to-capacity (v/c) ratio. With a low v/c ratio, granting 10 s of green extension without red truncation provides very marginal benefits; only a 2-s delay reduction per intersection is gained.
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Hua, Xuedong, Wei Wang, Yinhai Wang, and Ziyuan Pu. "OPTIMIZING PHASE COMPRESSION FOR TRANSIT SIGNAL PRIORITY AT ISOLATED INTERSECTIONS." TRANSPORT 32, no. 4 (2017): 386–97. http://dx.doi.org/10.3846/16484142.2017.1345787.
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Transit signal priority (TSP) is a promising low-cost strategy that gives preferential treatments for the buses to go through intersections with minimum delay time. In this paper, a new TSP control model was presented for isolated intersections to minimize bus delay and to reduce the impact of TSP on other vehicles by optimizing signal control phase selection and compression. This paper starts with the phase selection and compression strategies to provide treatments to bus priority requests. Then, two new features on phase selection and compression aspects are applied to TSP, i.e. the time that a bus priority request needs is provided by the phase(s) with the lowest traffic volume, and multi-phases can be selected to serve a bus request. Field data are collected from a major traffic corridor in Changzhou (China) and applied for VISSIM simulation. The proposed TSP control model as well as the fixed-time control and the conventional TSP control models are tested and compared under different traffic demands, headways and maximum saturation degrees. The comparative results showed that the proposed model outperformed the conventional TSP control model in terms of reducing bus delay, minimizing the impact on other vehicles and reducing the stop rate for buses. This paper reveals that, the proposed TSP strategy can significantly optimize the phase compression process and improve transit efficiency.
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Kaufmann, P., P. L. Kaufmann, S. V. D. Pamboukian, and R. Vilhena de Moraes. "Signal Transceiver Transit Times and Propagation Delay Corrections for Ranging and Georeferencing Applications." Mathematical Problems in Engineering 2012 (2012): 1–15. http://dx.doi.org/10.1155/2012/595823.
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The accuracy of ranging measurements depends critically on the knowledge of time delays undergone by signals when retransmitted by a remote transponder and due to propagation effects. A new method determines these delays for every single pulsed signal transmission. It utilizes four ground-based reference stations, synchronized in time and installed at well-known geodesic coordinates and a repeater in space, carried by a satellite, balloon, aircraft, and so forth. Signal transmitted by one of the reference bases is retransmitted by the transponder, received back by the four bases, producing four ranging measurements which are processed to determine uniquely the time delays undergone in every retransmission process. A minimization function is derived comparing repeater’s positions referred to at least two groups of three reference bases, providing the signal transit time at the repeater and propagation delays, providing the correct repeater position. The method is applicable to the transponder platform positioning and navigation, time synchronization of remote clocks, and location of targets. The algorithm has been demonstrated by simulations adopting a practical example with the transponder carried by an aircraft moving over bases on the ground.
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Xianmin, Song, Yuan Mili, Liang Di, and Ma Lin. "Optimization Method for Transit Signal Priority considering Multirequest under Connected Vehicle Environment." Journal of Advanced Transportation 2018 (June 26, 2018): 1–10. http://dx.doi.org/10.1155/2018/7498594.
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Aiming at reducing per person delay, this paper presents an optimization method for Transit Signal Priority (TSP) considering multirequest under connected vehicle environment, which is based on the travel time prediction model. Conventional arrival time of transit depended on the detection information and the front road state, which restricted the effect of priority seriously. According to the bidirectional and real-time information transmission under connected vehicle environment, this paper establishes a more accurate forecasting model of bus travel time. Based on minimizing the total person delay at the intersection, the decision mechanism of multirequest is devised to meet the priority needs of buses with different arrival times. And the green time compensation algorithm is developed after considering the arrival information of the buses in the next cycle of compensational phase. Finally, the paper combines the COM interface of VISSIM and Matlab to achieve the proposed method under connected vehicle environment. Four control methods were tested when the VCR was 0.5, 0.7, and 0.9. The results illustrated that the proposed method reduced per person delay by 18.57%, 11.88%, and 18.96% and decreased the private vehicle delay by 3.73%, 7.62%, and 13.10%, respectively.
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Gao, Liu Yi, Xiao Jian Hu, Wei Wang, and Xue Dong Hua. "A Study of an Adaptive Two-Phrase Signal Control Strategy for Resolving Conflicting Transit Signal Priority Calls." Applied Mechanics and Materials 505-506 (January 2014): 1028–36. http://dx.doi.org/10.4028/www.scientific.net/amm.505-506.1028.
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This paper presents the development and evaluation of an adaptive two-phrase signal control strategy to resolve conflicting Transit Signal Priority (TSP) requests. The strategy was designed to provide adaptive transit signal priority control, using vehicle systems and existing traffic control devices. In this paper, the strategys efficiency was tested using a micro-simulation software VISSIM and build one arterial road contains five intersections and serves more than twenty conflicting bus lines. The VAP module was used to control TSP of conflicting requests. In the simulation, actual data was used. Finally, control efficiency about adaptive signal control strategy is discussed. The results show that the presented strategy can improve the operation efficiency of bus corporations. This signal control strategy reduced the travel delay time by 33 % to 55% of transit, while has little impact on private traffic. The strategy shows promising results. In addition, with minor upgrades, it can be applied to any type of intersection.
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Wu, Kan, S. Ilgin Guler, and Vikash V. Gayah. "Estimating the Impacts of Bus Stops and Transit Signal Priority on Intersection Operations: Queuing and Variational Theory Approach." Transportation Research Record: Journal of the Transportation Research Board 2622, no. 1 (2017): 70–83. http://dx.doi.org/10.3141/2622-07.
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Transit signal priority (TSP) can be used to improve bus operations at signalized intersections, often to the detriment of general car traffic. However, the impacts of TSP treatments applied to intersections with nearby bus stop locations are currently unknown. This paper quantifies changes in intersection capacity, car delay, and bus delay when priority is provided to buses that dwell at near- or farside bus stop locations through green extension or red truncation. Variational and kinematic wave theories are used to estimate car capacity and bus delay for oversaturated traffic conditions; queuing theory is used to estimate car and bus delays for undersaturated conditions. Numerical analyses are conducted to explore the impacts on various bus stop locations and bus dwell time durations. These results illustrate clear trade-offs between reduced bus delays and increased car delays or reduced intersection capacities that can be quantified with the proposed method. The results also reveal that the effects of TSP vary dramatically with bus dwell times for a given bus stop location. The proposed method and associated results can be used to implement TSP strategies to meet the specific needs of local agencies.
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Yang, Hairong, and Dayong Luo. "Acyclic Real-Time Traffic Signal Control Based on a Genetic Algorithm." Cybernetics and Information Technologies 13, no. 3 (2013): 111–23. http://dx.doi.org/10.2478/cait-2013-0029.
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Abstract This paper presents an acyclic real-time traffic signal control model with transit priority based on a rolling horizon process for isolated intersections. The developed model consists of two components, including: an Improved Genetic Algorithm (IGA)-based signal optimization module and a microscopic traffic simulation module. The acyclic real-time traffic signal control model optimizes the phase sequence and the phase length with the aim to minimize the total delay of both transit vehicles and general vehicles for the next decision horizon. Numerical results show that the proposed IGA signal optimization module could provide a more efficient search for optimal solutions. The results also show that the acyclic real-time traffic signal control model outperforms the fixed-time control model. It prioritizes transit vehicles while minimizing the impact on the general vehicles.
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Yang, Min, Gang Sun, Wei Wang, Xin Sun, Jian Ding, and Jing Han. "Evaluation of the pre-detective signal priority for bus rapid transit: coordinating the primary and secondary intersections." Transport 33, no. 1 (2015): 41–51. http://dx.doi.org/10.3846/16484142.2015.1004556.
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Since the traditional transit priority strategy can only adjust signal timing in a limited range and is not suitable for all kinds of signal timing designs, it cannot provide enough priority for Bus Rapid Transit (BRT). In addition, traditional transit priority strategy has caused serious interferences with other traffic. This study proposes a pre-detective signal priority strategy for BRT with coordination between primary and secondary intersections. By pre-detecting, the time buses arrive at the primary intersection, the signal timing of both the primary and secondary intersections, along with the offsets, are adjusted simultaneously, based on the common length and the green ratio of each phase. In this method, the signal cycle constraints are clarified, and the bus control coordination between intersections has been taken into consideration. In this paper, one direction traffic is taken as a study example to testify the effectiveness of this method. The study uses the data collected from Changzhou, China, and a microscopic traffic simulation software PTV VISSIM with four simulation scenarios defined: no signal priority, traditional signal priority, pre-detective signal priority and pre-detective signal priority with coordination. This paper selects a set of indicators to evaluate the traffic operation for both public transit and private traffic. Results show that pre-detective signal priority with coordination is the most effective, with the total bus intersection delay decreases by 67.4% and the bus headway adherence declines by approximately 40% at all the primary and secondary stations of BRT line 1. Moreover, the negative effects that could happen with providing signal priority for BRT, such as increasing the delay and length of queue of private traffic at the intersections, are significantly reduced.
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Truong, Long T., Graham Currie, Mark Wallace, and Chris De Gruyter. "Does Combining Transit Signal Priority with Dedicated Bus Lanes or Queue Jump Lanes at Multiple Intersections Create Multiplier Effects?" Transportation Research Record: Journal of the Transportation Research Board 2647, no. 1 (2017): 80–92. http://dx.doi.org/10.3141/2647-10.
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An extensive body of literature deals with the design and operation of public transport (PT) priority measures. However, there is a need to understand whether providing transit signal priority with dedicated bus lanes (TSPwDBL) or transit signal priority with queue jump lanes (TSPwQJL) at multiple intersections creates a multiplier effect on PT benefits. If the benefit from providing priority together at multiple intersections is greater than the sum of benefits from providing priority separately at each of those individual intersections, a multiplier effect exists. This paper explores the effects of providing TSPwDBL or TSPwQJL at multiple intersections on bus delay savings and person delay savings. Simulation results reveal that providing TSPwDBL or TSPwQJL at multiple intersections may create a multiplier effect on one-directional bus delay savings, particularly when signal offsets provide bus progression for that direction. The multiplier effect may result in a 5% to 8% increase in bus delay savings for each additional intersection with TSPwDBL or TSPwQJL. A possible explanation is that TSPwDBL and TSPwQJL can reduce the variations in bus travel times and thus allow signal offsets—which account for bus progression—to perform even better. Furthermore, results show little evidence of the existence of a multiplier effect on person delay savings, particularly for TSPwQJL with offsets that favor person delay savings. A policy implication of these findings is that considerable PT benefits can be achieved by providing both time and space priority in combination on a corridorwide scale.
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Li, Ning, Shukai Chen, Jianjun Zhu, and Daniel Jian Sun. "A Platoon-Based Adaptive Signal Control Method with Connected Vehicle Technology." Computational Intelligence and Neuroscience 2020 (June 1, 2020): 1–10. http://dx.doi.org/10.1155/2020/2764576.
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One important objective of urban traffic signal control is to reduce individual delay and improve safety for travelers in both private car and public bus transit. To achieve signal control optimization from the perspective of all users, this paper proposes a platoon-based adaptive signal control (PASC) strategy to provide multimodal signal control based on the online connected vehicle (CV) information. By introducing unified phase precedence constraints, PASC strategy is not restricted by fixed cycle length and offsets. A mixed-integer linear programming (MILP) model is proposed to optimize signal timings in a real-time manner, with platoon arrival and discharge dynamics at stop line modeled as constraints. Based on the individual passenger occupancy, the objective function aims at minimizing total personal delay for both buses and automobiles. With the communication between signals, PASC achieves to provide implicit coordination for the signalized arterials. Simulation results by VISSIM microsimulation indicate that PASC model successfully reduces around 40% bus passenger delay and 10% automobile delay, respectively, compared with signal timings optimized by SYNCHRO. Results from sensitivity analysis demonstrate that the model performance is not sensitive to the number fluctuation of bus passengers, and the requested CV penetration rate range is around 20% for the implementation.
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Wang, Q. L. "Studies on the Technology and Application of Transit Signal Priority on Exclusive Line." Applied Mechanics and Materials 743 (March 2015): 774–79. http://dx.doi.org/10.4028/www.scientific.net/amm.743.774.
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Bus priority is the effective methods of reducing traffic jam in large and medium-sized cities. Application and assessment of bus signal priority is studied, bus signal priority whole scheme is put forward based on GPS pointing and intelligent dispatch by investigating the situation of No.36 bus waiting time at stops and intersections. Based on Zigbee active request bus signal priority, dataflow process under local request and central request is analyzed, the principle of bus signal priority on balanced distance headway is put forward, and adjustment of key features parameters realized combining with SCATS traffic signal control system. The application assessment shows that, there are average 651 priority requests and 286 priority buses every day, priority efficiency is 43.9%.The average speed of No.36 bus increased 15.8%, the delay time reduced 13.2%, the stopping times reduced 27%, the twice stop situation at intersections basically disappeared, average delay at each intersection increased 3%.
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Yang, Zhao Sheng, Chun Lin Tian, and Song Nan Liu. "A Signal Priority Algorithm for BRT Based on Intersection Resource Integration." Applied Mechanics and Materials 253-255 (December 2012): 1396–400. http://dx.doi.org/10.4028/www.scientific.net/amm.253-255.1396.
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Real-time scheduling and signal priority strategies play a critical role in improving the service quality of Bus Rapid Transit (BRT) system. The delays of public passengers and social vehicles are essential factors that should be considered for signal priority control. This paper proposes a signal priority algorithm for BRT based on intersection resource integration from the angle of intersection time and space combinatorial optimization, which combined optimize lane functional partitioning and green ratio allocation. The results of the data validation proves that the optimization model can significantly reduce the BRT vehicle delay at the intersection, while reducing the adverse effects of social vehicles.
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Zhou, Wen, Yun Bai, Jiajie Li, Yuhe Zhou, and Tang Li. "Integrated Optimization of Tram Schedule and Signal Priority at Intersections to Minimize Person Delay." Journal of Advanced Transportation 2019 (July 18, 2019): 1–18. http://dx.doi.org/10.1155/2019/4802967.
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Modern trams, as a rapidly developed high-volume transport model, have strict requirements on schedule, because the delay will reduce the attractiveness of public transportation to passengers. To improve punctuality and reliability, Transit Signal Priority (TSP) has been employed at intersections, which can extend or insert green phase to trams. However, extending or inserting the green phase for every tram might lead to heavy delays to crossing vehicles. To address this problem, this study developed an integrated optimization model on tram schedule and signal priority which can balance the delay between trams and other vehicles to minimize person delay. Three conditional strategies named early green, green extension, and phase insertion are proposed for the signal priority. Simultaneously, arrival time, departure time of trams at stations, and stop line are optimized as well. The proposed model is tested with a numerical case and a real-world case at Ningbo tramline in China. The results indicate that the integrated optimization can reduce the average delay of all passengers on trams and other vehicles, compared to timetable optimization only and TSP only. It is also found that the proposed model is able to adapt to the fluctuation in the ratio of tram passenger to auto vehicle user, compared with only minimizing tram passenger delay or auto vehicle user delay.
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Alsop, D. C., and J. A. Detre. "Reduced Transit-Time Sensitivity in Noninvasive Magnetic Resonance Imaging of Human Cerebral Blood Flow." Journal of Cerebral Blood Flow & Metabolism 16, no. 6 (1996): 1236–49. http://dx.doi.org/10.1097/00004647-199611000-00019.
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Herein, we present a theoretical framework and experimental methods to more accurately account for transit effects in quantitative human perfusion imaging using endogenous magnetic resonance imaging (MRI) contrast. The theoretical transit time sensitivities of both continuous and pulsed inversion spin tagging experiments are demonstrated. We propose introducing a delay following continuous labeling, and demonstrate theoretically that introduction of a delay dramatically reduces the transit time sensitivity of perfusion imaging. The effects of magnetization transfer saturation on this modified continuous labeling experiment are also derived, and the assumption that the perfusion signal resides entirely within tissue rather than the arterial microvasculature is examined. We present results demonstrating the implementation of the continuous tagging experiment with delay on an echoplanar scanner for measuring cerebral blood flow (CBF) in normal volunteers. By varying the delay, we estimate transit times in the arterial system, values that are necessary for assessing the accuracy of our quantification. The effect of uncertainties in the transit time from the tagging plane to the arterial microvasculature and the transit time to the tissue itself on the accuracy of perfusion quantification is discussed and found to be small in gray matter but still potentially significant in white matter. A novel method for measuring T1, which is fast, insensitive to contamination by cerebrospinal fluid, and compatible with the application of magnetization transfer saturation, is also presented. The methods are combined to produce quantitative maps of resting and hypercarbic CBF.
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Gao, Qian, Shuyang Zhang, Guojun Chen, and Yuchuan Du. "Two-Way Cooperative Priority Control of Bus Transit with Stop Capacity Constraint." Sustainability 12, no. 4 (2020): 1405. http://dx.doi.org/10.3390/su12041405.
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Signal priority control and speed guidance are effective ways to reduce the delay of buses at intersections. Previous work generally focused on the optimization strategy at the intersection area, without simultaneously considering the influence on adjacent downstream bus stops. This probably leads to the size of the passed bus platoon exceeding the capacity of berths and queuing, which in turn causes additional delay to the overall bus travel time. Focusing on this problem, this paper proposes a two-way cooperative control strategy that constrains the size of the upstream platoon. Besides this, to avoid bus bunching, no more than two buses from the same route can be admitted in the same platoon. Based on these principles, we modeled how to make buses pass without stopping by simultaneously considering the signal control and speed guidance. Finally, the effectiveness was validated by simulation in Verkehr in Städten Simulation (VISSIM, German for “Traffic in cities—simulation”), a microscopic traffic simulator. The results show that compared to the existing methods, which only use signal control, the cooperative strategy reduces the total delay at the intersection and the downstream stop. It alleviates the queuing phenomenon at the downstream bus stop greatly, and the bus arrivals tend to be more uniform, which helps improve the reliability and sustainability of bus services.
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Abdy, Zeeshan R., and Bruce R. Hellinga. "Analytical Method for Estimating the Impact of Transit Signal Priority on Vehicle Delay." Journal of Transportation Engineering 137, no. 8 (2011): 589–600. http://dx.doi.org/10.1061/(asce)te.1943-5436.0000242.
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Liou, J. J., and H. Shakouri. "Collector signal delay time and collector transit time of HBTs including velocity overshoot." Solid-State Electronics 35, no. 1 (1992): 15–19. http://dx.doi.org/10.1016/0038-1101(92)90297-p.
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Devitt, Graham, Mahmood Mahmoodi Nesheli, Ehab Diab, and Amer Shalaby. "Empirical Performance Analysis of Bus Speed and Delay at Intersections for Emerging Spot Improvement Programs." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 3 (2020): 57–68. http://dx.doi.org/10.1177/0361198120909108.
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Many North American cities are increasingly interested in implementing small-scale localized spot treatments to surface routes as a simpler approach than top-down, disruptive route change, or redesign. This research seeks to support the identification of effective spot treatments at intersections using a systematic, data-driven approach. By analyzing key bus performance indicators in Toronto, this study developed insights into factors affecting peak-period bus speeds and delays at the segment and intersection levels for a wide variety of route and intersection configurations across eight high-frequency routes. Candidate treatments were then identified to improve bus performance. Data were sourced from the automatic vehicle location system, general transit feed specification, and a specialized ride check and GPS survey. Features of the approaches of 100 signalized intersections along the study routes were analyzed using K-means clustering, ordinary least squares regression, and regression trees, with target variables as their morning and evening peak operating speeds, segment-level delays, and signal delays. The results showed that long signal split is a significant contributor to higher operating speeds and lower delays, suggesting signal timing adjustments are an effective treatment. Clustering analysis suggested turning restrictions, particularly for right turns at intersections with near-side stops, could be effective, since turning volumes of similarly configured intersections were lower at locations with better transit performance. Regression analyses showed that queue jump lanes are an effective treatment if signal timing plans cannot be adjusted. The results from this study are intended to assist in informing transit authorities wishing to implement future spot improvement programs.
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Gu, Tian Hong, and Hui Jian Cao. "Research on the Improved Algorithm of Transit Signal Priority Based on Bi-Objective Optimization Model." Applied Mechanics and Materials 380-384 (August 2013): 1641–44. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1641.
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Optimization of adaptive traffic signal timing is one of the most complex problems in traffic control systems. In order to obtain control parameters of transit signal priority of the urban roads, a bi-objective optimization model for signal timing is established. The delay and stop times as the goal of optimization are calculated respectively. And the corresponding constraint condition is built. The method can optimize green splits and offset at the urban arterial road. A VISSIM simulation was developed to evaluate the performance of the proposed bi-objective optimization model. The results show that the optimizer can produce TSP timing plans that benefit the transit vehicles while minimizing the impact of TSP on the general vehicles.
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Gu, Tian Hong, and Hui Jian Cao. "Research on Calculating the Parameters of Signal Timing for TSP Based on Enumeration Method." Advanced Materials Research 756-759 (September 2013): 3094–98. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.3094.
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It is of importance to calculate the parameters of signal timing for TSP (Transit Signal Priority). However, most studies computing the delay are provided based on formula of triangle area. With communication technology developing precisely calculating the delay time of buses can be achieved. The kernel algorithm of TSP still has room for improvement. In this paper, the algorithmic flow of the most of functions is presented based on Enumeration Method.Meanwhile the study uses the VISSIM simulation model to evaluate the impact of a number of alternative priority strategies on both the prioritized buses and general traffic. The priority logic that is considered in the study provides signal timing parameters within a real-time traffic signal control environment. A case study was conducted to validate the model results. Simulation results shows that this method effectively reduces average delay time of the travelers.
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Bayrak, Murat, and S. Ilgin Guler. "Determining Optimum Transit Signal Priority Implementation Locations on a Network." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 10 (2020): 387–400. http://dx.doi.org/10.1177/0361198120934792.
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Transit signal priority (TSP) can be used to improve bus operations at intersections. However, implementing TSP can often increase the delay of non-transit modes. Therefore, it is necessary to evaluate the effects of TSP both on car and bus operations to determine optimal locations to equip with TSP to improve network operations. To do so, the link transmission model is used to evaluate the travel times of both cars and buses on the network while accounting for dynamic queuing and queue spillover. This method is then used to evaluate different combinations of locations for TSP implementation and to determine the optimal configuration that can minimize the total travel time of network users, including bus and car passengers. The sensitivity of the proposed algorithm to demand level, changes in transit network, implementation strategy, and solution method are also evaluated. For all tested scenarios, the TSP configurations found to be optimum achieve a significant reduction of total bus passenger travel time while creating minimal effect on total car travel time. The results reveal that in general, not all intersections should be equipped with TSP, and intersections that carry high demand within a network are promising locations for TSP implementation to reduce the total travel time of network users. Additionally, it is found that the total travel time of network users can be further decreased by only activating TSP for buses with more than a certain number of on-board passengers.
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Bhuiyan, Mohammad Zahidul H., and Elena Simona Lohan. "Advanced Multipath Mitigation Techniques for Satellite-Based Positioning Applications." International Journal of Navigation and Observation 2010 (December 9, 2010): 1–15. http://dx.doi.org/10.1155/2010/412393.
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Multipath remains a dominant source of ranging errors in Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS) or the future European satellite navigation system Galileo. Multipath is generally considered undesirable in the context of GNSS, since the reception of multipath can make significant distortion to the shape of the correlation function used for time delay estimation. However, some wireless communications techniques exploit multipath in order to provide signal diversity though in GNSS, the major challenge is to effectively mitigate the multipath, since we are interested only in the satellite-receiver transit time offset of the Line-Of-Sight (LOS) signal for the receiver's position estimate. Therefore, the multipath problem has been approached from several directions in order to mitigate the impact of multipath on navigation receivers, including the development of novel signal processing techniques. In this paper, we propose a maximum likelihood-based technique, namely, the Reduced Search Space Maximum Likelihood (RSSML) delay estimator, which is capable of mitigating the multipath effects reasonably well at the expense of increased complexity. The proposed RSSML attempts to compensate the multipath error contribution by performing a nonlinear curve fit on the input correlation function, which finds a perfect match from a set of ideal reference correlation functions with certain amplitude(s), phase(s), and delay(s) of the multipath signal. It also incorporates a threshold-based peak detection method, which eventually reduces the code-delay search space significantly. However, the downfall of RSSML is the memory requirement which it uses to store the reference correlation functions. The multipath performance of other delay-tracking methods previously studied for Binary Phase Shift Keying-(BPSK-) and Sine Binary Offset Carrier- (SinBOC-) modulated signals is also analyzed in closed loop model with the new Composite BOC (CBOC) modulation chosen for Galileo E1 signal. The simulation results show that the RSSML achieves the best multipath mitigation performance in a uniformly distributed two-to-four paths Rayleigh fading channel model for all three modulated signals.
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Beak, Byungho, Mehdi Zamanipour, K. Larry Head, and Blaine Leonard. "Peer-to-Peer Priority Signal Control Strategy in a Connected Vehicle Environment." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 18 (2018): 15–26. http://dx.doi.org/10.1177/0361198118773567.
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This paper presents a methodology that enhances the priority signal control model in the multi-modal intelligent traffic signal system (MMITSS). To overcome the range limit of vehicle to infrastructure (V2I) and the intersection geometry message (MAP) distance limits, peer-to-peer intersection communications are utilized to send priority requests from adjacent intersections. Through integrated communication, the peer priority control strategy can create a signal plan for prioritized vehicles that considers longer term (headway) arrival times. Transit vehicles are considered in this study. The longer-term signal plan provides a flexible signal schedule that allows local phase actuation. The peer priority strategy is effective in reducing the number of stops and delay for priority eligible vehicles, while minimizing the negative impact on regular vehicles. To validate the strategy, a simulation experiment was designed to compare fully actuated control, coordination, and MMITSS priority control using two different VISSIM simulation networks (Arizona and Utah). The result shows that the peer-to-peer long term planning strategy can improve transit service reliability while limiting the adverse impact on other traffic.
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Fülöp, R. H., A. T. Codilean, K. M. Wilcken, et al. "Million-year lag times in a post-orogenic sediment conveyor." Science Advances 6, no. 25 (2020): eaaz8845. http://dx.doi.org/10.1126/sciadv.aaz8845.
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Understanding how sediment transport and storage will delay, attenuate, and even erase the erosional signal of tectonic and climatic forcings has bearing on our ability to read and interpret the geologic record effectively. Here, we estimate sediment transit times in Australia’s largest river system, the Murray-Darling basin, by measuring downstream changes in cosmogenic 26Al/10Be/14C ratios in modern river sediment. Results show that the sediments have experienced multiple episodes of burial and reexposure, with cumulative lag times exceeding 1 Ma in the downstream reaches of the Murray and Darling rivers. Combined with low sediment supply rates and old sediment blanketing the landscape, we posit that sediment recycling in the Murray-Darling is an important and ongoing process that will substantially delay and alter signals of external environmental forcing transmitted from the sediment’s hinterland.
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Martin, Layla, Michael Wittmann, and Xinyu Li. "The Influence of Public Transport Delays on Mobility on Demand Services." Electronics 10, no. 4 (2021): 379. http://dx.doi.org/10.3390/electronics10040379.
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Demand for different modes of transportation clearly interacts. If public transit is delayed or out of service, customers might use mobility on demand (MoD), including taxi and carsharing for their trip, or discard the trip altogether, including a first and last mile that might otherwise be covered by MoD. For operators of taxi and carsharing services, as well as dispatching agencies, understanding increasing demand, and changing demand patterns due to outages and delays is important, as a more precise demand prediction allows for them to more profitably operate. For public authorities, it is paramount to understand this interaction when regulating transportation services. We investigate the interaction between public transit delays and demand for carsharing and taxi, as measured by the fraction of demand variance that can be explained by delays and the changing OD-patterns. A descriptive analysis of the public transit data set yields that delays and MoD demand both highly depend on the weekday and time of day, as well as the location within the city, and that delays in the city and in consecutive time intervals are correlated. Thus, demand variations must by corrected for these external influences. We find that demand for taxi and carsharing increases if the delay of public transit increases and this effect is stronger for taxi. Delays can explain at least 4.1% (carsharing) and 18.8% (taxi) of the demand variance, which is a good result when considering that other influencing factors, such as time of day or weather exert stronger influences. Further, planned public transit outages significantly change OD-patterns of taxi and carsharing.
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Hall, Randolph W., and Nilesh Vyas. "Buses as a Traffic Probe: Demonstration Project." Transportation Research Record: Journal of the Transportation Research Board 1731, no. 1 (2000): 96–103. http://dx.doi.org/10.3141/1731-12.
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The congestion probe feature of the Orange County Transportation Authority (California) bus probe project was evaluated by comparing automobile and bus trajectories and examining alternative congestion detection methods. The focus was city streets on which delays occur at signalized intersections and bus delays at bus stops. The analysis revealed that when automobiles have long delays, buses traveling nearby on the same route are also likely to be delayed. The reverse situation, however, is not always true, because buses frequently wait for extended periods when they run ahead of schedule. Any useful bus probe algorithm needs to distinguish between actual congestion and a stopping delay. Although the transit probe was designed to measure congestion on roadway segments, a more useful approach would be to measure congestion approaching major intersections, where delays are likely to occur. Moreover, because delays randomly fluctuate according to a vehicle’s arrival time relative to the signal cycle, the most sensible approach is to set off a "congestion alarm" when a vehicle is delayed by more than one cycle at an intersection. A congestion alarm would indicate oversaturation and delay well above normal.
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Zhou, Haosheng, and D. L. Pulfrey. "Computation of transit and signal delay times for the collector depletion region of GaAs-based HBTs." Solid-State Electronics 35, no. 1 (1992): 113–15. http://dx.doi.org/10.1016/0038-1101(92)90312-z.
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Mutsaerts, Henri JMM, Jan Petr, Lena Václavů, et al. "The spatial coefficient of variation in arterial spin labeling cerebral blood flow images." Journal of Cerebral Blood Flow & Metabolism 37, no. 9 (2017): 3184–92. http://dx.doi.org/10.1177/0271678x16683690.
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Macro-vascular artifacts are a common arterial spin labeling (ASL) finding in populations with prolonged arterial transit time (ATT) and result in vascular regions with spuriously increased cerebral blood flow (CBF) and tissue regions with spuriously decreased CBF. This study investigates whether there is an association between the spatial signal distribution of a single post-label delay ASL CBF image and ATT. In 186 elderly with hypertension (46% male, 77.4 ± 2.5 years), we evaluated associations between the spatial coefficient of variation (CoV) of a CBF image and ATT. The spatial CoV and ATT metrics were subsequently evaluated with respect to their associations with age and sex – two demographics known to influence perfusion. Bland–Altman plots showed that spatial CoV predicted ATT with a maximum relative error of 7.6%. Spatial CoV was associated with age (β = 0.163, p = 0.028) and sex (β = −0.204, p = 0.004). The spatial distribution of the ASL signal on a standard CBF image can be used to infer between-participant ATT differences. In the absence of ATT mapping, the spatial CoV may be useful for the clinical interpretation of ASL in patients with cerebrovascular pathology that leads to prolonged transit of the ASL signal to tissue.
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Chang, James, John Collura, François Dion, and Hesham Rakha. "Evaluation of Service Reliability Impacts of Traffic Signal Priority Strategies for Bus Transit." Transportation Research Record: Journal of the Transportation Research Board 1841, no. 1 (2003): 23–31. http://dx.doi.org/10.3141/1841-03.
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Recent progress in technology has facilitated the design, testing, and deployment of traffic signal priority strategies for transit buses. However, a clear consensus has not emerged about the evaluation of these strategies. Each agency implementing these strategies can have differing goals, and there are often conflicting issues, needs, and concerns among the various stakeholders. To assist in the evaluation of such strategies an evaluation framework and plan was developed that provides a systematic method to assess potential impacts. The use of this framework and plan is illustrated on the Columbia Pike corridor in Arlington, Virginia, with the use of the INTEGRATION simulation package. In building on previous efforts on this corridor, the work presents a method of simulating conditional priority to late buses to investigate the impacts of priority on service reliability. By using the measures developed in this research, a conditional priority strategy designed to increase bus service reliability without resulting in severe traffic-related impacts was tested. Simulation results indicated statistically significant improvements of 3.2% in bus service reliability and 0.9% for bus efficiency, whereas negative traffic-related impacts were found in the form of increased overall delay to the corridor of 1.0% on a vehicle basis or 0.6% on a person basis. These results are also comparable and consistent with the results of other research.