Signal Priority Research Articles

Integrated Optimization of Tram Schedule and Signal Priority at Intersections to Minimize Person Delay

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.

Hybrid Signal Priority and Full Actuation for Isolated Large Four-Leg Circular Intersections

AbstractIn cities with bus rapid transit (BRT) systems, median bus-only lanes (MBLs) may extend to a circular intersection of two arterials. Making the MBLs traverse the central island is advantage...

Novel Method for Increased Power Conservation in Voice over NR (VoNR) devices

With the introduction of 5G New Radio (NR), telecom operators are planning to integrate network elements of NR in different configurations for a phased and overlaid deployment and coexistence with 4G. Third Generation Partnership Project (3GPP) standardizes the deployment operation mode of the next-generation network, viz. working in Stand Alone (SA) NR scenarios and Non-Stand Alone (NSA) NR mode scenarios. As defined in the specification, Option 7 is where UE connects to 5G Core Network (5GCN) via either 4G enhanced Node B (eNB) cell or 5G next-generation NodeB (gNB) cell. The power consumption for a User Equipment (UE) is dependent on the physical resource allocation strategy in the serving cell. Available procedures of system selection defined in 3GPP are based on measurement of reference signal power levels and priority criteria as defined in the System Information of the 5G/4G network. In this paper, we have discussed novel protocol and algorithm through which the UE maintains a history of availability of features like Semi-Persistent Scheduling (SPS), Connected Mode Discontinuous Reception (CDRX) and Voice over NR (VoNR) in the serving area of a cell and uses this information later during system reselection evaluation due to mobility. Through our proposed changes, a UE a) gets VoNR service more often and b) conserve more energy when the user activates VoNR service. We present an analytical model and through simulation show that during VoNR service, power is conserved due to SPS and CDRX on the selected cell.

Demonstrating Transit Schedule Benefits with a Dedicated Short-Range Communication-Based Connected Vehicle System

A vehicle-to-infrastructure (V2I) connected vehicle system was installed along Redwood Road in Salt Lake City, Utah, United States, in November 2017 using dedicated short-range communication (DSRC) radios to connect transit buses to traffic signals. One of the goals of this system was to improve the schedule reliability of the bus by providing signal priority at traffic signals when the bus is behind its published schedule by a certain threshold. Data for the analysis were obtained from the DSRC communications, the Automated Traffic Signal Performance Measures (ATSPM) system, and the transit operations system. The robust data available from these three systems allow for detailed analysis of priority requests made, requests served, and bus on-time performance in a way that is not possible without these data sets. By comparing actual schedules of the four DSRC-equipped buses over a 4-month period from April to July 2018 with buses which do not have the ability to request signal priority, it has been determined that the equipped buses meet their published schedule about 2% to 6% more frequently, depending on direction and time of day, with the most significant improvement of 6% in the southbound PM peak.

Bid-Based Priority Signal Control in a Connected Environment: Concept

Though the loss of time is considered equivalent to opportunity loss, little research has been conducted in the field of signal control that accounts for individual differences in subjective opportunity loss. Because bids reflect the subjective valuation of opportunity loss, this paper introduces the concept of a bid-based priority signal control that accommodates indeterministic characteristics of queue formation in a connected environment and addresses several key elements of such a concept. Within this conception, drivers can bid for their desired signal indication. Based on these bids, an algorithm extends a green interval as long as the cumulative opportunity loss observed in stopped movements remains less than the value that would be lost through the termination of that green interval. The effects of this new type of control on user benefit and queueing delay were assessed using the asymmetric simple exclusion process. Simulation results showed that the bid-based priority signal control produced a greater subjective user benefit when measured in relation to a pre-timed control with a similar green interval. In addition, the bid-based priority signal kept the average maximum queue length relatively equal to its pre-timed equivalent. The bid-based priority signal control also balanced out the expected values of user benefit in conflicting movements. Bid-based signal priority control was recommended for further study to investigate the effects of bidding distributions on effectiveness and queue length in high-fidelity microsimulations.

Estimating the impacts of transit signal priority on intersection operations: A moving bottleneck approach

Transit Signal Priority (TSP) is a commonly used strategy to improve bus operations at signalized intersections. However, the impacts of TSP in mixed traffic environments has not been analytically studied. This is a challenging problem since car queues can slow down buses, while slow-moving buses can create bottlenecks for cars in mixed traffic. Furthermore, it is typically assumed that TSP is activated using bus information obtained from a fixed detector. The benefits of TSP to buses could be improved by using information from connected buses or even connected cars. To tackle these challenges, this paper models buses as moving bottlenecks, incorporating it into a kinematic wave theory (KWT) model. A dynamic programming (DP) algorithm is developed to evaluate the changes in delays to buses and cars caused by TSP using KWT and queuing theories considering the bus as a moving bottleneck. The proposed algorithm is utilized for sensitivity tests to determine the changes to car and bus delays as a result of TSP implementation as a function of the bus detector location, bus stop location and dwell duration, the existence of a downstream bottleneck, and bus detection technology. The detector location sensitivity analysis reveals that there exists an optimal (and different) bus detector location associated with each demand. The bus stop location and bus dwell duration sensitivity tests show that TSP implementation can reduce system-wide (i.e., total car and bus) delays. However, in general, it is found that the presence of a downstream bottleneck can diminish the benefits of providing TSP. Finally, different bus detection technologies are tested to quantify the benefits of using connected buses or connected cars for TSP provision in terms of car and bus delay savings. As a result of this test, it is found that connected cars can significantly improve both car and bus delays if used for TSP provision.

Analysis of Cooperative Bus Priority at Traffic Signals

Transit signal priority (TSP) is an effective strategy to control bus schedule adherence, increase ride comfort, and, in turn, reduce fuel consumption. However, its provision may cause negative externalities on general traffic. In this paper, we demonstrate how coordinated in-vehicle driver advisory systems (DASs) can partly reduce the signal priority control requests. Such cooperative solution, enabled by the connectivity between vehicles and the signal control system, allows combining signal adjustments with dwelling and speed advisories. We show that combining in-vehicle advisory with signal priority can reduce stops at signals, decrease trip time when compared with TSP used alone and, in some case, achieve the same performance without resorting to TSP. In addition, we demonstrate that DASs used alone have marginal impact on trip times, hence can be applied unconditionally. A simulation-based analysis indicates that the effectiveness of a control strategy—or a combination of different strategies—depends on the bus stop placement. When it comes to reduction of stop frequency at traffic signals, speed and dwell time advisories used together deliver similar performance to an unconditional TSP with green signal extensions and recalls lasting up to 10 s.

Traffic signal control by leveraging Cooperative Adaptive Cruise Control (CACC) vehicle platooning capabilities

Vehicles equipped with Cooperative Adaptive Cruise Control (CACC) have the capability to broadcast their real-time speed and location information via wireless communications. They can also safely operate in multi-vehicle strings while keeping shorter than normal gaps among adjacent vehicles in the high-speed traffic stream. Such capabilities can greatly benefit the management of urban signalized intersections. In this study, we have developed a cooperative signal control algorithm that adopts the CACC datasets and the datasets collected by the traditional fixed traffic sensors to predict the future traffic conditions. The prediction allows the signal controller to assign signal priority to the intersection approach that accommodates the most CACC strings. Such a control strategy can significantly enhance the CACC string operation, which ultimately improves the overall intersection performance. The effectiveness of the algorithm has been tested in a simulated 4-way signalized intersection. The algorithm substantially outperforms the traditional actuated controller as it perceives the traffic flow more comprehensively and assigns the green time resource more efficiently than the traditional controller. Particularly, the average vehicle speed and the average vehicle miles travelled per gallon fuel consumed (MPG) can be increased by more than 10% when the CACC market penetration is 100%. In mixed traffic where CACC fleets frequently interact with manually driven vehicles, the algorithm is found to be more beneficial. The speed and MPG improvement exceed 30% when the CACC market penetration is 40%. The signal control algorithm can bring about significant benefit even when the CACC market penetration is 0%. In this case, it completely relies on the datasets obtained from the traditional traffic sensors. This finding demonstrates the robustness of the algorithm. It makes the proposed algorithm suitable to implement in real-world intersections under various CACC market penetrations and different levels of vehicle connectivity.

Continuous and discrete representations of feature-based attentional priority in human frontoparietal network

ABSTRACTPrevious studies suggest that human frontoparietal network represents feature-based attentional priority, yet the precise nature of the priority signals remains unclear. Here, we examined whether priority signals vary continuously or discretely as a function of feature similarity. In an fMRI experiment, we presented two superimposed dot fields moving along two linear directions (leftward and rightward) while varying the angular separation between the two directions. Subjects were cued to attend to one of the two dot fields and respond to a possible speed-up in the cued direction. We used multivariate analysis to evaluate how priority representation of the attended direction changes with feature similarity. We found that in early visual areas as well as posterior intraparietal sulcus and inferior frontal junction, the patterns of neural activity became more different as the feature similarity decreased, indicating a continuous representation of the attended feature. In contrast, patterns of neural activity in anterior intraparietal sulcus and frontal eye field remained invariant to changes in feature similarity, indicating a discrete representation of the attended feature. Such distinct neural coding of attentional priority across the frontoparietal network may make complementary contributions to enable flexible attentional control.

Coordinated Transit Signal Priority Model Considering Stochastic Bus Arrival Time

This paper presents an advanced transit signal priority (ATSP) control model that considers bus progression at downstream intersections when giving priority at upstream intersections and stochastic bus arrival times. The ATSP control model is applicable to arterials with bus lanes. At the center of the ATSP control model is a stochastic programming model formulated to find the optimum priority strategies at each intersection of interest, which minimize bus delays while having the least negative impact on general traffic. The uncertainty in bus arrivals is taken into account by considering stochastic bus dwell times. The ATSP control is implemented in a traffic micro-simulation environment and compared with conventional transit signal priority (CTSP) control. Extensive simulation experiments are conducted with different traffic congestion levels, bus headway levels, and dwell-time distributions. Results show that the ATSP control generates an additional reduction in bus delay of around 10% when compared to the CTSP control.

A Bi-Level Model to Resolve Conflicting Transit Priority Requests at Urban Arterials

Conflicting transit signal priority (TSP) requests can significantly influence the efficiency of TSP. Determining the best serve sequence for TSP requests is important for both the transit and other vehicles. The majority of previous studies focused on resolving conflicting TSP requests at the intersection level. For urban arterials, few studies take coordination into consideration, so the benefits of TSP may be lost due to the lack of progression. In view of this, this paper proposes a bi-level optimization model to resolve the problem of conflicting TSP requests at arterial corridors. The upper level of the model is progression control and the lower level is intersection control. At the progression control level, by considering the characteristics of bus operation, this paper proposes a signal coordination method that generates a green band between the two adjacent bus stops (stop-to-stop). At the intersection control level, a linear programming model is developed to resolve conflicting TSP requests. Then, this paper uses a hybrid genetic algorithm to solve the proposed model. Finally, an arterial with seven intersections in Nanjing, China, is selected to evaluate the performance of the proposed model. Three other models (the baseline model without TSP, Model 1 with the regular TSP and the classical coordination, and Model 2 with the lower model and the classical coordination) are also utilized to conduct the comparison analysis. The results show the proposed model can significantly reduce the bus passenger delay and stops compared to the three other models and meanwhile the operation of other vehicles will not turn worse.

Novel Design Method for Bus Approach Lanes with Bus Guidance and Priority Controls for Prioritizing Through and Left-Turn Buses

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.

Neural correlates of attentional capture by stimuli previously associated with social reward

ABSTRACTOur attention is strongly influenced by reward learning. Stimuli previously associated with monetary reward have been shown to automatically capture attention in both behavioral and neurophysiological studies. Stimuli previously associated with positive social feedback similarly capture attention; however, it is unknown whether such social facilitation of attention relies on similar or dissociable neural systems. Here, we used the value-driven attentional capture paradigm in an fMRI study to identify the neural correlates of attention to stimuli previously associated with social reward. The results reveal learning-dependent priority signals in the contralateral visual cortex, posterior parietal cortex, and caudate tail, similar to studies using monetary reward. An additional priority signal was consistently evident in the right middle frontal gyrus (MFG). Our findings support the notion of a common neural mechanism for directing attention on the basis of selection history that generalizes across different types of reward.

Automatic generation of entity-oriented summaries for reputation management

Producing online reputation summaries for an entity (company, brand, etc.) is a focused summarization task with a distinctive feature: issues that may affect the reputation of the entity take priority in the summary. In this paper we (i) present a new test collection of manually created (abstractive and extractive) reputation reports which summarize tweet streams for 31 companies in the banking and automobile domains; (ii) propose a novel methodology to evaluate summaries in the context of online reputation monitoring, which profits from an analogy between reputation reports and the problem of diversity in search; and (iii) provide empirical evidence that producing reputation reports is different from a standard summarization problem, and incorporating priority signals is essential to address the task effectively.

Effect of transit signal priority on bus service reliability

As every user knows buses tend to bunch. To alleviate this problem, transit agencies introduce slack into their schedules and then hold buses back to schedule at pre-established control points along their routes. Unfortunately, this practice retards buses and only works with low frequency systems; i.e., when the headways are long. For higher frequency systems, which effectively operate without a schedule, headway-based control strategies show promise but unfortunately, they also retard buses. To alleviate bus retardation in all its forms, transit signal priority (TSP) is commonly used. Curiously however, the potential of TSP to enhance bus control practices has not been explored in detail.This paper evaluates a form of TSP designed for this purpose. In this version of TSP, which we call conditional signal priority (CSP), buses send priority requests only when the requests improve reliability. The evaluation includes both scheduled (low frequency) systems, and unscheduled (high frequency) systems operated by headways. A mathematical model based on Brownian motion is proposed for the former. This model allows us to optimize the CSP strategy and to develop formulas for the expectation and variance of the steady state deviations from the schedule–with CSP, with conventional TSP and with neither. Simulations confirm the accuracy of these findings. It is found that CSP improves reliability considerably and that it is better for traffic than TSP because it reduces the number of priority requests. For high frequency systems operated with a fixed number of buses CSP is shown to not just improve reliability and reduce the number of priority requests of TSP (by about 50%) but also to reduce the average headway by speeding up the buses.

Effect of Transit Signal Priority on Bus Service Reliability

Abstract As every user knows buses tend to bunch. To alleviate this problem, transit agencies introduce slack into their schedules and then hold buses back to schedule at pre-established control points along their routes. Unfortunately, this practice retards buses and only works with low frequency systems; i.e., when the headways are long. For higher frequency systems, which effectively operate without a schedule, headway-based control strategies show promise but unfortunately, they also retard buses. To alleviate bus retardation in all its forms, transit signal priority (TSP) is commonly used. Curiously however, the potential of TSP to enhance bus control practices has not been explored in detail. This paper evaluates a form of TSP designed for this purpose. In this version of TSP, which we call conditional signal priority (CSP), buses send priority requests only when the requests improve reliability. The evaluation includes both scheduled (low frequency) systems, and unscheduled (high frequency) systems operated by headways. A mathematical model based on Brownian motion is proposed for the former. This model allows us to optimize the CSP strategy and to develop formulas for the expectation and variance of the steady state deviations from the schedule-with CSP, with conventional TSP and with neither. Simulations confirm the accuracy of these findings. It is found that CSP improves reliability considerably and that it is better for traffic than TSP because it reduces the number of priority requests. For high frequency systems operated with a fixed number of buses CSP is shown to not just improve reliability and reduce the number of priority requests of TSP (by about 50%) but also to reduce the average headway by speeding up the buses. This paper has been accepted for a podium presentation at the 23rd International Symposium on Transportation and Traffic Theory (ISTTT23) July 24-26, 2019 in Lausanne, CH.

Variable Signal Progression Bands for Transit Vehicles Under Dwell Time Uncertainty and Traffic Queues

Signal priority controls have long been viewed as one of the viable strategies to minimize bus delays at intersections so as to reduce the travel time variability or increase headway stability. Such control strategies, however, are often not effective for arterials serving heavy bus flows, because frequent signal priority calls will inevitably disrupt the arterial signal plan and incur excessive delays to general traffic. To overcome such deficiencies, this paper presents a bus-based signal progression model for arterials with heavy bus flows as in most major cities in Asia and Europe. The proposed model features its properties of accounting for the impacts of average bus dwell time, its variance, and the bus stop capacity. The impacts of various upstream traffic flow rates and signal plans on the available bus progression band have also been included in computing the optimal bus-progression offsets. Extensive simulation experiments have confirmed the effectiveness of the computed bus progression bands under various traffic congestion levels. The proposed bus-based pre-timed signal system can serve as a base plan for real-time operations of priority control for bus progression if the congestion level on the arterial or dwelling time variance as well as traffic queues have exceeded the operational capacity of the bus-based progression system.

Transit Priority Signal Control Scheme Considering the Coordinated Phase for Single-Ring Sequential Phasing Under Connected Vehicle Environment

Real-time transit signal priority (TSP) controls is affected by coordination phase and deprive non-transit traffic benefits. In this paper, fully considering the migration states of coordinated phases and queuing states of non-transit vehicles, a transit signal priority controlling method is proposed for the single-ring sequential phasing under the connected vehicle (CV) environment. The queue length of the non-transit phase is estimated using real-time parking position of the probe vehicles in CV environment, and then the compression capability of phase can be confirmed. Under the premise of not destroying the green waveband of the intersection group, three models are proposed, including the green time extension, red time truncation, and phase insertion models. In the proposed model, the maximum priority effect and the minimum time deviations for the non-transit phase are taken as the optimization object. The maximum/minimum green time, total cycle length, and the backward/forward migration time of coordinated phases are taken as the constraints. Through the analysis of experimental results with examples, the transit priority control model proposed in this paper effectively improves the transit priority efficiency, and minimizes the impact on the non-transit traffic benefits while considering the coordinated phase state and not destroying the coordination effect.

Timetable Optimization for a Two-Way Tram Line With an Active Signal Priority Strategy

Modern trams typically run along semi-exclusive right-of-way. Although tram lanes isolate trams from other traffic in the running sections, the operation process will be affected by signal control. To improve the service quality of trams and reduce the negative impact on intersections caused by bidirectional priority requests, we propose a timetable optimization method for a single two-way tram line based on active transit signal priority strategy. Combining with the characteristics of bidirectional signal priority strategy, trams can pass through the intersections without stopping by adjusting the running times and dwell times. A multiobjective optimization model of a tram timetable is established to minimize the total travel time, dwell time increment, and negative effect of the signal priority strategy. For obtaining a timetable with equal satisfaction for the three objectives, we adopt the fuzzy mathematical programming approach to transform the problems into mixed integer linear programming (MILP) problems, which can be solved by using standard solvers. The case study of Nanjing Qilin Tram Line 1 shows that the timetable optimization method designed in this paper can effectively improve the service efficiency of trams, and reduce the negative impact of the signal priority strategy on social vehicles. These empirical findings can give us some useful insights on the optimum design of tram timetable.

Bus Priority Control for Dynamic Exclusive Bus Lane

One problem with the existing dynamic exclusive bus lane strategies is that bus signal priority strategies with multi-phase priority request at intersections are not adequately considered. The principle of bus signal priority... | Find, read and cite all the research you need on Tech Science Press