Signal Priority Research Articles

An integrated intersection design for promoting bus and car traffic

Signal priority and exclusive bus lanes are common measures used to promote bus travel at signalized intersections. However, these bus priority measures create significant damage to the car traffic especially at intersections with heavy bus and car traffic. For this reason, bus priority is not welcome at busy intersections. We examine a novel intersection approach design that can solve the above dilemma. The design integrates a bus lane, bus signal priority, and a midblock pre-signal for sorting different car traffic streams in tandem in the approach. Car capacity gains from the use of pre-signal can potentially recover the car capacity lost to bus lane and signal priority schemes. This paper first presents how the pre-signal and main signal can be timed to realize bus signal priority, and where the pre-signal should be placed. Models are then formulated for estimating the expected bus delay and car capacity under the integrated design. They are compared against three alternative designs, including a conventional intersection design without bus priority or pre-signal. Numerical results unveil that the integrated design produces not only significant bus delay savings, but also higher car capacities in most instances. Even greater car capacity gains are observed with higher bus frequencies. Moreover, the benefits are fairly robust when real-world operating features, such as bus arrival time prediction error, are considered. Thus, the integrated design can potentially promote both bus and car traffic at congested intersections.

Identification of Affecting Factors on the Travel Time Reliability for Bus Transportation

Public bus transit travel time is affected by many factors, including traffic signals and traffic condition. Transit agencies have implemented transit signal priority (TSP) strategies to reduce transit travel time and improve service reliability. However, due to the lack of empirical data, these factors' collective impact and bus travel time strategies have not been studied at the stop-to-stop segment level. This research focuses on the factors affecting travel time reliability, emphasising the variability between operators and the policy implications of such differences. One-way analysis of variance (ANOVA) statistical methods have been used to assess the quality implications of public bus transportation time reliability. This research seeks to investigate the factors affecting the travel time (TT) reliability of bus transport. Studies were conducted along three bus routes serving different areas. Factors strongly related to TT reliability include route length, number of signalised intersections, day of the week, bus stops, departure delays, bus lane, passenger boarding and alighting, weather condition, and fare structure. Based on the proposed model factors affecting TT reliability, it was found that TT is strongly affected by the number of bus stoppings and also the length of the route. The reliability of all three routes during the weekday is low because of delays in departure. The number of signalised intersections along the route affects reliability. Meanwhile, more passengers boarding and paying cash increased the travel time reliability of buses.

Bus Rapid Transit System Introduction in Johor Bahru: A Simulation-Based Assessment

Bus rapid transit (BRT) is one of the strategies to promote improvements in urban mobility. In this study, BRT scenarios, which integrate exclusive bus lanes and bus priority signal control in mixed traffic scenarios, were modelled using a VISSIM microsimulation. Three scenarios of BRT were modelled to represent 16:84, 38:62 and 54:46 modal splits between public transport and private vehicles. It was found that Scenario 4 (the 54:46 scenario) offers better benefits in terms of delay time saving and economic benefits. In general, it was found that the BRT system enhances the functioning of the transport system and provides people with faster and better mobility facilities, resulting in attractive social and economic benefits, especially on a higher modal split of public transport. It is regarded as one strategy to alleviate traffic congestion and reduce dependency on private vehicles. The finding of this study provides an insight on the effective concept of the BRT system, which may promote the dissemination of an urban mobility solution in the city. The results can help policymakers and local authorities in the management of a transport network in order to ensure reliable and sustainable transport.

Eco-Driving of Freight Vehicles With Signal Priority on Congested Arterial Roads

This paper investigates a cooperative optimization framework of eco-driving and signal priority for freight vehicles in signalized arterial road. Considering the congestion of passenger vehicles at the signalized intersections, the problem is modeled as a multi-stage mixed integer optimization problem containing continuous variables (speed trajectory) and discrete ones (signal timing). The optimal speed trajectory is obtained with the objective of minimizing the fuel consumption of freight vehicles. Meanwhile, freight-priority optimal signal timing is achieved by minimizing the queueing delay of passenger vehicles at the intersections, while ensuring freight vehicles to avoid stopping and idling. The cooperative optimization problem is non-convex due to constraints from the queues and traffic signals in the network; therefore, a sub-optimal strategy restoring convexity is proposed to solve the problem. Comparison studies of the result and some benchmark methods are performed via numerical simulations, showing significant improvement of traffic efficiency and fuel economy with faster calculation.

An Overlapping Phase Approach to Optimize Bus Signal Priority Control under Two-Way Signal Coordination on Urban Arterials

With the consideration of the uneven traffic volume distribution at intersections on urban arterials, this paper aims to minimize the overall passenger delay (buses and private vehicles) at intersections and identify the applicable conditions of the proposed method with field data. The overlapping phase-based signal control logic and the bus priority control algorithm under two-way signal coordination on arterial roads are proposed. The vehicular capacities and occupancies for buses and passenger cars are considered in the evaluation of the method performance. A field test was carried out at two major intersections on an arterial road in Hefei, China. With the test data, the proposed method is examined and the possible influencing factors are analyzed for identifying the corresponding applicable conditions. The analysis result shows that the application of the overlapping phase helps to provide a relatively flexible signal control for the varying traffic demands at intersections. Compared to the conventional phase, it isof more practical significance to consider overlapping phase and apply bussignal priority control under two-way signal coordination according to the condition of uneven traffic volumedistribution at intersections on urban arterials. The proposed method can effectively decrease the total passenger delay at the intersections on urban arterials under certain applicable conditions. The possible factors influencing the method applicability are identified as well. It is verified that bus signal priority control under the two-way signal coordination, based on overlapping phases, is more conducive to improving traffic efficiency on urban arterials. Regarding the influencing factors and the applicability of the proposed method, the results show that not all situations are conducive to decreasing passenger delay at intersections. The proposed method should be applied under certain applicable conditions and principles in order to efficiently and effectively improve the traffic efficiency on arterial roads.

Why signal suppression cannot resolve the attentional capture debate

ABSTRACT Luck et al. (2021, Progress toward resolving the attentional capture debate. Visual Cognition, 29(1), 1–21. https://doi.org/10.1080/13506285.2020.1848949) propose that proactive suppression can help to resolve the long-standing attentional capture debate. They argue that salient but task-irrelevant stimuli automatically generate a priority signal, which leads to attentional capture if it is not suppressed. While this signal suppression framework provides a refreshing new perspective on attentional capture, it cannot fully resolve this debate. To do this, it would have to be demonstrated that task-contingent capture effects in spatial cueing tasks are linked to proactive feature-based suppression preventing attentional capture by salient but irrelevant objects. I argue that there is little evidence if any evidence for such a link. I consider possible reasons why suppression does not seem to play a major role in spatial cueing tasks, and also highlight important general limitations of proactive inhibitory control in visual search.

An integrated MPC and deep reinforcement learning approach to trams-priority active signal control

The problem of active signal priority control for trams is investigated. A combined model predictive control (MPC) and deep reinforcement learning solution is proposed, to minimize stopping of trams at intersections while reducing delay of general vehicles. An efficient new deep reinforcement learning (DRL) framework is introduced to improve the proximal policy optimization with model-based acceleration (PPOMA). The DRL module is strengthened by a model predictive controller, which provides low-precision prediction of the real-time traffic dynamics to improve the learning performance. The problem is modeled as a high-dimension Markov decision process. Dynamic phase sequence is used to improve the flexibility of signal priority control, instead of only optimizing a signal cycle in a fixed phase sequence as in other methods. The optimal traffic signal sequence is obtained by using real-time traffic information collected from vehicular networks. Experiments with SUMO have shown the advantage of our method in comparison with the existing methods.

Multi-Agent Fuzzy-Based Transit Signal Priority Control for Traffic Network Considering Conflicting Priority Requests

The performance of transit signal priority (TSP) with conflicting priority requests highly depends on the serving sequence of multiple TSP requests. A series of existing methods have been developed to determine the priority level of requests. However, most of these methods focused on isolated intersections or a small number of intersections, which are not applicable to complex, dynamic and nonlinear urban traffic networks. In this regard, we propose a multi-agent TSP control method at the network level considering conflicting priority requests. Fuzzy inference is used to manage signal control. We further develop a specific control algorithm. The performance of the proposed method is verified by a case study with a sizeable traffic network with 20 intersections and 49 links. Simulation results demonstrate that the proposed method outperforms other three benchmarking methods under different traffic demands and bus departure frequencies. It is worth-noting that the improvement becomes more notable with the increase of traffic demands and the reduction of bus departure frequencies.

An analytical approach to real-time bus signal priority system for isolated intersections

Bus signal priority (BSP) is an active traffic management measure to reduce bus travel delay at signalized intersections and to improve the bus service reliability. In this paper, we present a real-time BSP system with a primary focus on its practical implementation. We tackle two inter-related issues of existing priority systems, namely, real-time computation and solution optimality, using an analytical approach. The core of the proposed priority system involves two signal controller actions – red truncation (RT) and green extension (GE), which determine the priority timings based on the objective of minimizing total person delay incurring at the subject intersection. We demonstrate the analytical approach by deriving closed-form expressions for optimal RT and GE for a two-phase signal using cumulative count curves. The inputs required for these priority models are based on average traffic and bus conditions limited to the current signal cycle alone. Solutions for the RT and GE models indicate that three dimensionless variables – ratio of bus-arrival time to traffic queuing time, ratio of bus passenger occupancy to other vehicles’ average passenger occupancy, and ratio of traffic demand to saturation flow ratio – govern the priority decisions. Simulation results showed significant delay reduction for buses (≈22%) with a negligible impact on other traffic users during low to medium traffic conditions and high bus frequencies (3 min headway).

Sensitivity Analysis of the Transit Signal Priority Requesting Threshold and the Impact on Bus Performance and General Traffic

An analysis was performed to evaluate the impact of changing the transit signal priority (TSP) requesting threshold on bus performance and general traffic, using field-generated data exclusively. Route 217, a conventional bus route that uses a dedicated short-range communication (DSRC)-based TSP system as part of its normal day-to-day operations, was analyzed over a three-month period from May 2019 through August 2019. The requesting thresholds evaluated for Route 217 were 3, 2, and 0 min, which stipulate how far behind schedule the bus must be to request TSP. For each requesting threshold, bus performance was evaluated through on-time performance (OTP), schedule deviation, travel time, and dwell time, while the traffic analysis was performed by evaluating split failure, change in green time, and the frequency at which TSP was served. A combination of observational and statistical analyses concluded with convincing evidence that OTP, schedule deviation, and travel time improve as the requesting threshold approaches zero with negligible impacts on general traffic. As the requesting threshold changed from 3, to 2, to 0 min, OTP increased 2.0% and 2.5%, respectively; mean schedule deviation improved by 15.9 s and 20.9 s, respectively; and travel time decreased at 75% of timepoints. Meanwhile, negative impacts to traffic occurred if an increase in split failure was measured after TSP was served, a phenomenon observed a maximum of once every 43 min. Thus, it is concluded that bus performance improves as the requesting threshold approaches zero with inconsequential impacts on general traffic.

Bus Trajectory Optimization With Holding, Speed and Traffic Signal Actuation in Controlled Transit Systems

We propose an optimal actuation of operational commands for regularizing bus headways. Assuming that a transit headway control system manages the bus operation by issuing reference arrival times at the next station for a bus, the problem is how to implement the control decisions for the bus in terms of three nonexclusive alternative actions: holding the bus at stops; varying bus speeds; and controlling traffic lights. Mathematical programming provides the basis of the approach. The constraints specify the bus trajectory model and the operator objectives are formulated as a multi-objective cost function solved by a lexicographic method. Results for a bus run on a single segment between two stops highlight the properties of the solution. A simulation study of an entire transit corridor in Quebec City, Canada, shows the advantage of the method over both headway control based on pure holding at stops and on one that combines holding and absolute transit signal priority.

Deep Reinforcement Learning for Transit Signal Priority in a Connected Environment

Deep Reinforcement Learning for Transit Signal Priority in a Connected Environment

Design and Evaluation of V2X-Based Dynamic Bus Lanes

In mixed traffic, the popularity of public transport (PT) is still affected by relatively low operating speeds compared to private vehicles. To overcome this, PT priority measures have been proposed and adopted extensively. However, existing solutions such as exclusive bus lanes or traffic signal priorities are often limited in terms of available road space or large-scale feasibility. In this paper, we propose a Vehicle-to-Vehicle/Infrastructure (V2X)-based dynamic PT priority concept in mixed traffic called Virtual Right of Way (VROW). Private vehicles in front of a PT vehicle make spaces through collaborative lane changes within a dynamic clearing distance computed based on the current traffic situation. This allows a more efficient allocation of road space while still maintaining a high level of PT priority. In this paper, we evaluate the potential traffic impacts of VROW on both PT and private vehicles by conducting microscopic traffic simulations within a small urban network and a highway scenario. Comparisons with mixed traffic and other existing bus lane priority strategies, in terms of operation and safety concerns, are analyzed and highlighted. Simulation results show that VROW improves the PT operational performance with only a marginal influence on private vehicles measured by their average travel time and the number of lane changes.

Dynamic Thresholds Identification for Green Extension and Red Truncation Strategies for Bus Priority

Among the different strategies adopted to improve the efficiency and reliability of the bus services, bus signal priority is a low cost and less infrastructure- demanding solution that has the potential to reduce bus travel times in urban arterials. This paper develops analytical models for finding the thresholds for Green Extension (GE) and Red Truncation (RT) for a four-phase signal system with buses on conflicting phases. The thresholds are developed based on reducing the total person delay after considering buses from the current cycle and unserved buses from the previous cycle for priority decisions. The proposed models aim for zero-delay service for the buses from the current cycle and reducing delay for the unserved buses from the previous cycle. The models reveal that at multi-phase signals, several bus priority alternatives are possible to reduce total person delay and agencies can choose alternatives based on their requirements and constraints. These models are evaluated in VISSIM microscopic simulation environment. The evaluation results indicate a 16.7 to 42.8% reduction in total person intersection delay due to the implemented bus priority.

Content or status: Frontal and posterior cortical representations of object category and upcoming task goals in working memory

To optimize task sequences, the brain must differentiate between current and prospective goals. We previously showed that currently and prospectively relevant object representations in working memory can be dissociated within object-selective cortex. Based on other recent studies indicating that a range of brain areas may be involved in distinguishing between currently relevant and prospectively relevant information in working memory, here we conducted multivoxel pattern analyses of fMRI activity in additional posterior areas (specifically early visual cortex and the intraparietal sulcus) as well as frontal areas (specifically the frontal eye fields and lateral prefrontal cortex). We assessed whether these areas represent the memory content, the current versus prospective status of the memory, or both. On each trial, participants memorized an object drawn from three different categories. The object was the target for either a first task (currently relevant), a second task (prospectively relevant), or for neither task (irrelevant). The results revealed a division of labor across brain regions: While posterior areas preferentially coded for content (i.e., the category), frontal areas carried information about the current versus prospective relevance status of the memory, irrespective of the category. Intraparietal sulcus revealed both strong category- and status-sensitivity, consistent with its hub function of combining stimulus and priority signals. Furthermore, cross-decoding analyses revealed that while current and prospective representations were similar prior to search, they became dissimilar during search, in posterior as well as frontal areas. The findings provide further evidence for a dissociation between content and control networks in working memory.

New transit signal priority scheme for intersections with nearby bus rapid transit median stations

To improve the accessibility of bus rapid transit (BRT) systems, the median stations are usually located beside intersections. However, due to the limited storage space at the stations, high bus volumes and fluctuant bus arrival patterns may cause queue spillbacks and consequently block the intersections. Traditional transit signal priority control could deteriorate such situations when a green extension or a red truncation is activated. Hence, it is essential to develop a new operational framework that is capable of both reducing bus travel time and preventing queue spillbacks at the median stations. This study presents a novel signal control scheme to integrate both priority (i.e. green extension and red truncation) and suppression strategies (i.e. green truncation and red extension) for approaching buses. Notably, the suppression control is only implemented to the farside directional traffic. To evaluate the proposed signal control system, this study tests the algorithms on a real BRT network in Jinan, China. Simulation results of multiple experiments show that the developed method has great promise in bus delay reduction and spillback avoidance in the station area. Other further explorations with sensitivity analysis find that the proposed control will be more effective when the signal is able to provide longer priority and suppression durations.

Progress toward resolving the attentional capture debate

ABSTRACT For over 25 years, researchers have debated whether physically salient stimuli capture attention in an automatic manner, independent of the observer’s goals, or whether the capture of attention depends on the match between a stimulus and the observer’s task set. Recent evidence suggests an intermediate position in which salient stimuli automatically produce a priority signal, but the capture of attention can be prevented via an inhibitory mechanism that suppresses the salient stimulus. Here, proponents from multiple sides of the debate describe how their original views have changed in light of recent research, as well as remaining areas of disagreement. These perspectives highlight some emerging areas of consensus and provide new directions for future research on attentional capture.

Evaluating Suitable Glosa-Algorithms by Simulation Considering Realistic Traffic Conditions and V2X-Communication

Abstract Vehicle-to-Everything (V2X) communication allows infrastructure elements, e.g., traffic lights, to directly communicate with vehicles, thereby allowing services like Green Light Optimized Speed Advisory (GLOSA), Probe Vehicle Data (PVD), and Traffic Signal Priority Request (TSP). The idea behind GLOSA is to assist vehicles approaching an intersection with speed advices in order to fulfill a given objective, e.g., minimizing fuel usage, emissions and/or delay. In a prior work (Kloeppel et al., 2019), several GLOSA algorithms were examined and their fitness (in the form of CO2 emissions, fuel usage and delay) were evaluated under largely realistic conditions. This paper is an extension of the prior work and presents further examinations, which include a more detailed study on the behaviour of Diesel-powered vehicles when using the GLOSA algorithm of Stebbins et al. (2017) as well as a study considering fixed-time control coupled with intelligent vehicles.

Modeling and optimizing bus transit priority along an arterial: A moving bottleneck approach

Bus operations on arterials are often hindered by traffic signals and car queues. Transit signal priority (TSP) strategies can be used to improve bus operations on arterials. Analytically quantifying the impacts of TSP in mixed traffic, where cars and buses share lanes, is challenging since car queues can slow down buses, while slow-moving buses can create bottlenecks for cars. Furthermore, computational costs increase significantly when considering an arterial with multiple intersections. To tackle these challenges, this paper first develops a dynamic programming framework to model and evaluate TSP along an arterial. Next, the algorithm is utilized to determine the changes to car and bus delays as a result of TSP implementation along an arterial, and the sensitivity of the algorithm to the signal timing plan, bus stop locations and dwell durations, and the bus headway is evaluated. Next, a bi-level optimization framework is proposed to determine the optimal location of TSP implementation along arterials. Finally, the results of integrating TSP with dedicated bus lanes is evaluated. The results suggest that the benefits of TSP largely depend on the signal setting, and bus stop location, and that as the bus headway decreases, the marginal benefit of providing TSP also decreases. Additionally, the results suggest that the specific intersection at which TSP is implemented can play a large role on its operational impacts. Finally, it is found that in some scenarios, the benefits of implementing TSP alone can be larger than implementing dedicated bus lanes alone.

Authority and priority signals in automatic summary generation for online reputation management

AbstractOnline reputation management (ORM) comprises the collection of techniques that help monitoring and improving the public image of an entity (companies, products, institutions) on the Internet. The ORM experts try to minimize the negative impact of the information about an entity while maximizing the positive material for being more trustworthy to the customers. Due to the huge amount of information that is published on the Internet every day, there is a need to summarize the entire flow of information to obtain only those data that are relevant to the entities. Traditionally the automatic summarization task in the ORM scenario takes some in‐domain signals into account such as popularity, polarity for reputation and novelty but exists other feature to be considered, the authority of the people. This authority depends on the ability to convince others and therefore to influence opinions. In this work, we propose the use of authority signals that measures the influence of a user jointly with (a) priority signals related to the ORM domain and (b) information regarding the different topics that influential people is talking about. Our results indicate that the use of authority signals may significantly improve the quality of the summaries that are automatically generated.