Transit Priority Research Articles

A Value Proposition of Cooperative Bus-Holding Transit Signal Priority Strategy in Connected and Automated Vehicles Environment

In this study, we assess a cooperative bus-holding transit signal priority strategy (C-BHTSP) in a connected and automated vehicles (CAV) environment. The research objectives of this study are to quantify the benefits of C-BHTSP to transit, its impact on opposing non-transit traffic, and the CAV market penetration rate required to neutralize that impact. A simulation model was developed in VISSIM using detailed, high-quality, up-to-date data for transit, non-transit traffic, and signal control parameters. Our assessment shows that the proposed strategy results in about a 60% reduction in transit delay compared to the base scenario. The results also show that a CAV MPR of 32% was found sufficient to overcome the negative impact of C-BHTSP on the opposing non-transit traffic while maintaining transit benefits. Higher MPRs produce substantial improvements in the overall travel time, delay, fuel consumption, and greenhouse gas emissions. The framework and findings of this study provide a blueprint for the decision-making process of implementing transit priority under varying CAV MPRs.

Ridership and Operations Visualization Engine: An Integrated Transit Performance and Passenger Journey Visualization Engine

Transit agencies collect a vast amount of data on vehicle positions, passenger loading and, increasingly, origin–destination flows. Collecting and synthesizing these data to support operations and planning are significant challenges and can be constrained by information silos within transit agencies. In this paper, an open-source bus performance and journey visualization dashboard, Ridership and Operations Visualization Engine, is presented, which integrates multiple disparate data sources into a flexible and iterative analysis tool. It differs from existing commercial products by including origin–destination flows along with standard performance metrics, and is designed to be adaptable and relevant to any transit agency. Two case studies are presented to demonstrate the functionality of the dashboard: planning transit priority infrastructure and evaluating network design changes. The dashboard was developed in partnership with Chicago Transit Authority and Massachusetts Bay Transportation Authority, and practical details from the installation and maintenance procedures are included for prospective users.

Network-level control of heterogeneous automated traffic guaranteeing bus priority

Guaranteeing the quality of transit service is of great importance to promote the attractiveness of buses and alleviate urban traffic issues such as congestion and pollution. Emerging technologies of automated driving and V2X communication have the potential to enable the accurate control of vehicles and the efficient organization of traffic to enhance both the schedule adherence of buses and the overall network mobility. This study proposes a novel network-level control scheme for heterogeneous automated traffic composed of buses and private cars under a full connected and automated environment. Inheriting the idea of network-level rhythmic control proposed by Lin et al. (2021b), an innovative rhythmic control scheme for heterogeneous traffic, i.e., RC-H, is established to organize the mixed traffic in a rhythmic manner. Realized virtual platoons are designed for accommodating vehicles to pass through the network, including dedicated virtual platoons for buses to provide exclusive right-of-ways (ROWs) on their trips and regular virtual platoons for private cars along with an optimal assignment plan to minimize the total travel cost. A mixed-integer linear program (MILP) is formulated to optimize the RC-H scheme with the objective of minimizing the weighted travel costs of both buses and private cars. A bilevel heuristic solution method is designed to relieve the computational burden of MILP. Numerical examples and simulation experiments are conducted to evaluate the performance of the RC-H scheme under different scenarios. The results show that the bus punctuality can be guaranteed and the traveler delay can be minimized under various demand levels with transit priority. Moreover, compared with traffic signal control (TSC) strategies, including those with fixed timing and those with bus priority, the RC-H scheme shows significant advantages in handling heavy traffic demand, in terms of both reducing vehicle delay and enhancing network throughput.

Transitioning services for eating disorder treatment, the relative importance of factors from patient, carer and clinician perspectives: a Q-methodology study

PurposeEffective transitions from child and adolescent to adult services are important for continuity of care for patients with eating disorders. This study aims to examine the relative importance of a series of statements about the transition process, elicited from an earlier service evaluation, from the perspectives of patients, parents/carers and clinicians.Design/methodology/approachTwenty-eight participants completed a Q-sort task ranking 40 statements, developed from an earlier study, using a normal distribution pattern on a scale, which ranged from strongly agree to strongly disagree, to identify their priorities for transition. Analysis resulted in the extraction of four factors explaining 52% of the variance.FindingsFour distinct factors were elicited: “parents and carers need including too”, “facilitating effective transfer between services”, “supporting the patient through transition” and providing “timely, patient-centred care”. The study enabled similarities and differences in priorities to be observed for the three respondent groups.Practical implicationsThese rankings, noting the differences between the respondent groups, can be used to inform the development of effective transition protocols. This study suggests these protocols should ensure a person-centred approach; timely planning; include parents/carers; provide continuous care and have good transfer of information and sensible timing of transitions. Differences in priorities/opinions can be addressed through open communication channels.Originality/valueTo the best of the authors’ knowledge, this is the first UK-wide study examining priorities for transition from the perspectives of patients, parents/carers and clinicians.

Optimal control to improve reliability of demand responsive transport priority at signalized intersections considering the stochastic process

Bus priority has been proposed for many years to improve traffic congestion, energy conservation, and emissions reduction. Transit signal priority is a main measure of executing bus priority. Moreover, because the time that buses arrive at an intersection should be predicted quite precisely to make a signal control scheme in advance, bus lane is an important segment in transit priority at signalized intersections to avoid disturbances from other vehicles on the road. However, in practice, the bus route of demand responsive transport is widespread, which is not inappropriate to set bus lane for each bus route because of low frequency. Therefore, in this paper, a robust optimization control method is proposed to solve the bus priority problem at signalized intersections without exclusive bus lanes and improve reliability of demand responsive transport priority at signalized intersections. First, the bus delay probability density function is formulated to describe the interaction mechanism about the bus and other vehicles at the signalized intersection. Then, the accurate bus delay expectation and variance calculation mathematical models are formulated based on the bus delay probability density function. Furthermore, a robust optimal signal control method is proposed followed by the discussions of boundary conditions. Finally, simulation test and case study were conducted to illustrate the performance of the robust optimization control method proposed in this paper. The results show that the proposed control method could significantly improve bus delay compared to considering the bus operation process as stable.

Hybrid pedestrian and transit priority zoning policies in an urban street network: Evaluating network traffic flow impacts with analytical approximation

Pedestrianized zones are becoming an increasingly popular policy tool for cities seeking to improve “walkability”, “livability”, and reduce congestion in the urban center by prohibiting automobiles from entering a designated zone. However, pedestrianized zones can be inappropriately implemented in locations without justifiable congestion or sufficient transit alternatives. For mixed-traffic transit (e.g., bus and light-rail streetcars), the lack of reasonable transit alternatives is an issue further compounded by the traffic congestion generated from diverted driving trips concentrated around the pedestrianized zone, inadvertently slowing down both automobile traffic and mixed-traffic transit in tandem. Alternatively, to mitigate the traffic congestion impact on transit, policy makers can also designate a “transit priority” zone around the pedestrian zone, where transit is unimpeded by congestion either through transit signal priority, dedicated lanes, or both. This ensures transit provides a consistent travel alternative as congestion varies, creating a stable demand equilibrium that would otherwise be suppressed by congestion. While such a solution has been proposed in advocacy, no research has explored such a combined policy in analytical terms. This research explores the potential complementary benefits and optimal sizing of pedestrianization and transit priority zones through analytical evaluation in an idealized rectilinear city. The model is intended to provide insights regarding traffic impacts, optimal zone sizing, system capacity, and the justifiable thresholds for implementing complementary pedestrianization and transit priority zones in a city.

Type-2 fuzzy logic based transit priority strategy

We proposed in this paper Type-2 Fuzzy Logic-based transit priority strategy. The developed strategy belongs to the class of active priority strategies. At the same time, it is a conditional priority strategy. We tried to find out the finest trade-off between transit and traffic delay. The suggested approach used the data collected from the VISSIM analysis. The simulation tests were performed on the section of an arterial with two intersections in downtown Belgrade, Serbia. The obtained results are promising. It looks that the developed strategy could improve traffic operations in cities, or areas, with high bus frequencies and/or low or medium traffic volume.

Using GTFS to Calculate Travel Time Savings Potential of Bus Preferential Treatments

Dedicated bus lanes and other transit priority treatments are a cost-effective way to improve transit speed and reliability. However, creating a bus lane can be a contentious process; it requires justification to the public and frequently entails competition for federal grants. In addition, more complex bus networks are likely to have unknown locations where transit priority infrastructure would provide high value to riders. This analysis presents a methodology for estimating the value of bus preferential treatments for all segments of a given bus network. It calculates the passenger-weighted travel time savings potential for each inter-stop segment based on schedule padding. The input data, ridership data, and General Transit Feed Specification (GTFS) trip-stop data are universally accessible to transit agencies. This study examines the 2018 Metropolitan Atlanta Rapid Transit Authority (MARTA) bus network and identifies a portion of route 39 on Buford Highway as an example candidate for a bus lane corridor. The results are used to evaluate the value of time savings to passengers, operating cost savings to the agency, and other benefits that would result from implementing bus lanes on Buford Highway. This study does not extend to estimating the cost of transit priority infrastructure or recommending locations based on traffic flow characteristics. However, it does provide a reproducible methodology to estimate the value of transit priority treatments, and it identifies locations with high value, all using data that are readily available to transit agencies. Conducting this analysis provides a foundation for beginning the planning process for transit priority infrastructure.

Analytical characterization of multi-state effective discharge rates for bus-only lane conversion scheduling problem

An accurate quantification of traffic flow characteristics with and without bus-only lane is important for determining transit priority strategies. Examinations of real-world vehicle trajectory data, like those from the NGSIM dataset, found that an effective discharge rate may be discounted when merging or lane-changing behaviors are observed. To deal with this, this manuscript analytically derives the effective discharge rate of a roadway segment by considering multi-stage merging behavior and vehicular traffic kinematics near a side entrance, for optimal bus-only lane conversion. The classic fluid-based approximation model by Newell that characterizes the queuing and dissipation process is extended to a multi-state queuing analysis framework. Three effective discharge rate discount factors are explicitly derived, for bus-only lane, general-purpose lane, and mixed-traffic lane, respectively. The derived effective discharge rates are represented by mathematically-simple expressions in a closed-form, and correctly account for the effects of demand inputs, such as arrival rate and the ratio of vehicles of different types, vehicular performance (such as acceleration rate), and traffic flow characteristics (such as backward wave speed and jam density). The bus-only lane conversion scheduling problem is then formulated as an optimization model to minimize total traffic delay. Validation, using NGSIM data, showed that our model reduced the effective discharge rate estimation error significantly on both arterials and freeways. Sensitivity analysis revealed that the optimal bus-only lane scheduling time varied in response to traffic demand and vehicle ratios, and the developed optimization model was always beneficial when compared with the demand-oriented strategy.

Understanding Socio-Technological Systems Change through an Indigenous Community-Based Participatory Framework

Moving toward a sustainable global society requires substantial change in both social and technological systems. This sustainability is dependent not only on addressing the environmental impacts of current social and technological systems, but also on addressing the social, economic and political harms that continue to be perpetuated through systematic forms of oppression and the exclusion of Black, Indigenous, and people of color (BIPOC) communities. To adequately identify and address these harms, we argue that scientists, practitioners, and communities need a transdisciplinary framework that integrates multiple types of knowledge, in particular, Indigenous and experiential knowledge. Indigenous knowledge systems embrace relationality and reciprocity rather than extraction and oppression, and experiential knowledge grounds transition priorities in lived experiences rather than expert assessments. Here, we demonstrate how an Indigenous, experiential, and community-based participatory framework for understanding and advancing socio-technological system transitions can facilitate the co-design and co-development of community-owned energy systems.

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.

Mining understandable state machine models from embedded code

Program understanding is a time-consuming and tedious activity for software developers. Manually building abstractions from source code requires in-depth analysis of the code. Automatic extraction of such models is possible, but cannot derive meaningful abstractions that are not already contained in the code. The automated extraction even has problems to decide which aspects of the code are important and which are not. Therefore, interactive semi-automatic approaches are the compromise of choice. In this article, we describe how state machines that describe the behaviour of a function can be extracted from code. The approach includes interaction – the user decides which aspects of the identified potentially relevant information is really relevant and which is not. This helps to reduce the resulting state machines to an understandable degree. However, these state machines in their raw form have transition conditions that are very complex and thus not understandable for humans. Therefore, we also introduce a technique to reduce these guards to an understandable form. The technique is a combination of heuristic logic minimization, exploitation of infeasible paths, and using transition priorities. We evaluate the approach on industrial embedded C code, first in a case study with hundreds of extracted state machines, and then in two experiments with professional developers. The results show that the approach is highly effective in making the guards understandable, and that guards reduced by our approach and presented with priorities are easier to understand than guards without priorities. We also show that the overall approach is beneficial for program comprehension. The guard reduction approach itself is quite generic and can also be applied to other problems. We demonstrate that for the simplification of mode switch logic.

Evaluating impacts of intelligent transit priority on intersection energy and emissions

A signal priority strategy (SPS) is implemented to encourage the development of public transportation, but this strategy may delay other vehicles to produce more emissions, especially at intersection. This study aims to develop an intersection energy consumption and emissions model framework with an embedded SPS to analyse the impacts of the SPS on the intersection. To validate this model framework, an intersection in Shenzhen, China was selected for simulation as a case study. In this study, we compared the effects of an active SPS, a real-time SPS and the real-time SPS improved under Intelligent Vehicle Infrastructure Cooperation System (i-VICS) on the energy consumption and emissions of the targeted intersection. The simulation results illustrate that, the active strategy could decrease fuel consumption and emissions with a maximum reduction of 13.33% in fuel consumption, and the real-time strategy maintains a smooth fluctuation in the total fuel consumption and emissions during the entire period. Compared with the two in-use strategies, the i-VICS-based transit priority strategy demonstrates the best environmental performance, by reducing the greatest negative environmental influences and cutting down the most emissions of nearly 28.86% in the case study. The developed intersection energy consumption and emissions model framework can be applied to evaluation of different SPSs on the environment respect, which can benefit to urban transportation management in a more sustainable way.

Resilient Schedule Coordination for a Bus Transit Corridor

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.

Optimization of Actuated Traffic Signal Plans Using a Mesoscopic Traffic Simulation

AbstractTraffic signal plan designs become more complex with developments in the fields of sensing and communication and the introduction of features, such as transit priority or pedestrian actuati...

Dynamic lane restrictions on congested arterials

Buses operating in mixed traffic experience problems with delay and travel time variability in peak periods. Numerous transit priority measures are found in the literature but most rely on separating buses from other vehicles. Complete separation such as dedicated bus lanes might underutilize the system capacity when the frequency of buses is not high. We propose a “dynamic bus lane policy”, where control adjusts the proportion of cars to buses in one lane of a multi-lane arterial instead of enforcing complete separation of vehicle types. This strategy is analyzed with aggregated macroscopic dynamics for different models of lane choice. It is shown to benefit both cars and buses by maintaining higher outflow during the peak period and helping the system to recover more quickly at the end of the peak. Greater reductions in travel time are possible with increased information available to vehicles. Analytical derivations and non-linear optimization are then used to obtain the system optimal allocation of cars, as well as the toll needed to achieve it. The system optimal tolling would be difficult to implement in practice. Another optimization which includes tolls paid in its objective is nearly as good at reducing vehicle hours traveled and produces a much simpler pricing structure amenable to feedback control. A microsimulation with feedback control confirms the results of the macroscopic model and shows additional benefits attributable to driver behavior. Future work will look into varying control parameters to achieve a global minimum travel time and will incorporate user heterogeneity to test pricing strategies.

Smart Infrastructure for Future Urban Mobility

Real‐time traffic signal control presents a challenging multiagent planning problem, particularly in urban road networks where, unlike simpler arterial settings, there are competing dominant traffic flows that shift through the day. Further complicating matters, urban environments require attention to multimodal traffic flows (vehicles, pedestrians, bicyclists, buses) that move at different speeds and may be given different priorities. For the past several years, my research group has been developing and refining a real‐time, adaptive traffic signal control system to address these challenges, referred to as scalable urban traffic control (Surtrac). Combining principles from automated planning and scheduling, multiagent systems, and traffic theory, Surtrac treats traffic signal control as a decentralized online planning process. In operation, each intersection repeatedly generates and executes (in rolling horizon fashion) signal‐timing plans that optimize the movement of currently sensed approaching traffic through the intersection. Each time a new plan is produced (nominally every couple of seconds), the intersection communicates to its downstream neighbors what traffic it expects to send their way, allowing intersections to construct longer horizon plans and achieve coordinated behavior. Initial evaluation of Surtrac in the field has demonstrated significant performance improvements, and the technology is now deployed and operating in several U.S. cities. More recent work has focused on integrating real‐time adaptive signal control with emerging connected vehicle technology, and exploration of the opportunities for enhanced mobility that direct vehicle (or pedestrian) to infrastructure communication can provide. Current technology development efforts center on vehicle route sharing, smart transit priority, safe intersection crossing for pedestrians with disabilities, real‐time incident detection, and integrated optimization of signal control and route choice decisions. This article provides an overview of this overall research effort.

Simultaneous Optimization of Passive Transit Priority Signals and Lane Allocation

This paper presents an integrated optimization model for the concurrent design of passive bus priority signal settings and lane allocation including lane markings for general traffic and exclusive bus lanes at isolated intersections. Traditional passive transit signal priority (TSP) strategies considered both lane markings for general traffic and exclusive bus lane settings as exogenous inputs. However, in our method, two modes of transportation (passenger cars and buses) have been considered in a centralized framework while exclusive bus lane settings, lane markings, and the optimal passive transit priority signal settings can be optimized concurrently. Minimization of the weighted delay of buses and cars is adopted as the aim of the integrated optimization model. Based on traditional National Electrical Manufacturers Association (NEMA) phase constructure, a precedence graph was employed, by which the mathematical optimization model is formulated. A set of restrictions have been set up to verify efficiency and safety for the resulting optimal lane markings and signal settings. A simulated annealing (SA) algorithm is designed to resolve the mix-integer-nonlinear-programming (MINLP) problem. In order to demonstrate the efficacy of the method proposed, numerical examples have been provided. The results from sensitivity analysis show that the proposed method can generate sub-optimal solutions for the intersection of different combinations of car demand, bus demand, and left turn ratios.

Simultaneous Optimization of Passive Transit Priority Signals and Lane Allocation

This paper presents an integrated optimization model for the concurrent design of passive bus priority signal settings and lane allocation including lane markings for general traffic and exclusive bus lanes at isolated intersections. Traditional passive transit signal priority (TSP) strategies considered both lane markings for general traffic and exclusive bus lane settings as exogenous inputs. However, in our method, two modes of transportation (passenger cars and buses) have been considered in a centralized framework while exclusive bus lane settings, lane markings, and the optimal passive transit priority signal settings can be optimized concurrently. Minimization of the weighted delay of buses and cars is adopted as the aim of the integrated optimization model. Based on traditional National Electrical Manufacturers Association (NEMA) phase constructure, a precedence graph was employed, by which the mathematical optimization model is formulated. A set of restrictions have been set up to verify efficiency and safety for the resulting optimal lane markings and signal settings. A simulated annealing (SA) algorithm is designed to resolve the mix-integer-nonlinear-programming (MINLP) problem. In order to demonstrate the efficacy of the method proposed, numerical examples have been provided. The results from sensitivity analysis show that the proposed method can generate sub-optimal solutions for the intersection of different combinations of car demand, bus demand, and left turn ratios.

Optimal Design of Overtopping Breakwater for Energy Conversion (OBREC) Systems Using the Harmony Search Algorithm

The European Union, in its Framework Strategy for A Resilient Energy Union, as described in the “Clean Energy for all Europeans” package of measures, marked its energy priorities for transition to a low-carbon, secure and competitive economy. Following this direction, the paper deals with the exploitation of one of the most significant and extensively available energy sources, that of nearshore waves. More specifically the paper emphasizes in the optimal design of Overtopping Breakwater for Energy Conversion systems, known as OBREC, using a novel and very effective, meta-heuristic optimization technique, the Harmony Search Algorithm. The proposed methodology is based on the combined application of wave propagation equations that simulate the compound wave field near coastal structures where the waves are subjected to the combined effects of shoaling, refraction, diffraction, reflection - total and partial - and breaking, with an optimization algorithm, aiming at the identification of the optimal dimensions of an OBREC reservoir. In order to demonstrate the effectiveness of the methodology, the harbor of Heraklion in the island of Crete in Greece, is used as a case study. The results of the application are very promising and strongly support the statement that the proposed methodology provides a new concept in the design of OBREC systems.