Public Transportation Agencies Research Articles

New Zealand public transport agencies' responses to COVID‐19: Understanding public transport services, infrastructure and communication measures

AbstractCOVID‐19 brought public health challenges to the public transport system throughout the world. As a result, a range of response measures were implemented to ensure the safety of passengers while maintaining a functioning system. This paper explores the responses of public transport agencies in New Zealand's metropolitan cities (Auckland, Christchurch and Wellington) to the COVID‐19 pandemic by examining their physical and communication measures. We analysed public transport agencies' websites to understand the response measures implemented, including the accessibility of COVID‐19‐related information, and the communication of information via websites and social media platforms. The results show that 13 service responses were implemented across the three public transport agencies, with Auckland implementing the most measures. Seven infrastructural responses were implemented, with Christchurch implementing all seven. Wellington was found to be the public transport agency that used social media the most during the pandemic. The website accessibility findings suggest that the more accessible a public transport agency's website was, the less information was present. The research concludes that all three public transport agencies in New Zealand performed reasonably well and were able to maintain a safe and responsive public transport system.

If You Cut It Will They Ride? Longitudinal Examination of the Elasticity of Public Transport Ridership in the Post-Pandemic Era

In the past two years, public transport ridership has declined because of COVID-19 pandemic health measures and new working from home policies. This decline in ridership has caused major financial stress on public transport agencies around the world. Several agencies have responded to this financial stress by reducing services. The extent to which these service cuts will affect transit ridership is unknown because of the changing operational environment in the post-pandemic world. Our study uses a longitudinal panel data from Montréal, Quebec, Canada, to explore the relationship between route-level ridership and operational factors over time. We find that public transport ridership demand at the route level is highly elastic when compared to trip frequency and has become more elastic after the COVID-19 pandemic. Our findings imply that agencies cutting service in the post-pandemic era run a much more significant risk of creating a “doom spiral,” where service reductions spur greater declines in ridership, forcing further reductions. Demand was found to be most elastic on more frequent routes, so agencies should prioritize maintaining services on their core routes in the post-pandemic era. This study can be of use to public transit planners and policymakers considering making service changes to attract more riders or trying to respond to post-COVID-19 financial stress.

Feasibility of Modernizing the Acceptable International Roughness Index Value

The U.S. National Highway System has set a standard for acceptable pavement roughness, measured by the international roughness index (IRI) at less than 2.68 m/km (170 in./mi). This value corresponds to a present serviceability rating (PSR) of 2.5, where half of the highway drivers perceive the pavement ride quality as unacceptable with a repair need. For over 3 decades, public transportation agencies in the U.S. have used this IRI value to determine when pavement surface rehabilitation is needed. However, with advancements in vehicle suspension systems improving ride quality, the current acceptable IRI value corresponding to 2.5 PSR has been questioned. To our knowledge, studies in the literature have yet to explore this issue. This study aims to evaluate the feasibility of modernizing the acceptable IRI value through nationwide, large-scale field testing, which is typically expensive and time-consuming. The IRI-present serviceability index (PSI) equation that is capable of converting the acceptable IRI value into the estimated 2.5 PSR (i.e., the PSI) was selected and calibrated by applying test quarter-car parameters synthesized through a literature review. Then, the calibrated IRI-PSI equation was used to find a new acceptable IRI value that was evaluated for the statistical significance and the financial benefits of the new value. The evaluation results suggest a need for a nationwide field test to modernize the current acceptable IRI value. Public transportation agencies can easily adapt the technical approach we used to calibrate the IRI-PSI equation without altering their current IRI measurement systems.

The impact and value of information system audit enterprises risk management influencing quality assurance and system optimization—a touch from supply chain domains

The industries significantly rely on information technology for effective operations; however, there are hazards like data breaches and system breakdowns. Information system audits are essential to reducing these risks, ensuring quality control, and optimizing the system. These audits evaluate gaps in controls, non-compliance concerns, and vulnerabilities, allowing for the installation of efficient risk mitigation measures. Information system audits are essential for locating and reducing hazards related to an organization's information systems.Vulnerabilities, threats, and control flaws can be found through routine audits, which then allows for the deployment of the necessary controls and risk-reduction measures. Additionally, audits support quality assurance by assessing data reliability, accuracy, and completeness, as well as system performance, regulatory compliance, and industry best practices.The deployment of remedial steps to improve data integrity and system reliability is made possible by their assistance in assisting organizations in identifying gaps and flaws. Information system audits also aid system optimization by revealing details about the functionality and performance of the system.  An extensive evaluation of the literature and case study analysis was used to perform the research.For the analysis of this research, a sequential mixed technique (qualitative and quantitative) study was conducted. Delphi questionnaires were used twice to conduct the study. It encompasses organizations and entities involved in various aspects including but not limited to logistics companies, freight carriers, shipping and distribution firms, public transportation agencies, and supply chain service providers. Data from the semi-structured interviews for the qualitative study were collected via a Delphi survey, and 14 nodes and six themes were then generated.Audits assist organizations in identifying areas for improvement and informing decisions about system upgrades or alterations by analyzing system utilization, response times, resource allocation, and scalability. The results of this study highlight the importance of information system audits in assuring the prosperity, effectiveness, and resilience of businesses engaged in supply chain operations. Organizations can attain a greater level of enterprise risk management, quality assurance, and system optimization, which will improve supply chain operations in general, by managing risks, improving data quality, and optimizing system performance.

Integrating ride-hailing services with public transport: a stochastic user equilibrium model for multimodal transport systems

Public transport (PT) agencies are increasingly keen on integrating ride-hailing (RH) services with PT to improve overall mobility. Understanding the traffic flow distribution in the integrated system is vital for the policy decision-making and services design of such a system. We propose a stochastic user equilibrium (SUE) model for multimodal transport systems consisting of private car, PT and RH. The travel costs in the SUE model are investigated using a multimodal graph representation to capture the relationship of different travel modes in the integrated system. We apply the proposed model to a toy case and a real-world case. A RH subsidy strategy is compared with the benchmark to demonstrate travellers’ route and mode shifts in the integrated system. Our findings offer insights on subsidising RH services through the proposed model, and provide valuable knowledge on the planning and design of the integrated system.

Quality Assurance Methods for Hourly Nonmotorized Traffic Counts

Growing numbers of public transportation and recreation agencies have implemented automated bicycle and pedestrian traffic monitoring programs. To support these initiatives, researchers and agency analysts have developed programs, methods, and measures to ensure data quality. These methods include statistical tests for identifying and flagging outliers and other invalid counts and procedures for imputing or managing missing and censored counts. Because statistics such as annual average daily bicyclists are used frequently in planning and engineering, analysts have focused on validation of daily counts using data from permanent monitors. Procedures for ensuring the validity of hourly counts have not been standardized. This paper presents quality assurance (QA) methods for hourly nonmotorized traffic counts at 115 short-duration and nine permanent monitoring sites on multiuse trails monitored by the Minnesota Department of Natural Resources (MnDNR) and the Minnesota Department of Transportation (MnDOT) between 2016 and 2021. These methods include statistical tests for flagging and censoring invalid hourly counts and procedures for imputing estimates for censored or missing counts. Differences in traffic flow estimates with and without QA are documented, and hourly patterns and factors are presented. Use of quality assurance methods for hourly counts can increase the validity of estimates of nonmotorized traffic.

Smart Passenger Center: Real-Time Optimization of Urban Public Transport

This paper introduces the Smart Passenger Center (SPaCe), MerMec's solution for real-time optimization of urban public transport. The proposed system, based on cutting-edge artificial intelligence technologies, provides real-time vehicle status information and passenger activity monitoring. All of the information acquired from the vehicles is used to optimize the performance of the vehicle fleet for real-time traffic management.The purpose of the paper is to explain the reasons and benefits of such Intelligent Transport System (ITS) with a deep understanding of its architecture and advanced functionalities.Additionally, a practical application of the data collected by SPaCe is proposed for the task of bus timetable optimization.The goal is to schedule bus trips in a way that maximizes multiple conflicting goals such as service quality and operating costs, based on real time collected data.The reported results show how the developed optimization system can support the decision-making process to balance the interests between passengers and public transport agencies.

Does the squeaky wheel get the complaint? Linking bus performance, sociodemographic characteristics, and customer comments

Public transit agencies rely on service operations performance measures to guide service improvement efforts. They also collect customer feedback on performance to measure levels of satisfaction among users. Connecting these two performance measures can help public transport agencies increase ridership satisfaction and loyalty. In this study, we link service performance measures obtained from automatic vehicle location (AVL) and automatic passenger count (APC) with customer complaints. This is done while controlling for the amount of ridership to understand if routes with worse service performance, as identified by operations measures, also have more service complaints. We also investigated if an area’s level of affluence affects the number of service complaints per rider that the route receives while controlling for route service performance and ridership. The AVL/APC and customer-feedback data were provided by Portland, Oregon’s TriMet transport agency for the period between August 2018 and January 2019. Descriptive statistics at the route level and a series of mixed-effect multilevel logistic regression models were used to quantify the relationship between route service performance, service complaints, and a service-area vulnerability index, at the route-day level. The likelihood of receiving a service complaint for a route in a day was found to increase based on service performance and the vulnerability of the neighborhood being served by that route, all else held equal. Findings from this research unmask the relationship between service complaints, bus operations and socioeconomic characteristics of the neighborhood a route is serving, offering insights to transport planners and researchers in the psychology behind bus performance complaints.

The sustainable transport planning index: A tool for the sustainable implementation of public transportation

AbstractThe transportation sector contributes significantly to global greenhouse gas emissions, so it is crucial to assess and measure the sustainability of transportation systems. In this context, this study was conducted to develop an integrated index through the use of the multi‐criteria decision analysis method. The method combines existing discrete indexes into one comprehensive evaluation of public transportation, resulting in the sustainable transport planning index (STPI). In the STPI model, sustainability of transportation systems is assessed based on social, economic, and environmental factors that support the implementation of zero emission busses. The weight of each indicator is determined through the analytical hierarchy process, where expert judgment is used to assess the relative importance of each indicator. Normalization of indicators is performed to ensure comparability and consistency. The final STPI index is calculated as the weighted average of the normalized indicators. The STPI model reduces bias in the decision‐making process by considering multiple aspects and utilizing a structured approach to transport planning. The results of this method can provide valuable insights for decision‐makers, public transport agencies, government ministries, the private sector, and other stakeholders. As case study model, the STPI model was applied to the public transport system of the United Kingdom from 2007 to 2019, however; the methodology and lessons learned are applicable to all countries that are in the process of assembling data sets to weigh trade‐offs and inclusions in relation to sustainable transit such as accessibility and health impacts.

A data-driven decision support tool for public transport service analysis and provision

Public transport service (PTS) analysis and provision is an important and challenging issue for public transport agencies. The results of the PTS analysis help transport planners to identify the areas in need of PTS improvement. Furthermore, relevant policy actions need to be determined for service provision to reach the desired level of PTS improvement in the identified areas. Without an appropriate decision support tool, planners need to apply several blind trials to find a policy action which improves the PTS in the examined areas. This paper introduces a data-driven decision support tool for PTS analysis and provision. The proposed framework combines a potentially large number of PTS measures while taking the correlation among the investigated measures into account and develops high-dimensional supervised classification models that predict the PTS levels for different policy actions. With this approach, planners can identify and prioritize the areas in need of PTS improvement, determine what policy actions should be targeted to improve the PTS in the identified areas, and predict the PTS impacts of these policy actions in the examined areas. The application of the proposed framework is demonstrated in detail through a case study of Budapest, Hungary, which is followed by a hypothetical policy implementation. The results show that mostly outskirts are in need of PTS improvement. Furthermore, the underlying reasons behind the areas with poor overall PTS are studied to target the relevant policy actions that improve the PTS in the identified areas. The PTS impacts of the targeted policy actions are studied by using the developed high-dimensional supervised classification models.

Feasibility Study of Using Close-Range Photogrammetry as an Asset-Inventory Tool at Public Transportation Agencies

Feasibility Study of Using Close-Range Photogrammetry as an Asset-Inventory Tool at Public Transportation Agencies

IMPORTANCE INDEX THEORY APPLIED TO ALLIANCE PROJECT GEOTECHNICAL RISK STRATEGY

Alliance contracts are consummated before the subsurface investigation to support the final geotechnical design is complete, forcing clients and their industry partners to operate with high levels of geotechnical uncertainty during the negotiation of the alliance agreement. Research has shown that perceptions of each stakeholder of this key area of uncertainty are very different, making it challenging to achieve alignment. The purpose of this paper is to propose an objective methodology for alliance members to prioritize geotechnical risk factors during the agreement negotiation process to determine those factors that should be clarified before determining a target outturn cost. This paper proposes an objective methodology based on importance index theory computed from each geotechnical factor’s frequency and impact. Survey data collected from 46 public transportation agency and industry experts provided the input. The paper proposes that a prioritized list of project-specific geotechnical risks be used to guide the negotiations and potentially identify the need for preliminary subsurface investigations to support the development of the target outturn cost. The framework is applied to a typical alliance project to demonstrate its efficacy. The paper’s primary contribution is the importance index-based methodology for ranking geotechnical risk factors, which may be utilized as a checklist to guide negotiations of geotechnical risk distribution in the alliance agreement.

GIS-Based Support System for On-Demand Flexroute Transit Service

Geographic Information Systems (GIS) are a proven resource for public transportation service planning and evaluation. In particular, their spatial analysis and database management capabilities make them well suited for such applications. The primary cost incurred in a GIS application is for the development and maintenance of high-quality spatial databases. Due to this cost, public transportation agencies want to utilize these databases to support a wider array of applications. As desktop GIS software and computer hardware become more powerful, GIS can be used to develop applications for “real-time “ operations. In this research effort, a GIS-based prototype system was developed and tested to support the scheduling and dispatch functions of an on-demand flexroute transit service. The effectiveness of the prototype demonstrates the potential of GIS to support time-critical transit operations.

Citizens or Customers? Transit Agency Approaches to Community Engagement

Aristotle, in his work Politics, expressed his view that a citizen attains his or her fullest humanity by engaging in the work of the government by accepting ownership of the policymaking apparatus of the work of the polis. Such a perspective contrasts with those who consider citizenship to be merely a legal status, unconcerned with the affairs of the public and passive recipients of government services. This research considers what public administrators at mass transit agencies say they do in pursuit of engagement with their communities. The decisions that public administrators in transit agencies make regarding service retrenchment or expansion have deep, profound consequences on poor and vulnerable transit-dependent populations. Such transit administrators exercise a great deal of power over their ridership’s lives since agency decisions have real-world consequences. Therefore, it is a critical research question to examine the methods, techniques, and underlying rationale of transit administrators’ pursuit of community engagement. This research finds that public transportation agency approaches to community engagement can be typified into two broad perspectives of how the agency views individuals in their community: Community as Citizens and Community as Customers.

An Automated Sound Barrier Inventory Method Using Mobile LiDAR

A sound barrier, also called a noise barrier, plays an irreplaceable role in traffic noise abatement. The Federal Highway Administration’s (FHWA) highway noise regulation requires each state highway agency to maintain a complete inventory of all constructed noise-abatement features. Although key information for most of the newly constructed sound barriers has been inventoried, public transportation agencies are still struggling to keep close track of the in-service barriers because their inventory information is nonexisting, and manual inventory remains time-consuming, labor-intensive, and often dangerous. Therefore, many agencies have shown more interest in exploring the possibility of using light detection and ranging (LiDAR) data for assisting in sound barrier inventory, thanks to the widely available data set and much-improved data quality. This study proposes a LiDAR-based sound barrier inventory method to automatically extract the sound barrier’s location and measure the corresponding geometry. The extraction of a sound barrier is achieved using its unique features after random sample consensus (RANSAC)-based ground extraction and region-growing segmentation. The geometry measurement of the sound barrier is performed by analyzing the detailed dimension of the extracted point cloud, including location, height, length, and lateral offset. The experimental test conducted near Carver, Massachusetts showed the results with a precision rate of 99.9% and a recall rate of 93.8%. Moreover, the outcome of the experimental test has demonstrated the robustness of the proposed method in different complexities of the background and sound barrier types (linear and zigzag). This study has demonstrated the feasibility of using LiDAR for effectively inventorying in-service barriers. Besides the critical application of asset management, the detailed location and geometry information provided by the proposed method can provide valuable insight for other critical applications, such as traffic noise modeling.

Can Public Transportation Compete with Automated and Connected Cars?

Over the next 30 years, technological innovation will make automobile travel more convenient. Automated and connected vehicles will perform an increasing number of driving tasks without human input and will lure customers away from traditional public transportation. This paper first explores key characteristics of public transportation demand in the United States today—based on an international comparison with other Western countries. Next, the paper provides potential pathways on how public transportation agencies and local governments in the United States could respond to the emergence of automated and connected vehicles. The paper argues that space efficiency in urbanized areas and the rush hour commute will remain public transportation’s key strengths. In addition, public transportation will retain its important role in providing mobility for all—in particular, for those who cannot afford costly automated and connected vehicles. To remain competitive with the car, public transportation agencies and governments have to harness emerging automated and connected technologies for public transportation, integrate public transportation with other mobility services, coordinate and integrate public transportation services regionally, and coordinate planning for public transportation and land use.

COVID-19 incidence in a cohort of public transport workers.

Previous research has shown an excess risk of COVID-19 among several occupations, but data on public transport workers are scarce. To investigate the occupational risk posed by contact with the public, we followed up the incidence of COVID-19 in a cohort of public transport workers. We identified the incident cases of COVID-19 between 1 September 2020 - 6 May 2021 in a cohort of 2,052 employees of a public transport agency in Sardinia, Italy. The diagnosis of COVID-19 was based on a positive molecular test. To calculate the expected events, we applied the age- and gender-specific incidence rates of the regional population in the same time period to the correspondent strata of the study cohort. We estimated the relative risk (RR) of COVID-19 as the ratio between the observed and the expected events and its 95% confidence interval (95% C.I.) among the total cohort and in two sub-cohorts: bus drivers, and the rest of the personnel (administrative staff, train and metro drivers, workers in the mechanical shop, and in the railroad maintenance, and security). Bus drivers run an elevated risk of COVID-19 (RR = 1.4, 95% C.I. 1.07 - 1.79). There was no excess risk among the sub-cohort including the rest of the personnel. Our study suggests an excess risk of COVID-19 among bus drivers even in a relatively low incidence area, which could imply inadequacy of the preventive measures in place. Further, larger size studies with detailed information on personal and lifestyle characteristics are warranted.

Estimation of the effect on air quality of retrofitting SCRT on urban buses in Copenhagen

ABSTRACT This study estimates the effect on air quality of retrofitting SCRT on about 300 urban buses in Copenhagen from September 2015 to March 2016. The retrofitted buses were of Euro III, Euro IV and EEV emission standards. The specific SCRT technology applies ammonia as injected into the exhaust as a gas as opposed to normally as a liquid (urea). This technology is more efficient in reducing NOx emissions, especially under urban driving conditions with relatively low exhaust temperatures. The estimation of the effect is based on air quality model calculations for 98 selected busy streets in Copenhagen for 2015 based on, among others, information from the Zealand public transport agency about buses with and without retrofitted SCRT. More detailed analyses were conducted for two of the streets where fixed air quality measuring stations are located in Copenhagen. Furthermore, a before-after analysis of the development of measured concentrations at fixed measuring stations was carried out to isolate the effect of the retrofitted SCRT. The model calculations showed substantial reductions in emissions of NOx and exhaust particles from each bus (90%) but low reductions in concentrations of NO2, PM2.5 and PM10, respectively 3% for 98 streets on average for NO2, and 0.1%[0.2%] for PM2.5 and 0.07%[0.1%] for PM10 for H.C. Andersen Boulevard and [Jagtvej]. Based on the analysis of trends in the measurements it was not possible to isolate an effect of SCRT on urban buses in Copenhagen probably due to the large variations in meteorology affecting the variations in concentrations.

Particle swarm optimization and RBF neural networks for public transport arrival time prediction using GTFS data

Accurate prediction of Public Transport (PT) mobility is important for intelligent transportation. Nowadays, mobility data have become increasingly available with the General Transit Feed Specification (GTFS) being the format for PT agencies to disseminate such data. Estimated Time of Arrival (ETA) of PT is crucial for the public, as well as the PT agency for logistics, route-optimization, maintenance, etc. However, prediction of PT-ETA is a challenging task, due to the complex and non-stationary urban traffic. This work introduces a novel data-driven approach for predicting PT-ETA based on RBF neural networks, using a modified version of the successful PSO-NSFM algorithm for training. Additionally, a novel pre-processing pipeline (CR-GTFS) is designed for cleansing and reconstructing the GTFS data. The combination of PSO-NSFM and CR-GTFS introduces a complete framework for predicting PT-ETA accurately with real-world data feeds. Experiments on GTFS data verify the proposed approach, outperforming state-of-the-art in prediction accuracy and computational times.

Transit Stigma: Transit Administrators’ Views of the Role of Policy Elites in Perpetuating Stigma

Public transportation use is heavily stigmatized in the United States. As a result, those who depend on public transportation services for mobility are marginalized and subject to unjust social assumptions about their character, work ethic, and overall place in society. Prior research documents that public transit administrators are actively working to combat transit stigma in their service area; however, questions remain regarding how public transit administrators view the role of policy elites (elected or appointed political figures) in perpetuating transit stigma. Through a series of in-depth interviews with 20 transit administrators from across the United States, this research finds that policy elites maintain transit stigma through both formal and informal roles by devaluing the role of transit in society, focusing on short-term political goals, and restricting funding opportunities for public transportation agencies.