Public Transport Management Research Articles

Relationship between urban traffic crashes and temporal/meteorological conditions: understanding and predicting the effects

Urban traffic accidents pose significant challenges to public safety and transportation management. Previous studies have revealed that temporal and meteorological factors are the key contributors to accident rate. Besides the inconsistent observations or lack of exploration in some aspects such as snowfall, fog, wind and daily temperatures, it has been shown that these factors are essentially entangled. Furthermore, existing methodologies of analysis or prediction have been limited to relative risk or traditional models. Hence, this study is centered on understanding the detailed correlations between temporal and meteorological factors and accident rate of two types of crashes – moving vehicle and fixed-object crashes using the traffic accident data from Dalian. Further, by incorporating a diverse set of the features, a prediction model leveraging the random forest algorithm is proposed and proved effective in anticipating accident occurrences on the district level. The feature importance analysis has shown that time period and factors such as holiday, temperature and season are most important factors. The rate is higher on working days and in spring, and collisions of both types peak at 6–7 am. When the highest daily temperature is 27 °C and the lowest is 20 °C or -8 °C, the incidence is relatively higher. On the basis, the recommendations are aimed at optimizing transportation systems, mitigating accident risks, and enhancing public safety in urban environments.

Accurate crowd counting for intelligent video surveillance systems

The paper presents a novel deep learning approach for crowd counting in intelligent video surveillance systems, addressing the growing need for accurate monitoring of public spaces in urban environments. The demand for precise crowd estimation arises from challenges related to security, public safety, and efficiency in urban areas, particularly during large public events. Existing crowd counting techniques, including feature-based object detection and regression-based methods, face limitations in high-density environments due to occlusions, lighting variations, and diverse human figures. To overcome these challenges, the authors propose a new deep encoder-decoder architecture based on VGG16, which incorporates hierarchical feature extraction with spatial and channel attention mechanisms. This architecture enhances the model’s ability to manage variations in crowd density, leveraging adaptive pooling and dilated convolutions to extract meaningful features from dense crowds. The model’s decoder is further refined to handle sparse and crowded scenes through separate density maps, improving its adaptability and accuracy. Evaluations of the proposed model on benchmark datasets, including Shanghai Tech and UCF CC 50, demonstrate superior performance over state-of-the-art methods, with significant improvements in mean absolute error and mean squared error metrics. The paper emphasizes the importance of addressing environmental variability and scale differences in crowded environments and shows that the proposed model is effective in both sparse and dense crowd conditions. This research contributes to the advancement of intelligent video surveillance systems by providing a more accurate and efficient method for crowd counting, with potential applications in public safety, transportation management, and urban planning.

Smart Commute Application for Public Transport Management

An urban city's ever-growing population and everyday commuters have created a serious issue, making it difficult for the governing bodies to handle public transit. This project attempts to present a concise overview of the main issues. The latest technical developments, such as IOT, GPS, smartphones, etc., must b e incorporated.This study proposes a bus tracking system that uses software technologies such as flutterflow and firebase database management system to monitor and control bus movements. Here, we suggest a system that integrates the newest technology into already-in-use bus networks so that passengers may learn about the buses' current location as well as their arrival and departure timings via display boards at bus terminals or through apps on smartphones. Keywords— Public transportation, governing body, daily commuters, management, technological advancements, IOT, GPS, Smartphone, App’s, flutterflow, firebase, bus terminal.

AICTSL: Sustainable Capacity Planning by Cash Flow Management

The case study introduces Atal Indore City Transport Services Limited (AICTSL), a public transport management body in Indore, at a crucial juncture pertaining to fleet capacity management. Located in the central state of Madhya Pradesh in India, Indore has been a popular destination for industrial activity. Amid a cash crunch, increasing travel demands, the need for route expansion and myriad socio-economic factors, Rahul Shrouti, the senior operations manager, has to make a strategic decision to increase the number of buses. The dilemma faced by Shrouti is formed by the investments required, time period to recover the investment, operating expenses and the variability of the associated costs. Hence, the case highlights a context of capacity expansion, which calls for efficient change management. Besides, macro factors, concepts such as the time value of money, payback period, internal rate of return and linear regression have been brought about explicitly. The case study will drive multi-faceted classroom discussion through MS Excel-based number crunching. The case study will help the practitioners in making decisions for capacity planning and support change management.

Detecting synthetic population bias using a spatially-oriented framework and independent validation data

Models of human mobility can be broadly applied to find solutions addressing diverse topics such as public health policy, transportation management, emergency management, and urban development. However, many mobility models require individual-level data that is limited in availability and accessibility. Synthetic populations are commonly used as the foundation for mobility models because they provide detailed individual-level data representing the different types and characteristics of people in a study area. Thorough evaluation of synthetic populations is required to detect data biases before the prejudices are transferred to subsequent applications. Although synthetic populations are commonly used for modeling mobility, they are conventionally validated by their sociodemographic characteristics, rather than mobility attributes. Mobility microdata provides an opportunity to independently/externally validate the mobility attributes of synthetic populations. This study demonstrates a spatially-oriented data validation framework and independent data validation to assess the mobility attributes of two synthetic populations at different spatial granularities. Validation using independent data (SafeGraph) and the validation framework replicated the spatial distribution of errors detected using source data (LODES) and total absolute error. Spatial clusters of error exposed the locations of underrepresented and overrepresented communities. This information can guide bias mitigation efforts to generate a more representative synthetic population.

Resilience-based post-disaster repair strategy for integrated public transit networks

The resilience of public transit systems has become a critical issue due to their essential role in urban mobility. However, the challenges of repair selection and sequencing in integrated public transportation networks (IPTN) have not been fully explored. Therefore, we propose a bi-level resilience-based repair strategy optimisation (RRSO) model to investigate the optimisation of resilience in IPTN. To consider trip selection and account for cascade failure processes, a lower-level traffic assignment model was integrated into a single-layer RRSO model. In the traffic assignment model, perceived travel time reflects the traffic impedance of public transportation. Additionally, to assess the performance of the RRSO model under emergency repair conditions, random variables were introduced to represent uncertain factors in the traffic environment. Finally, the results demonstrate that the RRSO model outperforms standard empirical repair strategies. This study provides theoretical insights into the management of urban public transportation.

Unlocking urban charm for liveable street: transformative design strategies to boost pedestrian appeal in Asian cities

Walking as a mode of transportation faces challenges in Asian cities due to the proliferation of private motorized vehicles and lacking public transportation management. Despite contributing to people’s physical and mental well-being, walking is often considered the last option for transportation. Previous research has highlighted the link between walking, urban design qualities, individual reactions, and a sense of place. Other studies have suggested that a sense of place fosters a sense of belonging and attachment to the location. This paper aims to propose transformative design strategies to enhance pedestrians’ willingness to walk through the design of street junctions. Street junctions, especially those featuring corner buildings, offer opportunities for walking, observing, and resting, all of which are crucial elements for vibrant public spaces. The findings reveal that street junctions in cities like Surabaya (Indonesia) are predominantly perceived as “spaces to move” rather than “places to be.” To advance walkability in street junctions, transformative design strategies need to be addressed. Encouraging pedestrians’ willingness to walk can focus on their experiences and perceptual qualities. Developing policies aimed at enhancing street junctions in Asian cities emerges as a pivotal strategy for strengthening a culture of walking.

Improving the Profitability of Public Transport by Daily Forecasting of Passenger Loads and Bus Trip Distribution

The degree of utilization of passenger vehicle capacity affects the economic component of public transport operation. This is due to the fact that it depends on the number of passengers transported, as well as on the capacity of the passenger vehicle used for transportation. One of the tasks formulated in the state program of transport development of the Republic of Belarus is to achieve full self-sufficiency of public transport operation. One of the ways to achieve this goal can be maximizing the degree of use of passenger vehicle capacity by ensuring its compliance with the existing parameters of passenger flow. In this paper, based on the values of passenger flows in one of the cities of Belarus, obtained as a result of field observations in 2019 and 2024, we calculate an indicator that assesses the degree of utilization of passenger vehicle capacity, the factors that determine it, and the regularities of its change. Based on such calculations, the feasibility of creating a new public transport management technology based on daily forecasting of passenger traffic and distribution of passenger vehicles of different capacity to the routes taking this into account is shown.

Moving from classical towards machine learning stances for bus passengers’ alighting estimation: A comparison of state-of-the-art approaches in the city of Lisbon

Passenger alighting estimation is a critical task in public transport (PT) management, especially for entry-only Automatic Fare Collection (AFC) transport systems where passenger alighting are not recorded. Effective estimation methods are necessary for trip analysis and route planning, offering valuable insights into passengers’ mobility patterns and, subsequently, improving the quality of service. However, the stochastic nature of passenger behaviour challenges the degree of successful alighting estimates. A classic approach to infer the alighting stops of passengers is the use of trip-chaining principles. Since these principles are dispersed across the literature in the field, their comprehensive review is pivotal to establish the best practice for alighting estimation. Still, trip-chaining approaches are unable to infer the alighting of non-commuting passengers. This paper addresses these two research gaps by: i) providing a critical overview of the existing principles and methods for alighting estimation; ii) proposing an approach to improve alighting estimation that consistently integrates the most effective state-of-the-art principles on trip-chaining; and iii) further introducing a frequent pattern mining and density-based clustering solutions to support alighting estimation for non-commuting passengers. Considering the public bus transport in Lisbon city as the guiding case study, the achieved estimation rate by the proposed assembled model is 92%. Moreover, the density-based clustering solution is found to improve the estimation of 11pp against classic trip-chaining principles. Furthermore, the proposed model and acquired results yield actionable value to enhance PT operations and services, ultimately leading to improved bus routing and quality of service.

Collaborative Governance in Management of the JakLingko Program (Case Study on Public Transportation Management in DKI Jakarta)

High population density and mobility in Jakarta have triggered persistent traffic congestion. The impacts are not only on time and cost but also on deteriorating air quality. Government efforts to provide alternative public transportation have not been fully effective, due to low public interest caused by inadequate facilities and limited accessibility. The solution is evident in the JakLingko Program, an initiative that integrates the public transportation system. To ensure the success of this program, the Jakarta Transportation Agency collaborates with public transportation modes and relevant businesses. Through this synergy, it is expected that public interest in using public transportation will increase, reducing the use of private vehicles, thereby alleviating traffic congestion and improving air quality in Jakarta. This research employs the collaborative governance model proposed by Ansell and Gash, encompassing four dimensions: initial conditions, institutional design, facilitative leadership, and collaboration processes. The research methodology is qualitative-descriptive. The research results indicate that collaborative governance in managing the JakLingko Program in Jakarta is fairly optimal, but not yet fully so.

The Current Development and Optimization of Smart Public Transportation in Taiyuan City

"With the development of technology and the smartification of cities, the urbanization process is accelerating rapidly. The population and the number of motor vehicles in cities are increasing rapidly, leading to evident issues such as traffic congestion and air pollution. Smart public transportation, as an integral component of smart cities, can reduce passengers' travel costs, improve travel efficiency to some extent, and provide big data support for the development of smart transportation and even smart cities. It is a cost-effective, convenient, and environmentally friendly mode of transportation.This article first analyzes the current situation of smart public transportation in Taiyuan city. It points out issues such as uneven allocation of public transportation resources, prolonged travel times for passengers using public transportation, and overcrowding during peak hours. Drawing on the development experiences of smart public transportation in cities both domestically and internationally, the article proposes optimization suggestions for the current state of smart public transportation in Taiyuan. These include refined management of public transportation, skip-stop operations, smart resource allocation, and improvement of infrastructure construction. The aim is to provide theoretical guidance for the optimization and improvement of smart public transportation in Taiyuan, enabling more efficient development of 'smart public transportation' in the city.".

Conflict Management in the Operation of Trans Padang Corridor VI

Padang Mayor Regulation Number 127 of 2021 sets minimum service standards for the management, implementation, and service of Trans Padang public transportation. This research uses a qualitative research method with a descriptive method to find out how the Padang City government handles the demo conflict that occurred between Padang angkot drivers and Trans Padang drivers on the Trans Padang travel route in Corridor VI. This research uses a descriptive method because the research describes, tells, and interprets a situation or event as it is. The study investigated the location of the conflict, Corridor VI of Trans Padang, and asked the government and the Padang City Transportation Office about the people directly involved in the conflict between Trans Padang and Padang angkot drivers. The results show that conflict management in Trans Padang corridor 6 is not going well. The government and stakeholders should communicate more and work together to resolve this conflict. In addition, the government should consider the interests of the angkot drivers and find a solution that benefits all parties.

ГРОМАДСЬКИЙ ТРАНСПОРТ: ОРГАНІЗАЦІЙНО-ЕКОНОМІЧНІ І СОЦІАЛЬНІ ЗАСАДИ ФУНКЦІОНУВАННЯ

The article shows that the integral function of public transport is to promote social justice, accessibility of transport services for the general population and environmental sustainability. The public transport system has been proven to be efficient and competitive by helping to reduce congestion, pollution and social isolation, as well as ensuring accessibility to transport services and mobility for all city residents. Strategies for overcoming the shortcomings of the fixed infrastructure of public transport in terms of smart planning, implementation of flexible management systems, constant renewal and modernization are justified. It has been proven that the following will contribute to improving the mobility of city residents and reducing the problem of disconnection between different transport subsystems: integrated payment through the introduction of a single ticket system or cashless payment technologies; development of transplant nodes; facilitating movement between different public transport systems; integrated planning of urban development by taking into account the interaction of different types of transport. Ways to improve the pricing mechanism for public transport services based on the introduction of social justice approaches to their pricing and tariff differentiation are proposed. The importance of ensuring the effectiveness of the use of subsidies to support public transport in terms of its accessibility as a socio-economic type of activity for city residents has been proven. It is shown that the development of supporting subsystems of public transport management in large cities of Ukraine will be facilitated by the implementation of measures to ensure its availability, efficiency and sustainability. Public feedback has been proven to be an important component of effective urban public transport management and helps create a more efficient, accessible and convenient transport system for all city residents. It is also shown that the creation of a single public transport management body in the city will ensure a holistic approach to planning routes, transport schedules and tariffs, which will contribute to a more efficient and convenient service for city residents.

Public Transportation Assessment Along Kathmandu Bhaktapur Route

The transportation sector of Kathmandu Valley is facing numerous intricacies because of soaring population density. According to the Kathmandu Valley Traffic Police Office, the number of vehicles that ply the Valley roads at present is 1.75 million. Just a year ago, traffic police data showed the number to be 1.4 million. Also, only about 20% of the vehicles are used for public service suggesting that public transportation management has been a major challenge in Kathmandu Valley. This leads to an increase in travel time coupled with huge traffic congestion. The Kathmandu Bhaktapur route is around 13 KM in length and is used by more than 68000 passengers on normal days and more than 56000 passengers on public holidays; but the service offered is not reliable and systematic and needs to be upgraded. Significant travel duration due to low running speed, and unnecessary and frequent stops at short distances proved to be the major issues. After the removal of unnecessary stations, 3200 passengers’ hours can be saved.

A review of map-matching algorithms

The public transport system is a key factor for the development of cities and for the satisfaction of citizens. For this reason, public transport management systems based on IT solutions were created. One of the problems that arise in public transport planning is tracking vehicle routes when using GPS information with signal interruptions or erroneous data. In these cases, it is necessary to implement some map-matching algorithms to solve these problems and follow the correct route for good information of the citizens waiting in the stations and for tracking the routes. This work aims to present the main map-matching algorithms and compare them, highlighting their utility and efficiency.

Connecting Internet of Drones and Urban Computing: Methods, protocols and applications

This comprehensive survey explores the connection between the Internet of Drones (IoD) and Urban Computing (UC). Drones offer substantial benefits across diverse urban applications encompassing public safety, transportation management, delivery services, and emergency response, among others. To ensure the seamless operation of these applications, efficient airspace management is imperative. Consequently, an essential foundation is to establish a communication infrastructure coupled with an accompanying supportive system that caters to drones, control bases, service providers, and the Internet. Termed the IoD, this framework facilitates drones’ control management, synchronization, coordination and monitoring of drones to attain their objectives effectively. Moreover, IoD applications are poised to propel societal advancement by aligning with the goals of UC. UC is an interdisciplinary domain to enhances human well-being by harnessing data from various sources, including the Global Positioning System (GPS), cameras, proximity sensors, and social networks. This survey thoroughly examines and analyzes multifaceted aspects underpinning how the IoD can significantly benefit UC. It encompasses applications, their requisites, design protocols specific to IoD, and the challenges inherent within this evolving realm. To the best of our knowledge, our work is one of the first studies to directly relate and show how the IoD can contribute to all UC-applications categories.

Smart Public Transportation Sensing: Enhancing Perception and Data Management for Efficient and Safety Operations.

The use of cloud computing, big data, IoT, and mobile applications in the public transportation industry has resulted in the generation of vast and complex data, of which the large data volume and data variety have posed several obstacles to effective data sensing and processing with high efficiency in a real-time data-driven public transportation management system. To overcome the above-mentioned challenges and to guarantee optimal data availability for data sensing and processing in public transportation perception, a public transportation sensing platform is proposed to collect, integrate, and organize diverse data from different data sources. The proposed data perception platform connects multiple data systems and some edge intelligent perception devices to enable the collection of various types of data, including traveling information of passengers and transaction data of smart cards. To enable the efficient extraction of precise and detailed traveling behavior, an efficient field-level data lineage exploration method is proposed during logical plan generation and is integrated into the FlinkSQL system seamlessly. Furthermore, a row-level fine-grained permission control mechanism is adopted to support flexible data management. With these two techniques, the proposed data management system can support efficient data processing on large amounts of data and conducts comprehensive analysis and application of business data from numerous different sources to realize the value of the data with high data safety. Through operational testing in real environments, the proposed platform has proven highly efficient and effective in managing organizational operations, data assets, data life cycle, offline development, and backend administration over a large amount of various types of public transportation traffic data.

Public Transportation Management Strategies in a Low-Carbon Economy

The importance of public transportation in social and economic development is undeniable. With the rising concerns of environmental pollution and resource depletion in recent times, China has made significant efforts to transition towards a low-carbon economy. To advance this transition, it is imperative to confront the obstacles faced by public transportation and enact effective management strategies that promote both economic and environmental sustainability. In this regard, the author has evaluated the existing status of public transit within the context of a low-carbon economy and put forth targeted management approaches. This research is expected to make a valuable contribution towards enhancing the quality of public transportation management.

Sustainable mobility governance in smart cities for urban policy development – a scoping review and conceptual model

PurposeThe aim of this study is to propose a governance model and key performance indicators on how policymakers can contribute to a more accessible, inclusive and sustainable mobility within and across smart cities to examine sustainable urban mobility grounded on the rational management of public transportation infrastructure.Design/methodology/approachThis study employed desk research methodology grounded on secondary data from existing documents and previous research to develop a sustainable mobility governance model that explores key factors that influence future urban policy development. The collected secondary data was descriptively analyzed to provide initiatives and elements needed to achieve sustainable mobility services in smart cities.FindingsFindings from this study provide evidence on how cities can benefit from the application of data from different sources to provide value-added services to promote integrated and sustainable mobility. Additionally, findings from this study discuss the role of smart mobility for sustainable services and the application for data-driven initiatives toward sustainable smart cities to enhance mobility interconnectivity, accessibility and multimodality. Findings from this study identify technical and non-technical factors that impact the sustainable mobility transition.Practical implicationsPractically, this study advocates for the use of smart mobility and data-driven services in smart cities to improve commuters' behavior aimed at long-term behavior change toward sustainable mobility by creating awareness on the society and supporting policymakers for informed decisions. Implications from this study provide information that supports policymakers and municipalities to implement data-driven mobility services.Social implicationsThis study provides implications toward behavioral change of individuals to adopt a more sustainable mode of travels, increase citizens’ quality of life, improve economic viability of business involved in providing mobility-related services and support decision-making for municipalities and policymakers during urban planning and design by incorporating the sustainability dimension into their present and future developments.Originality/valueThis paper explores how urban transportation can greatly reduce greenhouse gas emissions and provides implications for cities to improve accessibility and sustainability of public transportation, while simultaneously promoting the adoption of more environmentally friendly means of mobility within and across cities. Besides, this study provides a detailed discussion focusing on the potential opportunities and challenges faced in urban environment in achieving sustainable mobility. The governance model developed in this study can also be utilized by technology startups and transportation companies to assess the factors that they need to put in place or improve for the provision of sustainable mobility services.

MULTI-CRITERIA OPTIMIZATION OF PUBLIC TRANSPORT ON DEMAND

With economic development, we are witnessing a high intensity of road traffic in general and especially public transport in particular. Unfortunately, this situation has negative environmental and economic consequences in the urban environment. To remedy this, several research have been made to optimize this type of transport. In this paper, we propose an optimal public transport management system which minimizes different criteria including travel distance, vehicle service time and safety obstacles (radius of curvature of turns and degree of slopes). The application of our model on different datasets gives better results compared to other works.