Public Transport Network Research Articles

Analysis of the Influence of Public Transport Fleet on Regional Development through Community Accessibility and Road Connectivity in the City of Lhokseumawe

Currently, a new concept in the transportation system has developed, namely a sustainable transportation system. The purpose of this research is to analyze the effect of the public transportation network system on community connectivity in Lhokseumawe City. The analytical method used in this research is a descriptive quantitative method using primary and secondary data. Quantitative descriptive is a type of research that is used to analyze data by describing or describing the data that has been collected as it is. This research uses multiple linear regression analysis tools. The results showed that the number of fleets, passenger capacity, routes had a positive and significant effect on the accessibility of the people in Lhokseumawe City. The number of fleets, passenger capacity and public transport routes have a positive and significant effect on community connectivity. The results of research on community accessibility and road transportation connectivity have a positive and significant effect on the development of the Lhokseumawe City area.

The integrated on-demand bus routing problem: Combining on-demand buses with a high-frequency fixed line public transport network

In this work we analyze the performance of integrating a large-scale on-demand bus system with a high-frequency fixed line public transport network in an urban context. Given are a high-speed metro network, a set of real-time requests, a set of bus station locations and a fleet of fixed capacity minibuses. Requests have a set of possible departure/arrival bus stations within walking distance of the actual departure/arrival location and have to be served within a certain time window. The aim is to simultaneously (1) decide on the trip type for each passenger (only bus, only metro or mixed), (2) route the on-demand buses, (3) in the case of a bus-leg in the trip, assign each passenger to a departure and arrival bus station (bus station assignment), and (4) in the case of a metro-leg in the trip, decide the assigned transfer station(s) and used metro lines (transfer station assignment). We call this problem the integrated on-demand bus routing problem. After presenting a mathematical model, we propose a quick and scalable insertion-based heuristic to solve the problem.The results found by the heuristic are further used to compare the performance of an integrated system, to a system that only uses on-demand buses. It is concluded that the integrated system always performs better regarding the service rate or number of served requests. Depending on the speed and layout of the metro network, also the average user ride time per passenger improves by the integration.

Integrating intelligent and sustainable transportation systems in Jeddah: a multidimensional approach for urban mobility enhancement

Abstract This research examines the transportation system in Jeddah, Saudi Arabia, specifically focusing on integrating intelligent and sustainable practices to address its current and emerging challenges. Central to these challenges are the city’s heavy reliance on private vehicles, an underdeveloped public transportation network, and the unique climatic conditions that pose additional complexities. This study adopts a multidimensional approach. It analyzes various factors, including technological advancements in transportation, sustainable and environmentally friendly practices, and the cultural and policy landscapes that shape transportation systems. It draws parallels and contrasts with transportation systems in urban settings similar to Jeddah, such as Dubai and Riyadh, to understand the potential and applicability of various solutions. One of the critical areas explored is the potential for intelligent transportation systems to revolutionize traffic management and enhance the efficiency and safety of the transportation network in Jeddah. The study also delves into the prospects of developing a sustainable public transit system that can reduce the city’s dependence on private vehicles and contribute to environmental conservation. Moreover, the research acknowledges the critical role of cultural influences in shaping transportation preferences and practices in Jeddah. It highlights the importance of culturally sensitive urban planning and policy making, ensuring that the proposed transportation solutions are not only technologically sound and environmentally sustainable but also aligned with the social and cultural fabric of the city. The study’s findings agree that a successful overhaul of Jeddah’s transportation system will require a synergistic blend of technological innovation, comprehensive policy reform, and a deep understanding of cultural nuances. The research underscores the necessity of this integrated approach as a blueprint for transforming urban transportation in Jeddah, setting a precedent for other cities with similar challenges.

Does Density Foster Shorter Public Transport Networks? A Network Expansion Simulation Approach

One argument for containing urban densities is that cities need a critical population density to sustain sufficiently available public transportation. However, the question of whether denser cities foster shorter public transport networks empirically is problematic because real-world transport nets are a product of many additional factors presumably not related to urban form. This paper adopts a network expansion simulation approach to generate and analyze counterfactual data on network lengths for 36 world cities, in which all networks are generated with similar expansion restrictions and objectives. Denser cities are found to have shorter simulated public transport networks, regardless of the tested model parameters. This provides additional proof that densities are needed to facilitate the provision of proximate public transport infrastructure, with potentially self-reinforcing effects.

A Systematic Literature Review on Transit-Based Evacuation Planning in Emergency Logistics Management: Optimisation and Modelling Approaches

Increasing disasters in recent years have necessitated the development of emergency logistics plans. Evacuation planning plays an important role in emergency logistics management, particularly when it comes to addressing transit-dependent populations that are often neglected in previous studies. This systematic literature review explores the current state of transit-based evacuation planning and examines the current gaps. We focused on transit-based evacuation planning problems that used optimisation and modelling approaches. This review conducts an extensive analysis of relevant studies to provide a comprehensive overview, identify research gaps, and outline future directions in the evacuation planning body of knowledge. Using an integrated systematic review methodology, a thorough search of the Scopus and Web of Science databases was conducted, resulting in a total of 538 articles. These articles were screened and evaluated based on predetermined inclusion and exclusion criteria, ultimately yielding 82 studies for final analysis. The findings highlight the growing importance of optimisation and modelling approaches within transit-based evacuation planning. Studies emphasize the integration of public transportation networks into evacuation strategies to enhance operational efficiency, optimize resource allocation, and ensure evacuee safety. Transit-based evacuation planning is vital for both those without personal vehicles, making evacuation more equitable, and vehicle owners, particularly in earthquakes where vehicles might be inaccessible or trapped, demonstrating its wide usefulness in all emergency scenarios. Various optimisation and modelling approaches have been employed in transit-based evacuation planning studies to simulate and analyse the flow of evacuees and vehicles during emergencies. Transit-based evacuation planning exhibits unique characteristics within disaster management, including the consideration of spatial and temporal dynamics of transit systems, integration of social and demographic factors, and involvement of multiple stakeholders. Spatial and temporal dynamics encompass transportation schedules, capacities, and routes, while social and demographic factors involve variables such as income, age, and mobility status. Stakeholder engagement facilitates collaborative decision-making and effective plan development. However, transit-based evacuation planning faces challenges that require further research and development. Data availability and accuracy, model validation, stakeholder coordination, and the integration of uncertainty and dynamic factors pose significant hurdles. Addressing these challenges necessitates advances in data collection, robust modelling frameworks, and improved communication and coordination mechanisms among stakeholders. Addressing these gaps requires interdisciplinary collaborations and advances in data analytics and modelling techniques.

Exploring Willingness to Pay across Different Passenger Traits

In recent years, the transportation landscape has seen a notable shift towards shared mobility, driven by its advantages over traditional systems fraught with inefficiencies. This shift has ushered in demand-responsive transport (DRT) systems, enabled by mobile technology. DRT offers a promising solution for the sustainability of public transport, also for rural Slovakia; however, higher individual journey costs and the necessity for online booking create adoption barriers for this new form. This paper conducts a thorough willingness-to-pay analysis in seven rural Slovak settlements, with the goal of understanding variations and comparing the findings with the existing research. Location, household size, age, car and train usage, and previous experiences with bus transport significantly impact the willingness to pay. Consequently, tailored DRT strategies are necessary for different target groups. To maximize the efficiency of this service, integrating DRT into the regional or national public transportation network is recommended. Insights from this study hold significant implications for policymakers tasked with transforming regional transportation, particularly by integrating DRT into fixed-route bus systems.

Подходы к формированию и оценке эффективности маршрутной сети на примере Нового Уренгоя

The relevance of optimizing the route network of public transport in Novy Urengoy is related to the annual increase in the length of urban routes, in particular due to the expansion of bus routes, and the uneven distribution of passenger traffic. The article refers to the methods for optimizing the public urban passenger transport system to meet the existing transport demand. The example of the development of a route network for Novy Urengoy have been used to performed the topology analysis of route tracing and the analysis of the cartogram of the city. Based on the results of the study, measures have been proposed to optimize the route network of public urban transport. The relevance of the present study is related to the use of algorithms and methods developed by the author to optimize transport systems while making research in the largest cities of the Russian Federation - Perm, Ekaterinburg, Samara, Kurgan, Yoshkar-Ola and Chita.

Price optimal routing in public transportation

We consider the price-optimal earliest arrival problem in public transit (POEAP) in which we aim to calculate the Pareto-set of journeys with respect to ticket price and arrival time in a public transportation network. Public transit fare structures are often a combination of various fare strategies such as, e.g., distance-based fares, zone-based fares or flat fares. The rules that determine the actual ticket price are often very complex. Accordingly, fare structures are notoriously difficult to model, as it is in general not sufficient to simply assign costs to arcs in a routing graph. Research into POEAP is scarce and usually either relies on heuristics or only considers restrictive fare models that are too limited to cover the full scope of most real-world applications. We therefore introduce conditional fare networks (CFNs), the first framework for representing a large number of real-world fare structures. We show that by relaxing label domination criteria, CFNs can be used as a building block in label-setting multi-objective shortest path algorithms. By the nature of their extensive modeling capabilities, optimizing over CFNs is NP-hard. However, we demonstrate that adapting the multi-criteria RAPTOR (McRAP) algorithm for CFNs yields an algorithm capable of solving POEAP to optimality in less than 400 ms on average on a real-world dataset. By restricting the size of the Pareto-set, running times are further reduced to below 10 ms.

ECONOMIC IMPACT OF COMMUTERS AND DRIVERS’ PERCEPTION OF MINIBUS (KOROPE) AS A MEANS OF PUBLIC TRANSPORTATION IN OSOGBO, OSUN STATE, NIGERIA

The Osogbo metropolitan has seen several transportation-related problems due to its dense population, limited road space, land-use characteristics, absence of mass transit, poorly executed development plans, and encroachments on private property. The specific objectives are to identify the socioeconomic characteristics of the participants in Osogbo, Osun state; investigate commuters' and drivers' perceptions of Korope transport services in Osogbo, Nigeria; and evaluate the function of Korope transport services in the study area concerning public transportation. Data was gathered using a structured survey design questionnaire. The purposive sampling method was employed. In Osogbo, Osun state, Nigeria, commuters, passengers, and Korope transport operators and owners make up the study's population. However, 1,500 of those commuters, passengers, and Korope transport operators reside in Osogbo, Osun state, Nigeria. The study's sample frame consists of passengers in Osogbo, Osun state, Nigeria, as well as Korope transport providers and owners. A sample of 177 respondents was chosen at random. Both inferential and descriptive statistics were used in the data analysis. The findings show that the F test yields asymptotic significance values of 0.000 (less than p value of 0.05) and 54.534 (more than the tabulated f-value of 2.32). Consequently, the null hypothesis is disproved and the alternative is approved. There is evidence to support the effects of connectivity, affordability, dependability, accessibility, and ease of use on intraurban mobility in Osogbo. Korope, or minibuses, are a crucial component of Osogbo, Osun State's public transportation network. Despite their increased security and overall quality, minibuses as a mode of transportation nevertheless have several obvious drawbacks. However, the report recommended that stricter safety regulations be implemented and upheld for minibuses. Frequent car inspections, driver education programs, strict adherence to speed limits and other traffic rules should all be part of these laws.

A Multi-Criteria Decision Making TOPSIS Fusion Approach for Selection Best Strategy Charging for Electric Bus Systems

An essential part of electrifying bus networks is deciding on the appropriate charging strategy among the many available alternatives, such as opportunistic (rapid) charging techniques and overnight (slow) charging. The broad usage of electric buses in public transportation networks and the increasing demand for environmentally friendly transportation options have elevated the significance of this step. This research establishes a multi-criteria decision-making (MCDM) fusion method for choosing the optimal electric bus charging strategy by considering various variables, including operational, quality-of-service, social, environmental, and economic factors. To determine what matters most for making decisions in this field, we surveyed electric bus specialists and reviewed the literature extensively. We used the TOPSIS method as an MCDM fusion method to combine the criteria and alternatives. We compute the weights of criteria by the average method. Then, the TOPSIS fusion method selects and ranks the alternatives. We collected the 20 criteria and five alternatives in this study. We show that overnight is the best charging strategy in the electric bus system. We performed a sensitivity analysis to show the different cases in criteria weights, then ranked the alternatives under different weights to establish the stability of the results.

A physicist’s approach to public transportation networks

The above picture shows public transportation on the Halyts’ka Square in my home city of Lviv, Ukraine. One can date the photo simply by having a closer look at the trams with the knowledge that the electric tram appeared in Lviv during 1894 and the horse tram ceased to exist by 1908.

ЕКОНОМІКО-ОРГАНІЗАЦІЙНІ ПРОБЛЕМИ РОЗВИТКУ ГРОМАДСЬКОГО ТРАНСПОРТУ В УМОВАХ ВОЄННОГО СТАНУ

The modern conditions in which the cities of Ukraine find themselves dictate new conditions for the development and functioning of public transport infrastructure, which is primarily due to the challenges of martial law, threats of constant shelling by the enemy, and increased safety requirements for passengers. However, the problems of loading city transport networks have not receded into the background, but have become even more acute. Therefore, the substantiation of organizational and economic tools that will change approaches to the effective functioning and development of public transport in the conditions of martial law requires serious research. The article defines the economic importance of public transport and defines its key prospects for citizens and the entire city. Public transport is a socially important service that is usually provided or simply controlled by the state. Socio-economic indicators, which depend on the developed infrastructure of public transport, are substantiated. A model for optimizing routes and entire public transport networks is proposed. Optimal models of public transport system functioning under martial law are analyzed. The criteria of the public transport optimization project have been determined: existing transport, transport demand, the desired transport model of the city, data on passenger flows for calibration and the desired optimization criteria. Conflicting reasons for residents' choice of individual transport rather than public transport have been studied. Comfortable and profitable tools for passengers using public transport are offered. The European experience and standards of public transport infrastructure functioning of European countries are systematized. The experience of European countries shows that in order to optimize public transport routes, specialists create special transport models that reflect the current or projected future demand for transport. On the basis of the conducted research, the main directions of the development of public transport in Ukrainian cities in the conditions of martial law are proposed.

The Influence of the COVID-19 Pandemic on Travel Behaviour in the Greater Copenhagen Area

The COVID-19 pandemic drastically changed the way of living for billions of people and severe restrictions were implemented by governments around the world, affecting the travel patterns of all citizens. This article investigates how travel patterns changed in the Greater Copenhagen area of Denmark during the full two-year period covering 2020 and 2021, thus allowing for an analysis of both the short-term and medium-term impacts as society gradually reopened and restrictions were lifted. The analysis covers large-scale travel survey data as well as a segmentation clustering analysis of public transport smart card data. The results showed that impacts were strongly linked to changes in trip purpose and were thus not uniformly distributed throughout the public transport system. User segmentation analysis revealed that most users changed to less intense travel use of public transport. The results highlight important policy implications in terms of how to adapt service provision within a public transport network more efficiently.

Quantification and comparison of hierarchy in Public Transport Networks

Network hierarchy describes the relative arrangement of network elements and reflects its fundamental structure. We propose a multi-dimensional topology-based method for quantifying and comparing the extent to which different Public Transport Networks (PTNs) exhibit a hierarchical structure. The proposed method considers the uneven distribution of node importance with different definitions (e.g., degree centrality and betweenness centrality) in a PTN, the clustering of nodes and the node connection patterns. We apply the developed method on 63 high-capacity PTNs worldwide using General Transit Feed Specification (GTFS) data. In addition to global indicators, we use the goodness-of-fit between the probability density function of local indicators and a skew-normal distribution to quantify the extent of PTN hierarchy. Results show that the scale-free network structure and preferential attachment do not vary much across PTNs. In contrast, stop accessibility and traffic intermediacy vary considerably across PTNs as reflected by the closeness centrality and betweenness centrality distributions. Lastly, metro systems exhibit a more hierarchical structure than their tram and Bus Rapid Transit (BRT) counterparts. This work makes a first step towards a better mapping and comparison of different PTNs, which can assist academics and practitioners in better (re)designing and planning the PTNs of the future.

Сравнительный анализ транспортного спроса и предложения в моделях транспортных систем городских агломераций

Purpose: To analyze the methods of mathematical modeling used to determine the demand for urban transportation and predict the intensity of flow distribution in the public transport network. To determine the zones of effective use of network and pre-network methods for the formation of transport models of urban agglomerations. To conduct a comparative analysis of the parameters of transport demand and offer in the network and pre-network variants of urban transport systems modeling. Methods: Mathematical modeling, processing large amounts of data, geoinformation analysis. Results: The methods of determining transport demand and offer used in modern transport models are analyzed. A comparative analysis of pre-network and network methods in transport modeling is carried out, the zone of their effective use is defined. The approbation of the problem solution of determining the transport demand and offer is carried out on the example of the urban transport system model of the St.Petersburg agglomeration. Based on the modeling results, the dependencies of transport demand and offer on the input data and model limitations are analyzed. It is concluded that it is necessary to calibrate the value of each parameter when using transport modeling. Practical significance: The results obtained can be the basis for improving mathematical modeling methods used in urban transport planning. The proposed approaches to modeling transport demand and offer can be used in the creation of forecast models used to justify project decisions in the documentation of territorial and transport planning.

Retracted: Optimization of New Energy Public Transportation Network Based on Ant Colony Algorithm and Low-Carbon Concept

Retracted: Optimization of New Energy Public Transportation Network Based on Ant Colony Algorithm and Low-Carbon Concept

Efficient Transit Network Design, Frequency Adjustment, and Fleet Calculation Using Genetic Algorithms

The main objective of this study was to implement a computational prototype in two stages: the first stage primarily focused on generating efficient routes based on an evolutionary algorithm. In other words, the complex computational problem was solved in the first stage. The second stage then shifted its focus towards determining the fleet size and frequencies using an allocation algorithm. This approach was designed to address the complex combinatorial search problem within a public transportation network. In the first stage, the prototype utilizes the metaheuristic known as Genetic Algorithms (GA). Within the GA operators, an innovative method called "aggregated crossover" is employed, with an additional mutation procedure that maintains feasible descendants. In the second stage, an allocation algorithm is used, taking into account the routes generated in the first stage. The results demonstrate that in the first stage, the GA metaheuristic consistently delivers highly efficient routes in each run, confirming that the combinatorial complexity of the problem is effectively resolved in this initial phase. These results were validated on Mandl's Swiss Road network, showing superior solutions compared to those presented in previous studies. Notably, the execution time for this process is only 35 minutes.

Assessing the Hierarchical Diversity of Public Transportation Considering Connectivity and Its Implication on Regional Sustainability

Given a decreasing and aging population, there is a growing need to establish convenient public transportation systems that offer a variety of transportation modes seamlessly connected to one another. This study attempts to develop an index to assess the hierarchical diversity of public transportation, drawing an analogy between public transportation networks and ecosystems. By considering both hierarchical (meta-physical) and physical connections among respective modes, which are aspects that have not been addressed in previous studies, this study aims to enhance the spatial resolution of the analysis units in the index. The diversity indices were applied to the northern Osaka area in Japan as the study site. The results show a correlation between the diversity index, population, and public transportation modal share. We then discuss the influence of hierarchical diversity on the sustainability of public transportation systems and regional development.

The performance of the digital city projects in urban studies of the megalopolises (the case studies of Kharkiv and Dnipro cities)

Introduction of the research problem. Urbanization drives Digital City Projects (DCPs) to create smarter urban environments using advanced technologies. DCPs aim to make cities more connected and responsive, adapting to changing needs. The objective of this paper is to evaluate the performance of DCPs in megalopolises, focusing on Kharkiv and Dnipro in Ukraine. The previous works done. The various literature sources demonstrate the rise of Digital Cities stemming from Smart Cities. Kharkiv and Dnipro in Ukraine exemplify digitalization's role amid Russian aggression. Exposition of the main research material. The performance of the theoretical urbogeosystemic approach and its UOM in the provision of practical Digital City projects. This subsection delves into the practical application of the urbogeosystemic approach and its Urban Ontological Model (UOM) in DCPs. The UOM guides urban studies by defining components and relationships. Implementing DCPs begins with building simulation models using LiDAR data. Case Study First - Kharkiv: A feasible perspective of a full-format DCP implementation. This subsection discusses implementing a DCP in Kharkiv, emphasizing data integration from OpenStreetMap (OSM) and LiDAR. The authors propose that a DCP should serve as a comprehensive model of a real city, encompassing all its structural elements and key objects, going beyond the capabilities of a typical GIS project. Possible user’s scenarios include energy consumption analysis, population estimation, and visibility gradients assessment. The subsection highlights the comprehensive DCP approach with LiDAR data processing software (iQ City CCM) and urban geosituational analysis. Case Study Second - Kharkiv: a perspective of geomarketing within the “Digital Kharkiv” project as a routine GIS one. This subsection delves into the integration of geomarketing into the "Digital Kharkiv" project. Geomarketing plays a pivotal role in mapping socioeconomic elements tied to market interactions. "Digital Kharkiv," primarily sourced from OSM data, is lauded for its versatility in urban studies during peacetime and war. The text urges exploration of geomarketing within "Digital Kharkiv" in the context of post-Russian aggression rehabilitation, particularly in optimizing humanitarian object placements. Changes in geomarketing potential pre- and post-invasion in various city districts have been analyzed, highlighting areas with stagnation and those witnessing growth due to population resettlement. Case Study Third - Dnipro: implementation of a typical GIS-project for analyzing provision of the city population with public transportation infrastructural networks. This subsection discusses the implementation of the "Digital Dnipro" project as part of the DCP framework. The project focuses on analyzing the provision of public transportation networks in the city of Dnipro. It utilizes data from OSM to create a virtual model of the city, which includes attribute information for urban objects. This subsection also highlights the impact of war on urban planning and the need for sustainable updates to adapt to changing conditions. Conclusion. This section summarizes the key findings and takeaways from the research on DCPs in Ukrainian cities like Kharkiv and Dnipro. It highlights the importance of an urbogeosystemic approach in implementing DCPs effectively. The study emphasizes the flexibility and efficiency of the relevant GIS tools in urban research and transformation.

Performance of Public Transport Appraisal using Machine Learning

Public passenger transport holds immense significance in the overall transportation system. Forecasting the movement of public transport has emerged as a crucial problem in transport planning due to its practical implications. Recently, there has been a lot of significant attention in Intelligent Transportation Systems (ITS), introducing various advancements and innovative applications to develop conditions for public transit that are safer, more effective, and fun. To fully leverage the potential of ITS applications and deal with road situations proactively, it becomes crucial to have a reliable method for predicting traffic flow. This opens up opportunities for ITS applications to anticipate and address potential challenges in advance. Enhancing the efficient functioning of Public Transport (PT) networks is a primary objective for urban area authorities, and the proliferation of location and communication devices has led to an abundance of operational data. Applying appropriate Machine Learning (ML) methods can help identify patterns in the data to improve the Schedule Plan. This research focuses on heterogeneous information that influences the prediction value, aiming to predict the required transport demand for specific routes and the arrival time of public transport. Utilizing DBSCAN clustering with SARIMA Algorithm, real-time passenger demand forecasting is extensively promoted to enhance dynamic bus scheduling and management. Furthermore, this paper compares the accuracy of the proposed Prophet Model with traditional time series models like ARIMA and SARIMA. The aim is to provide precise and robust passenger demand predictions, enabling more effective planning and management of PT services.