Public Transport Routes Research Articles

Analysis of the Performance of the City Transport Route Network System (AKDP) in Gorontalo Province, Indonesia

This study evaluates the performance of the intercity public transportation route network system (AKDP) in Gorontalo Province, Indonesia, with a focus on aspects of service coverage, overlap, density, and route network deviations. Data were obtained through field surveys. The research method includes spatial analysis using Geographic Information Systems (GIS) to evaluate the coverage and distribution of routes, as well as statistical analysis to measure the density and ratio of routes based on operational data and field surveys. The research results show that the coverage of route services is not yet even, with some areas being underserved. Route overlaps were identified on several main corridors, resulting in operational inefficiencies. The density of the routes shows significant variation, with some routes experiencing overcrowding while others are underutilized. The route ratio also shows an imbalance between the number of vehicles and passenger needs. Deviations from the established route plan were also found, which could potentially reduce service reliability. Based on these findings, it is recommended to restructure the route network and improve operational management to enhance the efficiency and quality of transportation services in Gorontalo Province.

A study of short-term passenger flow forecasting for public transportation based on the time series method

Abstract. In order to solve the conflicts between the supply and demand of urban transport, improve the living standard of urban residents, raise the level of urbanization, and promote the sustainable socio-economic development of the whole city, it is necessary to increase the pace of urban transport construction, planning and management in China. And at the same time, its necessary to take various measures to regulate the structure of urban transport and guide urban transport to develop in the direction of taking public transport as the mainstay. The experience of the development of urban transportation in China and abroad also proves that prioritizing the development of public transportation is the fundamental way to solve the problem of urban transportation. Public transport passenger flow data is the basis for optimizing public transport operations and scheduling. Accurate passenger flow forecasts on public transport routes can effectively guide public transport operation decisions, formulate operation scheduling plans and effectively improve the operational efficiency of the public transport system. The following are some of the key factors that can be taken into consideration when making passenger flow forecasts. The main contribution of this article is to propose the use of data mining technology, use bus IC card data and bus GPS data to integrate and organize them, conduct correlation analysis on the data, and on this basis, obtain the main distribution characteristics of bus passenger flow, and provide short-term Passenger flow forecast provides relevant ideas.

Will new tram lines enhance the connectivity and walkability? A case study of Sakarya

<p>This study investigates the impact of planned tram lines on walkability and accessibility in Sakarya, utilizing Geographic Information Systems (GIS) for spatial analysis. The research evaluates the catchment areas of proposed tram stops, assessing their suitability and coverage, and examines how these areas integrate with existing public transport routes. By calculating time-oriented catchments for 5, 8, and 10-minute walking distances, the study identifies service gaps and redundancies in the public transport network. The findings reveal that the new tram lines will enhance accessibility by extending coverage to high-density areas and potentially reducing the demand on existing bus services. The analysis also highlights the overlap between bus transit lines and tram stops, suggesting optimizations to improve network efficiency. The results offer valuable insights for urban planners, aiming to optimize Sakarya’s public transport system to be more inclusive and sustainable. This study contributes to urban mobility planning by providing a detailed understanding of how new tram lines can improve connectivity and support sustainable urban development.</p>

Exploring Hybrid Vehicle Integration in Nablus Urban Shared-Taxis: Cost-Benefit and Exhaust Emissions Assessment

There is a worldwide concern about the increase in vehicles’ exhaust emissions of traditional fuels and the rise in fuel prices. Nablus city is a major city in the West Bank, Palestine with peculiar topography and traffic congestion. This increases fuel consumption and the gas emission of the diesel operated public transport (PT) shared-taxi vehicles. This paper investigates the viability of introducing hybrid vehicles to the urban shared-taxis in highly congested areas with peculiar topography. Interviews were conducted and questionnaires were distributed among PT drivers and route managers to obtain the operational and cost characteristics of each route. The existing expenses and revenues and gas emissions of diesel vehicles were analyzed. Expenses-revenues analysis revealed that there is no immediate urgency in switching all diesel-fuel shared-taxis to hybrid; therefore, two scenarios were developed. The first was replacing old PT cars (2009 or older) with hybrid vehicles, which provided an average financial saving of 20.9% with a reduction in exhausts emission of CO2-equivalent by 33%. The second scenario included replacing PT vehicles with production dates from 2009-2014, which produced financial savings of 15% and reduction of exhaust emissions by 35%. The comparison showed a preference for the first scenario at the current time, while implementing other scenarios gradually. The first scenario is simple and close to reality; as old vehicles should typically be replaced. The study recommends using hybrid vehicles for new shared-taxis introduced to the service, and establishing national level policies to encourage the use of alternative fuels for the transportation sector, focusing on PT. However, several critical factors must be considered, including topography and route characteristics.

Green commuting within the x-minute city: Towards a systematic evaluation of its feasibility

In cities, carbon emissions associated with commuting transport is large and significant. This study integrates data about the jobs-housing relationship, road network configurations, public transport availability, and real-time traffic conditions during peak hours to evaluate the commuting feasibility and performance of green travel modes (walking, cycling and public transport) and explore the potential determining factors. In the context of the x-minute city, the green travel commuting feasibility (GTCF) indicator measures the percentage of the working population who can commute via green travel modes within specific x-minute thresholds. 15, 30, 45 and 60 min have been considered. In comparison, the car travel commuting feasibility (CTCF) indicator is developed to evaluate the corresponding commuting performance by car. Nanshan district of Shenzhen in China is taken as a case study. Results show that distinct gaps exist between GTCF and CTCF. Public transport performs well only for long-distance (> 8 km) commuting trips, and cycling does well for short (< 3 km) and medium-distance trips. Geographically, areas with large differences of GTCF and CTCF are identified for improving green travel modes with priority. Potential factors influencing GTCF are explored with a regression model and case-based analysis. Smaller street blocks, bus route realignment and better jobs-housing balance should be targeted. Designing cycling short-cuts and public transport routes that avoid traffic jams are also recommended to promote green commuting. The findings demonstrate that real-time trip-planning information is of great value in evaluating the commuting feasibility of multimodal travel and identifying influential factors for achieving the x-minute city.

Implementation of smart mobility and relationship with transportation planning and regional development: A case study of South Tangerang city

Urbanization and suburbanization have led to high population growth in certain city regions, resulting in increased population density and mobility. Therefore, there is a need for a concept to address congestion, public transportation, information and communication systems, and non-motorized vehicles. Smart mobility is a concept of urban development as part of the smart city concept based on information and communication technology. Through this concept, it is expected that transportation services will be easily accessible, safe, comfortable, fast, and affordable for the community. This research aims to analyze smart mobility and its relationship with regional transportation planning and the development of South Tangerang, as well as to design a policy strategy model for the planning and development of South Tangerang with smart mobility. The research method used in this study is a mixed method, including analyzing the relationships and weighting of relationships between variables using the Cross Impact Multiplication applied to a classification (MICMAC) matrix. Multi-criteria decision analysis (MCDA) with Promethee software is also used to obtain the necessary policies. The results of this research indicate that the measurement of relationships between variables shows that smart mobility influences regional transportation planning, smart mobility affects regional development, and regional planning affects regional development. This research also provides alternative policies that policymakers should implement in a specific order. First, ensure the availability of public transportation; second, improve public transportation safety; third, enhance public transportation security; fourth, improve public transportation routes; fifth, provide real-time information access; sixth, improve transportation schedules; and seventh, increase the number of bicycle lanes.

A comparison of meta-heuristic and hyper-heuristic algorithms in solving an urban transit routing problems

&lt;p class="p1"&gt;Public transport is a serious problem that is difficult to solve in many countries. Public transport routing optimization problem also known as urban transit routing problem (UTRP) is time-consuming process, therefore effective approches are urgently needed. UTRP aims to minimize cost passenger and operator from a combination of route set. UTRP can be optimize with heuristics, meta-heuristics, and hyper-heuristics methods. In several previous studies, UTRP can be optimized with any meta-heuristics and hyper-heuristics methods. In this study we compare the performance of meta-heuristic methods, i.e. ill-climbing, simulated annealing, and hyper-heuristics method based on modified particle swarm optimization algorithm. The experimental results showed that the proposed methods could solve UTRP effectively. Regarding their performance, the results show that despite the generality of hyper-heuristics, their performance are competitive. More specifically, hyper-heuristics method is the best method compared to the other two methods in each dataset. In addition, compared to prior studies results, he proposed hyper-heuristics could outperform them in term of cost passenger of small dataset Mandl. The main contribution of this paper is that to best of our knowledge, it is the first study comparing the performance of meta-heuristics and hyper-heuristics approaches over UTRP.&lt;/p&gt;

Evaluation of Public Transportation System through Social Network Analysis Approach

In response to the phenomenon of global warming, the transportation sector aims to mitigate carbon emissions by promoting the use of public transportation. This study employs social network analysis to propose effective improvements to the public transportation system, focusing on bus stop locations and route networks in Hwaseong City, South Korea. Two networks were constructed based on existing public transportation routes and usage data at each bus stop. The findings and implications are as follows: Analyzing the public transportation network from a network perspective can effectively contribute to improving the public transportation network route system. By evaluating centrality and brokerage for the existing routes, it is possible to identify inefficient routes and develop efficient route modification plans. Based on actual usage patterns, excessive bus supply and unnecessary bus stop locations can be identified, allowing for the establishment of appropriate operational plans. This can lead to improved operational efficiency and cost savings. Rational route design and operational planning can enhance public transportation services and promote increased use of public transportation. Ultimately, this contributes to sustainable development through carbon reduction in the transportation sector.

A novel choice model combining utility maximization and the disjunctive decision rules, application to two case studies

Most choice models, e.g. Multinomial Logit (MNL), rely on random utility theory, which assumes that a compensatory utility maximization decision rule explains an individual’s choice behaviour. Research has shown, however, that behaviour is sometimes better explained by non-compensatory decision rules. While some research has used Latent Class Choice Models (LCCMs) to account for multiple decision rules, many of them – such as the disjunctive rule – have yet to be explored. This paper formulates, estimates, and evaluates a LCCM that combines the MNL with a Generalised Random Disjunctive Model (GRDM), a new choice model we develop. Addressing deficiencies of existing disjunctive choice models, the GRDM allows for relative importance between attributes and is insensitive to irrelevant attributes. Unlike most non-compensatory models, it is tractable and incorporates random error terms for capturing unobserved heterogeneity across choice situations. The GRDM can be expressed as a Universal Logit (UL) model, which helps derive welfare metrics such as Marginal Rates of Substitution and elasticities and makes it possible to estimate the model with traditional software packages. The LCCM combining the GRDM and the MNL is estimated in two large-scale case studies: cyclists’ route choice and public transport route choice. Results are compared with other relevant LCCM specifications and the individual choice models, where it is found that the MNL + GRDM LCCM provides the best fit to the data. We also interpret the fitted parameters and calculate the Marginal Rates of Substitution, which align with behavioural expectations.

Дослідження процесу перевезення пасажирів з моделюванням роботи зупинок громадського транспорту

Public transport is characterized by its accessibility and sharing and is intended for a wide range of people, regardless of social status or income. The main function is to provide the ability to move people from one place to another within the city. Bus stops are a strategic place to ensure territorial accessibility from central to peripheral neighborhoods. They maintain order and organization in the operation of public transport. It is the study of the network of public transport routes and stops that is crucial for improving the quality of service, increasing the efficiency of transport systems and ensuring convenience for users. However, in each case, it is necessary to use an individual approach to organizational and planning decisions. The article describes the peculiarities of the functioning of public transport in the city of Dubno, Rivne region, in the context of research on infrastructure, route network, passenger flow, location and modeling of stops, taking into account the future development of new neighborhoods. It was found that the route network in Dubno includes 22 public transport routes with 64 stops. On average, 19544 passengers use public transport and get off at bus stops every day - 54% of all city residents. The rapid development of the city requires the arrangement of new public transport stops with changing routes, the operation of which in the overall transportation system was investigated by simulation modeling. The results obtained will make it possible to develop schedules and routes for public transport and to perform technical and economic calculations for the modern arrangement of stops. The research reported in this article was conducted at the National University of Water and Environmental Engineering with the support of the Department of Economics and Property of the Dubno City Council.

Urban Mobility Pattern Detection: Development of a Classification Algorithm Based on Machine Learning and GPS.

This study introduces an innovative algorithm for classifying transportation modes. It categorizes modes such as walking, biking, tram, bus, taxi, and private vehicles based on data collected through sensors embedded in smartphones. The data include date, time, latitude, longitude, altitude, and speed, gathered using a mobile application specifically designed for this project. These data were collected through the smartphone's GPS to enhance the accuracy of the analysis. The stopping times of each transport mode, as well as the distance traveled and average speed, are analyzed to identify patterns and distinctive features. Conducted in Cuenca, Ecuador, the study aims to develop and validate an algorithm to enhance urban planning. It extracts significant features from mobility patterns, including speed, acceleration, and over-acceleration, and applies longitudinal dynamics to train the classification model. The classification algorithm relies on a decision tree model, achieving a high accuracy of 94.6% in validation and 94.9% in testing, demonstrating the effectiveness of the proposed approach. Additionally, the precision metric of 0.8938 signifies the model's ability to make correct positive predictions, with nearly 90% of positive instances correctly identified. Furthermore, the recall metric at 0.83084 highlights the model's capability to identify real positive instances within the dataset, capturing over 80% of positive instances. The calculated F1-score of 0.86117 indicates a harmonious balance between precision and recall, showcasing the models robust and well-rounded performance in classifying transport modes effectively. The study discusses the potential applications of this method in urban planning, transport management, public transport route optimization, and urban traffic monitoring. This research represents a preliminary stage in generating an origin-destination (OD) matrix to better understand how people move within the city.

Efficient and Exact Public Transport Routing via a Transfer Connection Database

Efficient and Exact Public Transport Routing via a Transfer Connection Database

ХАРАКТЕРИСТИКА МАРШРУТНОЙ СЕТИ ОБЩЕСТВЕННОГО ТРАНСПОРТА ГОРОДА БАРНАУЛА

The development of a city is closely related to the state of its transport system and the spatial organization of urban public transport. In general, a number of transport problems can be noted for the city related to the waiting time for transport, the provision of various areas with urban public transport routes, etc. These problems have become particularly relevant in the 21st century and have become very actively discussed. The article is devoted to the analysis of the route network of the city of Barnaul, as well as the number of rolling stock on the routes. Particular attention is paid to routes where there is a shortage of rolling stock. The purpose of the work is to analyze the current state of the route network of the city of Barnaul and identify problems. The main methods were literature analysis, as well as monitoring public transport using the 2GIS service. In general, it can be noted that the city’s public transport runs stably and interruptions occur due to weather conditions (in particular freezing) or traffic situations (congestion in the morning and evening); there is also a dependence of preferential traffic to the city center and from the city center to depending on the time of day.

Streets classification models by urban features for road traffic noise estimation

Road traffic is the primary source of environmental noise pollution in cities. This problem is also spreading due to inadequate urban expansion planning. Hence, integrating road traffic noise analysis into urban planning is necessary for reducing city noise in an effective, adaptable, and sustainable way. This study aims to develop a methodology that applies to any city for the stratification of urban roads by their functionality through only their urban features. It is intended to be a tool to cluster similar streets and, consequently, traffic noise to enable urban and transportation planners to support the reduction of people's noise exposure. Three multivariate ordered logistic regression statistical models (Model 1, 2, and 3) are presented that significantly stratify urban roads into five, four, and three categories, respectively. The developed models exhibit a McFadden pseudo-R2 between 0.5 and 0.6 (equivalent to R2 >0.8). The choice between Model 1 or 2 depends on the scale of the city. Model 1 is recommended for developed cities with an extensive road network, while Model 2 is most suitable in intermediate and growing cities. On the other hand, Model 3 could be applied at any city scale but focused on local management of transit routes and for designing acoustic sensor installations, urban soundwalks, and identification of quiet areas. Urban features related to road width and length, presence of transport infrastructure, and public transport routes are associated with increased traffic noise in all three models. These models prove useful for future action plans aimed at reducing noise through strategic urban planning.

Passenger valuation of interchanges in urban public transport

Understanding how passengers perceive public transport interchanges is important to better explain current public transport mode and route choice behaviour and to better predict future demand levels. In this study we derive how passengers value a public transport interchange in a metropolitan context entirely based on recent, large-scale, Revealed Preference data, explicitly distinguishing between different types and modes of public transport interchanges. For this purpose we estimate three discrete choice models using maximum likelihood estimation, based on over 26,000 passenger route choices observed in June 2023 in the Greater London Area. We find that each public transport interchange is on average valued equivalent to 5 min uncrowded in-vehicle time. Additionally, our model results provide quantitative evidence that cross-platform interchanges between two metro journey legs are valued 20–25 % less negatively than a regular metro interchange where a level change is required. Multimodal bus-metro interchanges and out-of-station interchanges are perceived most negatively by passengers. Passengers value bus-bus interchanges on average about 60 % more negatively than metro-metro interchanges, possibly driven by factors such as comfort, service frequency, reliability and (perceived) safety. Our study results can be used for business case and appraisal purposes, when quantifying the impact of service changes which affect the number or type of interchanges.

Automation proposal applied to Trolleybus current collector

Automation proposal applied to Trolleybus current collector

Simulation of Transfer Probability in the City Route Network: Case Study of Lviv, Ukraine

The correct organization of transfers in the public transport system allows to reduce the congestion of the route network while maintaining a sufficient level of service quality for users of transport services. When modelling the probability of transfer, it is advisable to separate the probability of a public transport user choosing a trip with a transfer and the probability of making a transfer at a certain stop of the public transport system. The first probability largely depends on the socio-economic characteristics of the passenger and the time parameters of the trip. The probability of transfer at a certain stop is affected by the information provision of the stop and the number of routes. The general configuration of the route network determines the "basic need for a transfer in the network" - the ratio of the number of pairs of transport zones between which there is no direct public transport route to the total number of pairs of transport zones. The simulation carried out in the PTV Visum software environment for Lviv city made it possible to assess the impact of the tariff system on the change in the number of transfers and to determine critical stops and routes of the network. The inclusion of data on the structure of the city's population in the model makes it possible to use mathematical functions of the probability of transfer on the socio-economic characteristics of the passenger (age, gender, income level) when calculating the forecast number of transfers on the network.

Smart City Public Transportation Route Planning Based on Multi-objective Optimization: A Review

Smart City Public Transportation Route Planning Based on Multi-objective Optimization: A Review

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.

Urban Mobility Analysis Using Geospatial Analysis

This project proposes a method to analyze the traffic and urban mobility of a locality with advanced visualization and understanding mechanisms. urban areas worldwide face escalating challenges in managing transportation systems efficiently. This research delves into the realm of urban mobility analysis, leveraging geospatial data to extract insightful patterns and trends. The project aims to contribute a comprehensive understanding of the dynamics governing urban transportation, enabling informed decision- making for city planning and infrastructure development. The methodology encompasses the collection of extensive geospatial datasets, including traffic flow, public transportation routes, and demographic information. Utilizing advanced geospatial analysis techniques, such as Geographic Information Systems(GIS) and spatial analytics, the study explores spatial-temporal patterns of traffic congestion, public transit usage, and pedestrian movement. Machine learning algorithms are employed to predict future mobility trends and assess the impact of potential interventions. The findings of this research offers valuable insights for urban planners, policymakers, and transportation authorities. By identifying key bottlenecks, optimizing transit routes, and understanding the interplay between land use and growing populations and foster sustainable urban development. This project not only contributes to academic understanding of urban mobility but also provides actionable recommendations for creating smarter and resilient cities. The integration of geospatial analysis techniques in urban planning emerges as a powerful tool to address the complexities of modern urban transportation systems. Keywords: informed decision-making, geospatial data, Geographic Information System(GIS), spatial analysis, sustainable urbandevelopment.