Urban Transportation Planning Research Articles

Big data in transportation: a systematic literature analysis and topic classification

AbstractThis paper identifies trends in the application of big data in the transport sector and categorizes research work across scientific subfields. The systematic analysis considered literature published between 2012 and 2022. A total of 2671 studies were evaluated from a dataset of 3532 collected papers, and bibliometric techniques were applied to capture the evolution of research interest over the years and identify the most influential studies. The proposed unsupervised classification model defined categories and classified the relevant articles based on their particular scientific interest using representative keywords from the title, abstract, and keywords (referred to as top words). The model’s performance was verified with an accuracy of 91% using Naïve Bayesian and Convolutional Neural Networks approach. The analysis identified eight research topics, with urban transport planning and smart city applications being the dominant categories. This paper contributes to the literature by proposing a methodology for literature analysis, identifying emerging scientific areas, and highlighting potential directions for future research.

Emission calibrated traffic model for environmental-sensitive decision making in Sri Lanka: Review

Air pollution from road transportation is a growing concern in urban areas, particularly in Sri Lanka, where vehicle emissions account for a significant portion of air pollutants. The increase in the number of vehicles on the road and the resulting traffic congestion exacerbate this problem. Therefore, accurate prediction of emissions and air quality related to road traffic is essential for informed decision-making in traffic planning and management. While Sri Lanka has made progress in developing driving cycles and traffic flow simulations tailored to its unique context, there remains a gap in calibrating these models with local emission values, which are influenced by specific driver behaviours and operational modes. An emission-calibrated traffic model specific to the Sri Lankan context can integrate both traffic-related and environmental factors, providing a comprehensive tool for analyzing the impact of traffic management strategies on emissions and air quality. By addressing the discrepancies between global manufacturer data and local conditions, this model can enable more environmentally friendly decisions in urban transportation planning, contributing to the reduction of air pollution. The study identifies, through a comprehensive review, the need for an emission-calibrated traffic model to address the unique challenges posed by Sri Lanka's evolving traffic landscape. While traffic modelling has made strides in Sri Lanka, this study identifies a significant research gap in modelling the emissions generated by these traffic models, especially considering the unique characteristics of the region's roads and vehicles. Further, the paper concludes that an emission-calibrated traffic model specifically tailored to the Sri Lankan context is essential to guide environmentally friendly traffic planning decisions and bridge the gap between traffic data and its environmental consequences.

Causal inference of Seoul bike sharing demand

The global surge in environmental consciousness has significantly boosted the demand for rental bikes, particularly in metropolitan areas such as Seoul. This study delves into the causal relationships affecting this demand using a dataset from Seoul’s bike-sharing system. Unlike previous research focusing predominantly on predictive analytics, this work innovatively applies multiple linear regression models to uncover causal inferences, offering insights that extend beyond mere forecasting. The challenges addressed include dealing with non-linear relationships and heteroscedasticity by employing the logarithmic transformation of rental counts. This approach not only aids in normalizing the data but also enhances the interpretability of the regression outcomes, emphasizing the changes in demand as a function of various environmental and temporal variables. Recent developments in causal inference methodologies have allowed for more robust and detailed analysis, paving the way for this study’s contribution to the field. The findings underscore the significant influence of factors such as hour of the day, humidity, and seasonal changes on bike rental volumes, which can inform policy-making and operational strategies in urban transport planning.

Development of a Method for Assessing the Quality of Public Transport Services within Urban Transportation Planning Systems

Development of a Method for Assessing the Quality of Public Transport Services within Urban Transportation Planning Systems

Exploring the Landscape of Autonomous Vehicles Research: A Scientometric Analysis in the Context of Urban Transportation Planning

Exploring the Landscape of Autonomous Vehicles Research: A Scientometric Analysis in the Context of Urban Transportation Planning

Traffic modeling and accidental data analysis using GIS: A Review

Nowadays, congestion and accidents are creating major risks to cities, including delays, higher fuel usage, and compromised safety. Effective traffic modelling and accident data analysis are critical for identifying high risk identifying accident-prone locations, understanding the causes of accidents and creating focused actions to enhance traffic flow and safety. GIS is an effective tool for integrating, analysing and visualizing different geographical data relevant to transportation networks such as, traffic flow, infrastructure, and safety. It enables geographical analysis and visualization of accident hotspots by integrating accident data, road conditions, traffic numbers, and environmental factors. The use of GIS in traffic modelling and accident data analysis provides considerable benefits in urban transportation planning and management. The aim of the paper is to provide an overview of the application of GIS in traffic modelling and accidental data analysis, highlighting the methodologies, advancements, and challenges in this field. The review shall provide a comprehensive assessment of the current state of traffic modelling and accidental data analysis using GIS. It will highlight the significant contributions of GIS technology, identify key research gaps, and offer insights into future directions for enhancing transportation planning and decision-making processes.

Urban Transportation Planning in the Perspective of Public Health in the City of Jakarta, Indonesia

Public health is one of the basic sectors that are influenced by transportation. Public health factors related with transportation performances are environmental quality, people access to health facilities, traffic safety, mode choice and its relationship with health, and disease spreading risk. Based on the case of Transportation Master Plan (Rencana Induk Transportasi Jakarta, RITJ) of Capital Jakarta, Indonesia, this paper explores the topic of how adequate urban transportation planning in Indonesia accommodate health factors in its process and substance. This study takes quantitative method to identify Jakarta transportation condition in relation with health sector and to understand to what extent transportation planning accommodate health factors. Qualitative method is also used to analyze people perception regarding the level of the transportation planning process in accommodating their interest in health. The research concludes that the negative impact of transportation activities to the health sector in Jakarta such as air pollution, traffic accident, and passive mode choice are still high. The RITJ planning process did not accommodate urban health criteria adequately. This paper suggests a better transportation planning to assure adequate accommodation of urban health criteria both in its process and substances.

Characterising travel behaviour patterns of transport hub station area users using mobile phone data

Understanding the travel behaviour of transport hub users is vital for improving transport services. Although previous research has explored passenger behaviour in and around transport hubs, there is a lack of comprehensive studies on travel patterns within hub station areas. To this end, this study harnessed mobile phone data to analyse the travel behaviour within a hub station area, using Beijing South Railway Station as a representative case. A series of recognition criteria was set up based on spatio-temporal information to categorize users within the station area. We categorised station area users into transport hub users (THU) and non-transport-hub users (NTHU) and examined their distinct travel patterns. The results reveal distinct travel patterns for THU and NTHU. NTHU are predominantly concentrated in and around the station area. THU, however, display longer trip distances and more widely distributed endpoints. In terms of travel time distribution, NTHU show evident morning and evening peak phenomena, while the travel time distribution of THU fluctuates throughout the day. The study also employed association rule analysis to illustrate strong connections between the station area, Beijing's core, central areas, and even urban fringe areas. The results reveal that the station area is most closely connected to the core and central areas of Beijing, from where many users are attracted to the station area. In addition, some urban fringe areas also have strong connections with the station area. These findings inform urban transport planning and personalised travel services.

The role of traffic flow modeling in solving current problems of transport planning in Ukraine

The main current problems of the transport and planning infrastructure of Ukraine are identified. A brief description of traffic flows as an object of the street-road network is given including all off the factors that are affecting its functionality and the main reasons for the difficulty of studying them are listed and divided in. Modelling is proposed as one of the most effective tool in dealing with modern traffic problems with application of informational technologies. A brief history of the development of urban transport planning and modelling is given, highlighting its four most significant time periods with the description of notable changes during that time. Description of basic principles of transport modelling is structured and formalized. Four-stage computerized transport model is highlighted as the most common used and flexible, its basic assumptions and principles is mentioned. Various transport modeling techniques are proposed for consideration as one of the ways to aid in traffic flows managing. Definition of macromodelling, micromodelling, mesomodelling with its area of research, types of problems it is used to solve, basic advantages and disadvantages is given. The main software packages used today to solve various transport and planning tasks are listed, divided by the level of modelling it is capable to effectively perform. The main transport modelling software packages development companies is named with mentioning of its country-of-origin year of establishing and the most popular products. Along with that, a brief overview for the company's production is given taking into account their advantages and disadvantages and ability to be capable of working in different modelling levels at the same time. Conclusions are drawn summarizing the modern state of urban transport modelling in Ukraine with application of classical paradigm of traffic flow management and regarding further directions of research in this area for the most optimal use of modeling in issues of transport planning, such as creati ng of hybrid systems that make it possible to simultaneously study various characteristics of traffic flows at several levels of abstraction.

Exploring the Influences of Safety and Energy Expenditure Parameters on Cycling

Several determinants affect the reason to cycle or not, and some of them are described in a detailed way in the current technical literature review. The recent spread of new modes of active mobility brings up questions for urban transport planners on how to foresee future demand and assess safety conditions; from this comes the need to explore the relationships among several determinants. In this paper, after the collection of the main data required, three Regression Models are proposed, which demonstrate evidence for the role of safety and energy expenditure issues as important predictors. The method is applied to a dataset of 90 Italian cities selected according to their class of dimensionality and geographical position. The three models for each class of dimensionality (50,000–100,000 no. of inhabitants, 10,000–50,000 no. of inhabitants, and 0–10,000 no. of inhabitants) show a good accuracy (in terms of adj-R2 values of 0.6991, 0.7111, and 0.6619, respectively). The results show that energy expenditure, which is related to the terrain characteristics of an urban area and individual aerobic abilities, and safety perception, which is related to cycle network extensions, appear to be significant determinants in predicting bicycle modal share. The aim is to provide a useful and simplified tool, when only aggregated-type data are available, to help urban road designers and city planners in identifying and forecasting bike-sharing.

Introducing a Novel Framework for the Analysis and Assessment of Transport Projects in City Regions

A profound appraisal framework has been developed and refined in transport economics and planning literature for decades, mainly characterised by welfare economic theory, cost–benefit analysis, and transport demand modelling. In summary, the appraisal methodology and its applications have concentrated on single infrastructure measures, marginal impacts identified through ceteris paribus comparisons, forecasts based on trends from the past, and monetary assessments of all quantifiable impacts. However, this framework has been continuously contested in transport planning literature, for instance, for its focus on travel demand and short-term travel time savings. Therefore, we suggest a novel approach for planning and assessing transport schemes in city regions, combining accessibility analyses, quantitative target indicators, and cost-effectiveness analysis. We develop and test this approach by assessing a proposed underground rail project in the Munich city region, the U5 southeast extension. In this case, we define an accessibility target level and estimate the potential for push measures along with the U5 project. We find modest impacts on quantitative targets in the Munich city region: Even when the U5 southeast extension is bundled with push measures in selected transport cells, the contribution to passenger transport-related carbon dioxide emission targets and primary energy consumption targets is low. Nevertheless, we demonstrate that the proposed assessment framework can support strategic transport planning in city regions. We argue for a change in perspective towards supply-side-oriented urban transport planning. Our proposed methodology is a first step in a different direction towards a sustainable mobility planning paradigm.

TRANSPORT POLICIES, TRANSIT-ORIENTED AND DEVELOPMENT REDISTRIBUTION OF POPULATION IN PERI-URBAN: LESSONS FROM KUALA LUMPUR AND JAKARTA METROPOLITAN AREA

Transit-Oriented Development (TOD) is the representation of a compact land-use management strategy relying on a mixture of land use and transport concepts to manage urban sprawl and population. The concept promotes high-density housing, mixed land use, and integrated mobility. Therefore, this article aims to discuss the incorporation process of TOD concept into urban policies and transport planning in Southeast Asian metropolitan cities. The effects of the policies on population movement patterns are examined, specifically in peri-urban areas, which are the most difficult parts of cities. In addition, the case studies include Jakarta and Kuala Lumpur, representing two of the most rapidly developing metropolitan areas in Southeast Asia where TOD has been progressively adopted. Data and information are collected from documentary reviews and interviews. The results show that the duration of TOD policy implementation gives rise to distinct trajectories in peri-urban population redistribution experiences within the two metropolitan areas.

Alternative prioritization for mitigating urban transportation challenges using a Fermatean fuzzy-based intelligent decision support model

Practitioners and decision-makers often face difficulties in selecting and prioritizing effective strategies to address challenges to sustainable urban transportation development. Although there has been considerable research conducted on the subject, the Tanzanian context, which is greatly affected by social and environmental problems, has received inadequate attention. Therefore, this study intends to bridge this gap by pinpointing the obstacles to sustainable urban transportation and proposing the most appropriate strategies to tackle them. The study proposes seven strategies and determines five criteria to prioritize them. To accomplish this, the study proposes a novel Fermatean fuzzy-based intelligent decision support model to assess the criteria weights and prioritizes strategies based on the weighted criteria. The study validates the proposed methodology by conducting a sensitivity analysis, which indicates that restricting car use (A5), improving sector coordination (A1), and conducting extensive research on transportation issues (A7) are the top three strategies for promoting sustainable urban transportation. The study’s findings hold significant value in providing urban transportation planners with helpful guidance to develop optimization techniques that can improve transportation systems.

Entropy-Based Node Importance Identification Method for Public Transportation Infrastructure Coupled Networks: A Case Study of Chengdu.

Public transportation infrastructure is a typical, complex, coupled network that is usually composed of connected bus lines and subway networks. This study proposes an entropy-based node importance identification method for this type of coupled network that is helpful for the integrated planning of urban public transport and traffic flows, as well as enhancing network information dissemination and maintaining network resilience. The proposed method develops a systematic entropy-based metric based on five centrality metrics, namely the degree centrality (DC), betweenness centrality (BC), closeness centrality (CC), eigenvector centrality (EC), and clustering coefficient (CCO). It then identifies the most important nodes in the coupled networks by considering the information entropy of the nodes and their neighboring ones. To evaluate the performance of the proposed method, a bus-subway coupled network in Chengdu, containing 10,652 nodes and 15,476 edges, is employed as a case study. Four network resilience assessment metrics, namely the maximum connectivity coefficient (MCC), network efficiency (NE), susceptibility (S), and natural connectivity (NC), were used to conduct group experiments. The experimental results demonstrate the following: (1) the multi-functional fitting analysis improves the analytical accuracy by 30% as compared to fitting with power law functions only; (2) for both CC and CCO, the improved metric's performance in important node identification is greatly improved, and it demonstrates good network resilience.

Transport-related social exclusion and mobility in developing countries: the South African case

IntroductionTransport-related social exclusion has been studied in many countries, and from many different perspectives. In Africa, however, there is little recent research into the phenomenon, even though African cities tend to have poor transport services, urban sprawl is extensive usually resulting in long travel times and high travel costs, and certain areas experience high levels of crime. By implication, there are several factors that impact the ability of people to access economic and societal opportunities, however these are not well documented. Building on previous work from several authors, this research sought to describe transport-related social exclusion in a large metropolitan area in an emerging economy.MethodsUsing a qualitative methodology, 60 interviews were conducted with City of Johannesburg residents. The data was analyzed using manual thematic and classic content analysis.ResultsThe study found that residents often did not have access to services due to availability, but also that economic, geographic and fear-based exclusion were particularly prevalent in the sample, although there were several other psychological exclusion dimensions, as well as information exclusion.DiscussionThis study is the first recent study in South Africa to consider a wide range of commuters from varying demographic strata, thus providing a novel perspective on TRSE in a major urban area in the country. The study recommends that policy actions be considered, taking into account the minibus taxi industry, which is often overlooked in government policy. TRSE should also be an inherent element in urban (and other) transport planning, as well as take into account the broader societal realities faced by citizens. Future research directions include conducting broader quantitative studies across a variety of urban areas in South Africa, and beyond, to determine specific TRSE dimensions in various urban areas. Policy analysis is also recommended, to determine TRSE policy gaps and align interventions with specific commuter needs.

Benchmarking the Functional, Technical, and Business Characteristics of Automated Passenger Counting Products

Urban transport planning and the integration of various mobility options have become increasingly complex, necessitating a thorough understanding of user mobility patterns and their diverse needs. This paper focuses on benchmarking different Automatic Passenger Counting (APC) technologies, which play a key role in Mobility as a Service (MaaS) systems. APC systems provide valuable data for analysing mobility patterns and informing decisions about resource allocation. Our study presents a comprehensive data collection and benchmark analysis of APC solutions. The literature review emphasises the significance of passenger counting for transport companies and discusses various existing APC technologies, such as pressure sensors, wireless sensors, optical infrared sensors (IR), and video image technology. Real-world applications of APC systems are examined, highlighting experimental results and their potential for improving accuracy. The methodology outlines the data collection process, which involved identifying APC companies, conducting interviews with companies and customers, and administering an ad hoc survey to gather specific information about APC systems. The collected data were used to establish criteria and key performance indicators (KPIs) for the benchmarking analysis. The benchmarking analysis compares APC devices and companies based on ten criteria: technology, accuracy, environment, coverage, interface, interference, robustness (for devices), price, pricing model, and system integration (for companies). KPIs were developed to measure performance and make comparison easier. The results of the benchmarking analysis offer insights into the costs and accuracy of different APC systems, enabling informed decision making regarding system selection and implementation. The findings fill a research gap and provide valuable information for transport companies and policy makers, and we offer a comprehensive analysis of APC systems, highlighting their strengths, weaknesses, and business strategies. The paper concludes by discussing limitations and suggesting future research directions for APC technologies.

Using mobile phone big data and street view images to explore the mismatch between walkability and walking behavior

Stimulating more citizens to walk plays an essential role in building a healthy city. This paper explores the mismatch between walkability and walking behavior, using mobile phone data, street view images, and various sources of open data. Using Shenzhen as our case study, we identified walking trips of 6 months in 2021 from cellular mobile data, taking the rule-based heuristics approach. We collected ground truth GPS data to validate the walking trip extraction method. Open data and deep learning enabled quantifying walkability from the perspective of four pedestrian needs: safety, convenience, continuity, and attractiveness. We employed geospatial techniques to identify the mismatch areas between walkability and walking behavior in the city. We also explored the spatially varying effects of walkability on walking behavior. Our results showed that the mismatch areas with high-level walking trips but low-level walkability mainly occurred in the fringe areas of the central business district (CBD) and subcenters that require prioritizing more interventions. Moreover, walkability showed strong effects on walking trips in the inner suburbs. For the four aspects of our walkability framework, safety and convenience had greater positive effects on walking trips in suburbs than in urban areas. Continuity promotes walking trips mainly in the city’s western sector. The positive effect of attractiveness on walking trips clustered in the central and western parts of the city. Based on the findings, we provide prioritized and contextualized built-environment intervention strategies and policy recommendations for urban designers and transportation planners.

Skotovoz, pripiski and the “law of labour settlement”: Transportation planning and management in the USSR

Transport specialists in the USSR persistently called for mathematical expressions of fundamental laws in urban transportation, to assist the development of efficient transportation systems. However, the specificity of the planned economy meant that these appeals did not receive substantial financial support. In response to challenges such as falsified data and political interference, practitioners developed an “imaginative” approach based on intuition, tradition and experience. Analysis of academic literature written in Russian, archival sources and new data gained from interviews shows that the demand for quantitative methods was a bureaucratic response to the uncertainties of public transport administration, while planning documents functioned as leverage in political bargaining for resources. In practice, urban transport planners and transport company employees relied on their own creativity and innovation to compensate for pervasive resource and methodological deficits.

Factors influencing the residential location choice of individuals working at an integrated township

The ‘Integrated Township Project’ is an urban development policy scheme by the Government of India to promote mixed land-use and result in reduced trip lengths. This study examines the prevalence of short work trip length scenario and the factors influencing the residential location choice at the Megapolis Township (MGT), Pune, India. The mean work trip length worked out from the trip data collected from individuals working at some of the employment centres in the MGT does not certify the short work trip length scenario as expected. With the help of a Stated Preference (SP) survey data administered on these individuals and the land-use data of Pune, a binary logit model is developed. Mixed land-use, house rental value, household size, and car ownership are found to be the significant factors influencing the residential location choice. This study infers that the promotion of mixed land-use through Integrated Townships coupled with the regulation of house rental prices within the townships can help in reducing work trip lengths. As an alternative to the regulation of house rental prices, provision of incentives to attract the individuals (working at various employment centres in the township) to reside within the township may help in reducing the work trip lengths and thus aid the process of sustainable urban land-use and transport growth. Hence, this study calls for necessary attention regarding the regulation of house rental values or alternative strategies at Integrated Townships to promote short work trip length scenario from policy makers involved in urban infrastructure and transport planning.

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.