Public Transport Stations Research Articles

The level of air quality at public transport stations: The Case of Torhailoch-Ayat main road in Addis Ababa

IntroductionThe increase of population and rapid spatial expansion of urban areas generate high travel demand and increase of motorization, which is directly related to air quality of urban environment. The continuous increase in traffic congestion and fuel consumption deteriorates air quality. Public transportation stations are places where people spend a considerable amount of time in the open and get exposed to transport-related emissions. The aim of this study is to investigate the level of air quality at public transport stations in Addis Ababa city along the major route from Torhailoch to Ayat focusing on the concentration of PM2.5, PM10, Air Quality Index (AQI) and CO2. Methods and materialsObservation, vehicle count and field measurements of air quality were used to collect the data. Primary data were collected via field surveying using IQAir AirVisual® pro model air quality measuring device from five public transport stations at peak and off-peak hours. ResultsThis study found that increase in peak hour traffic volume at stations contributes high concentration of PM2.5, PM10, AQI and CO2. High levels of air pollutants were found during peak hours compared to off peak hours. The maximum 30 min’ average concentrations of PM2.5 were found to be 89 μg/m3 during peak hours and 61 μg/m3 during off peak hours, which is far exceeding the WHO air quality standard (35.4 μg/m3). Regression model shows dependent variable (PM2.5) and independent variables is statistically significant. ConclusionThe temporal and spatial distributions of the air pollutants in this study demonstrated that rush hours were the most polluted, having high concentrations of PM2.5 and PM10 while an off-peak hour have low concentration of air pollutants. RecommendationIt is recommended that the city government should encourage zero emission vehicles, provision of efficient public transport and green development in order to reduce the current condition of transport-related air pollutants.

Evaluation of Public Transportation Station Area Accessibility Based on Walking Perception

Evaluation of Public Transportation Station Area Accessibility Based on Walking Perception

Methodology for public transport mode detection using telecom big data sets: case study in Croatia

Determining the number of passengers using public transport services is a challenging and time-consuming task that relies either on manual observations (e.g. manual counting passengers in vehicles or at stations) or the application of technical solutions (using data from automatic fare collection system (AFC) or automatic passenger counters (APC), which is characterized either by the provision of an incomplete picture (AFC) or by a solution which in practice is installed in a small number of vehicles if any (APC). The new approach which uses anonymized telecom-originated big data sets and data science principles can be used as a smart data driven approach for determining the use of public transport. Anonymized telecom big data sets represent “digital breadcrumbs” that people leave while moving through the city. When paired with additional data sets (e.g. public transport timetables, location of public transport stations, information on public transport lines, etc.), it can be used for modal split detection. In this paper, a new methodological approach is proposed that uses anonymized telecom big data sets and a statistical modelling approach to identify possible public transport trips among all other trips. This methodology has been tested in a case study in the City of Rijeka and validated using ground truth data obtained from traditional sources.

Air quality analysis on a frequently congested road section

This paper will focus on analysing the air quality on a frequently congested road section in the vicinity of Timisoara, Romania. The placement of the measurement equipment will be made next to a public transport station measuring the extent of different pollutants which affect the well-being of passengers waiting in these stations. The traffic congestion is present due to the unloading from the highway, reduced capacity of only a one lane road and because of the high amount of industrial area workplaces. The results presented will be part of the PhD thesis of the main author.

Urban expansion and differential accessibility by car and public transport in the Greater Kumasi city-region, Ghana—A geospatial modelling approach

There is a growing recognition of the worsening problems of accessibility in Africa's major urban centres and city-regions. Yet, research assessing differential accessibility in these contexts is limited, partly because of the lack of population and land-use data at granular spatial resolutions. In this paper, we contribute to addressing the existing challenges by presenting a geospatial modelling approach that combines historical urban physical development data extracted from Landsat satellite images, travel time data from Openrouteservice and Google Maps API services, and relevant transport infrastructure data. We apply the approach to analyse place-based (100 m2) accessibility in the Greater Kumasi city-region of Ghana. The analysis reveals a strong co-evolutionary relationship between physical development and geographical accessibility, with an estimated 83% of the emergent physical development located within half-a-kilometre distance of a primary road. First-and-last-mile accessibility in terms of walking time to public transport stations and public transport service routes are quantified. We reveal huge first-and-last-mile accessibility deficits, with an estimated 14% and 33% of the city-region's built-up area having a 5-minute and 10-minute walking time reachability to a public transport station, as a critical node of accessibility. Differential accessibility by car and public transport is analysed, focusing on the city-region's most important functional centre (i.e. CBD). The results show that the CBD is within 15 min and nearly 30 min reach by car and public transport respectively, for only 1% of the city-region's built-up area. This implies that overall accessibility is poor regardless of mode choice, due to congestion. The findings underscore the need for integrative urban development and accessibility planning in the city-region for equitable transport and mobility outcomes.

Park & Ride facilities and suburban sprawl

ABSTRACT This study investigates the effects of Park & Ride (P&R) facilities, which aim to increase the attractiveness of commuting by public transport, on population growth in suburban areas. We employ a difference-in-differences approach to parking capacity extensions of seven P&R facilities outside the central business district of the city of Vienna between 2012 and 2016. Specifically, using fine-grained grid population data, we compare population growth in close distance to the P&R facility to population growth in surrounding municipalities. We find that the expansion of a P&R facility, which is located at least 20 min away from a main public transport station in Vienna, causes population growth of, on average, 1.6–1.9% in neighbouring municipalities compared to those where the P&R facility is located. This accounts for up to 15% of the total population growth in the respective regions between 2008 and 2019 and highlights the role of P&R facilities in fostering suburbanization and the suburban sprawl.

A Spatiotemporal Study and Location-Specific Trip Pattern Categorization of Shared E-Scooter Usage

This study analyzes the temporally resolved location and trip data of shared e-scooters over nine months in Berlin from one of Europe’s most widespread operators. We apply time, distance, and energy consumption filters on approximately 1.25 million trips for outlier detection and trip categorization. Using temporally and spatially resolved trip pattern analyses, we investigate how the built environment and land use affect e-scooter trips. Further, we apply a density-based clustering algorithm to examine point of interest-specific patterns in trip generation. Our results suggest that e-scooter usage has point of interest related characteristics. Temporal peaks in e-scooter usage differ by point of interest category and indicate work-related trips at public transport stations. We prove these characteristic patterns with the statistical metric of cosine similarity. Considering average cluster velocities, we observe limited time-saving potential of e-scooter trips in congested areas near the city center.

Spatial Integration of Non-Motorized Transport and Urban Public Transport Infrastructure: A Case of Johannesburg

Sustainability of transport infrastructure integration begins with involving an all-inclusive transportation chain instead of only focusing on one part of the journey. This is achieved by facilitating spatial integration between diverse transport modalities to allow for a multiplicity of travel opportunities. This paper unpacks the extent of the spatial integration of non-motorized transport and urban public transport infrastructure within the city of Johannesburg in South Africa. Cycling activity datasets derived from Strava Metro and the spatial data of urban public transport infrastructures were collected to demonstrate existing spatial patterns and infrastructure connectivity. Exploratory spatial data analysis and focal statistics analysis were central in the data processing. The findings reveal that cycling activities are separated from urban public transport infrastructure, and the city of Johannesburg’s transport system is characterized by spatially fragmented commuting and cycling operations, with limited to no sharing of infrastructure. Most public transport stations are not easily accessible for non-motorized transport and are characterized by inadequate cycling facilities. In conclusion, the identification of an urban public transportation catchment area becomes essential for developing cities such as Johannesburg. This can be used as tool for planning infrastructural upgrades and forecasting potential public transport ridership while also assessing the impacts of investments in transit planning. There is thus a need to integrate motorized urban public transport and cycling infrastructural developments toward promoting multi-mobility and infrastructure sharing.

COVID-19 Risk Mapping with Considering Socio-Economic Criteria Using Machine Learning Algorithms.

The reduction of population concentration in some urban land uses is one way to prevent and reduce the spread of COVID-19 disease. Therefore, the objective of this study is to prepare the risk mapping of COVID-19 in Tehran, Iran, using machine learning algorithms according to socio-economic criteria of land use. Initially, a spatial database was created using 2282 locations of patients with COVID-19 from 2 February 2020 to 21 March 2020 and eight socio-economic land uses affecting the disease—public transport stations, supermarkets, banks, automated teller machines (ATMs), bakeries, pharmacies, fuel stations, and hospitals. The modeling was performed using three machine learning algorithms that included random forest (RF), adaptive neuro-fuzzy inference system (ANFIS), and logistic regression (LR). Feature selection was performed using the OneR method, and the correlation between land uses was obtained using the Pearson coefficient. We deployed 70% and 30% of COVID-19 patient locations for modeling and validation, respectively. The results of the receiver operating characteristic (ROC) curve and the area under the curve (AUC) showed that the RF algorithm, which had a value of 0.803, had the highest modeling accuracy, which was followed by the ANFIS algorithm with a value of 0.758 and the LR algorithm with a value of 0.747. The results showed that the central and the eastern regions of Tehran are more at risk. Public transportation stations and pharmacies were the most correlated with the location of COVID-19 patients in Tehran, according to the results of the OneR technique, RF, and LR algorithms. The results of the Pearson correlation showed that pharmacies and banks are the most incompatible in distribution, and the density of these land uses in Tehran has caused the prevalence of COVID-19.

If you build it, they will change: Evaluating the impact of commuter rail stations on real estate values and neighborhood composition in the Rotterdam–The Hague metropolitan area, the Netherlands

In many metropolitan regions, transit-oriented developments are built to motivate the use of sustainable travel by promoting urban growth within walking distances of public transport stations. Changes in residential property values are a common way to assess the success of transit-oriented developments. However, studies that focus on property values alone have reported mixed effects. This paper attempts to evaluate the land value impact around commuter rail stations by analyzing the change in property values within the context of the transformation of socio-spatial neighborhood attributes. The study sets out to estimate the effect of Randstad Rail stations using real estate transaction data of residential properties and neighborhood socio-spatial attributes in the Rotterdam–the Hague metropolitan area of the Netherlands covering a period from 1985 to 2018. Adopting a quasi-experimental design, the effect is estimated for properties within different catchment zones around three commuter rail stations using a Difference-in-Differences Model and Multivariate Analysis of Variance. The results demonstrate the overall negative effect of the Randstad Rail on the value of residential properties at a distance equal to or less than 400 meters from the selected rail stations in the range of -18.8% to -11.5%. In contrast, a positive effect is observed for the residential properties located within a radius of 400 to 800 meters from the rail stations, which is estimated to be +15% to +33.2%. The findings also indicate a considerable socio-spatial transformation in the neighborhood composition after the opening of the rail stations in terms of neighborhood population density, land-use density, housing characteristics, and car ownership, which significantly affect the magnitude and direction of the impact.

Factors Affecting Drivers to Participate in a Carpooling to Public Transport Service

Several studies have focused on understanding travelers’ attitudes and characteristics toward using carpooling services. However, few of these studies have focused the driver’s behavior and carpooling services that are organized to feed public transport. This research investigates the willingness of drivers to accept a carpooling ride, as part of their trip, to/from public transport stations (i.e., rail, tram and metro). Data from the EU project Ride2Rail are used, for which a survey (n = 327) was conducted in EU27 and the UK. Fisher’s exact and chi-square tests are used to explore the relationships between drivers/non-drivers and explanatory variables. A binary logit model is developed to estimate the likelihood of carpooling as a driver to/from a public transport station. The results show that delay, convenience, residence location, security and the number of passengers influence the drivers’ decision toward using their private vehicle in carpooling services. Findings provide concrete recommendations for carpooling drivers regarding the planning of a successful carpooling service. The recommendations to “recruit” the drivers become significant, as the concept of carpooling cannot be realized without them.

Transit-oriented development form on traffic assignment, transit and land-use features

Transit-oriented development (TOD) is one of the most beneficial strategies that addresses both urban and transportation issues in solving urban traffic problems. To achieve more sustainable transport and resolve urban sprawl problems, this paper establishes a TOD evaluation criterion and formulates a novel TOD site-selection method, which fulfills the principle of sustainable transportation for the city of Qazvin. This paper outlines plausible TOD locations through three complementary steps: first, the saturated links of network are investigated by traffic assignment which were 12 zones; second, the cross points of high demand for public transport stations and top saturated links are considered and third, the three essential criteria of density, diversity and distance (3Ds) are calculated for each of the selected stations to rank them by the analytical hierarchy process method. The results show that the three top-ranked TOD locations with the highest potential are nominated for TOD implementation among the 43 candidates.

ASSESSING THE CURRENT IMPLEMENTATION OF COMPACT AND MIXED-USE DEVELOPMENT WITHIN PUBLIC RAIL TRANSIT STATIONS IN MALAYSIA

In the past years, the concept of Transit-Oriented Development has been adopted in cities and countries including Malaysia and Singapore. The integration of land use and public transport stations through Transit Oriented Development (TOD) as part of urban and cities strategy is highly acclaimed in promoting sustainable development concept in cities development. To understand the performance of TODs implementation in Klang Valley, this study has selected eleven stations in of Mass Rapid Transit (MRT) Putrajaya Line as case studies. This paper aims to evaluate the current implementation of TODs in Malaysia, benchmarked against the TOD land use composition and percentage from Singapore’s model. The findings show that Raja Uda, Ampang Park and Persiaran KLCC stations show significant performance. However, Bandar Malaysia North station displayed poor result with the lowest percentage of residential and commercial components. All stations did not achieve the ideal TOD value for residential land use and eight out of eleven stations recorded higher than the ideal TOD value for roads. However, highest number of stations achieved the ideal TOD value for mixed-use and commercial land uses. These results would help policymakers to improve the current implementation of TODs in Malaysia.

Structural model for the relationships between age-friendly communities and quality of life of older adults in Hefei, China

PurposeChina is experiencing tremendous changes of rapid urbanization and aging society. The development of age-friendly communities (AFCs) has been encouraged for improving health and well-being of older adults. Hence, this study aimed to deepen the understanding of AFCs in China and to investigate the integrated relationships between AFCs and the quality of life (QoL) of older adults, using a large-scale questionnaire survey.Design/methodology/approachA questionnaire survey was conducted in Hefei, China, to investigate the complicated relationships between the components of AFCs and the QoL of older adults. Ultimately, 1,383 valid questionnaires were collected from senior respondents aged more than 60 years. Several statistical methods, including reliability analysis, correlation analysis and structural equation modeling (SEM), were adopted to develop an integrated model for AFC components and the QoL of older adults.FindingsSix AFC components and four older adults' QoL factors were identified. The SEM results revealed integrated relationships between specific AFC components and the QoL of older adults: (1) physical QoL was affected by outdoor spaces, public transportation, housing and community and health services; (2) psychological QoL was predicted by most of the AFC components except community and health services; and (3) environmental QoL and social QoL were both influenced by outdoor spaces, communication and information and community and health services.Practical implicationsIn order to enhance the QoL of older adults, it is suggested that outdoor spaces need to be enlarged by fully using the facilities and playgrounds of middle schools and renovating the older buildings. The locations of public transportation stations are recommended to be revised to be within a 5-minute walking distance of senior residents. Improvements to the social environment of AFCs, by increasing the coverage of medical services and creating multiple approaches to recreational activities, are encouraged.Originality/valueThese findings have empirical significance for urban planners and policy-makers in regard to identifying major components of AFCs and understanding the effect of those components on the QoL of older adults.

Go-along with older people to public transport in high-density cities: Understanding the concerns and walking barriers through their lens

IntroductionWe applied a go-along interview, a mobile method that enhances the contextual basis of qualitative research, to understand how older people interact with walking environments when approaching public transport in high-density cities. MethodsWe collected concerns, walking barriers and areas of improvement from older people's views by walking along with 72 participants on pre-designed walking paths towards public transport stations and stops in Hong Kong, a high-density city 90% of daily travels are made by public transport. We used content analysis with script close reading to analyse the natural conversations revolving in environmental, personal, safety and transportation factors. ResultsWe found narrow sidewalks but with high pedestrian flow posed a challenge for older people. Participants worried about being bumped and would frequently dodge other pedestrians. Females worried about sidewalk crowdedness more than males. Participants have concerns to use footbridges and undergrounds due to a lack of effortless connecting facilities, and the concerns reached a peak for participants aged 70–74. Long walking in the station underground might prevent the older people from using the metro, and a seamless connection of escalators or lifts was much desirable for older people to walk from street to station underground and concourse. Other areas of improvement included pavement evenness, obstruction by store goods on the sidewalk, railing between road and pavement, seat and rest areas in the metro underground, street crossing on collector roads, and traffic signal time. ConclusionOur study yielded insights into which, how and why the walking environment affected public transport use of older people using the go-along method. The findings can help to address the mismatch between public transport supply and demand for older people in achieving healthy ageing in the high-density city of Hong Kong and elsewhere.

Optimization of Urban Bus Stops Setting Based on Data Mining

The unreasonable setting of urban bus stops is a common problem in real life, which seriously affects people’s happiness, sense of belonging and brand in the city. However, the existing related research on the above problems generally has the defects of high technical complexity and high cost. Therefore, we aim to propose a way to optimize the setting of urban public transportation stations and reduce the technical complexity and high cost of existing public transportation station optimization by using artificial intelligence algorithms. First, we extract and integrate bus GPS data and bus card swipe data in the business system and perform exploratory analysis on the pre-processed data. Second, the original k-NN algorithm is improved, and an ik-NN algorithm is proposed to determine the cardholder’s boarding point. Then, we divide the upstream and downstream lines to calculate the total number of upstream and downstream passengers. Third, we propose an algorithm for calculating the number of passengers getting off at bus stations and calculating the number of passengers getting on and off at each bus station. Finally, according to the number of passengers getting on and off at each bus station, the OD matrix is constructed, the residents’ travel rules are analyzed, and optimization suggestions for the setting of urban bus stations are proposed. This paper selects the public transit GPS data set and swipe card data set of Shenzhen, China for experiments. The experimental results show that: (1) Compared with K-means, the ik-NN algorithm we proposed can effectively determine the actual car station of each cardholder, and the algorithm is less sensitive to feature dimensions. At the same time, the ik-NN algorithm has a high operating efficiency and is less affected by the “[Formula: see text]” value. (2) The calculation algorithm for the number of passengers getting off at bus stations can effectively use the existing data of the business system to determine the number of passengers getting off at each bus station. Therefore, the calculation times of this algorithm are low, and the accuracy is high. (3) The optimization suggestions for bus stations based on the OD matrix analysis of residents’ travel rules meet the needs of urban development and have certain reference value.

Modeling the impact of dock-less bike-sharing system on outpatient trips

Better transportation and medical service systems contribute to urban sustainable development. Dock-less bike-sharing system (DLBS) is an innovative, sustainable, and flexible travel mode that has been a worldwide spread. This paper addresses a pioneer research aims to explore the characteristics of DLBS usage in outpatient trips and its impacts on travelers’ mode choice behavior. The data sources include the survey at Beijing Friendship Hospital and the trip data from a DLBS company. The research results show that DLBS has evidently decreased the private bike usage by over one third and become a replacement. It is also an important feeder mode for public transport service to the medical service. Among 1,348 DLBS usage in outpatient trips, more than 40 % trip transactions are connecting the hospital and public transport stations. Over 70 % travelers ride DLBS only in a single trip while having other activity purpose after leaving the hospital. Multinomial logit (MNL) model is used to investigate the factors that influence the DLBS daily usage. Education and online payment have positive effects. This study can be extended to DLBS usage in other trips with similar characteristics such as appointment-based, short-duration, and multiple activities.

The heartbeat of the city.

Human activity is organised around daily and weekly cycles, which should, in turn, dominate all types of social interactions, such as transactions, communications, gatherings and so on. Yet, despite their strategic importance for policing and security, cyclical weekly patterns in crime and road incidents have been unexplored at the city and neighbourhood level. Here we construct a novel method to capture the weekly trace, or "heartbeat" of events and use geotagged data capturing the time and location of more than 200,000 violent crimes and nearly one million crashes in Mexico City. On aggregate, our findings show that the heartbeats of crime and crashes follow a similar pattern. We observe valleys during the night and peaks in the evening, where the intensity during a peak is 7.5 times the intensity of valleys in terms of crime and 12.3 times in terms of road accidents. Although distinct types of events, crimes and crashes reach their respective intensity peak on Friday night and valley on Tuesday morning, the result of a hyper-synchronised society. Next, heartbeats are computed for city neighbourhood 'tiles', a division of space within the city based on the distance to Metro and other public transport stations. We find that heartbeats are spatially heterogeneous with some diffusion, so that nearby tiles have similar heartbeats. Tiles are then clustered based on the shape of their heartbeat, e.g., tiles within groups suffer peaks and valleys of crime or crashes at similar times during the week. The clusters found are similar to those based on economic activities. This enables us to anticipate temporal traces of crime and crashes based on local amenities.

Analysis of Bus Accessibility Based on GIS and Big Data of Crowd -- Taking Wansheng Economic Development Zone as an example

Public transportation issues are increasingly becoming a key constraint to the sustainable development of urban economic and social development. Based on crowd big data and GIS spatial analysis methods, this article analyzes the accessibility of the public transportation in Wansheng Economic and Technological Development Zone (hereinafter referred to as the development zone). A comprehensive evaluation and analysis was conducted to study the matching relationship between population density and existing public transportation stations, and to propose the optimal suggestions. The results show that the overall public transportation accessibility in the development zone is average level, and the public transportation accessibility is better in the densest crowded areas, but in the east and southeast of the development zone, crowd activities are poorly matched with the public transportation network, and residents’ travel demands can’t get public transportation with timely responses.

Travel Behaviours of Sharing Bicycles in the Central Urban Area Based on Geographically Weighted Regression: The Case of Guangzhou, China

Mobile information and communication technologies (MICTs) have fully penetrated everyday life in smart societies; this has greatly compressed time, space, and distance, and consequently, reshaped residents’ travel behaviour patterns. As a new mode of shared mobility, the sharing bicycle offers a variety of options for the daily travel of urban residents. Extant studies have mainly examined the travel characteristics and influencing factors of public bicycles with piles, while the travel patterns for sharing bicycles and their driving mechanisms have been largely ignored. Using one week’s travel data for Mobike, this study investigated the spatial and temporal distribution patterns of sharing bicycle travel behaviours in the central urban area of Guangzhou, China; furthermore, it identified the influences of built environment density factors on sharing bicycle travel behaviours based on the geographically weighted regression method. Obvious morning and evening peaks were observed in the sharing bicycle travel patterns for both weekdays and weekends. The old urban area, which had a high degree of mixed function, dense road networks, and cycling-friendly built environments, was the main travel area that attracted sharing bicycles on both weekdays and weekends. Furthermore, factors including the point of interest (POI) for the density of public transport stations, the functional mixing degree, and the density of residential POIs significantly affected residents’ travel behaviours. These findings could enrich discourse regarding shared mobility with a Chinese case characterised by rapidly developing MICTs and also provide references to local authorities for improving slow traffic environments.