Utilization Of Public Transport Research Articles

Exploring the effects of public transport subsidies on satisfaction and ridership

The determinants of public transport demand are multifaceted, necessitating consideration of various factors that extend beyond the objective aspects of operation. In addition to travel time and costs, it is imperative to comprehend psychosocial factors influencing public transport usage to enhance policies geared toward fostering ridership and sustainable mobility. Empirical evidence suggests that subjective attributes, such as satisfaction and attitudes, exert a discernible influence on travel behavior and the utilization of public transport. Nevertheless, these linkages remain largely unexplored, especially within the context of large public transport networks in cities of the Global South. This paper aims to address this gap by evaluating the impact of demand-side subsidies in the form of travel vouchers on public transport ridership to understand the mediating effect of satisfaction levels according to the users’ socioeconomic characteristics. These satisfaction levels are related to overall satisfaction with transport, employment and educational opportunities, and life. To achieve this, a large-scale randomized controlled experiment was conducted in Bogotá, Colombia, involving a sample of frequent public transport users (N = 1,607). The participants were divided into a treatment group, which received the travel vouchers loaded onto their smart travel cards for four months, and a control group. Hybrid-ordered logit models were employed to estimate the average number of weekly trips undertaken before, during, and after the intervention. The result shows an increase in ridership by the treatment group, which does not solely depend on improved affordability; but is influenced by a complex interplay of socioeconomic factors and shifts in satisfaction levels. This confirmed that travel satisfaction can contribute to increased public transport demand.

Deep learning-based prediction of lithium-ion batteries state of charge for electric vehicles in standard driving cycle

Significant climatic shifts occurred during this period, resulting in threatening consequences for people's lives and industries. Global warming is one of the most serious consequences of these climate changes, and it has disastrous consequences for daily human existence. The utilization of public transportation has been encouraged at the societal level as a solution. An all-electric vehicle is evaluated in this research paper. Using two various types of regular driving cycles, we were able to evaluate the battery performance of electric vehicles (EVs). The variables influencing vehicle performance, such as battery state of charge (SOC), energy consumption, and battery functioning temperature, are investigated. The results demonstrate that the rate of urban traveling significantly impacts travel efficiency and the range. In addition, owing to the significance of battery capacity, the influences of different variables on forecasting battery state of charge were assessed in the second step. The results show that the driving behavior and acceleration rate of the vehicle influence the SOC of the battery. The results of this study also showed that city driving has a significant effect on Ev performance in the travel distance range.

Influences on Public Transport Utilization: The Case of Auckland

Regression analysis is applied to cross-sectional data for 318 census area units served by the public transportation system in Auckland, New Zealand. The goal is to ascertain the determinants of public transport patronage for the purpose of commuting to work in the region. The analysis addresses both the modifiable areal units problem and spatial autocorrelation. Elasticity estimates are derived for a number of hypothesized drivers of patronage. The paper shows that adjusting for spatial autocorrelation improves the fit of the regression model to the data, a finding that should be of interest to public transportation planners and analysts working with cross-sectional data of a geographic nature.

Impact of Road Network Topology on Public Transportation Development

Planning of road networks is fundamental for public transportation. The impact of road network density on public transportation has been extensively studied, but few studies in this regard involved evaluation indicators for connectivity and layout of road networks. With 29 cities in China as the study cases, this paper quantifies the layout structure of the road network based on the network’s betweenness centralization and establishes a multivariate linear regression model to perform regression of the logarithm of the frequency of per capita public transportation on betweenness centralization. It is found in the present work that there is a significant correlation between the layout structure of an urban road network and the residents’ utilization degree of public transportation. A greater betweenness centralization of the urban road network, namely a more centralized road network, means a higher frequency of per capita public transportation of urban residents and a higher degree of the residents’ utilization of public transportation. In the development of public transportation, centralized and axial-shaped layout structures of road networks can be promoted to improve the utilization of public transportation.

A Case-Control Study of Contextual Factors for SARS-CoV-2 Transmission.

Background: Knowledge on the settings and activities associated with a higher risk of SARS-CoV-2 transmission is essential to inform decision-making. We thus designed a case-control study to identify relevant settings for community transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Portugal.Methods: We evaluated 1,088 cases, identified through the national surveillance system, and 787 community controls, recruited using random digit dialing. Sociodemographic characteristics, individual protective measures, and activities or visited settings were obtained through telephone interview. We report sex-, age-, education-, and citizenship-adjusted odds ratios (aOR) with 95% confidence intervals (95% CI).Results: Household overcrowding (aOR = 1.47; 95% CI 1.14–1.91) and work in senior care (4.99; 1.30–33.08) increased while working remotely decreased the risk of infection (0.30; 0.22–0.42). Going to restaurants/other dining spaces (0.73; 0.59–0.91), grocery stores (0.44; 0.34–0.57) or hair salons (0.51; 0.39–0.66), or the use of public transportation did not present a higher risk of infection (0.98; 0.75–1.29), under existing mitigation strategies. Lower education ( ≤ 4 years vs. tertiary education: 1.79; 1.33–2.42) and no Portuguese citizenship (5.47; 3.43–9.22) were important risk factors.Conclusions: The utilization of public transportation, restaurants, and commercial spaces was not associated with increased risk of infection, under capacity restrictions, physical distancing, use of masks, and hygiene measures. Overcrowding, foreign citizenship, low education and working on-site were positively associated with SARS-CoV-2 infection.

Understanding Commuter’s Motivation of Transportation Choice: A Case Study of Greater Jakarta

Among the various modes of transportation, road transport is one of the most common modes of transport due to the comfortability and ease of commute. It is no wonder that road transport has become the primary energy consumption, which also significantly contributes dangerous levels to the ever-increasing pollution. Jakarta as the capital city of Indonesia is undeniably the most massive contributor to pollution in the world, and its complex transportation problems led to the city ranks highest in CO2 emission. One of the leading causes of transportation problems in Jakarta is the low percentage utilization of public transport. Therefore, the primary purpose of this study is to explore the reasons behind the people's decision in selecting travel options, especially the adoption of green commuting behavior like public transportation; the analysis of which was explicitly taken from daily commuting using probit regression. The estimation results reveal that in Greater Jakarta, both educational attainment and population density have a negative correlation with the people’s decision to utilize mass transportation since the unreliability of the transportation system lessens the benefit of using public transport in comparison with that of private transport.

Understanding Commuter’s Motivation of Transportation Choice: A Case Study of Greater Jakarta

Among the various modes of transportation, road transport is one of the most common modes of transport due to the comfortability and ease of commute. It is no wonder that road transport has become the primary energy consumption, which also significantly contributes dangerous levels to the ever-increasing pollution. Jakarta as the capital city of Indonesia is undeniably the most massive contributor to pollution in the world, and its complex transportation problems led to the city ranks highest in CO2 emission. One of the leading causes of transportation problems in Jakarta is the low percentage utilization of public transport. Therefore, the primary purpose of this study is to explore the reasons behind the people's decision in selecting travel options, especially the adoption of green commuting behavior like public transportation; the analysis of which was explicitly taken from daily commuting using probit regression. The estimation results reveal that in Greater Jakarta, both educational attainment and population density have a negative correlation with the people’s decision to utilize mass transportation since the unreliability of the transportation system lessens the benefit of using public transport in comparison with that of private transport.

MO644:DIABETES AND DIALYSIS:PROPOSAL FOR A CONTAGION PREVENTION PROTOCOL IN COVID-19 PANDEMIA

Background and AimsAfter the official coronavirus (SARS-CoV-2) pandemic declaration by the WHO, Italy had the second-largest number of confirmed cases, after China. The Italian government introduced progressive infection-mitigation measurements, thus dramatically reducing social interactions and preventing virus spread. During the summer, infection containment measures progressively loosened until, due to an unjustified interpretation of some permissions and the excessive utilization of public transportation at school reopening, the contagion rate progressively increased until causing a severe challenge for our NHS again. Aim of the study: to assess the efficiency of our previously described protocol in 18 Campania region-located Nefrocenter Consortium DCs as further adapted to new knowledge under the new ubiquitous contagion conditions and to identify SARS-CoV-2-infection mortality rate and risk factors.MethodDialysis patients did so too during that period according to the expected shifting prevalence over time (mean ± SD: 853 ± 30 per month; range 825 to 873) ± (11.8% in April, and 14.8% in November vs. a pre-COVID-19 12.0% rate in January).ResultsMore patients got infected in November (10.19%) than in April (0,24%), and 22 patients of the 89 from the SARS-CoV-2 November positive subjects required hospitalization for moderate-severe symptoms (24.72%), with death unavoidably coming in 19 (86.36% of hospitalized and 21.35% of infected patients) compared to the only one recorded in April (0.12%). The pandemic's two periods showed a strong association between mortality rate and often co-existing comorbidities, primarily represented by arterial hypertension, type 2 diabetes mellitus (T2DM), and chronic kidney disease (CKD).ConclusionThe prevously efficient contagion containment measures adopted by our DCs were not enough in November to fight the global infection risk pending on the whole Italian social community around. The Authors discuss possible reasons and put forward further suggestions for the best handling of any future infection wavesMO644 Table 1.General features of subjects on chronic dialysis as of April 23, 2020, and co-morbidities observed according to diabetes status. *IHD/AF/HF= composite outcome: Ischemic Heart Disease/ Atrial Fibrillation/ Heart Failure. Data expressed as Mean+SD, range, or n; (%). In no case were HIV Infection, Autoimmune Disease, and Obesity present.SARS-CoV-2 positive patients (n. 89)SARS-CoV-2 negative patients (n. 784)Total n.N (%)N (%)pComorbiditiesIHD/AF/HF *12 69.16386 49.23<.0001398 Stroke 7 7.87176 22.45<.001183 Arterial Hypertension 76 85.39509 64.92<.01585 Type 2 Diabetes Mellitus 79 88.76253 32.40<'0001332 Chronic Obstructive Pulmonary Disease 31 34.83178 22.70<.01209 Active Cancer in the past 5 years 2 2.250 --2 Dementia 9 10.1127 3.44<.0536 Chronic Liver Disease 19 21.35156 19.90n.s.175 Respiratory Failure 14 15.73134 17.59n.s.148Number of Comorbities00 -5 0.64-510 -105 13.39-10520 -189 24.11-1893 at least89 100.00485 61.86<'0001574MO644 Table 2.Most common co-morbidities observed in SARS-CoV-2 positive patients compared to negative ones in the second pandemic period (1st august - 13th November). In no case were HIV Infection, Autoimmune Disease, and Obesity present. *IHD/AF/HF = composite outcome = Ischemic Heart Disease/ Atrial Fibrillation/ Heart Failure. MO644 Figure 1 :Identification and management flowchart of SARS-CoV-2 positive dialysis patients. *asymptomatic, pre-symptomatic or mild symptomatic infection (fever, cough, dysgeusia, disosmia, headache, myalgia, in the absence of dyspnea and X-ray abnormalities (stage 1 and 2 according to NIH classification [64]); ° moderate, severe or critical illness according to the same classification.

A Study on Transfer Resistance Focused on the Utilization of Public Transportation

A Study on Transfer Resistance Focused on the Utilization of Public Transportation

Coronavirus Disease-2019, Diabetes and Dialysis in Southern Italy: The Second Wave Follow-up

Background After the official coronavirus (severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)) pandemic declaration by the World Health Organization (WHO), Italy had the second-largest number of confirmed cases, after China. The Italian government introduced progressive infection-mitigation measurements, thus dramatically reducing social interactions and preventing virus spread. During the summer, infection containment measures progressively loosened until, due to an unjustified interpretation of some permissions and the excessive utilization of public transportation at school reopening, the contagion rate progressively increased until causing a severe challenge for our National Health Service (NHS) again. Aim To assess the efficiency of our previously described protocol in 18 Campania region-located Nefrocenter Consortium dialysis centers (DCs) as further adapted to new knowledge under the new ubiquitous contagion conditions and to identify SARS-CoV-2-infection mortality rate and risk factors. Methods 381 HCP members underwent regular monitoring on April 1 and November 13, 2020. Dialysis patients did so too during that period according to the expected shifting prevalence over time (mean±SD:853±30 per month; range 825 to 873) vs (11.8% in April, and 14.8% in November vs. a pre-coronavirus disease-2019 (COVID-19) 12.0% rate in January). Results More patients got infected in November (10.19%) than in April (0,24%), and 22 patients of the 89 from the SARS-CoV-2 November positive subjects required hospitalization for moderate-severe symptoms (24.72%), with death unavoidably coming in 19 (86.36% of hospitalized and 21.35% of infected patients) compared to the only one recorded in April (0.12%). The pandemic’s two periods showed a strong association between mortality rate and often co-existing comorbidities, primarily represented by arterial hypertension, type 2 diabetes mellitus (T2DM), and chronic kidney disease (CKD). Conclusion The previously efficient contagion containment measures adopted by our DCs were not enough in November to fight the global infection risk pending on the whole Italian social community around. The author, discuss possible reasons and put forward further suggestions for the best handling of any future infection waves.

Two-Stages Carbon Emission Pinch Analysis for Integrated System of Renewable Energy and Electric Vehicle

The introduction of electric vehicles to the transportation fleet has merged the power generation and transportation sectors into an integrated system. Rather than fuel sources, electricity is used to charge electric vehicles, so these vehicles play a vital role as an important green technology that could reduce carbon emissions in the transportation sector. This study aimed to develop a multi-stage carbon emission pinch analysis for an integrated system to optimise the energy mix for electricity generation. In the first stage, the minimum number of electric vehicles required to reduce transportation emissions was determined. In the second stage, the optimal energy mix for power generation sector was determined while including the electricity demand for the electric vehicle. Four scenarios, namely the business-as-usual scenario (S1); the public transport utilization scenario (S2); the electrification of vehicle scenario (S3); and the Integrated-Policies scenario (S4) were developed based on Peninsular Malaysia as a case study, to analyse the impact of different mitigation strategies on the country’s economy. S1 was set as baseline for all the cases i.e., without any mitigation strategies. The results reveal that S4 was the best scenario, yielding a total cost saving percentage of 51.42 % compared to S1. For the power generation sector, 52 % of renewable energy (solar PV, biomass and biogas) utilisation would be needed in the energy mix to achieve the emission reduction target.

Personalized predictive public transport crowding information with automated data sources

The paper proposes a methodology for providing personalized, predictive in-vehicle crowding information to public transport travellers via mobile applications or at-stop displays. Three crowding metrics are considered: (1) the probability of getting a seat on boarding, (2) the expected travel time standing, and (3) the excess perceived travel time compared to uncrowded conditions. The methodology combines prediction models of passenger loads and alighting counts based on lasso regularized regression and multivariate PLS regression, a probabilistic seat allocation model and a bias correction step in order to predict the crowding metrics. Depending on data availability, the prediction method can use a combination of historical passenger counts, real-time vehicle locations and real-time passenger counts. We evaluate the prediction methodology in a real-world case study for a bus line in Stockholm, Sweden. The results indicate that personalized, predictive crowding information that is robust to varying data availability can be provided sufficiently early to be useful to travellers. The methodology is of value for agencies and operators in order to increase the attractiveness and capacity utilization of public transport.

COMPARISON OF WALKABILITY IN DIFFERENT URBAN DISTRICTS USING SPACE SYNTAX

The expansion of cities and increasing car traffic have brought problems such as increased greenhouse emission, noise pollution, and access problems that makes sustainable urban development one of the most significant concerns of urban governors. Obviously, the utilization of public transportation and walkability is one of the highly significant aspects of sustainable development. In an effort for the recognition of urban districts of Bojnourd, the current article compares the extent of walkability in each district. To investigate the walkability index using the opinions of experts and scholars 4 criteria and 22 sub-criteria were taken into consideration. In this regard, the ANP approach was also applied to improve decision making and grading the importance of criteria; districts were finally graded using the TOPSIS model concerning walkability. In the present study as an applied one, field surveys, questionnaires, library studies, and documents were the data collection tools. The findings revealed that the old district (central), have the highest walkability potential in comparison to medial, and the new development districts respectively. Since the old district has the highest amount of mixed land uses, passage connectivity, passage integration, public transport, and so forth, it can be concluded that walkability is closely related to the mentioned factors.

A SYNTHESIZED AHP-SPEARMAN MODEL FOR MENSURATION THE SEGREGATION OF PREFERENCES FOR PUBLIC TRANSPORT SYSTEM ENHANCEMENT

Latterly, a superior utilization of public transport can be a remedy to mitigate the traffic especially in big cities, thereby, to environmental, economic and public health problems. However, the alternatives for reclamation are myriad and in spite of this consensus of necessity, reclamation decisions are often censured by the public. Predominantly, a significant difference can be detected between planners’ and passengers’ notion about amelioration matter. The aim of this paper is to enumerate public demand for public bus transport improvement, by analyzing public bus transport supply quality criteria between planners and public in Mersin City, Turkey. As a methodology, a combined Analytic Hierarchy Process (AHP) and Spearman correlation technique have been applied in order to illuminate the chasms between planners and public.

Analysis of the public transport utilization in Lublin

Proper public transport vehicles utilization is a key factor in effective and efficient communication in every city. Number of vehicles in use at any point in time is crucial piece of information to both transportation organizers and carriers, since it allows for control and reaction in case of an emergency. This article presents an analysis of public transport vehicles utilization in regard to day of the week and carriers responsible for public transport in Lublin.

The Effect of High-density Residential Developments in Korea on Utilization of Public Transport - Focusing on the Sequence of Supply between Apartments and Subways in Seoul

The Effect of High-density Residential Developments in Korea on Utilization of Public Transport - Focusing on the Sequence of Supply between Apartments and Subways in Seoul

Evaluation of Inter-Regional Transportation Network Considering Multi-Mode Route Alternatives

Evaluation of the interregional transportation network is necessary to examine the efficient utilization and service supply planning of public transportation, with the consideration of multiple contradictory societal demands, including the improvement of transportation convenience and reduction of environmental load. Whenever one societal demand on a network is satisfied, another should not be forgotten. This study develops a method for evaluating interregional transportation networks, which considers multimode route alternatives by setting two evaluation criteria: consumer surplus and CO₂ emissions. The proposed method can provide the tendency of one criterion when the other is optimized. For example, when maximizing consumer surplus, the optimized network was found to have many links with increased frequency of service. Moreover, the increase in CO₂ emissions can be obtained quantitatively in connection with the maximization of consumer surplus.

Outdoor particulate matter (PM) and associated cardiovascular diseases in the Middle East.

Air pollution is a widespread environmental concern. Considerable epidemiological evidence indicates air pollution, particularly particulate matter (PM), as a major risk factor for cardiovascular diseases (CVD) in the developed countries. The main objective of our review is to assess the levels and sources of PM across the Middle East area and to search evidence for the relationship between PM exposure and CVD. An extensive review of the published literature pertaining to the subject (2000-2013) was conducted using PubMed, Medline and Google Scholar databases. We reveal that low utilization of public transport, ageing vehicle fleet and the increasing number of personal cars in the developing countries all contribute to the traffic congestion and aggravate the pollution problem. The annual average values of PM pollutants in the Middle East region are much higher than the World Health Organization 2006 guidelines (PM2.5 = 10 μg/m(3), PM10 = 20 μg/m(3)). We uncover evidence on the association between PM and CVD in 4 Middle East countries: Iran, Kingdom of Saudi Arabia, Qatar and the United Arab Emirates. The findings are in light of the international figures. Ambient PM pollution is considered a potential risk factor for platelet activation and atherosclerosis and has been found to be linked with an increased risk for mortality and hospital admissions due to CVD. This review highlights the importance of developing a strategy to improve air quality and reduce outdoor air pollution in the developing countries, particularly in the Middle East. Future studies should weigh the potential impact of PM on the overall burden of cardiac diseases.

A Logistic Regression Model with a Hierarchical Random Error Term for Analyzing the Utilization of Public Transport

Logistic regression models have been widely used in previous studies to analyze public transport utilization. These studies have shown travel time to be an indispensable variable for such analysis and usually consider it to be a deterministic variable. This formulation does not allow us to capture travelers’ perception error regarding travel time, and recent studies have indicated that this error can have a significant effect on modal choice behavior. In this study, we propose a logistic regression model with a hierarchical random error term. The proposed model adds a new random error term for the travel time variable. This term structure enables us to investigate travelers’ perception error regarding travel time from a given choice behavior dataset. We also propose an extended model that allows constraining the sign of this error in the model. We develop two Gibbs samplers to estimate the basic hierarchical model and the extended model. The performance of the proposed models is examined using a well-known dataset.

A dynamic programming based heuristic for locating stops in public transportation networks

The length of journey towards a bus stop or railway station greatly influences passenger satisfaction and, thus, the utilization of public transport offers. In this context, we investigate the maximum covering location problem in networks (MCLPN) where stops (or stations) are to be located in a given railway or bus network, such that the number of passengers reaching a stop within their particular coverage radius is maximized. Up to now, no specialized solution procedure directly addressing MCLPN exists, instead it is mainly referred to the well-known maximum covering location problem (MCLP), which, however, neglects the underlaying information of the given network structure. This paper exploits the network information, introduces a fast and efficient two-stage dynamic programming based heuristic specifically tailored to MCLPN, and compares it to existing procedures for MCLP. The results show that our heuristic delivers near optimal solutions, i.e., 87% of our test instances are solved to optimality, within a few seconds of computational time.