Investigating the Spatiotemporal Imbalance of Accessibility to Demand Responsive Transit (DRT) Service for People with Disabilities: Explanatory Case Study in South Korea

This study analyzed the operation-related historical data of the call taxi service for disabled people in Seoul, South Korea. The study investigated how unevenly distributed the accessibility of disabled people to transportation is in terms of time and space. In addition, the reasons that cause imbalanced accessibility were investigated in areas with good and poor accessibility. Accessibility was defined as how quickly call taxi services for the disabled are available at specific times and locations. For the analysis, the log data for tracking the status of taxis in time and space were processed to calculate their availability, an index that reflects the dwelling time and the number of taxis available at a specific time and in a specific area. This index was divided into time and space and used as a surrogate measure to assess accessibility. The results showed that there were spatial and temporal accessibility imbalances in demand responsive transit (DRT) service. The insufficient supply during the night resulting from the current DRT operating schedule has reduced the accessibility of call taxis for the disabled, and the concentration of drivers’ breaks also affected the accessibility of service during the daytime. This suggests the need for (1) an increase in supply and (2) evenly distributed breaks for the drivers. In terms of space, the outer areas of Seoul generally were found to be more accessible than the central areas. In addition, areas near depots that serve as hubs and resting places for taxi drivers, areas with excellent medical infrastructures for people with disabilities, and areas with good traffic environments tended to have good accessibility; this suggests the need to reallocate garages and improve the traffic environments to improve accessibility.

Route Optimization via Environment-Aware Deep Network and Reinforcement Learning

Vehicle mobility optimization in urban areas is a long-standing problem in smart city and spatial data analysis. Given the complex urban scenario and unpredictable social events, our work focuses on developing a mobile sequential recommendation system to maximize the profitability of vehicle service providers (e.g., taxi drivers). In particular, we treat the dynamic route optimization problem as a long-term sequential decision-making task. A reinforcement-learning framework is proposed to tackle this problem, by integrating a self-check mechanism and a deep neural network for customer pick-up point monitoring. To account for unexpected situations (e.g., the COVID-19 outbreak), our method is designed to be capable of handling related environment changes with a self-adaptive parameter determination mechanism. Based on the yellow taxi data in New York City and vicinity before and after the COVID-19 outbreak, we have conducted comprehensive experiments to evaluate the effectiveness of our method. The results show consistently excellent performance, from hourly to weekly measures, to support the superiority of our method over the state-of-the-art methods (i.e., with more than 98% improvement in terms of the profitability for taxi drivers).

A SYSTEM DYNAMICS MODEL FOR URBAN TAXI PRICE SIMULATION

Urban taxi services have been developing year on year, playing an increasingly important role in the economy and the transportation markets of each city. This increases interest in measuring their performance. This paper analysed the relationship among the four stakeholders (including administrative department, operational companies, taxi drivers and customers) for urban taxi passenger transport system in China, and applied System Dynamics (SD) model to explore the dynamic characteristics of urban taxi price system. The main achievements of this paper are as follows, firstly, this paper adopted stakeholder mapping to describe the relationships among the four stakeholders. Then analysed the causal flow diagrams and the different variables of urban taxi passenger transport system operation, and presented the SD model, which considers factors that affect the taxi operation. With the combination of taxi operation data of Harbin city, we simulated eleven urban taxi operation scenarios and proposed kinds of suggestions to improve urban taxi passenger transport system operation, which can provide a good basis for recommending policy decisions for urban taxi market.

Gambaran Tingkat Pengetahuan pada Ojek Online Terhadap Bantuan Hidup Dasar (BHD)

Background: Online motorcycle taxi drivers are part of a community that is very closely related to traffic. The high number of road accidents requires that anyone who looks to help both lay people or medical personnel. Knowledge of basic life support (BLS) is needed to provide correct help according to health procedures and minimize the risk of death. Objective : Finding out the level of knowledge in online motorcycle taxis on basic life support (BLS). Method : The research method used is the cross sectional approach. Total population of 102 online motorcycle taxi drivers in the Gombong area. The number of samples is 50 respondents. Data collection using a questionnaire. Data analysis using bivariate test is descriptive analysis test with SPSS. Results: The characteristics of the data obtained by the age of online motorcycle taxi drivers in the Gombong area in the final adolescent category were 26 respondents (52.20%). And o Online motorcycle taxi drivers education in the high school / equivalent category was 36 respondents (72.00%). Description of the level of basic life support knowledge in the majority of online motorcycle taxi drivers in the category of less than 31 respondents (62.00%). Descriptions of readiness to help the majority of online motorcycle taxi drivers in a good category of 29 respondents (58.00%). Conclusion: Level of basic life support knowledge (BHD) of readiness to help the online motorcycle taxi driver is lacking. And the results of readiness to help the online motorcycle taxi drivers with good categories.

Relationship of Nutritional Status to Incidency Symptom Respiratory on Online Ojek Drivers in Malang City, East Java, Indonesia

Backgrounds/Aims: Respiratory disease is one of occupational disease that increasing and becoming the biggest three diseases that contribute more than three-quarters of total work-related deaths with circulations disease and neoplasm. Exposure to dust, allergens and toxins are some of the risk factors for respiratory diseases. One of the jobs with a high risk of exposure to air pollution is online motorcycle taxi drivers, they inhale pollution from the transportation sector and pollutant gases in the air which can cause respiratory problems. In addition, nutrition and respiratory disorders have an important relationship. In the recovery process, nutritional status has an important impact in the process of breaking down proteins contained in muscles including respiratory muscles in the catabolism process. Methods: This study was an analytic observation and the data was collected retrospectively in online motorcycle taxi drivers in Malang City with inclusion criteria on April 2021. Results: 108 online motorcycle taxi drivers in Malang, aged 15-55 years, 96.3% men, respiratory disorders 76.9% respondents with 93.6% underweight. Respiratory symptom more having common cold 66,7%, cough 42,6% and phlegm 38,9%. The relationship between nutritional status and the incidence of respiratory symptoms was 8.1 times (95% CI (1.9-16.4) p = 0.017). Conclusions: There is a significant relationship between nutritional status and symptoms of respiratory disorders in online motorcycle taxi drivers in Malang City with 8 times. Keywords: acute ischemic, stroke, platelet lymphocyte ratio, poor outcome.

Bacteriological Evaluation of Nigerian Paper Currency (Naira Notes) Circulating In Owerri, Imo State, Nigeria

Generally, the contamination of currencies with various microbial species is increasingly being reported. This usually results from improper handling during exchange of goods, services and certain environmental factors. This study on the bacteriological evaluation of the Nigerian paper currency (Naira notes) circulating in Owerri, Imo State was carried out with the aim of evaluating the prevalence of bacteria contaminants of Nigerian currency notes in circulation. A total of One hundred and twenty (120) Naira notes of ₦5, ₦10, ₦20, ₦50, ₦100, ₦200, ₦500 and ₦1000 denominations were collected in separate polythene bags from traders, students, hawkers, meat sellers, food vendors, taxi drivers, keke drivers and banks for the study. The notes were chosen on the basis of denominations and physical appearance (Mint, Neat, dirty, very dirty and mutilated). Each of the notes was inserted into a sterile bottle containing 10mls of distilled water and allowed to stand for twenty minutes. Double dilution of the solution was inoculated into Nutrient agar, MacConkey agar, Mannitol Salt agar and Salmonella and Shigella agar for viable counts. Further identification of the bacteria was carried out using standard morphological and biochemical tests. The data from this study were subjected to statistical analysis using percentage, charts and anova. The result from the analysis showed that, 82 (68.33%) out of the 120 samples evaluated were contaminated. The study showed that dirty naira notes are potential routes for bacteriological disease transmission to man during handling and constitutes a public health risk. Therefore, the appropriate authorities should embark on public enlightenment campaign targeted at the handlers and associated risks.

Tipping in Crises: Evidence from Chicago Taxi Passengers during COVID-19

In early 2020, the novel coronavirus (COVID-19) spread to the United States and upended normal life. Using trip-level data on over 17 million taxi rides taken in Chicago from 2018-2021, I document how tipping behavior changed during the COVID-19 pandemic. I find that the average non-zero tip increased by almost 2 percentage points, from roughly 26% to 28% of the taxi fare. Meanwhile, the likelihood that a passenger left a tip at all declined by roughly 5 percentage points, down from a pre-pandemic likelihood of 95%. My preferred specification suggests that the effect on the intensive margin dominates that in the extensive margin, leading to an aggregate increase in tipping generosity during the pandemic. I leverage granularity in the data to explore the mechanisms behind these trends and offer two explanations consistent with thedata. First, passengers responded to the two economic shocks of the pandemic – unemployment and savingsoverhangs – by varying their tipping rates accordingly. Second, passengers internalized the increased risk of COVID-19 infection as an additional cost for taxi drivers and increased their tips as compensation. My analysis testifies to the sustainability of tipping in times of crises and offers theoretical insight into what drives tipping behavior.