Travel Convenience Research Articles

Telehealth use and acceptability amongst a diverse oncology patient population.

104 Background: Existing research describes numerous barriers to care for patients with cancer, including time constraints, cost, and additional health conditions. We sought to assess telehealth access and experience amongst a diverse patient population at an academic medical center. Methods: We administered a 60-question, cross-sectional, in-person survey to adult patients with a diagnosis of solid tumor or hematological malignancy on active treatment at Columbia University Irving Medical Center (CUIMC) in New York, NY between January 2023 and February 2024. The survey assessed access to and attitudes, beliefs and experience with telehealth as part of routine care and clinical trials. Demographics including age, gender, race/ethnicity, marital status, income, insurance type and education were self-reported. Results: The survey was administered to 100 patients with cancer (breast cancer, n=25; gastrointestinal cancer, n=25; genitourinary cancer n=25; and hematologic malignancy, n=25); 37% were actively enrolled or previously enrolled on a clinical trial. The mean age was 61 years; 51% were female; 45% non-White, and 23% Hispanic. The majority (63%) reported traveling >30 min to their treatment, with 48% reporting travel costs >$20 per visit. Six percent reported difficulty receiving treatment due to cost, and 23% reported difficulty getting to visits due to other conditions or disabilities. The majority (87%) reported having access to a computer or electronic device; 99% of those had internet access and 81% were comfortable using the internet. Of those who had prior video visits (59%), almost all (97%) reported that video visits addressed their issues/questions well. About a quarter of the patients who had not had a video visit reported that they would prefer to have video visits about a cancer-related issue rather than going into the office. For those who preferred a video visit (n=18), top reasons included elimination of travel, convenience, and not feeling rushed. Top barriers among those who expressed hesitance (n=23) included lack of access to necessary technology, not knowing how to use the technology, concern about getting the same level of care, or preference for in-person communication. Similar to video visits, 52% participants reported that they had a scheduled telephone visit with their oncologist instead of going to the office; 98% reported that their issues were either somewhat or very well addressed. Conclusions: In this cross-sectional study amongst a racially, ethnically and socioeconomically diverse population, we found that most patients with cancer on active treatment had access to telehealth and were satisfied with telehealth visits. Those who had not utilized telehealth were interested given convenience and elimination of travel. We found minimal barriers to telehealth access in this diverse urban population. Telehealth may offer an adjunct to reduce financial and logistic barriers to cancer care.

Revolutionizing Roads: The Impact of Autonomous Vehicles on Future Travel

This project focuses on developing an autonomous self-driving car by integrating advanced algorithms with cutting-edge hardware. The vehicle is designed to perceive its environment, make informed decisions, and navigate complex traffic scenarios autonomously by leveraging machine learning and computer vision technologies. Essential methods include using deep learning algorithms for object detection and classification, sensor fusion techniques to combine data from cameras, LiDAR, and radar, and reinforcement learning for decision-making in dynamic environments. The project emphasizes the critical role of AI in enabling the car to interpret and respond to dynamic road conditions while ensuring reliable performance through rigorous testing and validation in simulated and real-world scenarios. Initial results from testing indicate that the car can successfully navigate complex traffic situations, such as merging onto highways and responding to pedestrians, with a high degree of accuracy. By pushing the boundaries of autonomous vehicle technology, this research aspires to contribute to the ongoing evolution of self-driving cars and their potential to revolutionize mobility. With a focus on safety, efficiency, and innovation, this endeavor represents a significant step forward in developing autonomous vehicles, offering new possibilities for the future of transportation. The project promises to improve travel convenience and significantly reduce traffic accidents, ultimately contributing to a safer and more efficient road system.

Behavior of Decision Making of Purchasing the One District One Product (ODOP) Product from Champhon District, Savannakhet Province

This research aims to explore the buying behavior of One District One Product (ODOP) and analyze the factors that affect the buying behavior of One District One Product in Champhon District, Savannakhet Province, which includes 3 types of products: natural incense, saving stove and ancient salt. It is a question of opinions from the people of Kaisonpomvihan city, Savannakhet province, using a questionnaire to interview buyers and shopkeepers. Also, there is a mobilization of ideas to promote one city, one product to become a business from producer groups, group heads and village heads. The statistics used for analysis include descriptive statistics: frequency, percentage and inferential statistics used Binary logit regression analysis. The results of the study found that most of the people of KaisonPhomvihan City focus attention on Intellectual products at a moderate level for 48.9%, most of them prefer to buy the saving stove from Buang Thong Village for 72.2%, buy natural incense from Nook Kok Village for 27.8% and 61.1% were introduced by friends, followed by family and relatives for 26.7%. The decision to buy the product is wise because the features of the product are suitable for household needs for 75.6% who will buy immediately when they see the product, the place of purchase is mostly from the grocery store in the merchant's house directly because of the convenience of travel. They also buy at Sawannxay Market and Samakyxai Market in Kaisonphomvihan City, Savannakhet Province cover for 37.8%. The findings of an examination of the variables gender, age, and educational level that influence a one district one product's purchasing behavior in Champhon District, Savannakhet Province; Product, price, location, sales promotion, and customer understanding are factors that influence purchase behavior. The test of model suitability, which resulted in a statistical value of Chi-squared 78.45, Prob = 0.00, indicated that all of the initial variables had an effect on the opportunity to buy a single product in a single district. According to the model's goodness of fit test, 31.2% of the factors influencing (Odop) product's purchasing behavior can be predicted with 100% accuracy using all of the initial variables. The behavior simulation model's forecast, along with the variables influencing the purchasing decisions of a single district's worth of products, is 83.96% accurate. In Champhon District, factors including age, educational level, and customer awareness influence one district one product purchasing behavior. A bachelor's degree or higher will increase the likelihood of a customer purchasing an Odop product by 17.3%, and when a customer has a total of one point of opinion and understanding, the likelihood of a customer purchasing an Odop product in Champhon will increase by 1.3% at the level of statistical significance. These are the results of taking into account each variable.

Privacy-preserving estimation of electric vehicle charging behavior: A federated learning approach based on differential privacy

With the popularity of connected electric vehicles, the openness and sharing of charging data between stakeholders allows a more accurate estimation of charging behavior, which is valuable for optimizing energy systems and facilitating travel convenience. However, to enable such an effective mechanism, the challenge of data security and privacy should be addressed. Federated learning in the vehicular network is appealing for utilizing individual vehicle data while preserving data privacy. We propose an improved local differential privacy-based federated learning approach for modeling charging session prediction problems while preserving user privacy against the threat from a honest-but-curious server. In this approach, all vehicles, within the coordination of a cloud server, collaboratively establish a global regression network through parameter exchange. Meanwhile, the servers may belong to third-party model owners and can be semi-honest when inferring private information on the collected model parameters. Hence, local differential privacy is adopted to perturb the parameters. Additionally, a combination of local and global models via elastic synchronization is proposed to improve the accuracy of the learned noisy global model. Through the test on a real data set, the results show the superiority of the proposed algorithm over traditional noisy federated learning methods. Furthermore, the practical value of the proposed method is validated with a real-world charging case. Such an accurate charging session prediction service for electric vehicle drivers facilitates charging and travel convenience in the green transportation world.

Impact of high-speed rail on wage premiums for migrant workers in China

The extensive high-speed rail (HSR) network in China has significantly enhanced regional population mobility, yet its impact on the well-being of migrant workers remains underexplored. Utilizing data from the China Migrant Dynamic Survey (CMDS) from 2014 to 2018, this study investigates the influence of HSR on wage premiums for migrant workers and identifies the factors driving these premiums using the non-parametric nearest neighbor matching method. The findings reveal that HSR confers a significant wage premium of 13.1% for migrant workers in cities with HSR infrastructure compared to cities without it. This wage premium effect is particularly pronounced in less developed western China and in cities with larger populations and a higher proportion of tertiary sector economy. The study finds a 10.54% increase in wage premiums for intra-province migrant workers due to HSR, while the effect remains negligible for inter-province migrant workers. Moreover, the wage premium effect is stronger for higher-skilled labor and for migrant workers aged 16 to 45. It is particularly significant for professionals, administrative staff, and workers in the service industry. The HSR wage premium effect is multifaceted, exhibiting both level and growth effects, with the latter intensifying over time after HSR introduction. Overall, the findings suggest that HSR deployment positively influences migrant worker wages by enhancing travel convenience, improving market access, fostering knowledge spillovers, and facilitating industry transfers. However, these impacts vary by location, skill level, and industry.

Mode Choice and Value of Time on Long-Distance Vacation Trips

Long-distance travel for leisure purposes, especially international travel, has grown dramatically over the past decades. Although its share of the total number of trips is small, it accounts for a significantly larger share of total distance and greenhouse gas emissions, with the accompanying adverse environmental consequences. One remedy might be to urge tourists to travel on vacation by rail rather than car, which is less harmful to the environment. However, it is not clear how to persuade them to do so, since knowledge of the determinants of mode choice for international vacation travel is quite limited. To fill this gap, we collected survey data among tourists, mostly international, visiting the Austrian Alps and estimated a choice model between personal vehicle and rail. The results revealed a cost dumping effect, and the significant influence of factors related to overall travel convenience, luggage transport, travel party size, and the accessibility of the destination by rail. The tourists reacted with little elasticity to changes in cost and travel time, and exhibited a higher value of time than in other studies on long-distance travel, which was also higher than the hourly wage in their home countries. This article delivers valuable evidence that could contribute to improved long-distance rail services, more accurate project appraisals, and better marketing campaigns and transportation policies to make rail more competitive against the personal vehicle, and facilitate more sustainable vacation travel.

Traffic Violation Detection System

Travel convenience is impacted by a number of factors, including the condition of the road, traffic, length of trip, accidents, speed, etc. The daily increase in accident rates poses the biggest concern in Sri Lanka. These events not only result in fatalities but also increase the nation's financial losses. Traffic congestion is brought on by road users' lack of discipline and sentiments, which may result in traffic offenses. The goals of this research are to curb any traffic infractions as well as reduce corruption and nepotism on the road. This system was developed as separate three models namely edge server, fine management system and centralized server. Edge server developed in python is to detect traffic violations such as parking, single line cutting, double line cutting, one way and u turn in real time according to the changing rules and constraints configured by the traffic police admin via the fine management system which supports a configurable platform designed using canvas designing tools. Upon edger server identifying violations, the functions in the centralized server responsible to recognize the number plate of the violated vehicle will be triggered and send a sms to driver for further fine management and payment supported by the fine management system. The mobile application controlling server is responsible to track and inform the violations to nearest police officer in any case the system could not rectify the vehicle number plate.

The application of deep learning in autonomous driving

Autonomous driving technology is currently a globally prominent subject, with its relevance and impact readily apparent. Leveraging advanced sensors, sophisticated algorithms, and state-of-the-art computer vision techniques, autonomous vehicles can autonomously navigate, mitigate traffic accidents, and alleviate urban congestion. Furthermore, this technology is poised to accelerate innovation within the automotive sector, drive industrial advancement, and enhance people's convenience and safety in their travel experiences. The importance of autonomous driving technology is not only reflected in its own advantages, but also in its ability to lead the development direction of intelligent transportation in the future, helping to promote the development of intelligent transportation systems, realize the intelligent interconnection between vehicles and vehicles, vehicles and road infrastructure, and further enhance the safety and convenience of traffic travel. Therefore, autonomous driving technology is a significant innovation that will bring a better and more convenient future for mankind. In this study, a method based on sensor internal and external parameter calibration transformation matrix, road target detection algorithm, automatic vehicle detection method, pedestrian intention prediction technology and automatic pedestrian recognition system are analyzed, which are applied to object detection and obstacle avoidance. This article provides a good overview of the field of autonomous driving.

YAATRIASSIST : Passenger Facilitation Using AI and ML

YaatriAssist is a revolutionary travel application that reimagines global adventures with unmatched convenience and sophistication. This innovative app integrates essential functionalities seamlessly, offering real-time GPS navigation for confident exploration and integrated weather updates for preparedness in diverse climates. It features a comprehensive travel log for capturing and cherishing memories, along with an optimized scheduler to maximize trip enjoyment. The curated news hub keeps travelers informed about local events and global developments, while Travel mate fosters connections between fellow explorers, enhancing journey richness. Language barriers are effortlessly overcome with translation and OCR functionalities. Customizable settings ensure personalized experiences, evolving with individual travel needs. Facilitating bookings for flights, accommodations, and activities directly through the app streamlines trip management, offering unparalleled convenience. In summary, YaatriAssist stands as the epitome of travel convenience, catering to both seasoned globetrotters and business travelers, empowering users to navigate, explore, and engage with the world confidently and effortlessly.

A cooperative optimization method for the layout of shared bicycle parking areas and delivery quantity

With the popularity of shared bicycles in urban areas, more and more residents choose this fast and convenient mode of transportation for short-distance travel. By optimizing the layout of shared bicycle parking areas and delivery quantity, the investment cost of shared bicycle enterprises can be effectively reduced, and the convenience of residents' travel can be improved at the same time. In this paper, we develop a collaborative optimization model for the layout of the shared bicycle parking area and delivery quantity, aiming at minimizing the walking distance of residents and the investment cost of enterprises, while considering the constraints of the parking area's attractive range and the number of bicycles placed. Aiming at the characteristics of this mixed integer nonlinear problem, an improved genetic algorithm incorporating symmetric individual precision control mechanism is designed. Finally, taking the planned area between the Second Ring Road and the Third Ring Road in the northern part of Jin-niu District, Chengdu as the background, the proposed collaborative optimization model for the layout of shared bicycle parking areas and delivery quantity is applied to a real scene. The results show that after optimization, the number of parking areas is reduced by 2, and the total investment cost is reduced by about 12.2%.

Reform of Practical Teaching of Road Engineering Specialty Based on Cultivation of Innovative Ability

Road engineering, as a core component of urban transportation and infrastructure construction, is not only related to the travel convenience of urban residents but also directly related to the development of the urban economy and the sustainable progress of society with the continuous expansion of urban scale and the rapid growth of population. In this context, the importance of the road engineering profession has become more and more prominent. In this paper, we will focus on the innovation ability cultivation and practical teaching reform of the road engineering profession. Through in-depth discussion of the development trend of the road engineering profession, as well as the design of innovative practical teaching strategies, optimization of the curriculum system, and strengthening of the practical ability, we aim to provide an effective way to cultivate the innovation consciousness, problem-solving ability and teamwork spirit of the students of the road engineering profession.

An evolutionary multi-task assignment method adapting to travel convenience in mobile crowdsensing

Mobile crowdsensing (MCS) is a powerful IoT sensing model that leverages the mobility of workers and the sensors embedded in smartphones to sense diverse phenomena in the city. The task assignment in MCS is primarily location-based, with workers traveling to the corresponding location to complete tasks. Assigning tasks that are far away from a worker’s destination may cause inconvenience. Thus, this paper shortens remaining distances to improve workers’ travel convenience, which may, however, negatively impact the MCS platform’s utility. To strike a balance between these two objectives, we assign different weights to them and transfer them into a single objective optimization problem. Then we propose an evolutionary algorithm, the Travel Convenience Adaptive algorithm based on Genetic Algorithm (TCA-GA), to solve the objective optimization problem. We determine the appropriate weights for each objective under different experiment settings and conduct an experimental analysis based on synthetic and real-world datasets. The results verify that the proposed algorithm can effectively improve workers’ travel convenience while the MCS platform’s utility is maintained at a high level.

Prospect of Tourism Development in Khaptad National Park: A Local Perspective

Tourism in Nepal has flourished over the past two decades, making it one of the top global destinations for visit. Its abundant wildlife, stunning trekking routes, snow-fed rivers, picturesque lakes, and warm-hearted locals have been contributing perpetually to appeal to the global and local tourists. With the rise of the digital economy, tourism is experiencing modern advancements. This study aims to analyze the perceptions of local residents regarding tourism development. Structural Equation Modeling (SEM) was employed to validate the research results, utilizing both descriptive and inferential statistics. A sample size of 219 respondents was conveniently selected; indicating a higher interest among males and a predominance of economically active individuals aged 21-40 years. The study shows ICT development emerging as a common challenge for visitors to Khaptad National Park. The SEM results confirmed the fit and validity of five constructs. To establish KNP as a premier tourist destination, the Tourism Board, Government, and Municipality should prioritize its development and manage the influx of tourists. Notably, motivation and subjective norms significantly influence visitors’ behavior, while perceived behavioral control and behavioral intention do not. Local communities should actively engage in promoting tourism through effective marketing strategies, and the improvement of ICT facilities will enhance travel convenience. Hence, efforts should be made to promote local business activities and products. The findings of this analysis will benefit various stakeholders, including the Ministry of Culture, Tourism and Civil Aviation, Nepal Tourism Board, Department of Tourism, hotel associations, Travel agencies, local governments, researchers, professionals, and prospective students. This article is an original work with no potential conflict of interest regarding its research and publication.

Numerical Investigations of Tribological Characteristics of Biomimetic-Textured Surfaces

Rail transportation has dramatically improved travel convenience, but it has also led to environmental pollution and energy consumption issues. These challenges can be partially addressed by reducing friction loss in the mechanical transmission of rail systems. This paper examines the tribological properties of bionic-textured surfaces inspired by snake- and sharkskin. This study focuses on generating bionic textured surfaces with randomly distributed peaks through numerical simulation and connecting them to a transient Reynolds equation and friction fatigue model. The bionic surface wear lubrication model considers the lubricating film’s thickness and contact pressure obtained from the GT model. The results reveal that the existence of a bionic texture can reduce the friction coefficient and wear amount on the contact surface. The findings of this study not only offer a potential solution for reducing energy consumption and emissions in intelligent rail transit systems but also hold promise for providing further insights into the numerical simulation of bionic weaving and the investigation of tribological characteristics.

Proposed Marketing Strategy to Enhance Brand Awareness for Wisata Murah Indonesia

Tourism is one of the industries most impacted by the COVID-19 pandemic. As the virus recedes, the tourism industry is experiencing a revival, resulting in increased competition. Nevertheless, numerous businesses are unable to regain their prepandemic positions. Wisata Murah Indonesia is among the companies facing this situation due to the company’s lack of brand awareness. This research aims to raise awareness and develop a new marketing strategy for Wisata Murah Indonesia in order to boost revenue. This research uses two methods of analysis, namely the qualitative method and the quantitative method to conduct internal and external analysis. The outcomes were then used as the foundation for a SWOT analysis, which was followed by a TOWS analysis and a QSPM analysis to identify possible implementation strategies. This analysis results in a new business strategy to increase revenue at Wisata Murah Indonesia is to create affordable, trend-based special tour packages and to add passport and visa-making services so that customers are attracted by the convenience of travel. Additionally, raise awareness by conducting online and offline promotions. Online promotions include collaborating with influencers and adding new marketing channels, namely TikTok and YouTube. Offline promotion is by making tour packages with special prices or discounts for offline purchases, such as at the Travel Fair. Wisata Murah Indonesia can also improve their brand reputation to increase customer loyalty and potential customers.

Research on smart mobility in public transportation and solutions for mobility

As an important part of modern urban transportation system, smart mobility and public transportation are directly related to people's travel convenience, transportation efficiency and sustainable urban development. With the continuous progress of science and technology, smart mobility solutions play an increasingly important role in the field of smart travel and public transportation. As an important support of urban transportation system, public transportation is of great significance in reducing traffic congestion, improving air quality and saving energy. However, traditional public transportation systems often face problems such as irrational route design, improper scheduling, and untimely information transfer. Therefore, the introduction of smart mobility solutions, such as intelligent scheduling systems and passenger information services, will bring new improvement and development opportunities for public transportation. The research significance of this thesis is to conduct an in-depth study on smart mobility solutions in the field of smart mobility and public transportation, so as to explore how to promote the upgrading and improvement of the transportation system at the technical, managerial and policy levels. This paper will focus on the integration of smart mobility and public transportation, exploring the synergies between the two to achieve a more efficient, environmentally friendly and convenient way of traveling.

Geographic-Information-System-Based Risk Assessment of Flooding in Changchun Urban Rail Transit System

The frequent occurrence of urban flooding in recent years has resulted in significant damage to ground-level infrastructure and poses a substantial threat to the metro system. As the central city’s core transportation network for public transit, this threat can have unpredictable consequences on travel convenience and public safety. Therefore, assessing the risk of urban flooding in the metro system is of utmost importance. This study is the first of its kind to employ comprehensive natural disaster risk assessment theory, establishing an assessment database with 22 indicators. We propose a GIS-based method combined with the analytical hierarchy process (AHP) and an improved entropy weight method to comprehensively evaluate the urban flood risk in Changchun City’s metro systems in China. This study includes a total of nine metro lines, including those that are currently operational as well as those that are in the planning and construction phases, situated in six urban areas of Changchun City. In this study, we utilize the regional risk level within the 500 m buffer zone of the metro lines to represent the flood risk of the metro system. The proposed method assesses the flood risk of Changchun’s rail transit system. The results reveal that over 30% of Changchun’s metro lines are located in high-risk flood areas, mainly concentrated in the densely populated and economically prosperous western part of the central city. To validate the risk assessment, we vectorized the inundation points and overlaid them with the regional flood risk assessment results, achieving a model accuracy of over 90%. As no large-scale flood events have occurred in the Changchun rail transit system, we employed receiver operating characteristic (ROC) curves to verify the accuracy of the flood risk assessment model, resulting in an accuracy rate of 91%. These findings indicate that the present study is highly reliable and can provide decision makers with a scientific basis for mitigating future flood disasters.

Sustainable urban mobility: Flexible bus service network design in the post-pandemic era

The excessive traffic congestion in vehicles lowers the service quality of urban bus system, reduces the social distance of bus passengers, and thus, increases the spread speed of epidemics, such as coronavirus disease. In the post-pandemic era, it is one of the main concerns for the transportation agency to provide a sustainable urban bus service to balance the travel convenience in accessibility and the travel safety in social distance for bus passengers, which essentially reduces the in-vehicle passenger congestion or smooths the boarding–alighting unbalance of passengers. Incorporating the route choice behavior of passengers, this paper proposes a sustainable service network design strategy by selecting one subset of the stops to maximize the total passenger-distance (person × kilometers) with exogenously given loading factor and stop-spacing level, which can be captured by constrained non-linear programming model. The loading factor directly determines the in-vehicle social distance, and the stop-spacing level can efficiently reduce the ridership with short journey distance. Therefore, the sustainable service network design can be used to help the government minimize the spread of the virus while guaranteeing the service quality of transport patterns in the post-pandemic era. A real-world case study is adopted to illustrate the validity of the proposed scheme and model.

An Automatic Traffic Violation Ticketing System Using Radio Frequency Identification (RFID) Technology

Travel convenience is impacted by a number of factors, including the condition of the road, traffic, length of trip, accidents, speed, etc. The daily increase in accident rates poses the biggest concern. These events not only result in fatalities but also increase the nation's financial losses. Traffic congestion is brought on by road users' lack of discipline and sentiments, which may result in traffic offenses. The goals of this research are to curb any traffic infractions as well as reduce corruption and nepotism on the road. This system was developed using an Atmega328 microcontroller, which instructs the system to identify any driver who violates a traffic light and send an SMS message to the violator and the road management of the violation and the location where it was done. This identification is done with the help of a radio frequency identification (RFID) reader, which gets the unique ID of the vehicle and sends back the information to the microcontroller, which now instructs the GSM module to send the SMS message.

Analisis Kompetisi Moda Trans Padang pada Koridor V (Studi Kasus: Indarung - Pasar Raya Padang)

The Padang City is one of the cities that still provides angkot as one of the public transportation mode services. Most of users of this mode are students and students. City transportation routes in the city of Padang are spread to various parts of the city of Padang with the central center of movement from the Pasar Raya Padang. However, since the presence of Tans Padang in January 2014, city transportation modes have started to have new competitors. Since July 2022 Corridor V has been serving a new route, namely Corridor of Indarung - Pasar Raya Padang. This study aims to describe the characteristics of travelers in choosing the mode and explore the factors that influence travelers in choosing the mode of transportation. Data collection methods are carried out by surveys and interviews. The variables reviewed include aspects of travel convenience, travel safety, travel time and travel costs. The analysis technique uses multiple linear regression methods. Based on characteristic analysis data, it is known that 54.5% of mode users have income at an average level (Rp. 1,000,000 – 3,000,000). For users of this mode, the travel time variable (47.25%), the travel cost variable (43.25%), the travel convenience variable (36%), and the travel safety variable (8.25%) are still the factors that are the main considerations in choosing the mode. Keywords: City Transport, trans padang, mode of transportation.