Types Of Trips Research Articles

Characterizing human mobility patterns in rural settings of sub-Saharan Africa.

Human mobility is a core component of human behavior and its quantification is critical for understanding its impact on infectious disease transmission, traffic forecasting, access to resources and care, intervention strategies, and migratory flows. When mobility data are limited, spatial interaction models have been widely used to estimate human travel, but have not been extensively validated in low- and middle-income settings. Geographic, sociodemographic, and infrastructure differences may impact the ability for models to capture these patterns, particularly in rural settings. Here, we analyzed mobility patterns inferred from mobile phone data in four Sub-Saharan African countries to investigate the ability for variants on gravity and radiation models to estimate travel. Adjusting the gravity model such that parameters were fit to different trip types, including travel between more or less populated areas and/or different regions, improved model fit in all four countries. This suggests that alternative models may be more useful in these settings and better able to capture the range of mobility patterns observed.

What influences the substitution of ride-sourcing for public transit and taxi services in Toronto? An exploratory structural equation model-based study

The continued growth and utilization of ride-sourcing services have reshaped traditional perceptions of urban mobility. As the popularity of this relatively novel mode of travel has continued to grow, there has been a greater focus on the effect that the adoption and use of ride-sourcing have on the utilization of more traditional modes of transportation. With a few notable exceptions, prior studies on the topic often rely on descriptive statistics to understand the modes that are replaced by ride-sourcing for specific trips. This study utilizes structural equation models to investigate the factors influencing the decision to choose public transit and taxi as their so-called substitute alternative mode for a recent ride-sourcing trip, using data from a web-based survey of Toronto residents. The results indicate that socio-economic and trip-related attributes influence the selection of the substitute alternative mode, and to a lesser extent, attitudes toward ride-sourcing services. In particular, students, persons from lower-income households, and transit pass owners were found to be more likely to substitute ride-sourcing for public transit, while older respondents and persons from wealthier households were more likely to select taxi instead. The study outcomes shed light on the types of transit trips that are more likely to be replaced in favor of ride-sourcing services and the attributes of individuals who are more likely to make this replacement. This information can inform policies that aim to reduce the substitution of ride-sourcing for public transit, which can worsen both congestion and emissions.

Purpose-Based Walking Trips by Duration, Distance, and Select Characteristics, 2017 National Household Travel Survey.

New or enhanced activity-friendly routes to everyday destinations is an evidence-based approach for increasing physical activity. Although national estimates for some infrastructure features surrounding where one lives and the types of nearby destinations are available, less is known about the places where individuals walk. A total of 5 types of walking trips (N = 54,034) were defined by whether they began or ended at home (home based[HB]) and trip purpose (HB work, HB shopping, HB social/recreation, HB other, and not HB trip) (2017 National Household Travel Survey). Differences and trends by subgroups in the proportion of each purpose-oriented trip were tested using pairwise comparisons and polynomial contrasts. About 14% of U.S. adults reported ≥1 walking trip on a given day. About 64% of trips were HB trips. There were few differences in prevalence for each purpose by subgroup. For example, prevalence of trips that were not HB decreased significantly with increasing age and increased with increasing education and household income. Given age-related and socioeconomic differences in walking trips by purpose, planners and other professionals may want to consider trip origin and destination purposes when prioritizing investments for the creation of activity-friendly routes to everyday destinations where people live, work, and play.

Electric bike-sharing services mode substitution for driving, public transit, and cycling

In hopes of reducing traffic congestion, air and noise pollution, and energy consumption, bike sharing is becoming increasingly popular around the world. Underlying many of the benefits attributed to bike sharing is an assumption that bike share journeys replace a significant proportion of trips previously made by car. This paper examines factors correlated with the use of an electric bike-sharing system in Tricity, Poland. We use the double hurdle estimation approach on data from two matched surveys: before and after the implementation of the system. Our analyses indicate that electric bike rides did not act as a substitute for car trips. Shared e-bikes were used by residents as a substitute for public transportation or as a first/last mile of transport to/from public transportation stops. We examined the use of e-bikes for various types of trips and identified factors encouraging and discouraging people from usage of bike-sharing and cycling in general.

Identification of key determinants of travel satisfaction for developing policy instrument to improve quality of life: An analysis of commuting in Delhi

Commuting between an origin and destination pair is one of the most critical components of an individual's daily activity, and the associated trip satisfaction significantly influences a commuter's well-being. Owing to negative externalities associated with urban travel such as increased congestion, poor roadway infrastructure, inadequate and unreliable public transport system, safety and security concerns, a reduction in perceived trip satisfaction could be observed among Indian commuters. Thus, it is prudent to analyze commuters' perception towards associated trip satisfaction and related components for formulating policy instruments to improve commuters' experience. This paper identified the key determinants of perceived satisfaction related to different types of trips in the Indian capital New Delhi. A Travel survey questionnaire was designed to elicit commuters' perceived satisfaction associated with daily, work, and non-work trips. Based on 898 responses, a set of ordered logit models were estimated. It was found that socio-demographic factors such as gender and age, accessibility and built-environment characteristics such as streets' level of congestion, availability and existing condition of sidewalks, bus stop safety, and security were significant determinants of commuters' trip satisfaction. Results also indicated that the choice of mode and associated safety perception played a vital role in commuters' trip satisfaction levels. Public transport users were less satisfied compared to the car commuters for both work and non-work trips. Based on the findings, a set of policy measures such as illumination of roadways, reduction in street-congestion levels, up keeping existing sidewalks, improving public transportation accessibility, etc. could be implemented for enhancing the trip-satisfaction level of urban commuters belonging to a typical metropolitan city of a developing country like India.

Convolutional neural encoding of online reviews for the identification of travel group type topics on TripAdvisor

Previous studies have concluded that there are significant differences in travelers’ preferences depending on the trip type. The problem of extracting users’ preferences from a corpus of text can be solved by using traditional clustering algorithms, which work quite well when there is no predefined data structure. However, in this paper, we consider the problem of extracting users’ preferences when they belong to a finite number of classes represented by the trip type. In this paper, we propose an encoding method based on a Convolutional Neural Networks (CNNs), trained as a classifier for the classes that predefine data structure. The intuition behind convolutional neural encoding is its ability to maximize the distance between documents belonging to different classes in the new, derived feature space. Findings reveal that CNNs encoding has better discriminative properties than alternative encoding methods such as Latent Dirichlet Allocation or average word2vec encoding. Moreover, we demonstrate that CNNs encoding can be used to identify the unique topics associated with the predefined data structure determined, in this case, by the four trip types.

Commuter demand estimation and feasibility assessment for Urban Air Mobility in Northern California

This study aims to estimate passenger demand for Urban Air Mobility (UAM) and analyze the feasibility of operating the system in Northern California. UAM is a concept mode of transportation that is designed to bypass ground congestion for time-sensitive, price-inelastic travelers using autonomous, electric aircraft with Vertical Takeoff and Landing (VTOL) capabilities. This study focuses specifically on commuting trips, which are frequent and considered relatively more time-sensitive than other types of personal trips. The UAM mode's feasibility is studied using sensitivity analysis of UAM demand to cost per passenger mile and the number of vertiports placed in the region. This study also explores the spatial distribution of UAM demand in Northern California, which further helps in identifying the major commuter trip-attraction and trip-production zones for the UAM mode in the region. The results indicate that sufficient UAM demand for commuting trips can only be reached at optimistically low UAM offered fares. These fare levels could be challenging to obtain given the high real estate cost in Northern California's urban regions. Moreover, the reliability of the UAM mode must be comparable to the automobile mode; otherwise, it loses significant demand with increasing delays. The results also show that the commuting flows with promising UAM demand in Northern California are heavily one-directional, with San Francisco Financial District being a major attraction. Other types of trips should also be considered along with commuting trips to generate an economically viable system and reduce deadheading.

Psychological impacts of COVID-19 pandemic on the mode choice behaviour: A hybrid choice modelling approach

The COVID-19 pandemic is a pivotal moment in the history of mankind, which had a huge impact on the fast-paced world. The uncertainty associated with the plight of the pandemic, pushed the world towards a sense of insecurity and panic. Apart from the disease, the psychological problems connected to the lockdowns has caused an unprecedented change in the thought process of people towards travel. In the present study, we aim to statistically illustrate the change, the pandemic and lockdowns brought upon the travel mode choice behaviour. An Integrated choice and latent variable (ICLV) framework was adapted to understand the impact of the novel behavioural constructs, such as awareness of the disease and people's perception of the strictness of lockdown towards the mode choice in the post pandemic scenario. Different trip types were characterized according to the nature of the trip and their mode choice were assessed separately for the impact of the latent constructs. The results suggest that the awareness of the disease and the perception of strictness of the lockdown implemented play a major role in affecting the change of the mode choice of people. Further, the perception of safety in public transport, characterized by the social distancing and sanitization measures, determine the willingness of people towards the choice of public transit systems. The study concludes with a focus on the policies, which could be implemented for a safe travel in the post lockdown stage.

Bus rapid transit system as a potent agent for transit-oriented development: A study of Transjakarta passengers’ mode shift

Recently there has been discussions on the role of bus rapid (BRT) transit in transit-oriented development (TOD). This article explores a feature of bus rapid transit within the framework of TOD’s principle of developing built environment and transit systems that trigger its citizens to shift from using private motorised vehicle to using transit system for daily mobility. This article explores Transjakarta BRT’s ability to trigger mode shift from doing other way of travelling to using Transjakarta. This article was written through a descriptive-qualitative research using inductive reasoning. Mode shift data was collected through indirect interview using online questionnaire. Other way of travelling prior to using Transjakarta was asked to Transjakarta passengers. Detailed information regarding the passengers’ background and the type of trips the passengers are doing was also gathered. The data was processed using simple statistical analysis and Bartlett’s test for distribution variance. This article finds that Transjakarta is able to trigger mode shift among its passengers. Furthermore, Transjakarta is even able to trigger mode shift from using private motorised vehicle to using Transjakarta. The ability to trigger mode shift is relatively homogenous across all groups of Transjakarta passengers. This article proposes an alternate approach in evaluating a rapid transit system within the framework of TOD, that is evaluating its ability in triggering mode shift.

Comparative study on the aerodynamic performance of airfoil with boundary layer trip of various geometrical shapes

Performance of small scale wind turbine (SSWT) and miniature aerial vehicles (MAV) is always effected with Laminar separation bubble. The problem of a laminar separation bubble on the upper surface of an E216 airfoil operated at low Reynolds number (Re=100000) is investigated numerically. Incompressible steady two-dimensional simulation is carried out with Transition γ − Reθ turbulence model on the airfoil with a boundary layer trip (BLT). The performance of two different types of trips, namely, isosceles triangular (IT) and right-angled triangular (RA) is compared with that of the airfoil with a rectangular (RT) trip. The trip locations used are, 17% of the chord for location-1 and 10% of the chord for location-2 from the leading edge of the airfoil, while the trip heights selected are 0.3 mm, 0.5 mm, 0.7 mm, and 1 mm. Results showed that the boundary layer trip significantly affected the laminar separation and improved the aerodynamic performance of the airfoil. Maximum improvement in drag by 17.41% and corresponding lift to drag ratio by 10.86% are obtained for the isosceles trip at location-2 for the angle of attack of 6°. There is no observable advantage for isosceles and right-angled triangular trips over rectangular trips. Considering the geometrical complexity in fabrication, the rectangular trip is recommended.

Effect of Demographic Characteristics on the choice of Paratransit Modes

The absence of public transportation has led to the growth and expansion of paratransit modes. This has increased traffic congestion, traffic crashes and traffic pollution. This research assessed the effect of demographic characteristics on para transiting in Lagos with special focus on the mainland. To achieve the aim of this research, the mainland was divided into two zones based on the geographical location which are the Ikorodu and Ikeja zone. Domiciliary information techniques were used in data collection. This was backed up with an oral interview. Two hundred question (200) questionnaires were administered with 89% return rate. The information captured were demographic characteristics, the volume of trips, frequency of trips, trip types, operations of the paratransit transportation system, travel behaviour of passengers (travel time, travel cost, travel purpose). SPSS version 18 was used for the data analysis. The result of the survey revealed that paratransit modes serve as a feeder connection between neighbourhoods in the study area. Additionally, it provides a feeder connection between major arterial roads (truck A and B roads). Flexibility accounts for 41% of the reason why paratransit mode is preferred by respondents. The bivariate analysis showed a weak negative relationship for the correlation between frequency of trip and age. The outcome of this research will aid transportation planners, policymakers, and transportation experts on the appropriate strategy to adopt for effective mobility as a unimodal approach to providing effective movement may not be foreseeable in the study area.

An Optimal Day-Ahead Scheduling Framework for E-Mobility Ecosystem Operation With Drivers’ Preferences

The future e-mobility ecosystem will be a complex structure with different stakeholders seeking to optimize their operation and benefits. In this paper, a day-ahead grid-to-vehicle (G2V) and vehicle-to-grid (V2G) scheduling framework is proposed including electric vehicles (EVs), charging stations (CSs), and retailers. To facilitate V2G services and to avoid congestion at CSs, two types of trips, i.e., mandatory and optional trips, are defined and formulated. Also, EV drivers’ preferences are added to the model as cost/revenue threshold and extra driving distance to enhance the practical aspects of the scheduling framework. An iterative process is proposed to solve the non-cooperative Stackelberg game by determining the optimal routes and CS for each EV, optimal operation of each CS and retailers, and optimal V2G and G2V prices. Extensive simulation studies are carried out for two different e-mobility ecosystems of multiple retailers and CSs as well as numerous EVs based on real data from San Francisco, the USA. The simulation results show that the optional trips not only reduces the cost of EVs and PV curtailment by 8.8-24.2% and 26.4-28.5% on average, respectively, in different scenarios, but also mitigates congestion during specific hours while respecting EV drivers’ preferences. Moreover, the simulation results revealed the significant impact of EV drivers' preferences on the optimal solutions and cost/revenue of the stakeholders.

Bikeshare trips in Seoul, South Korea

The bikeshare program in Seoul, the capital of South Korea, generates more than a million trips per month with more than 1500 bikeshare stations and about 20,000 bikes operating across the city. We examine the spatial patterns of bikeshare usage in Seoul, which is a very densely populated city with a large metro system. We analyze the association between land use, subway stations, employment density, population density, and bikeshare usage with negative binomial conditional autoregressive models that account for spatial correlation. For all the models, results show a positive association of bikeshare usage with the number of subway stations and employment density, with the former having a larger effect. Agricultural and Amusement land uses have negative associations with bikeshare usage in many models. We also examine different types of trips to distinguish differences between “loop trips” (starting and ending at the same station) and purposeful trips between two destinations. The former displays a pattern suggesting “loop trips” are more likely to be recreational trips.

Effect of Price and Time on Private and Shared Transportation Network Company Trips

Transportation network companies (TNCs) offer two types of service: private-party ridehailing and shared ridehailing. Policymakers have an interest in encouraging shared over private ridehailing to promote more efficient use of the transportation network. While transportation researchers have analyzed ridehailing behavior before, there is limited literature describing the effect of price and time on a rider’s choice between private-party and shared ridehailing. This paper fills this gap by analyzing revealed preferences for private-party and shared ridehailing trips in 15 American cities coupled with a survey of 4,365 users of a large TNC that includes stated preference questions focused on various alternative options for their most recent trip choice. This study finds that an increase in the relative price difference of $1 per mile increases an individual’s probability of sharing by over 8%, while a decrease in the relative travel time difference of 1 min per mile increases the probability of sharing by over 33%. The survey results also show that that a sizable proportion of private-party TNC trips (approximately 35%) will be difficult or even impossible to convert to shared rides through a price-based incentive. Market segmentation analysis reveals user and trip types where price- and time-based incentives have a relatively greater effect on the choice between private and shared rides. Finally, heterogeneity in user time versus money trade-offs suggests new product possibilities that would increase TNC sharing.

A identidade do turista e o consumo colaborativo


 
 
 
 Por meio de plataformas digitais, o consumo colaborativo possibilita o acesso a diversos produtos e serviços, assumindo papel essencial na construção de identidades. Ao ampliar a participação dos indivíduos nas escolhas de suas viagens e permitir o contato direto entre os usuários, essa forma de consumo tem conseguido adesão de pessoas em busca de alternativas no mercado turístico, e dado espaço para o discurso anti-turista, direcionado para consumidores que procuram se distanciar do turismo tradicional, geralmente de massa. Compreendendo que os consumidores atuam na propagação de discursos e imagens sobre um serviço ou destino, bem como na construção de sua identidade de consumo, buscou-se entender como os usuários do Airbnb interpretam as mensagens apresentadas pela plataforma e as relacionam com a sua identidade de turista (tradicional) ou viajante (anti-turista). Os resultados deste estudo, de natureza qualitativa, obtidos a partir da análise dos dados gerados por entrevistas semiestruturadas, indicam que os respondentes se indetificam mais com a proposta dos serviços oferecidos pela plataforma do que com a ideia do ser turista ou viajante. Com interesses semelhantes, os usuários revelam possuir características de consumo comuns aos dois perfis de consumidores, variando conforme o tipo de viagem que cada um realiza.
 
 
 

Longitudinal Analysis of Transit-Integrated Ridesourcing Users and Their Trips

Several municipal transit agencies have partnered with transportation network companies to provide a range of services, but data restrictions have limited research on trip-level observations of transit-integrated ridesourcing users. The goal of this study was to understand how users’ trip-making behaviors adapted to a transit-integrated ridesourcing pilot in Waterloo, Ontario. This research conducted a longitudinal analysis of 178 unique users and temporal analyses of their 4,536 ridesourcing trips (rides) taken throughout the pilot from November 2018 to December 2019. Trip type and frequency changes over time were measured for frequent, average, and infrequent users. Transit, walking, and cycling alternatives to the pilot rides were generated and characterized based on their complementarity with transit. The number of unique users and daily ridership increased over time, as new users made their first trips and existing users made trips more frequently. Frequent users shifted toward less transit-competitive trip types whereas average and infrequent users had a sporadic but larger share of more transit-competitive trip types. The pilot was mostly used during off-peak service periods, when transit was less frequent, which suggests these systems are valuable for nonwork trips. Transit trip alternatives were not temporally competitive with rides. Cycling was competitive with 5% to 10% of rides and was consistently faster than walking and transit alternatives. Walking was not a practical alternative to rides in most cases. This analysis may inform other agencies of performance evaluation techniques for their transit-integrated ridesourcing pilots and the unique characteristics of trips taken by users of this mode.

The Impact of driver distraction and secondary tasks with and without other co-occurring driving behaviors on the level of road traffic crashes

Driving safety is typically affected by concurrent non-driving tasks. These activities might negatively impact the trips’ outcome and cause near-crash or crash incidents and accidents. The crashes impose a tremendous social and economic cost to society and might affect the involving individuals’ quality of life. As it stands, road injuries are ranked among top-ten leading causes of death by the World Health Organization. Distracted driving is defined as an attention diversion of the driver toward a competing activity. It was shown in numerous studies that distracted driving increase the probability of near-crash or crash events. By leveraging the statistical power of the large SHRP2 naturalistic data, we are able to quantify the preponderance of specific distractions during daily trips and confirm the causality factor of an ubiquitous non-driving task in the crash event. We show that, except for phone usage which happens more frequently in near-crash and crash categories than in baseline trips, both distracted driving and secondary tasks occur almost uniformly in different types of trips. In this study, we investigate the impact of the co-occurrence of distracted driving with other driving behaviors and secondary tasks. It is found that the co-occurrence of distracted driving with other driving behaviors or secondary tasks increase the chance of near-crash and crash events. This study's findings can inform the design and development of more precise and reliable driving assistance and warning systems.

Impact of COVID-19 pandemic on mobility in ten countries and associated perceived risk for all transport modes.

The restrictive measures implemented in response to the COVID-19 pandemic have triggered sudden massive changes to travel behaviors of people all around the world. This study examines the individual mobility patterns for all transport modes (walk, bicycle, motorcycle, car driven alone, car driven in company, bus, subway, tram, train, airplane) before and during the restrictions adopted in ten countries on six continents: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. This cross-country study also aims at understanding the predictors of protective behaviors related to the transport sector and COVID-19. Findings hinge upon an online survey conducted in May 2020 (N = 9,394). The empirical results quantify tremendous disruptions for both commuting and non-commuting travels, highlighting substantial reductions in the frequency of all types of trips and use of all modes. In terms of potential virus spread, airplanes and buses are perceived to be the riskiest transport modes, while avoidance of public transport is consistently found across the countries. According to the Protection Motivation Theory, the study sheds new light on the fact that two indicators, namely income inequality, expressed as Gini index, and the reported number of deaths due to COVID-19 per 100,000 inhabitants, aggravate respondents’ perceptions. This research indicates that socio-economic inequality and morbidity are not only related to actual health risks, as well documented in the relevant literature, but also to the perceived risks. These findings document the global impact of the COVID-19 crisis as well as provide guidance for transportation practitioners in developing future strategies.

Mobility and the effective reproduction rate of COVID-19

ObjectivesDue to the infectiousness of COVID-19, the mobility of individuals has sharply decreased, both in response to government policy and self-protection. This analysis seeks to understand how mobility reductions reduce the spread of the coronavirus (SAR-CoV-2), using readily available data sources. MethodsMobility data from Google is correlated with estimates of the effective reproduction rate, Rt, which is a measure of viral infectiousness (Google, 2020). The Google mobility data provides estimates of reductions in mobility, for six types of trips and activities. Rt for US states are downloaded from an on-line platform that derives daily estimates based on data from the Covid Tracking Project (Wissel et al., 2020; Systrom et al., 2020). Fixed effects models are estimated relating mean Rt and 80% upper level credible interval estimates to changes in mobility and a time-trend value and with both 7-day and 14-day lags. ResultsAll mobility variables are correlated with median Rt and the upper level credible interval of Rt. Staying at home is effective at reducing Rt,. Time spent at parks has a small positive effect, while other activities all have larger positive effects. The time trend is negative suggesting increases in self-protective behavior. Predictions suggest that returning to baseline levels of activity for retail, transit, and workplaces, will increase Rt above 1.0, but not for other activities. Mobility reductions of about 20–40% are needed to achieve an Rt below 1.0 (for the upper level 80% credible interval) and even larger reductions to achieve an Rt below 0.7. ConclusionsPolicy makers need to be cautious with encouraging return to normal mobility behavior, especially returns to workplaces, transit, and retail locations. Activity at parks appears to not increase Rt as much. This research also demonstrates the value of using on-line data sources to conduct rapid policy-relevant analysis of emerging issues.

From netnography to segmentation for the description of the rural tourism market based on tourist experiences in Spain

This study aims to offer a basis for developing appropriate response strategies through understanding tourists’ natural perceptions related to their rural tourism experiences and the characteristics of the rural tourism market segments. To achieve this purpose, the netnography methodology, which is an online participatory observation technique based on user-generated online content that enables market researchers to observe natural consumer behaviors, was conducted on 1002 tourists’ opinions in three online communities. Qualitative information derived from netnography combined with quantitative tools, multiple correspondence analysis and cluster analysis, allows for the segmentation of the rural tourism market. It has been confirmed that three market segments exist in rural tourism in Spain and three corresponding themes have also been derived from the results; comfort-driven visitor, rural ambiance spender, and active leisure seeker. This study is significant in that it began with the qualitative collection of user-generated online content from netnography and finished with the quantitative segmentation of the market based on tourist experiences. • Qualitative data combined with quantitative tools was used to describe the market. • Rural tourism experiences comprise a mix of cognitive, affective, and sensory parts. • Three primary segments in the rural tourism market in Spain were identified. • Defined as comfort-driven visitor, rural ambiance spender, and active leisure seeker. • These three segments differ in terms of trip types, price levels and region of origin.