Reviewing trip purpose imputation in GPS-based travel surveys

The global positioning system(GPS)has motivated rapid advances in mobility data collection.A massive amount of spatio-temporal information has made it possible to know where a person was and when,but not how and why(s)he travelled,creating the need for inference models.Compared with mode detection,purpose imputation has been insufficiently studied.However,the relative lack of attention to purpose identification does not mean that this field has not emerged.For this paper,which is the first review dedicated to inferringtrip purposes from GPS data,1162 non-duplicate papers from four databases(Scopus,Web of Science,ScienceDirect and TRID)were screened,and a corpus of 25 publications was selected for examination.Based on these papers,the purpose imputation problem is defined in the contexts of the evolution of GPS-based travel surveys and two research domains,transportation science(TS)and human geography(HG).Subsequently,three steps of the purpose detection process,namely trip end detection,input feature selection and main algorithms and validation,are surveyed.During these procedures,the differences between studies in TS and those in HG are highlighted.Finally,unresolved issues related to data and feature selection,algorithms and assessment are discussed substantially to provide potential research directions.This review may be an inform ative reference for those newly accessing the GPS-based purpose imputation field and/or intending to develop solutions to this problem.

Travel-Limiting Disabilities in the United States: Why Accessibility Matters?

This study evaluates the distribution of travel-limiting disabilities across genders and geographic locations in the United States. This study aims to describe and compare the socioeconomic and demographic variables of the people with and without travel-limiting disabilities across geographic locations and gender. The study further evaluates the trip purpose and impact of Covid-19 fourth wave pandemic on the use of public transit and travel to physical workplace for the people with and without travel-limiting disabilities across gender and geographic locations. The study uses the 2022 weighted National Household Travel Survey dataset and employs descriptive statistics. Results reaffirm the findings from previous literature that there are more people with travel-limiting disabilities in urban areas and among women. Over 50 percent of people aged 65 and above have a form of travel-limiting disabilities. The most trip for people with travel-limiting disabilities is made for shopping and medical purposes. Across all categories, rural areas, urban areas, male and female for the people without travel-limiting disabilities, COVID-19 fourth wave did not change the pattern of trips made to physical workplace as pre-COVID-19 era. This pattern is also observable for the people with travel-limiting disabilities in rural and urban areas. Females with travel-limiting disabilities reported making less trips to physical workplaces while male reported doing the same as before COVID-19 era. The study concludes that the quantification of travel-limiting disabilities across geographic location and gender is vital in disability study and could drive policy implementation for improved accessibility for the vulnerable population.

Travelers'attitudes toward carpooling in Lahore:motives and constraints

Traffic congestion has become a critical issue in developing countries,as it tends to increase social costs in terms of travel cost and time,energy consumption and environmental degradation.With limited resources,reducing travel demand by influencing individuals’ travel behavior can be a better long-term solution.To achieve this objective,alternate travel options need to be provided so that people can commute comfortably and economically.This study aims to identify key motives and constraints in the consideration of carpooling policy with the help of stated preference questionnaire survey that was conducted in Lahore City.The designed questionnaire includes respondents’ socioeconomic demographics,and intentions and stated preferences on carpooling policy.Factor analysis was conducted on travelers’ responses,and a structural model was developed for carpooling.Survey and modeling results reveal that social,environmental and economic benefits,disincentives on car use,preferential parking treatment for carpooling,and comfort and convenience attributes are significant determinants in promoting carpooling.However,people with strong belief in personal privacy,security,freedom in traveling and carpooling service constraints would have less potential to use thecarpooling service.In addition,pro-auto and pro-carpooling attitudes,marital status,profession and travel purpose for carpooling are also underlying factors.The findings implicate that to promote carpooling policy it is required to consider appropriate incentives on this service and disincentives on use of private vehicle along with modification of people’s attitudes and intentions.

Association between Active School Travel and Depressive Symptoms among 51,702 Adolescents in 26 Low- and Middle-Income Countries

Little is known about the role of active school travel(AST)on mental health among adolescents.Thus,this study aimed to explore the AST-depression association among adolescents aged 12–15 years from 26 low-and middle-income countries(LMICs).Data from the Global School-based Student Health Survey were analyzed in 51,702 adolescents[mean(SD)age 13.8(1.0)years;49.3%boys).Both depressive symptoms and AST were assessed by a single question self-reported measure,respectively.Participants who reported having 5 days or above were considered as AST.Multivariable logistic regression analysis(accounting for sampling weights)was performed while controlling for gender,age,physical activity,sedentary behavior,and food insecurity,and a countrywide meta-analysis was undertaken.The prevalence of depressive symptoms and AST were 30.1%and 37.0%,respectively.Compared with those not having AST,adolescents with AST were less likely to have self-reported depressive symptoms(OR=0.88,95%CI:0.85-0.93)regardless of gender.Countrywide meta-analysis demonstrated that having AST versus not having AST was associated with 12%lower odds for depressive symptoms(OR=0.88;95%CI:0.82-0.94)but with a moderate between-country heterogeneity(I^(2)=59.0%).Based on large samples of adolescents from LMICs,it would be expected that AST may play a critical role in preventing adolescent depression worldwide.However,it is necessary to consider more country-specific factors when implementing AST-related mental health interventions.Future studies should adopt the solid study design to confirm or negate our researchfindings.

Fuzzy Geometric Programming in Multivariate Stratified Sample Surveys in Presence of Non-Response with Quadratic Cost Function

In this paper, the problem of non-response with significant travel costs in multivariate stratified sample surveys has been formulated of as a Multi-Objective Geometric Programming Problem (MOGPP). The fuzzy programming approach has been described for solving the formulated MOGPP. The formulated MOGPP has been solved with the help of LINGO Software and the dual solution is obtained. The optimum allocations of sample sizes of respondents and non respondents are obtained with the help of dual solutions and primal-dual relationship theorem. A numerical example is given to illustrate the procedure.

Analysis of Transportation Users’ Preferences and Attitudes for Identifying Micro-Level Determinants of Transportation Network Companies’ (TNCs) Growth

Over the last decade, the popularity of Transportation Network Companies (TNCs) as a mode of travel has been increasing at a steady pace. This trend highlights the importance of identifying the determinants that influence transportation users to adopt TNCs as a preferred mode choice and the impacts of such preferences on their travel patterns and transportation network operation. This paper reports on a recent study undertaken in Birmingham, AL aiming at understanding and documenting the factors that influence transportation users to select TNCs (such as Uber/Lyft) for completing typical day trips. In doing so, a travel diary questionnaire survey was developed in accordance with the Institute of Transportation Engineers (ITE) Manual on Transportation Engineering Studies using the Qualtrics Research Core platform. The questionnaire was used to survey over 450 transportation users in the Birmingham Metro area. The survey participants provided detailed trip information for a typical 24-hr day along with demographic data and travel preference information. The survey responses provide high-resolution micro-level indicators of travel preferences and behaviors in a TNC-served area, which is a much-needed type of information for researchers and transportation planning agencies.

An empirical comparison of four technology-mediated travel survey methods

The increasing demana for advanced modelling methods, which can reflect complex travel activities of individuals, requires enhanced travel data collection methods. The introduction of GPS-assisted data collection methods has provided an alternative to the conventional methods of travel data collection. GPS-assisted data collection methods improve the accu- racy of data collection and enable capturing more details of individuals＇ travel behaviour. Recent technological advancements in smartphone-based positioning technologies and communication facilities have opened up new opportunities to apply smartphones as the media of GPS-assisted data collection. Although, different GPS-assisted methods have been employed recently, their performance has not been widely evaluated in real-world experi- ments compared to traditional data collection methods. Accordingly, this paper evaluates the performance of three GPS-assisted methods, namely handheld GPS tracking, smart- phone-based GPS tracking and smartphone-based prompted-recall data collection methods, in conjunction with the web-based data collection to shed light on different aspects of GPS- assisted data collection methods. These methods are compared in terms of the quality and accuracy of the collected data, the demographic attributes of participants and the specifi- cations of labelled trips. The results show that an appropriate employment of smartphones enhances the accuracy of data collection. It is also found that putting an extra burden on participants during a travel data collection survey results in lower trip-rates and poor data quality. Finally, it is found that the application of smartphone-assisted data collection methods help reporting non-motorised trips more accurately.

Public Attitudes Towards Policy Instruments for Congestion Mitigation in Shanghai

Congestion causes many externalities for the society, including time delays, excessive fuel consumption, air pollution, noise and safety concerns. In Shanghai, various policy options have been explored, piloted or applied; however, not all of them may be understood and accepted by the public. A survey was conducted to investigate people＇s attitudes towards several policy options. The main findings reveal that Shanghai residents are resistant to certain policies, such as congestion charges, higher parking charges in congested areas and car restrictions. Instead, they favor public transport provisions. The paper suggests that there is a case for promoting public transport and more efficient trips when the car ownership is still low, and for investing in a policy of educating the public on the ＇true＇ costs and causes of congestion before embarking on ,an intensive policy of congestion charges or restrictions.

Transportation Users’ Attitudes and Choices of Ride-Hailing Services in Two Cities with Different Attributes

The rapid technological developments in the 21st century created new opportunities for shared-use economy applications around the globe. Among other services, Transportation Network Companies (TNCs) like Uber and Lyft emerged in the US as a transportation alternative that offered a higher level of availability, reliability, and convenience than traditional modes. However, TNCs deployment was also blamed for increases in vehicle miles traveled (VMT) in large cities that embraced TNC services early on. Concerns about TNC adoption are also magnified by the current controversy in policy and legislation as to the regulation of TNCs. These new realizations create a need to examine the transportation users’ attitudes and perceptions regarding ride-hailing service, after nearly a decade of service in the Unites States market. In doing so, this paper compares and contrasts results from two recently completed studies aiming at creating links between socio-demographic factors and TNC use. The paper describes the methods employed to collect the data and presents findings from the analysis of 790 users’ responses in the Birmingham, AL and Miami Beach, FL markets. The study documents preferences and attitudes toward TNCs and highlights similarities and differences in travel behaviors related to local considerations. Moreover, the study uses the Least Absolute Shrinkage and Selection Operator (Lasso) method to identify predictors for TNC use based on the users’ responses in Birmingham and Miami Beach case studies. Vehicle availability and waiting time emerged as the only significant predictors for the Birmingham region whereas vehicle ownership, vehicle use, residency, and prior use of transit and TNC where some of the predictors identified for the Miami Beach area. Understanding the characteristics of TNC users and the leading reasons that drive people towards the use of TNCs services is expected to help transportation agencies and TNC providers in their efforts to plan for transportation services that meet customer needs in the future.

The stay coefficient: a novel quantification of the relationship between stay time and travel time for urban shopping behavior analysis

Shoppers typically want to spend an amount of time at a destination that is proportional to the travel time required to arrive there;thus,the travel time can be considered the cost of their trip.This is likely to be the case across regions with different urban structures and cultures.The purpose of this study was therefore to analyze the shopping behaviors contained in travel survey data from three metropolitan areas in Japan to identify common patterns and indicators based on travel time and stay time,thereby obtaining an understanding to inform future trade area analyses.Both the travel time and stay time associated with shopping behavior were found to be log-normally distributed regardless of metropolitan area,and four shopping behavior patterns common among the metropolitan areas were identified.The“stay coeffi-cient”was then defined to express the elasticity of stay time according to travel time,and its values were similar according to shopping behavior pattern regardless of metropolitan area.The stay coefficient proposed in this study can therefore be applied to identify shopping behavior patterns in any urban area based on the relationship between travel time and stay time,realizing a novel approach to the analysis of and marketing for trade areas when planning the construction or renovation of commercial facilities.This approach can help inform the decisions of urban policy makers,marketing advisors,and commercial facility operators,and should be of interest to researchers and practitioners working with geospatial,shopping,and other human behavioral characteristics.

Analysis of shopping behavior characteristics in the Keihanshin metropolitan area in Japan based on a person trip survey

This study analyzed weekday shopping behavior from a home base to a destination using data from the 4th Keihanshin metropolitan area person trip survey.We first analyzed the relationships between occupation and transportation means,transportation means and travel time,and transportation means and duration of time at the destination.Results of a chi-square test,residual analysis,and correspondence analysis confirmed that employed persons tend to travel by cars while unemployed persons tend to travel by bus or walk.The relationship between travel time and duration of time at the destination was also revealed according to transportation means.Results of a cluster analysis then classified shopping behaviors to expose four patterns.Finally,multiple regression analyzed the degree to which certain variables were related to duration of time at the destination.Results confirmed a strong relationship between duration of time at the destination and travel time.The degree of this factor’s influence on other variables was also clarified.The value of these findings is that the relationship between travel time by means of transportation and the duration of time at the destination was clarified using statistical analysis.We then found a highly accurate equation that estimates the duration of time at a destination from the travel time.If the duration of time at a destination can be estimated,it may be possible to more accurately develop the structure of rest facilities,the number of parking lots,the degree of congestion,and so on,which can be associated with the customer’s usage behavior in a shopping site.This research in this paper contributes to the field of urban analysis and marketing by presenting a new effective method for person trip survey and analysis.

An Epidemiological Survey of Patients at the Beijing Capital Airport

This article presents the epidemiological survey of the patients at the dispensary of the Beijing Capital Airport from July, 1991 to June, 1992. The constituent ratios of disease and age were analyzed. The results of this study may be proved helpful to the emergency treatment at certain Airports.

Application of Disaggregated Logit Modeling with Stated Preference Method in Park and Ride Behavior for Non-local Private Car Travelers in Big Events

During big events, non-local private car travelers can be divided into two types which were returning in one day and in several days. It was demonstrated that those two kinds of travelers have distinct behavior on park and ride （P＆R）, due to their different travel demand and behavior attributes. In this paper focusing on the travelers returning in several days, the travel attributes and requirements for P＆R were analyzed with stated preference survey. A P＆R choice behavior disaggregated logit model was established and calibrated based on random utility theory. The model concludes three variables, which were travel time, parking fee and comprehensive attractiveness index for suburban satellite towns comparing to urban district. The results revealed that for travelers returning in several days the primary key point is increasing the attractiveness of suburban satellite towns.

How has COVID-19 changed trip patterns by purpose in China?

COVID-19 has upended the whole world. Due to travel restrictions by governments and increased perceived risks of the disease, therehave been significant changes in social activities and travel patterns. This paper investigates the effects of COVID-19 on changes toindividuals’ travel patterns, particularly for travel purposes. An online questionnaire survey was conducted in China, which incorporatesquestions about individuals’ sociodemographic and travel characteristics in three different periods of COVID-19 (i.e. before theoutbreak, at the peak and after the peak;the peak here refers to the peak of the pandemic in China, between the end of January and1 May, 2020). The results show that trip frequency decreased sharply from the outbreak until the peak, and drastically increased afterthe peak. Nevertheless, the data fromthis study suggests that it has not fully recovered to the level before the outbreak. Subsequently,a series of random parameters bivariate Probit models for changes in travel patterns were estimated with personal characteristics.The findings demonstrate that during the peak of the pandemic, residents who did not live in more developed cities reached lowfrequencytravel patterns more quickly. For travel purposes, residents of Wuhan, China resumed travelling for work, entertainmentand buy necessities at a much higher rate than other cities. After the peak, students’ travel for work, entertainment and to buy necessitiesrecovered significantly faster than for other occupations. The findings would be helpful for establishing effective policies tocontrol individual travel and minimize disease spread in a possible future pandemic.

CH'AN TOWN Harvest of gold

The stately foyer of Ch'an Town beckons us past an imperial red throne towards a wall of shelved oddities-Jiangxi tea oil,crooked fungi,canisters of tea leaves and organic eggs.All at once,we're back in 20th-century Guangdong,surveying the exotic culinary repertoire that explorer Joseph Needham would have witnessed in his travels.