Daily Trips Research Articles

METHODS OF IMPLEMENTATION OF AN ALPINE SKIING SCHOOL

Nowadays, various programs are used in ski schools to teach beginners. All programs have the same goal, and that is to teach beginners specific body movements with which they will be able to manage their skis. Three programs are most commonly used in alpine skiing schools. According to one program, ski beginners are taught the basics of alpine skiing exclusively with elements of parallel skiing techniques. In the second program, ski beginners acquire knowledge using elements of snowplough and parallel ski technique. The third alpine skiing learning program combines these two methods. In addition to the program, in practice there are two approaches to learning alpine skiing. The first method involves a daily trip to a ski slope or a nearby winter tourist centre, where the skiing technique is adopted and beginners return to the place of residence the same day. The second way consists of an organized, usually seven-day, winter trip, during which the basics of alpine skiing are learned every day during the stay in the ski-resort. Regardless of the learning programs used, the safety of skiers is a priority in every alpine skiing school. Therefore, it is advisable for all beginner skiers to get involved in an alpine skiing school, as this is the best way to prevent injuries.

Mode effect analysis in the case of daily passenger mobility survey

Abstract In the autumn 2017, The Statistical Office of the Republic of Slovenia (SURS) has conducted for the first time a survey on daily passenger mobility of Slovenian residents. The key statistics are on persons’ daily traveling habits, such as number of trips, travelled distance, time spent on traveling, and so on. Two independent samples were selected for the simultaneous collection of data by two modes, face-to-face interview (CAPI) and online questionnaire (WEB). The goal of this study is to identify the possible sources of mode measurement errors, with the objective to better design and thus improve the whole data collection process. The detailed mode effect analysis is performed by the comparison of the key statistic estimates and the use of regression models. Usually the measurement mode effect is an issue in surveys on the more sensitive topics or persons’ opinions. This work points out that, first, the mode measurement effect can be an issue also in a more factual survey content, and second, the corresponding statistical data processes can have an important contribution to minimising measurement errors. The results show that WEB respondents are inclined to join two or more trips into one reported, which gives lower estimate of average number of daily trips. The main reason is the demanding questionnaire content. Additionally, the complex data editing process was still insufficient to correct completely for such measurement error. The possible improvements of the data collection process are also discussed.

Towards a novel set of GPS‐derived metrics to identify the differences between mobility patterns of cognitively intact older adults and older adults with dementia

AbstractBackgroundMaintaining an active lifestyle and participating in social activities are key components of healthy ageing. These components rely on the individuals’ ability to remain mobile out of home. The global positioning system (GPS) is increasingly used to assess outdoor mobility of older adults. However, there is a gap in establishing a framework that recognizes the differences between mobility patterns of cognitively intact older adults and older adults with dementia (OAwD). We propose a set of GPS‐derived metrics to identify these differences, which can be used to evaluate changes in mobility patterns of OAwD over time.MethodWe analyzed the mobility profiles of 15 older adults from the greater Toronto area using GPS technology. Participants were aged between 65 and 90 years (M=74.9, SD=7.05) and were either cognitively healthy (n = 8) or diagnosed with dementia (n = 7). First, we created GPS‐based features representing different dimensions of outdoor mobility. These features include (1) the typical distance covered by individuals, (2) randomness of the travel patterns, (3) the spatial variation of the GPS locations, (4) the number of distinct stops visited per day, (5) the number of daily trips away from home, (6) the score of three levels of outdoor life‐space, and (7) the maximum distance travelled from home. Then, we used Recursive Feature Elimination (RFE) with Random Forest (RF) to select the most important mobility features with respect to cognitive status.ResultA total of 55,580 GPS points were collected by the 15 unique participants over a period of 4 to 8 weeks. The RFE method indicated that features (1), (2), (3), and (5) had the strongest association with cognitive status. Our results suggested that OAwD displayed more predictability (i.e. smaller randomness) in travel patterns compared to the controls (OAwD: M=4.82, SD=0.57 vs. CTL: M=5.62, SD=0.71). Furthermore, the OAwD made fewer daily out‐of‐home trips compared to the controls (OAwD: M=1.06, SD=0.79 vs. CTL: M=1.65, SD=0.45), and covered smaller distances compared to the controls (OAwD: M=12.27, SD=11.73 km vs. CTL: M=15.78, SD=24.31 km).ConclusionThe proposed set of GPS‐based features identified the differences between mobility patterns of cognitively intact older adults and OAwD.

Travel diaries, GPS loggers and Smartphone applications in mapping the daily mobility patterns of students in an urban environment

Abstract Mapping the daily spatial mobility of university students in an urban environment is the focus of this paper. It uses the city of České Budějovice in the Czech Republic as a case study, employing three different research tools – travel diaries, GPS loggers and Smartphone applications. We focus our attention on the analysis of spatial patterns of mobility using basic mobility indicators (distance, number of daily trips, time spent mobility), travel behaviours (use of transport modes) and the detection of time-space bundles (spaces of concentration of particular time-space trajectories) within the city. We identified four main time-space bundles. Then we compare the three main research methods according to their tracking accuracy and informative value. The Smartphone applications (using the A-GPS technology) provided the best results for the spatial mobility of respondents, although the travel diaries method is still unique due to the extent of some socio-demographic and transport characteristics.

Bus scheduling considering trip‐varying travel times, vehicle availability and capacity

Bus scheduling is a well-known NP-hard problem, and it is addressed with the use of heuristic solution methods or graphical approaches. In this study, the author proposes an improved formulation of the bus scheduling problem that considers the vehicle availability, the vehicle capacity and the allowed headway variability among successive trip dispatches. His formulation expands the classic bus scheduling model formulation by including the aforementioned features. In his study, the bus scheduling problem is understood as the problem of setting the optimal dispatching times for a set of pre-determined daily trips of a particular bus line. His model facilitates the search of solutions that can improve the waiting times of passengers while meeting the operational requirements and avoiding overcrowding. His proposed mathematical program is proved to be non-convex, and it is solved with heuristic solution methods because numerical optimisation approaches cannot guarantee a globally optimal solution. The performance of his approach is tested in a case study using real operational data from bus line 302 in Singapore. A simulation-based evaluation demonstrates potential gains of up to 20% on average passenger waiting times and a major reduction in refused passenger boardings because of overcrowding.

Finite mixture survival model for examining the variability of urban arterial travel time for buses, passenger cars and taxis

Examining the travel time variability (TTV) of buses, passenger cars and taxis is essential to obtain reliable travel time in urban daily trips. TTV analyses of three travel modes are conducted using travel time data collected on two urban arterial roads in Xi'an City. Firstly, the TTV is evaluated using statistical indexes. The results reveal that the TTV differs from vehicle to vehicle, period to period and site to site. Secondly, the finite mixture survival model is proposed to address the heterogeneity of travel time data by decomposing the population into several sub-populations. Wasserstein distance and Kolmogorov–Smirnov test are used to further compare the sub-populations of different vehicle types during different periods on different roads. Finally, based on the model analysis, it can be found that the finite mixture survival model is an accurate tool to examine the variability by capturing the heterogeneity of travel time data. The difference among the sub-populations suggests different travel behaviours. It concludes that more diverse travel behaviours result in higher TTV. An accurate investigation on TTV is valuable for travellers’ mode choices and transportation management agencies to obtain reliable travel time information and improve traffic efficiency.

Direct demand modelling approach to forecast cycling activity for a proposed bike facility

ABSTRACT In the United States, planning and design efforts to generate bike-friendly environments through the greater provision of safe, low-stress bike infrastructure in our cities continue to advance. In Cambridge, Massachusetts, construction of the Grand Junction Pathway – an envisioned shared-use pathway – is at the heart of a citywide effort to enhance its active transportation system. However, a challenge – shared by many public agencies given that data on cycling activity are rarely frequently systematically gathered – is the creation of a baseline estimate of cycling demand for this planned network link. Using short-duration manual data supplemented with long-duration count data, this study employs a state-of-the-practice method for generating annual average daily bicycle trips for current bike network facilities. A statistical modelling strategy is then undertaken to forecast the volume of daily cyclists that the proposed off-street, shared-use path could expect to attract given its physical context and the socioeconomic attributes of nearby residents.

Traffic Assignment of Al-Kufa City Using TransCAD

Modern urban cities around the world suffer from high congestions due to high daily trips for different purposes. Al-Kufa city has a lot of congested roads in its road network. The main objective of this study is to evaluate the current traffic situation. Firstly, the number of links and nodes has been counted using GIS software. These links represent major and minor arterials. The collected data include flow, speed and geometric characteristics for each link and node in the network. The traffic assignment model (Stochastic User Equilibrium) in TransCAD software was adopted in this study. The results indicated that the value (v/c) for most of these roads is more than one which indicated congested roads.

Adjusting the service? Understanding the factors affecting bus ridership over time at the route level in Montréal, Canada

Like many cities across North America, Montréal has experienced shrinking bus ridership over recent years. Most literature has focused on the broader causes for ridership decline at the metropolitan or city level; few have considered ridership at the route level, particularly while accounting for various operational attributes and accessibility-to-jobs issues. Because service adjustments take place—and are felt by riders—at the route level, it is essential to explore bus-ridership phenomena at this same scale. Our study explores the determinants of bus ridership at the route level between 2012 and 2017 using two longitudinal random-coefficients models in Montréal. Our findings suggest that increasing the number of daily bus trips along a route and improving the average route speed are key factors in securing bus ridership gains. The service area’s regional accessibility to jobs by public transit around the route has a positive impact on bus ridership at the route level, showing the importance of land use and network structure. Additionally, our models show that reducing service frequency along a parallel route will lead to an increase in ridership along the main route. This study can be of use to transit planners and policymakers who require a more granular understanding of the factors that affect ridership at the route level.

Allocation Model of Urban Cores and Evaluation of Accessibility Regarding Daily Multipurpose Trip

市街地拡大と人口密度低下により，インフラ維持コストの増大や公共交通の衰退が懸念されている中で，都市機能と公共交通の一体的な考慮による効果的かつ実現可能な都市構造の構築が求められている．本研究では，住民施設利用の実態と自治体における現状の施設配置と公共交通網に基づき，複数施設利用のメリットを考慮した拠点配置手法を提案し，利用可能人口の割合（充足率）と複数施設利用のメリットから自治体の利便性の現状と施設改善効果を評価することを目的とする．まず，住民の日常生活の外出に関するWebアンケートから1回の外出で複数の施設の利用と公共交通によるアクセスが利便性の向上に重要な要素であることがわかった．次に，複数施設利用を考慮した拠点配置モデルを構築し，現状の市施設利用における充足率と複数施設利用メリットの2つの指標から評価した結果，施設は利用できるものの，複数施設利用メリットには優劣があることを明らかにした．その指標に基づいた利便性向上の方針を提案した．さらに，施設の新設場所と種類を求めるモデルを構築し，具体的な都市での拠点配置結果より，施設追加による充足率の改善に効果を示した．

Assessing the Role of Modal Shift in Minimizing Transport Energy Consumption, a Case Study of Kathmandu Valley

With rapid growing economies and population, there is an increasing trend of expansion of urban sprawl and auto-mobilization, in the cities of the Kathmandu Valley. With the rise in travel demand, transport energy is becoming a major concern for planners and policymakers. This paper aims to study the transport energy of daily trips that constitute work and educational trips, in context of the Kathmandu Valley. The study demonstrates the applicability of a 4-step travel demand model for the assessment of energy-saving measures in urban transport system by formulating scenarios. The results show that currently, daily trips consume 3666 TJ annually. Cars and motorcycles contribute to most of the consumption, accounting for over 80% of the total transport energy. As a mitigation measure to reduce transport energy, the introduction of the efficient public transport system in the form of Bus Rapid Transit System (BRTS) along major corridors, could bring down transport energy consumption significantly. The paper concludes with the essence, to address the need for modal shift to the mass transit system, as a step towards the minimization of transport energy.

Inferring temporal motifs for travel pattern analysis using large scale smart card data

In this paper, we proposed a new method to extract travel patterns for transit riders from different public transportation systems based on temporal motif, which is an emerging notion in network science literature. We then developed a scalable algorithm to recognize temporal motifs from daily trip sub-sequences extracted from two smart card datasets. Our method shows its benefits in uncovering the potential correlation between varying topologies of trip combinations and specific activity chains. Commuting, different types of transfer, and other travel behaviors have been identified. Besides, varying travel-activity chains like “Home→Work→Post-work activity (for dining or shopping)→Back home” and the corresponding travel motifs have been distinguished by incorporating the land use information in the GIS data. The analysis results contribute to our understanding of transit riders’ travel behavior. We also present application examples of the travel motif to demonstrate the practicality of the proposed approach. Our methodology can be adapted to travel pattern analysis using different data sources and lay the foundation for other travel-pattern related studies.

Compact development and adherence to stay-at-home order during the COVID-19 pandemic: A longitudinal investigation in the United States

In the absence of a vaccine and medical treatments, social distancing remains the only option available to governments in order to slow the spread of global pandemics such as COVID-19 and save millions of lives. Despite the scientific evidence on the effectiveness of social distancing measures, they are not being practiced uniformly across the U.S. Accordingly, the role of compact development on the level of adherence to social distancing measures has not been empirically studied. This longitudinal study employs a natural experimental research design to investigative the impacts of compact development on reduction in travel to three types of destinations representing a range of essential and non-essential trips in 771 metropolitan counties in the U.S during the shelter-in-place order amid the COVID-19 pandemic. We employed Multilevel Linear Modeling (MLM) for the three longitudinal analyses in this study to model determinants of reduction in daily trips to grocery stores, parks, and transit stations; using travel data from Google and accounting for the hierarchical (two-level) structure of the data. We found that the challenges of practicing social distancing in compact areas are not related to minimizing essential trips. Quite the opposite, residents of compact areas have significantly higher reduction in trips to essential destinations such as grocery stores/pharmacies, and transit stations. However, residents of compact counties have significantly lower reduction in their trips to parks possibly due to the smaller homes, lack of private yards, and the higher level of anxiety amid the pandemic. This study offers a number of practical implications and directions for future research.

Toward a deeper understanding of elderly walking for transport: An analysis across genders in a case study of Iran

Backgroundand purpose: The world's elderly population has been dramatically growing during the last few decades, and therefore, a big challenge for many societies will be to meet the future needs of this group especially their health problems. Promoting walking as an active mode of transportation in daily travel could have many benefits on the healthy lifestyle of the elderly. However, it has not received so much attention in the literature especially in developing countries. The main objective in this study was to understand the walking mode choice behavior of the elderly males and elderly females inside the urban areas of Rasht, the capital city of province Gilan, Iran which has the highest percentage of the elderly population among provinces in the whole country. MethodData for the analysis comes from the Rasht household travel survey (RHTS) containing information about travel characteristics and individual/household characteristics. In this study, trips made by individuals aged 60 years or more (representing the elderly) were selected for further analysis. This group contained 600 persons which account for about 3.4% of all participants in the RHTS. Of all elderly, more than 60% were males and the rest were females. This study treats travel as if it was just a trip for a single purpose with a single destination. In order to understand what will affect the likelihood of walking versus not walking a whole trip, separate binary logit models were developed for elderly males (using 774 trips) and elderly females (using 299 trips). ResultsFactors such as having a car and a presence of small children in household, trips for purpose of work, making trips between 8 and 10 a.m., and higher ratio of minor roads to major roads was only found with significant effect on older males' likelihood to walk. However, factors such as land-use mix measures representing diversity of an area and travel distance were found with significant effect on both groups. Result showed that while choosing walking in trips longer than 0.25 mile is a matter for older males'; older females’ do not mind walking up to 0.5 mile in daily trips. ImplicationsAccording to the results found, the top priority policy that may led to higher probability of choosing walking as a mode of transportation among elderly is to plan for higher mixed-use developments that could provide more accessibility and make the place more exciting for the elderly which could itself increase the propensity to walk and consequently enhance the community health indicators.

Valuation of travel time reliability: Considering the traveler's adaptive expectation with an indifference band on daily trip duration

Abstract In this article, we focus on the valuation of travel time reliability that considers the adaptive expectation with an indifference band on daily trip duration. Owing to the learning effect of adaptive expectation, travel time variation relates to the travel time forecast bias but not to the absolute deviation of daily trip duration. Meanwhile, the indifference band toward travel time variation moderates the adaptive expectation formation in daily trip repetition. In this case, travel time reliability follows the discrete probability distribution. We use the rank-dependent utility framework to capture the value of travel time reliability (VOR), in which the probability transformation accommodates the risk attitude toward random trip duration and provides us the subjective probability weight to each potential reliability point. Numerical simulation indicates that the traveler's subjective VOR awareness associates with both learning rate and indifference band in the adaptive expectation on daily trip duration. We also set forth some policy and practice implications of this research in the traffic assignment and network formulation.

A network-level sidewalk inventory method using mobile LiDAR and deep learning

Sidewalks are a critical infrastructure to facilitate essential daily trips for pedestrian and wheelchair users. The dependence on the infrastructure and the increasing demand from these users press public transportation agencies for cost-effective sidewalk maintenance and better Americans with Disabilities Act (ADA) compliance. Unfortunately, most of the agencies still rely on outdated sidewalk mapping data or manual survey results for their sidewalk management. In this study, a network-level sidewalk inventory method is proposed by efficiently segmenting the mobile light detection and ranging (LiDAR) data using a customized deep neural network, i.e., PointNet++, and followed by integrating a stripe-based sidewalk extraction algorithm. By extracting the sidewalk locations from the mobile LiDAR point cloud, the corresponding geometry features, e.g., width, grade, cross slope, etc., can be extracted for the ADA compliance and the overall condition assessment. The experimental test conducted on the entire State Route 9, Massachusetts has shown promising performance in terms of the accuracy for the sidewalk extraction (i.e., point-level intersect over union (IoU) value of 0.946) and the efficiency for network analysis of the ADA compliance (i.e., approximately 6.5 min/mile). A case study conducted in Columbus District in Boston, Massachusetts, demonstrates that the proposed method can not only successfully support transportation agencies with an accurate and efficient means for network-level sidewalk inventory, but also support wheelchair users with accurate and comprehensive sidewalk inventory information for better navigation and route planning.

Application of a binary logistic model in the development of strategies to encourage sustainable transportation in medium-sized cities: case of study

O protagonismo das cidades de médio porte demográfico na economia e na dispersão populacional dos países em crescimento gera o desenvolvimento e a expansão acelerada destas cidades, evidenciando a necessidade de um eficiente planejamento de mobilidade sustentável. Como a sustentabilidade está baseada nos transportes, é importante compreender a influência que as características socioeconômicas e de deslocamentos diários exercem na forma de utilização dos transportes. Para identificar e quantificar o impacto dessas características na utilização dos transportes, este artigo propõe um método de auxílio à promoção da sustentabilidade no planejamento da mobilidade dessas cidades, baseado na força de associação das características inerentes à sociedade com a escolha do meio de transporte e no modelo de regressão logística. Através da aplicação do método, concluiu-se que a modelagem estatística das variáveis inerentes à população das cidades de médio porte demográfico pode auxiliar na elaboração de políticas públicas sustentáveis na área de mobilidade.

Identifikasi Perilaku Perjalanan Melalui Metode Critical Path Method (CPM)

Mobilization in urban areas has increased every year along with the population growth and urban's development. Travel behaviors of the population in urban areas can be classified based on their travel characteristics. The identification of communities' travel behavior of Yogyakarta is based on the origin - destination and length of trip based on age characteristics. It will effects the travel patterns in the urban environment through spatial mapping. The method used in this research is critical path method. Critical Path Method (CPM) is used to determine the optimum path taken by the community based on its duration, which in this study CPM is used to determine the average travel of the community based on age groups when viewed from distance, length of trip and the number of daily trips. Based on the analysis, it shows that the average age of 15-22 years and 31-37 years have the highest travel time, which is about 9 hours and the average age of 23-30 years traveled the longest by 12.5 km. The average mobilization of travel behaviors in KPY is to the urbancenter of Yogyakarta. The KPY urban form does not have a compact form.

Activity-based travel as a social signal of the City Satisfaction Index. Study case in a medium-sized city of Argentina

The travel based on activities carried out daily by citizens is a social signal that helps interpret the City Satisfaction Index. In the present study, we characterized these daily trips by the mode of transport, motive, duration, area of origin, area of destination, etc, and explored their relationship with four dimensions of citizen satisfaction: Job Opportunities, Urban planning and diversity, Nature and recreation and Reproductive success. This relationship was studied by the partial least squares path modelling and the four dimensions establish a conceptual framework of factors that are relevant for the satisfaction of citizens with their place of residence. The results obtained suggest a double-entry channel: mandatory activities influence the City Satisfaction Index, whereas discretionary, emotional, and self-expressive activities are key indicators of the performance of the index. The data used were based on a survey of the daily commutes of citizens of Tandil, a medium-sized city of Argentina, collected between 2012 and 2016.

Observing the Characteristics of Multi-Activity Trip Chain and Its Influencing Mechanism

Understanding mechanism of daily activity trip chain especially multi-activity trip chain is significant for travel demand management and urban redevelopment. This paper explores the multi-activity trip chain behavior from both individual attributes and spatial attributes. Multiactivity trip chain is identified from people’s full-day travel diaries, then categorized into multi-activity intermittent trip chain and continuous trip chain to distinguish the characteristics and influencing factors of different chains. Using resident travel survey data of Xiaoshan District of Hangzhou, China, multinomial logistic regression model, transition probability matrix and activity analysis methods are employed to make analyses. Findings include: 1) making multi-activity trip chain can achieve multiple purposes with less average travel time for each purpose, but public transit is less used. 2) The choices of single or multi-activity trip chain and multi-activity intermittent or continuous trip chain are mainly affected by different individual attributes such as occupation, education, household income, etc. Moreover, household registration, driver’s license, gender, and household car ownership are related to the choice of activity sequence. 3) For typical trip chain with purposes of work, shopping/dining, and home, activity sequence is also obviously influenced by spatial distance between origin and destination, especially for the chain of work-shopping/dining-home.