Average Trip Length Research Articles

A Comparison of Women’s Travel to Mammography Services and Average Week Day Trip Length

<p><em>Long travel distances/times to a mammography service may act as a barrier that hinders women from seeking screening mammography on a recommended schedule. Average weekday trip length data from the New South Wales Travel Survey was compared with the average distance women travelled to a mammography service, the difference was tested using the Wilcoxon Signed Rank Test. The distance travelled to mammography services was statistically greater than the average week day trip length from the New South Wales Travel Survey (4.3 km, 95% CI 3.3 to 5.9 kms, p,0.001). This study has identified that within New South Wales there is a significant difference between average week day trip length travel and client travel to mammography services. Therefore, highlighting that women are undertaking a greater than normal travel burden to access mammography services. The comparison of normal weekday travel and travel to mammography services has enabled the burden of travel to mammography services to be identified. Reducing the burden of travel to mammography services is pivotal to increasing the utilization of mammography services and reducing the inequalities in health comes.</em></p>

Estimation of regional trip length distributions for the calibration of the aggregated network traffic models

The calibration of trip lengths is an important challenge for multi-regional MFD-based applications, as it can influence the dynamics of regional densities (and speeds). Existing research has not paid significant attention in the topic, giving opportunities for answering some fundamental questions. In this paper, we propose an original methodology to explicitly determine trip length distributions based on a subset of trips in the city network and its partitioning. Since the full description of all realized trips is difficult to estimate for a large city network, we propose to define a set of virtual trips corresponding to a full coverage of potential local origin-destination pairs and shortest-paths in distance. We investigate how different levels of information can influence the accuracy of the multi-regional dynamic MFD-based models, through the estimated trip length distributions. This information ranges from regional trip lengths without any information of origin, destination, previous or next regions up to the specific regional path associated to each trip.We test this methodology on a simulated environment with a significant amount of real information for a network with 757 links that corresponds to the 6th district of Lyon. We first provide guidance on how to properly define the set of virtual trips. We show that a single average trip length is not representative of all possible trip lengths estimated by the most detailed levels of information for one region. We also highlight that the first level of information assigns similar trip lengths for regional paths that are composed by the same regions, but in a reverse ordered sequence. Nevertheless, this is not the case for the most detailed levels of information since they capture the directed links city network topology. We propose a procedure to update the trip lengths when an update of the regional Origin-Destination matrix changes, without a need for a full recalculation. We also investigate the influence of the trip length tuning on the traffic dynamics of the regional network. The traffic states are modeled by a trip-based MFD model. We show that the setting of the trip lengths influences the traffic dynamics in the regions. Moreover, the traffic conditions predicted by the two most detailed levels of information are close.

The Investigation of Effective Parameters on Trip Length of Bikesharing Systems (BSS)

Various bike sharing systems (BSS) were designed and used in different cities of the world in the past decade. Many benefits of the BSS have supplied a rapid growth of this transport mode in all around the world. BSS mainly have many benefits such as traffic (flexible mobility and multimodal transport connections), health (physical activity) and cost (low trip cost). Also a planned BSS can serve an easy access to other public transportation system and can be an important actor of the public transportation system. Especially in many big cities, bike sharing systems becomes an important part of the public transportation and ensure short travel times to users. However, the growing may causes many problems such as demand, safety, effectiveness, cost etc. For this purpose many studies have conducted by the planners, researchers and decision makers to find best solutions to mentioned problems. In the scope of this study, the relation among average temperature, trip length and trip number was examined for a bike sharing system. For this purpose, Capital Bikeshare system (Washington, D.C., Arlington and Alexandria, VA and Montgomery County, MD) is chosen as pilot system to investigate. Study results showed that there is a strong and positive correlation among temperature, trip number and trip length. Additionally, it was obtained that bicycle utilization has a maximum value between 5-10 minutes. This results can be caused by the free utilization duration (30 minutes) of the system for the members.

Прояви міграції триплетних електронних збуджень у π-електрон-містких полімерах

The results of spectral studies of polymers with aromatic side groups are considered and analyzed. In particular, the phosphorescence spectra of polyvinylcarbazole (PVCa) polyvinyl-7-benzocarbazole (PV7BK) polypropylcarbazole (PEPC) are presented and analyzed. The phosphorescence of these polymers has been shown to be related to the migration of triplet excitons in macromolecules. The phosphorescence of PVC is determined at 77by deep traps (oxides), at 4.2 -shallow traps (monomer units of PVCa). The spreading length of triplet excitons in PVCa macromolecules is 600 A – that corresponds to the average distances between adjacent traps in the macromolecule. There are no such traps in PV7BK macromolecules. The boundary conditions for triplet excitons in macromolecules of PV7BCa were used for evaluation the excitons spreading length. With this aim the dependence of phosphorescence spectra on molecular weihgt were studied The effect of changing of spectral positions of phosphorescence bands when exciton rich the end macromolecular cell was used. The average trip length of triplet excitons is approximately 1000 A. This distance is in fact limited by the probability of the meeting of triplet excitons in the macromolecule and their annihilation at a given excitation intensity.

A model to evaluate energy efficient spatial structure for transportation via spatially balancing the job - house ratio - The case of Sri Lanka

The trend of haphazard land use practices has caused for a massive cost and a congestion in major transport corridors. In this case, a proper combination of land use distribution will be able to optimize the Vehicle Miles Travelled (VMT) to reduce the transportation-related energy consumption and city congestion. One of the significant approaches of integrating transport and urban development is developing an optimized ratio for administrative level job-house combinations. The objective of this re-search is to develop a method to identify a job-house ratio for each analysis zones where the road congestion will be optimized. The gravity model is used to perform the trip distribution and it is assigned to the road network using the graph theory. The main assumption taken in the study is that the trip generation by a group of population in a particular area is considered as work based trips. The result of the method for Colombo district indicated that the job-house ratio varies from 0.1 to 9.2 resulting an average trip length of 23 km between houses to work locations. However, the method suggested a minimum and maximum value of 0.5 and 4 which reduced the VMT from 46% and average fuel consumption by 22%.

A trip to reach the target? – The labor supply of Swedish Baltic cod fishermen

This paper uses logbook data from Swedish Baltic Sea cod trawlers to investigate the revenue target hypothesis. Incomes from fishing can be highly variable and difficult to predict and it is possible that fishermen set specific revenue targets for their fishing trips to simplify decision making. In this paper a discrete choice stopping model is used where the fishermen must decide to stop or continue fishing after each haul. At average trip length, the results indicate that when revenues are higher than expected, fishermen are more likely to return to port. This is in line with the revenue target hypothesis. When using estimated revenue targets the results suggest that the effect of getting higher revenues than expected is stronger when the targets have been reached.

Tracking random walks.

In empirical studies, trajectories of animals or individuals are sampled in space and time. Yet, it is unclear how sampling procedures bias the recorded data. Here, we consider the important case of movements that consist of alternating rests and moves of random durations and study how the estimate of their statistical properties is affected by the way we measure them. We first discuss the ideal case of a constant sampling interval and short-tailed distributions of rest and move durations, and provide an exact analytical calculation of the fraction of correctly sampled trajectories. Further insights are obtained with simulations using more realistic long-tailed rest duration distributions showing that this fraction is dramatically reduced for real cases. We test our results for real human mobility with high-resolution GPS trajectories, where a constant sampling interval allows one to recover at best 18% of the movements, while over-evaluating the average trip length by a factor of 2. Using a sampling interval extracted from real communication data, we recover only 11% of the moves, a value that cannot be increased above 16% even with ideal algorithms. These figures call for a more cautious use of data in quantitative studies of individuals' movements.

Optimal fleet size, frequencies and vehicle capacities considering peak and off-peak periods in public transport

The fleet for surface transit in urban areas - number of buses and vehicle size - is usually determined by the characteristics of demand during the peak period, adjusting frequencies for other periods where those characteristics are quite different. Here the problem is formulated analytically considering a representative single line where hourly passengers flow and average trip lengths differ between peak and off-peak periods. Analytical and numerical results show that minimizing social costs (operators and users) for the whole day yields a larger fleet of smaller buses than if only the peak period is considered. Contrary to previous results on this issue, optimal frequencies across periods differ by a large amount, as optimal peak and off-peak frequencies are larger and smaller respectively than what would be obtained modeling each period by itself. The optimal bus size lies in-between the capacities obtained when each period is independently optimized. Several other interesting counterintuitive results are shown.

A probability-based indicator for measuring the degree of multimodality in transportation investments

Although decision makers may favor a “multimodal” transportation system, it can be difficult to indicate the extent to which a given transportation investment is, or is not, multimodal. This lack of an indicator can be acute when the project selection process requires consideration of how a given investment supports increased multimodality. In response to this need, this research reports on a taxonomy for classifying the degree of multimodality for transportation projects. Probability theory was employed with principal component analysis to create a new indicator based on both demand (modal shares) and supply (monetary investment for each mode). The indicator offers three main benefits in the area of performance measurement: (1) it is applicable in cases when some data are missing; (2) it provides a way of comparing multimodality from diverse projects such as high-occupancy toll lanes or multimodal centers; and (3) it can help decision-makers quantify how multimodality has changed over time. For example, application of the indicator to six U.S. public-private partnership projects in Colorado, Florida, Rhode Island, and Virginia showed that the degree of multimodality increased by an average value of 57%. (While the manner in which the impact boundary is defined affects this calculation for specific projects, the average value remained relatively stable whether the impact boundary was equal to the average commute trip length or less than half that amount.) Given that some planners view multimodality as societally beneficial, the indicator proposed herein can help one evaluate the multimodal potential of proposed transportation investments.

New potential for multimodal connection: exploring the relationship between taxi and transit in New York City (NYC)

Taxi trips have been somewhat neglected in transportation mobility and multimodal connection studies. The socio-demographic characteristics of taxi riders are often not fully revealed and the relationship between the taxi and fixed-route public transportation has not been sufficiently quantified. This research operationalizes the multifaceted relationship between the taxi and transit in an innovative way. We categorize taxi trips into three types: transit-competing, transit-complementing, and transit-extending trips, by examining the spatial relationship of taxi trips’ origins/destinations and the locations of transit stations using a New York global positioning system taxi trip dataset. The distinct characteristics of the three types of taxi trips reflect the different market segmentations that taxis serve and the competing, complementary, and supportive nature of the relationship between the taxi and transit. We also explore the demographic characteristics of taxi riders and the result reveals the important role of taxis in providing mobility options to the economically or physically challenged population. Among our many findings are that transit-extending taxi trips have significantly shorter average trip lengths and larger proportions of people paying with cash than other trip types. These and other results point to important policy implications for improving the multimodal connection between the taxi and transit.

GPS-tracking and colony observations reveal variation in offshore habitat use and foraging ecology of breeding Sandwich Terns

Breeding success of seabirds critically depends on their foraging success offshore. However, studies combining at-sea tracking and visual provisioning observations are scarce, especially for smaller species of seabirds. This study is the first in which breeding Sandwich Terns were tracked with GPS-loggers to collect detailed data on foraging habitat use in four breeding seasons. The maximum home range of individual Sandwich Terns comprised approximately 1900km2 and the average foraging range was 27km. Trip durations were on average 135min with average trip lengths of 67km. Actual foraging behaviour comprised 35% of the time budget of a foraging trip. Substantial year-to-year variation was found in habitat use and trip variables, yet with the exception of 2012, home range size remained similar between years. Food availability, chick age and environmental conditions are proposed as the main driving factors between inter- and intra-annual variations in trip variables. Our multi-method approach also provided geo-referenced information on prey presence and we conclude that future combining of colony observations and GPS-loggers deployments can potentially provide a near complete insight into the feeding ecology of breeding Sandwich Terns, including the behaviour of birds at sea.

Public transportation adoption requires a paradigm shift in urban development structure

Urban passenger transportation in the U.S. has been heavily dependent on car modes, mainly due to prevailing trends in urban development. However, transportation mode choice studies are currently limited to micro-level and regional-level boundaries, lacking of presenting a complete picture of the issues and the root causes associated with urban passenger transportation choices in the U.S. To this end, further analysis from a system perspective is required to investigate the interdependencies among system parameters more thoroughly, thus revealing the underlying mechanisms contributing or causing the low public transportation use in the U.S. Hence, system dynamics modeling approach is utilized to capture complex causal relationships among the critical system parameters affecting public transportation ridership in the U.S. as well as to identify possible policy areas to improve public transportation ridership rates. Considering the high degree of uncertainties inherent to the problem, multivariate sensitivity analysis is utilized to explore the effectiveness of existing and possible policy implications up to the year 2050 in the terms of their potential to increase transit ridership and locating critical parameters that influences the most on mode choice and emission rates. Transportation mode choice behavior is projected to change slightly and reach up to a maximum of 7.25% of public transportation ridership until 2050. Analysis results reveal that the effects of trip length and rate are by far the most influential factors. Both parameters are 99% sensitive compared to all other factors including the effects of fuel tax policies, federal funds for public transportation, use of alternative green bus technologies, increasing private vehicle occupancy rates, etc. on negative environmental, economic, and social impacts of transportation. This finding highlights how important urban structures are to secure the future of public transportation in the U.S. as the existing urban structures and the shared-idea in the minds of the society about how urban transportation should be (the prevailing paradigm) are the root causes of excessive trip generation and increasing average trip lengths. Thus a paradigm-shift, a radical change in the shared-idea in the minds of the society about existing urban structures, is needed.

IMPLICATIONS OF SPRAWLED AND COMPACT DEVELOPMENT ON MOBILITY PATTERNS: A CASE-STUDY OF BHOPAL, INDIA

Cities across the world are witness to increasing phenomenon of urban sprawl. The paper contends that sprawl affects mobility in terms of increased dependence on private motor vehicle which is high in energy use and carbon emissions. The study is based on primary investigation of three neighbourhoods in Bhopal city (India), the first two lying within the city in varying contexts and the third outside the present city limits which can be classified as a sprawl. The analysis throws significant light on the changes in mobility pattern in areas with more compact development vis-à-vis those that have sprawled with relatively lower densities. It shows that densely populated areas having mixed use has higher share of walk trips and that the average trip length is higher in lower density areas in sprawls. The study further examines the role of land use planning, zoning regulations and urban form in encouraging sustainable mobility.

IMPLICATIONS OF SPRAWLED AND COMPACT DEVELOPMENT ON MOBILITY PATTERNS: A CASE-STUDY OF BHOPAL, INDIA

Cities across the world are witness to increasing phenomenon of urban sprawl. The paper contends that sprawl affects mobility in terms of increased dependence on private motor vehicle which is high in energy use and carbon emissions. The study is based on primary investigation of three neighbourhoods in Bhopal city (India), the first two lying within the city in varying contexts and the third outside the present city limits which can be classified as a sprawl. The analysis throws significant light on the changes in mobility pattern in areas with more compact development vis-Ã -vis those that have sprawled with relatively lower densities. It shows that densely populated areas having mixed use has higher share of walk trips and that the average trip length is higher in lower density areas in sprawls. The study further examines the role of land use planning, zoning regulations and urban form in encouraging sustainable mobility.

Losers and Pareto optimality in optimising commuting patterns

When optimising the overall commuting pattern for a city or a region, there are often winners and losers among commuters at the subdivision level. Losers are those who are burdened with longer commutes than before the optimisation. Knowing who or where losers are is of interest to both researchers and policy-makers. The information would help them efficiently locate losers and compensate them. Few, however, pay attention to such losers. By revisiting ‘excess commuting’ in the economic framework, we show that optimising the commuting pattern is comparable to restoring Pareto optimality in commuting. Using Beijing as a case study, we identify and geo-visualise the losers when the city’s bus commuting pattern is optimised. We examine the severity of the loss among the losers, the spatial pattern of the losers and their influencing factors. We find that most losers are located around the epicenter. The severity of the loss is independent of jobs/housing ratio but is associated with the commute distance before the optimisation. Workers whose commute distance is less than the global average are more likely to become losers. Places where losers reside have significantly lower employment density in a few industries than where non-losers reside. A low jobs/housing ratio in individual subareas does not necessarily increase the average trip length of commuters therein. A low jobs/housing ratio of one or several subareas, however, could influence the average trip length of all the commuters in the area. Locating diverse jobs and housing opportunities around or along transit corridors could compensate the losers and reduce the overall commuting cost.

Improving Rural Access to Orthopaedic Care Through Visiting Consultant Clinics.

Patients from rural areas tend to be older and less physically active and are more likely to be obese, increasing their need for orthopaedic services. However, few orthopaedic surgeons practice in rural areas. One approach to meeting the needs of rural patients is visiting consultant clinics (VCCs). In this study, we examined orthopaedic surgery outreach in Iowa, a state with a large rural population. We assessed the involvement of the 2014 Iowa orthopaedic surgery workforce in outreach activities for the geographically disadvantaged rural population and its effect on patient travel distances. The University of Iowa Carver College of Medicine annually tracks VCC locations and frequencies. Data from 2014 were used to estimate average trip length for participating orthopaedic surgeons and patients in all Iowa census tracts. Primary practice locations, visiting consultant clinic locations, and census tracts were classified according to the 2010 Rural-Urban Commuting Areas (RUCA) classifications. In 2014, 4,596 VCC days were provided in 80 predominantly rural sites. Overall, as a result of VCCs staffed by orthopaedic surgeons in Iowa and adjoining states, the number of Iowan counties with an orthopaedic surgeon increased from 35 (at his/her primary practice location) to 88 (at a VCC or primary practice location) of 99. Forty-five percent of all Iowa-based orthopaedic surgeons participated in a VCC. Visiting orthopaedic surgeons drove a total of 32,496 mi (52,297 km) per month to conduct these clinics. The average driving distance to the nearest orthopaedic surgeon was reduced from 19.2 mi (30.9 km) to 8.4 mi (13.5 km) for rural Iowans as a result of monthly VCCs. Monthly VCCs improved access to orthopaedic surgeons for between 450,000 and 670,000 Iowans from a total population of approximately 3 million. VCCs staffed by orthopaedic surgeons from Iowa and surrounding states improve access to orthopaedic care by reducing driving distances for rural patients.

Privacy-Aware Dynamic Ride Sharing

Dynamic ride sharing is a service that enables shared vehicle rides in real time and on short notice. It can be an effective solution to counter the problem of increasing traffic jams at peak hours in cities. The growing use and popularity of smart phones and GPS-enabled devices provides us with tools required to efficiently implement ride sharing and significantly enhance carpooling. However, privacy and safety concerns are the main obstacles faced when encouraging people to use such a service. In this work, we present “Match Maker,” a negotiation-based model that hides exact location information data for system participants while implementing privacy preserving ride sharing. We use the concept of imprecision (not being precise about location of the user out of set of n locations) and follow the idea of obfuscation, which equates a higher degree of imprecision with a higher degree of privacy. We identify two attack types that could circumvent privacy preserving ride sharing. We compare the Match Maker model with the standard central trusted server model collecting precise location data, which we term eBay model. We provide the first comprehensive approach that integrates privacy, safety and trust in a single model. We present a recursive ellipse-based algorithm to compute an optimal driver path as well as three negotiation strategies for drivers and passengers. We conduct extensive experiments on real road networks and compare the strategies for privacy and effectiveness of ride sharing in terms of traffic load and vehicle km reduction. We show that ride sharing saves between 9% and 21% (on average 12%) of vehicle km if drivers are only prepared to accept slight detours of their usual trips. In the city of Melbourne, with 11.6 million trips a weekday and an average trip length of 10.2 km, this would save 14.2 million km per weekday.

Work-Time Exposure and Acute Injuries in Inshore Lobstermen of the Northeast United States

ABSTRACTThe objective of this study was to inform efforts to reduce risk for musculoskeletal disorders among commercial lobstermen by characterizing and quantifying injuries that occur to people while harvesting lobsters commercially in the Northeast United States. This study aimed to estimate a denominator of exposure to lobstering in full-time equivalents (FTE), to estimate a fatality rate, and to calculate incidence rates for acute injuries within the sample population. Captains were randomly selected from those licensed to fish in Maine and Massachusetts. Data on work exposure and injuries with rapid onset that occurred on the boat (“acute injuries”) were collected using a survey, which was administered quarterly via phone or face-to-face interview with the captain. The quarterly survey assessed the number of weeks worked during the quarter, average crew size, number of trips per week, and average trip length in hours. In addition, this survey captured relevant information (body segment affected, type of injury, and whether treatment was received) on all acute injuries occurring during the quarter. FTE were estimated using fishermen days and fishermen hours. The annual FTE estimated using days was 2,557 and using hours was 2,855. As expected, the summer months (3rd quarter) had the highest FTE and the winter (1st quarter) the lowest FTE. Fall (4th quarter) and spring (2nd quarter) ranked second and third, respectively. The incidence rates for all injuries (49.7/100 FTE) and injuries requiring treatment (15.0/100 FTE) were much higher than those reported in other studies of fishing that used Coast Guard data.

Functionally Hierarchical Road Classification Considering the Area Characteristics for the Performance-oriented Road Planning

Functional hierarchy of road network classifies individual roads into several levels by taking account of the priority for mobility, access or residential functions, in order to manage traffic efficiently by segregating through traffic from accessing, parking and non-motorized traffics. This concept has been widely recognized and applied to road planning, design and operation in several countries such as Germany, the US and Australia. Their guidelines state the target performances (i.e., LOS or travel speed in general) of each hierarchical levels being used for the performance evaluation. However in Japan, target performances of roads are not shown in the current guideline, since a concept of the performance-oriented planning and design is still uncommon in practice. As a result, the operational performances are still not satisfactory enough especially on highways. In such a situation, this study attempts to find out the hierarchical road classification applicable to Japan, considering the distribution of region/district centers as well as the impact of terrain. The main questions are how many hierarchical levels need to be defined and how much travel speed and road spacing (or access distance) should be set as the targets for each level, so that the network performance, namely travel time between region/district centers, can achieve the given target values. The basic idea comes from the German guideline RIN, which states the target travel times by region/district center (central place), classifies roads and define their target travel speeds based on their connecting centers. However, it does not clearly mention how the difference in distribution of region/district centers and the impact of terrain can be reflected to set the efficient hierarchical classification. For example, the characteristic of metropolitan areas is quite different from that of mountainous areas in terms of trip lengths between region/district centers of which travel times are to be evaluated as network performance. In addition, because of the impact of terrain, construction cost per unit is generally quite higher in mountainous areas than in flat areas, whereas travel demand is usually lower in mountainous areas. This study incorporates these issues into road classification and demonstrates its impact for more efficient network system planning. The methodology consists of four steps: (1) defining the region/district centers to be connected and setting their target travel time, (2) developing alternative road classification scenarios, (3) mathematically formulating origin-destination travel time in a grid road network under the certain classification and (4) evaluating the classification scenarios considering the difference of average trip lengths of each combination of centers as well as the difference of system cost due to the impact of terrain and travel demand. Although the original intention of this study is to apply the result to Japan, the methodology itself is generally applicable to any region. At the end, case studies are conducted for several simplified areas for reflecting their typical characteristics of region/district centers distribution and terrain in Japan. Through them, the hierarchical road classifications by area type are suggested as a conclusion.

A comparative analysis of traditional four-step and activity-based travel demand modeling: a case study of Tampa, Florida

Activity-based travel demand modeling (ABTDM) has often been viewed as an advanced approach, due to its higher fidelity and better policy sensitivity. However, a review of the literature indicates that no study has been undertaken to investigate quantitatively the differences and accuracy between an ABTDM approach and a traditional four-step travel demand model. In this paper we provide a comparative analysis against each step – trip generation, trip distribution, mode split, and network assignment – between an ABTDM developed using travel diary data from the Tampa Bay Region in Florida and the Tampa Bay Regional Planning Model (TBRPM), an existing traditional four-step model for the same area. Results show salient differences between the TBRPM and the ABTDM, in terms of modeling performance and accuracy, in each of the four steps. For example, trip production rates calculated from the travel diary data are found to be either double or a quarter less than those used in the TBRPM. On the other hand, trip attraction rates computed from activity-based travel simulations are found to be either more than double or one tenth less than those used in the TBRPM. The trip distribution curves from the two models are similar, but both average and peak trip lengths of the two are significantly different. Mode split analyses show that the TBRPM may underestimate driving trips and fail to capture any usage of alternative modes, such as taxi and nonmotorized (e.g., walking and bicycling) modes. In addition, the ABTDMs are found to be less capable of reproducing observed traffic counts when compared to the TBRPM, most likely due to not considering external and through trips. The comparative results presented can help transportation engineers and planners better understand the strengths and weaknesses of the two types of model and this should assist decision-makers in choosing a better modeling tool for their planning initiatives.