Transportation Survey Research Articles

Strengths and vulnerabilities of teenagers who skateboard for transport in New Zealand

BackgroundSkateboarding as a mode of transport is not often considered when planning the built environment. Skateboarders are vulnerable road users and are often made to feel unwelcome no matter where they ride. In New Zealand (NZ), skateboarders can legally travel on the road but are often ostracized and feel obligated to use the footpath, where they can threaten the safety of other users, and skateboarding bylaws vary by city. MethodsA comprehensive online survey, querying teenagers about their transport habits and subjective well-being, was disseminated to secondary schools in Southland, NZ in 2015 (n = 775). ResultsOverall, 7% of adolescents (n = 50; 72% male) used skateboarding for transport. Those who skateboarded reported more physical activity during the previous week (μ = 5.2 days/week) than their counterparts who used other modes of transport (μ = 4.3 days/week). Skateboard users also accessed more activities during the previous month than their counterparts (μ = 17.4 and μ = 15.7, respectively), and exhibited higher self-perceived strengths than those who used other modes on a validated subjective well-being scale (μ = 14.4 and μ = 11.3, respectively). However, skateboarders also reported more screen time use (μ = 5.9 h/day) than the rest of the sample (μ = 4.7) and 52% reported feeling unsafe while travelling. ConclusionsSkateboarding for transport is a valid form of active transportation with perceived benefits for the user, and more research is needed to assess the potential bidirectional relationship between skateboarding and well-being. Skateboarding should be included as a transport mode in household transport surveys, to provide a more comprehensive understanding of both teenage well-being and transport modal split to inform research and policy endeavours.

The application of travel demand management initiatives within a university setting

A biennial transport survey at the University of Aberdeen was analysed over a ten-year period to better understand the influence of travel demand management (TDM) initiatives on the commuting habits of staff and students. Campus-based TDM initiatives such as a free inter-campus shuttle bus, charged parking permits and cycle infrastructure was introduced to encourage sustainable travel and to move away from single occupancy car journeys. To consider the impacts of TDM initiatives on staff and student travel choice, an index representing low emissions travel was created using estimated carbon intensity of travel options. Survey data was assessed across age categories, year, commuter travel distance, gender and status (staff or student) to enable discussion of how TDM implementations may have influenced clean travel choice across the survey periods.Outcomes indicated that TDM initiatives did not in themselves influence a substantial shift to clean transport options. A low carbon travel choice index was developed and median comparisons indicated that students travelled on average more by lower emissions transport methods, predominantly walking or cycling, than staff and showed greater variation across the full range of travel options. Staff exhibited significantly lower median index values. This is thought to be related to socio-economic factors between the groups combining with housing opportunities and residential choices over time.While TDM initiatives should be encouraged at institutions such as universities and hospitals, single institutions are unlikely to see a substantial transition to sustainable travel if wider societal infrastructure is not in place to enable people to be habituated to choosing sustainable options. Findings suggest that regional coordination is required for TDM to be societally accepted and successful.

Environmental Characteristics Associated with Older Adults' Social Participation: The Contribution of Sociodemography and Transportation in Metropolitan, Urban, and Rural Areas.

Although social participation fosters older adults’ health, little is known about which environmental characteristics are related to greater participation in social activities. The Canadian Community Health Survey (n = 2737), a transportation survey, and multiple secondary data sources were used to identify the environmental characteristics associated with older Quebecers’ social participation according to living area. Greater social participation was associated with: (1) a higher concentration of older adults (IRR = 2.172 (95% CI 1.600, 2.948); p < 0.001), more kilometers traveled by paratransit (IRR = 1.714 (95% CI 1.286, 2.285); p < 0.01), a lack of medical clinics (IRR = 0.730 (95% CI 0.574, 0.930); p = 0.01), and more funded home adaptations (IRR = 1.170 (95% CI 1.036, 1.320); p = 0.01) in large metropolitan areas; (2) larger paratransit fleets (IRR = 1.368 (95% CI 1.044, 1.791); p = 0.02) and a lower density of road intersections (IRR = 0.862 (95% CI 0.756, 0.982); p = 0.03) in regular metropolitan areas; (3) less social deprivation (IRR = 1.162 (95% CI 1.025, 1.318); p = 0.02) in urban areas; and (4) a higher concentration of older populations (IRR = 2.386 (95% CI 1.817, 3.133); p < 0.001) in rural areas. According to these findings, social participation interventions should target the local environment—for example, by providing more social interaction opportunities for older adults living in younger neighborhoods and by improving access to public transportation, especially paratransit.

Mixed applied survey methodology for planning/enforcement of urban logistics delivery bays– An application to the Moroccan context

Roads and parking areas represent a place of conflict between freight vehicles and other urban activities, especially on mixed residential and commercial streets. This conflict results in traffic congestion, illegal parking, pollution and road safety problems. The challenge is to allocate public space between the right operating activities, parking activities, public transport and so on. To address that, urban logistics delivery bays, also known as loading/unloading (L/U) zones, have become a real solution to facilitate the delivery and pick-up operations of urban freight vehicles, ensure accessibility for delivery drivers, reduce congestion and improve road safety. Therefore, this paper reports on planning and enforcement of urban delivery bays needs. It is part of the urban freight transport (UFT) surveys. This involves consolidating with new contribution the development, implementation and statistical analysis of a survey in order to quantify the need of delivery areas. Compared to the existing literature, this paper presents a mixed applied methodology which is divided into two parts : “Exploratory survey” and “Establishment-vehicle observation” survey. These two surveys techniques were conducted to offer an overview of the freight vehicle delivery and pick-up frequency according to the daytime and weekdays and the operations related to the loading/unloading activities. This makes it possible to estimate the delivery bays requirement in the study area. The findings from a methodological and practical angle are illustrated through a real case study in a commercial street in Morocco. The findings suggest that 60% of deliveries are made between 8:00 A.M and 12 A.M, and the movements generated by each establishment are 257 movements. For this, the study zone requires the development of three loading/unloading (L/U) bays. The main contribution is to propose an approach that urban authorities can use to estimate urban delivery areas efficiently and thus allow simple replication of the proposed framework in other cities.

Time-Series Analysis of the Causal Effects Among Perceived Quality, Satisfaction, Loyalty, and Frequency of Public Transportation Use

How to drive modal shift is one of the primary issues to create a sustainable society. By encouraging people to migrate from private car use to public transport, city planners can prepare for a super-aged society, reduce greenhouse gas emissions and mitigate negative externalities of private car use such as congestion, accidents, and noise. To achieve these goals, city planners are required to understand whether public transport usage can be increased by improving the service quality, and what roles user satisfaction and loyalty play in the process. The relations between service quality, user satisfaction, loyalty and user frequency have been studied for a long time. However, most of the studies are based on cross-sectional analysis. Cross-sectional analysis is less powerful in detecting causality as it does not show pre-post relations nor lagged effects between variables. To investigate causal and non-simultaneous relations among quality, satisfaction, loyalty and user frequency of public transport, we used data of the Benchmarking in European Service of Public Transport survey from 2001 to 2015 in 4 European cities, and applied Vector Auto Regressive (VAR) analysis. The result shows that improvement of service quality has positive effects on user’s satisfaction, loyalty and user frequency and that better satisfaction leads to higher loyalty and user frequency. More importantly, the result also shows that behavioral modification (change in user frequency) occurs with time lag while psychological modifications (changes in satisfaction and loyalty) occur immediately after changes in service quality. The findings suggest that city/transport planners ought to keep improving the service quality of public transport and monitoring the achievement from a long-term perspective.

Mobility needs, activity patterns and activity flexibility: How subjective and objective constraints influence mode choice

Denmark is one of the world-leading countries in terms of bicycle infrastructure and has a relatively good public transport system. Yet, a large share of commuters in the Greater Copenhagen Area still uses the car on a regular or semi-regular basis, causing severe problems of congestion and pollution. This article seeks to understand to what extent individuals’ perceived mobility necessities (PMN), activity pattern complexity, and temporal, spatial, social, or compulsory constraints in everyday activities inhibit switching from private motorized transport modes to more environmentally friendly modes. We formulate an Integrated Choice and Latent Variable model that accounts for PMN and activity patterns, complexity and constraints. To estimate the model, we used two datasets: the first dataset is the Danish National Transport Survey, which is a large dataset consisting of approximately 150,000 respondents; the second is a small(er) but highly detailed dataset, which contains relevant information regarding activity patterns, constraints and PMN. We found that the more complex the activity patterns are, the higher are both PMN and the probability of selecting car and bike, and this effect is even more evident when individuals are constrained by some activities. Consistently, individuals who perceive high mobility needs are more likely to select car and bike. The result that mobility needs and related constraints increase cycling conflicts with results found in low-cycling countries. Yet, it indicates that the bike can play a similar role as the car when the respective infrastructure is provided. Our results also indicate that structural improvements, such as flexible work and day-care times, day-care service close to the workplace, or escorting services for children are likely to lead to a substantial reduction in the use of the car.

Millennials and Reduced Car Ownership: Evidence from Recent Transport Surveys

This study examines the likelihood millennials are to own a car and the factors that have driven a reduction in car consumption. Based on a travel decision survey performed in 2015 in San Francisco, no significant evidence supports the claim that millennials are different from prior generations in terms of car ownership. Individuals with higher incomes and those that preferred more access and convenience were more likely to own a vehicle.

A framework for the impact of highly automated vehicles with limited operational design domains

Abstract Highly automated vehicles (AV) are in the early stages of deployment and are likely to have significant impacts on the United States transportation system. In particular, a broad deployment of shared, on-demand AVs might significantly impact vehicle ownership and transportation energy consumption; projecting these impacts is essential for climate, infrastructure, and policy planning. However, it seems increasingly likely that AVs will be deployed gradually over a period of decades, in which case there may be geographic or functional variation in their availability. This might occur for a combination of technological, policy, and economic reasons. This manuscript seeks to advance a new framework for projecting AV impacts, with a particular focus on energy consumption impacts. Specifically, we introduce a framework for AV impacts that allows for AVs catering to specific operating environments or ride types. As a demonstration of this framework, we use the 2009 National Household Transportation Survey (NHTS) to segment US household travel demand based on built environment and ride length. Our framework allows us to specify AV “availability” for each population segment and ride type and use that information to predict the impact of AVs. We analyze a case scenario where shared, on-demand AVs are mostly suited for short trips in highly urbanized environments. We project the impact on household relocation, private vehicle ownership, induced travel demand, and fuel consumption. Utilization of this framework would help identify policy levers for sustainable deployment of AVs.

The role of income in discrete choice models. Its importance in evaluation projects

Research on discrete choice models based on microeconomic principles has developed a framework for the detection of the income effect to estimate demands or even the measurement of well-being with special emphasis on the transport sector. However, these theoretical investigations have not been used frequently in the practice of evaluation projects. The aggregation of benefits between individuals requires sophisticated tools to avoid an erroneous specification of income in the models. The latter can potentially distort the results and inadvertently lead to suboptimal decisions that becomes critical in large investments. This document seeks to highlight the importance of considering the effect of income in evaluation projects. For this purpose, on the basis of the discrete choice theory, several models have been tested using multinomial logit models. The data set collected comes from an urban transport survey of Metropolitan Lima in 2004. The models have tried to detect the presence of the income effect, thus assuming an income level. It has been found that the people surveyed in the study can be statistically classified into two representative income groups. Then, following Jara-Díaz and Videla (1989), it shows that the marginal utility of income decreases with income and these are statistically different when they are calculated between groups.

Comparison of Traffic Flow Characteristics of Signal Controlled Intersection and Turbo Roundabout

In the Slovak republic, there is an increase of building roundabouts in both urban and non-build-up areas. The construction of roundabouts in urban areas brings mainly calming of traffic intensity. A roundabout in non-build-up areas could be built only within certain conditions. In this paper, we have been studying a small roundabout location and its traffic characteristics in the city of Hlohovec. In some cases, a small roundabout could be very good solution for exceeded traffic flow capacity of signal controlled intersections as well as for intersections with a high number of traffic incidents. But in our case, a small roundabout is not suitable for such intensity of vehicles as we measured in transport survey. So we focused on other possibilities how to improve this current situation. We have decided to make a proposal of signal controlled intersection as well as a turbo roundabout and compare the results of traffic characteristics of each proposal. We have made several simulations of each variant of traffic situation, using transport-planning software Aimsun, and calculate average values of all recorded traffic characteristics. As inputs, we have used intensities and other basic data obtained from transport survey. Using simulations outputs of transport planning software, we have been able to compare a current state with signal controlled intersection and turbo roundabout. Traffic characteristics of turbo roundabout show significant improvements compare to signal controlled intersection, f.e. in delay time (more than 68 %), travel time (more than 22 %), number of stops (more than 73 %). Turbo roundabout seems to be the best solution for traffic organising at this chosen intersection in the city of Hlohovec, regarding travel time, delays, number of stops and safety at all.

Mobile data usage in urban transport research

The article contains a review of technologies for using the information provided by mobile operators in creating a transport survey and studying patterns of travel behavior. The literature review shows the widespread of using mobile communications as an effective source of information in terms of population coverage and data availability. In article described the domestic experience of using this information in custom information systems and presented the author's system of city transport survey.

Estimating bus passenger volume based on a Wi-Fi scanner survey

The main objective of this study is to estimate bus passenger volume based on a Wi-Fi scanner transportation survey. The study proposes a new data cleaning procedure to characterize bus passenger volume using a combination of media access control (MAC) address and global positioning system (GPS) data. We used a Wi-Fi scanner to detect the MAC addresses of individual bus passengers. The Wi-Fi scanner, used as a tool to capture passenger device data, can engage in a probe request mode to capture the MAC addresses of mobile devices or other Wi-Fi-enabled modalities without connecting to the internet. The approach proposed in this study can yield the passenger volume outputs for various bus route sections. A comparison of the passenger volume results obtained from Wi-Fi data and ground truth data indicates that the number of passengers determined from the former is less than that from the latter. The correlation between Wi-Fi estimation and ground truth is 0.78, and the trend line in both methods is similar. Therefore, the cleaning procedure proposed in this study can effectively clean raw Wi-Fi data to extract passenger volume data.

INVESTIGATING FACTORS AFFECTING ROAD FREIGHT OVERLOADING THROUGH THE INTEGRATED USE OF BLR AND CART: A CASE STUDY IN CHINA

Overloading of road freight vehicles accelerates road damage, creates unfair competition in the transport market, and increases safety risk. There is a dearth of research on the mining of data of highway Freight Weight (FW), and this paper therefore aims to discover factors affecting road freight overloading based on highway FW data, with a view of developing strategies to mitigate such occurrences. A comprehensive sampling survey of road freight transportation was conducted in Anhui Province (China). Vehicle Characteristics (VC), Operation Mode (OM), and transportation information from a total of 3248 trucks were collected. In order to take advantage of the strengths associated with both statistical modelling techniques and non-parametric methods, a Classification And Regression Tree (CART) technique was integrated with Binary Logistic Regression (BLR) to reveal the factors affecting road freight overloading. The classification efficacy test shows that the BLR–CART method outperformed the BLR method in term of accuracy. It is also revealed that the factors affecting overloading of freight vehicles are the Type of Transportation (ToT), Rated Load (RL), OM, FW during the investigation period, interaction between RL and FW, and interaction among RL, FW, and Average Haul Distance (AHD). Road transport authorities should pay greater attention to these factors in order to improve efficiency and effectiveness of overloading inspection.

Moving Toward Physical Activity Targets by Walking to Transit: National Household Transportation Survey, 2001–2017

Public transportation systems can help people engage in physical activity. This study assesses sociodemographic correlates and trends in the daily time spent walking to and from transit in the U.S. from 2001 to 2017. This cross-sectional study used data from the 2001, 2009, and 2017 National Household Transportation Survey. Data were analyzed in 2019 to assess the daily level of physical activity attained solely by walking to and from transit. Regression models were used to examine predictors of daily transit‒associated walking. Compared with the full National Household Transportation Survey sample, transit users who walked to and from transit tended to be younger, from households earning <$25,000 per year, in areas with rail infrastructure, and did not have a household-owned car. Transit walkers spent a median of 20 minutes per day (95% CI=18.5, 21.5) walking to and from transit in 2017, compared with a median of 19 minutes (95% CI=17.5, 20.5) in 2001. Among transit walkers, daily transit-associated physical activity was 27% higher for those residing in areas with rail infrastructure (adjusted coefficient=1.27, 95% CI=1.11, 1.46) and 34% higher for those from households earning <$25,000 per year than those earning >$99,999 per year (adjusted coefficient=1.34, 95% CI=1.15, 1.56). As documented in a growing literature, most public transit trips include at least some walking; thus, efforts to encourage transit use are favorable to public health. Continued monitoring by transportation surveys is important as new forms of mobility and changing demographics may impact future transit use and associated physical activity.

On the requirements on spatial accuracy and sampling rate for transport mode detection in view of a shift to passive signalling data

GPS based campaigns have been hailed as an alternative to transportation surveys that promise relatively high accuracy at a relatively low burden on the participants and fewer forgotten trips. However they still necessitate the recruitment of participants and are thus potentially biased and certainly not encompassing significant parts of the population. Given the high penetration of mobile phones, passive tracking by telephone providers would alleviate those two shortcomings at the cost of reduced sampling frequency and positional accuracy. The trade-off in quality has not yet been quantified and therefore recommendations on sensible thresholds are not yet available. In this study therefore, instead of presenting yet another method for mode of transport classification, we therefore compare the performance of existing mode detection schemes under deteriorating sampling rates and positional accuracies. As a possibility to compensate for the deteriorating signal we also calculate features from users’ positional histories that could be beneficial if their behaviour is repetitive. The evaluation is not only based on pointwise accuracy, but includes quality measures that pertain to trips as a whole. We find that the necessary accuracy and sampling rate for applications will depend on whether the information of whole trajectories can be used, or whether only the current information is available. The former being relevant to ex-post analyses while the latter situation appears more frequently in near-time analyses. For segmentwise classification, there is no major impact on the quality of the classification by the tested levels of spatial accuracies as long as the sampling intervals can be kept at or below a minute, whereas for point based classification the sampling interval should be between 30 s and a minute and increasing spatial accuracy always improves the classification.

Evaluating interregional freight accessibility conditions through the combination of centrality and reliability measures

The main contribution of this paper is a new approach to evaluate and compare the freight accessibility conditions offered in a set of regions or cities. The key innovation of this approach lies in that it combines (statistical) centrality and reliability measures of accessibility, thus tackling one of the weaknesses that researchers have identified in the vast accessibility literature. The proposed approach is first explained in details for a hypothetical setting, and then is applied to Iran using data collected in the latest transport survey conducted in this country. The focus is placed on road transport, by far the dominant freight transport mode in Iran. The results obtained through this application provide clear insights into the relative positions of the main freight production and attraction zones of Iran with respect to road accessibility conditions, and therefore valuable information to assist transport authorities in their decisions regarding the evolution of the country's road network.

Data analytics for sustainable global supply chains

Based on the key metrics to monitor energy sector improvements from the International Energy Agency (IEA), transport emissions must decrease 43% by 2030. Freight logistics operations in Europe are struggling with ways to reduce their carbon footprints in order to adhere to regulations on governing logistics, while providing the increasing demand for sustainable products from the customers. This study investigates the anonymised microdata from the European Road Freight Transport Survey (2011–2014) to acquire patterns in logistic operations based on over 11 million journeys within 27 EU and EFTA countries involved. Different algorithms were implemented (Horizontal Cooperation, Pooling and Physical Internet) to analyse efficiency, in terms of vehicle utilisation, degree of vehicles’ loading during each journey and sustainability in terms of the amount of CO2 emissions per journey. This study shows that existing data can provide invaluable information on the efficiency of logistics operations and the positive effects data analytics can provide. Physical Internet algorithm has performed better in terms of reducing emissions and improving the logistics’ efficiency, especially when the sample sizes are large, but this would require a shift to an open global supply web.

Comparing Spatial Accessibility and Travel Time Prediction to Commercial Centres by Private and Public Transport: A Case Study of Oforikrom District

The relevance of accessibility in shaping transport planning has often been neglected, hampering on decisions to improve transport efficiency. This is increasingly becoming problematic, as they often impede on economic and technological developments. Many studies on accessibility assert that it is easier for public transport to reach an activity centre than it is for private transport. For this reason, the research compares travel time forecast and accessibility levels with private and public transports en route to commercial centres. The research involves a 21-day transport survey for private cars and public shuttles in Oforikrom district using Global Positioning System (GPS) probe to record the traffic performance indicators to be analyzed in a GIS environment. The results of the study display on a map the level of accessibility via the modes, and a comparative line plot of travel time with private and public transport. The study reveals that private cars in the district generally perform better than public shuttles on the level of accessibility, and travel time. The execution of the research shows that the convergence of choice of transport mode and travel time dynamics is crucial for policymakers to implement diverse transport modes and commuters to choose a mode that has low accessibility cost.

Long-distance travel patterns of rail users in Hungary - Findings of the new countrywide Origin-Destination (O-D) Survey

The paper gives a brief overview of the creation and methodology of elaborating the new nationwide Origin-Destination (O‐D) survey of the passenger rail transport. Firstly presents the general transport conditions in Hungary with respect to long-distance railway transport. Then explain the harmonization methodology and the characteristics of the 4 different data source (ticketing statistics, passenger survey with over 33.700 respondents, traffic counting, household survey). The paper finally also presents the key findings of the survey and the main socio‐economic factors which determine the rail user’s long‐distance travel patterns in Hungary.

Customer satisfaction survey of urban public transport

Customer satisfaction survey of urban public transport