Investigation on lowering commuters’ in-cabin exposure to ultrafine particles

To determine ways to reduce commuters’ ultrafine particle exposure, factors such as ventilation condition, mechanical airflow rate, driving speed, cabin air filter quality, and cabin air filter use are examined. The results show that the in-cabin to on-roadway ratio is reduced by 20% when the fan is set to recirculation-on versus when set to recirculation-off because fewer ultrafine particles are exchanged between the inside and outside of the cabin. Also, when the fan is set to recirculation-off, the ratio is reduced by 40% at lower mechanical airflow rates. The thickest cabin air filter resulted in a 30% in-cabin to on-roadway ratio decrease compared with the thinnest. Thus, driving conditions with the least UFP in-cabin to on-roadway ratio is when a vehicle is operating with a high efficiency cabin filter, the ventilation set to fan-on and recycling is recirculation on, and at a high ventilation airflow rate. Furthermore, recirculating in-cabin air through a high efficiency particulate air filter was found to significantly reduce in-cabin UFP exposure.     

Do millennials value travel time differently because of productive multitasking? A revealed-preference study of Northern California commuters

Transportation - Millennials, the demographic cohort born in the last two decades of the twentieth century, are reported to adopt information and communication technologies (ICTs) in their everyday...     

The effects of a compressed working week on commuters’ daily activity patterns

This study was based on 220 randomly selected government employees of the University of the Philippines in Los Baños, and was carried out after the Philippine government implemented an experimental two-month compressed working week scheme. The study aimed to examine compressed working week-related lifestyle pattern changes, especially changes in activity–time patterns. The moderating effects of compressed working week to the commuters were also explored. Survey results showed that two-hour increases in the compressed working week workday substantially impacted activity–travel patterns. Commuters reduced household activities by about one hour, sleeping time by about 20 minutes, and pre-work preparation time by about 30 minutes. Commuting times also significantly declined during the compressed working week. This study also identified factors that moderated the compressed working week plan’s effects on activity–travel patterns.     

Does crowding affect the path choice of metro passengers?

This paper investigates crowding effect on the path choice of metro passengers. We show people reroute not only to avoid the delay from crowding but also to evade crowding itself. More specifically, a logit model fits best when it uses the transit delay from crowding as well as the passenger load of a connection in addition to the conventional explanatory variables. Also, we demonstrate that crowding decreases the overall welfare of metro passengers. The model is tested on the real path choice data acquired by the recent algorithm by Hong et al. (2015) known to detect the real path choice from Smart Card data in more than 90% of the cases.     

Will autonomous vehicles change auto commuters’ value of travel time?

This paper examines the potential impact of autonomous vehicles on commuters’ value of travel time (VOTT). In particular, we focus on the effect on auto commuters in small and medium-sized metropolitan areas, concerning the spatial variability across urban areas, suburbs, and rural areas. We design a stated choice experiment to elicit potential changes in 1,881 auto commuters’ valuation of travel time in autonomous vehicles and apply a mixed logit model to quantify the changes in the value of travel time if taking autonomous vehicles. The results of this study suggest that the effect of autonomous vehicles on the VOTT is spatially differentiated. We find that riding in a private autonomous vehicle reduces the commuting VOTT of suburban, urban, and rural drivers by 32%, 24%, and 18%, respectively, compared to 14%, 13%, and 8% for riding in a shared autonomous vehicle. Finally, we discuss the implications of these lower values of time on transportation and land use planning.     

From willingness to action: Do push-pull-mooring factors matter for shifting to green transportation?

Motivating individuals to choose green transportation is becoming increasingly important. Based on push-pull-mooring framework, this study aims to explore how push, pull and mooring factors foster individual’s willingness to shift to green transportation. This study also analyzes the role of information provision in narrowing the gap between shifting willingness and behavior. The findings revealed that push factors, including perceived environmental threats and perceived inconvenience, drive individual’s mode-shift away from private cars, whereas the pull factors, including green transport policies and campaigns, and green transport system attract individual’s mode-shift to green transportation. Moreover, the mooring factor, namely inertia, not only negatively affects individual’s shifting willingness but also negatively moderates the effects of push and pull factors on individual’s shifting willingness. In addition, shifting willingness positively affects the shifting behavior and the information provision positively moderates the relationship among them. Such findings are vital to achieve the realization of China’s low-carbon goals.     

Can feedback from in-vehicle data recorders improve driver behavior and reduce fuel consumption?

This paper evaluates the effectiveness of feedback, based on In-Vehicle Data Recorders (IVDR), to improve driving behavior, increase driving safety, and reduce fuel consumption. We developed a framework for driving-behavior measurement, incorporating second-by-second data collected by IVDRs. IVDR units were installed in over 150 vehicles driven by more than 350 drivers for over a year. The experiment was divided into three stages. The first stage was a “blind”, control stage, with no feedback. The second stage incorporated verbal feedback given only to riskiest drivers. In the third stage all drivers received a bi-weekly written report about their driving performance. Safety events, such as braking, lateral acceleration or speeding, were recorded. Supplementary data regarding safety related events and fuel consumption were also collected. Safety incidents and fuel consumption were modeled as a function of IVDR measurement-based events, in order to identify which events best reflect safety incidents and excessive fuel consumption. Our results show that braking events best explain safety incidents, and all events together best explain fuel consumption. In addition, we found that for the riskiest drivers, feedback significantly reduced the IVDR events. Our models show that feedback can lead to a reduction of 8% in safety incidents, and 3–10% in fuel consumption, with a larger reduction obtained for large vehicles.     

Including passengers’ response to crowding in the Dutch national train passenger assignment model

Transit passengers’ response to crowded conditions has been studied empirically, yet is limitedly included in transport models currently used in the design of policy and infrastructure investments. This has consequences for the practical applicability of these models in studies on, for instance, timetabling, train capacity management strategies, project appraisal, and passenger satisfaction. Here we propose four methods to include the effect of crowding, based on existing studies on passengers’ perception and response as well as often-used crowding indicators. These four alternative methods are implemented in the train passenger assignment procedure of the Dutch national transport model, and evaluated with respect to their impacts on the model results for the Dutch railway network. The four methods relate to four different ways in which an additive trip penalty and/or time-multiplier can be incorporated in the train utility function for different travel purposes, to capture the disutility of crowding as measured by the load factor. The analyses of the test case favor the hybrid method using both a boarding penalty (capturing seat availability upon boarding) and a time-multiplier (capturing physical comfort and safety throughout the trip). This method produces consistent results, while the additional computational effort that it imposes is acceptable. Further empirical underpinning is needed to conclusively show which of these methods best captures passengers’ response behavior quantitatively (for different travel purposes and conditions).     

Charges on transport – To what extent are they passed on to users?

The paper first briefly reviews the extent to which profit maximising transport firms with identical cost functions and producing identical transport services pass-on output taxes to transport users under perfect competition, under different forms of imperfect competition and when they act as monopolists. Then the analysis is extended to derive the pass-on rates and activity reductions caused by an output tax when firms care both about profit and consumer surplus, produce symmetrically differentiated services and compete simultaneously in quantities and fare and when they collude. The pass-on rates and activity reductions are highest under collusion and lowest under Cournot competition when they produce complementary services. When they produce substitute services, the result is ambiguous and the competitive situation that yields highest pass-on depends on the firms’ objective functions and how fiercely they compete. Two important counterintuitive results are that the more intensely the firms compete and the more weight they put on consumer surplus, the higher the pass-on rates are.     

Means of transport and ontological security: Do cars provide psycho-social benefits to their users?

This paper presents some empirical evidence on the psycho-social benefits people seem to derive from their cars based on in-depth interviews with a sample of car owners and non-car owners in the West of Scotland. We suggest that psycho-social benefits of protection, autonomy and prestige may help to explain people's attachment to cars and also why studies have found consistently that car owners are healthier than non-car owners. In our study cars were seen to provide protection from undesirable people events, and a comfortable cocoon (but not as providing protection against accidents). Cars provided autonomy because car use was seen as being more convenient, reliable and providing access to more destinations than public transport. Cars were seen to confer prestige and other socially desirable attributes such as competence, skill and masculinity. We think that it is important for policy makers to consider how to make public transport more attractive by increasing its potential to provide similar sorts of benefits, and to do so by targetting the different needs of various population groups.     

Understanding the effects of travel demand management on metro commuters’ behavioural loyalty: a hybrid choice modelling approach

Transportation - As part of efforts to promote sustainable mobility, many cities are currently experiencing the rapid expansion of their metro network. The consequent growth in ridership motivates...     

Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach

Suburban sprawl has been widely criticized for its contribution to auto dependence. Numerous studies have found that residents in suburban neighborhoods drive more and walk less than their counterparts in traditional environments. However, most studies confirm only an association between the built environment and travel behavior, and have yet to establish the predominant underlying causal link: whether neighborhood design independently influences travel behavior or whether preferences for travel options affect residential choice. That is, residential self-selection may be at work. A few studies have recently addressed the influence of self-selection. However, our understanding of the causality issue is still immature. To address this issue, this study took into account individuals’ self-selection by employing a quasi-longitudinal design and by controlling for residential preferences and travel attitudes. In particular, using data collected from 547 movers currently living in four traditional neighborhoods and four suburban neighborhoods in Northern California, we developed a structural equations model to investigate the relationships among changes in the built environment, changes in auto ownership, and changes in travel behavior. The results provide some encouragement that land-use policies designed to put residents closer to destinations and provide them with alternative transportation options will actually lead to less driving and more walking.

Do changes in the residential location lead to changes in travel attitudes? A structural equation modeling approach

Transportation - Numerous studies have found that travel attitudes might not only affect travel behavior, but also the residential location choice as people might choose a residential location...     

Do travel cost models value transportation properly?

This paper examines whether travel cost models value transportation properly. It uses contingent behavior and contingent pricing analyses to explore the valuation of transport costs within the context of recreation demand. The contingent behavior analysis poses hypothetical increases in travel costs––travel distance and access fees––and examines the demand responses. In contrast, the ‘contingent pricing’ analysis asks respondents to state the increase in travel costs that is consistent with certain reductions in recreation demand, in this case, reductions that eliminate demand. By comparing distance-related responses to fee-related responses, the two analyses estimate factors for testing and improving the valuation of transport costs. To achieve these ends, the two analyses also explore the valuation of time costs.     

Do new sources of traffic data make the application of Chaos Theory to traffic management a realistic possibility?

Current signal systems for managing road traffic in many urban areas around the world lack a coordinated approach to detecting the spatial and temporal evolution of congestion across control regions within city networks. This severely inhibits these systems’ ability to detect reliably, on a strategic level, the onset of congestion and implement effective preventative action. As traffic is a time-dependent and non-linear system, Chaos Theory is a prime candidate for application to Urban Traffic Control (UTC) to improve congestion and pollution management. Previous applications have been restricted to relatively uncomplicated motorway and inter-urban networks, arguably where the associated problems of congestion and vehicle emissions are less severe, due to a general unavailability of high-resolution temporal and spatial data that preserve the variability in short-term traffic patterns required for Chaos Theory to work to its full potential. This paper argues that this restriction can now be overcome due to the emergence of new sources of high-resolution data and large data storage capabilities. Consequently, this opens up the real possibility for a new generation of UTC systems that are better able to detect the dynamic states of traffic and therefore more effectively prevent the onset of traffic congestion in urban areas worldwide.     

Are millennials more multimodal? A latent-class cluster analysis with attitudes and preferences among millennial and Generation X commuters in California

Transportation - Millennials tend to use a variety of travel modes more often than older birth cohorts. Two potential explanations for this phenomenon prevail in the literature. According to the...     

Reduced dwell times resulting from train–platform improvements: the costs and benefits of improving passenger accessibility to metro trains

Abstract

This paper examines whether a dwell time reduction on a high-intensity metro service, as a result of a series of accessibility enhancements, can contribute to an increased level of service and accessible public transport for passengers together with a reduction in costs for the operator. Actual train operation data were collected by on-site observations and from London Underground Ltd. A simple simulation is built to represent the effect on the overall cycle times of trains if certain parameters (e.g. dwell time) are changed. Four models are developed, concerning: (1) step height between train and platform, (2) an assumption of passenger service time to be no longer than 20 s, (3) door width and (4) the combination of step height and door width. From the application of the models it appears that the fourth model provides the highest reduction in dwell time and diminishes the overall cycle times of trains. However, it is the most expensive to implement as it requires work to raise platforms and the purchase of new rolling stock.     

Does urbanization lead to less energy use on road transport? Evidence from municipalities in Norway

The relationship between urbanization, energy use, and CO₂ emissions has been extensively studied in recent years, however little attention paid to the differences in urban forms. Previous studies implicitly assume that the urban form is homogenous across different urban areas. Such an assumption is questionable as urban form can have many different facets. This paper investigates the effects of urbanization on the road transport energy use by considering different urban forms from a dataset of 386 Norwegian municipalities from 2006 to 2009. Using the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model with an energy use identity equation, the main findings (1) confirm the well-established result that urban density has a negative and significant influence on road transport energy use, and (2) demonstrate that the effect of urbanization partly depends on the level of urban density. These results imply that additional increases in urbanization in dense areas yield greater decreases in road transport energy use per capita. Additional findings posit that (3) there is a non-linear (quadratic) relationship between road energy use per capita and urban population. This implies that an increase in total municipality population over a specific turning point can result in a decrease in road energy use per capita. However, (4) the ratio of urban residential buildings with private gardens has a negative and significant influence on road transport energy use. This implies that there may be a trade-off between compact and sprawl city development strategies, highlighting that sustainable energy use requires further investigation.     

Do partners influence each other’s travel patterns? A new approach to study the role of social norms

To better understand the role of social norms in relation to people’s travel behavior this study addresses the question whether and to what extent partners in two-partner households influence each other’s travel patterns. For example, is the male household head more likely to start using the bicycle if the female household head also uses the bicycle (and vice versa)? While this is a straightforward question, it has, to the best of the author’s knowledge, not been explored in previous research. Using data from 958 couples from the German Mobility panel, the bidirectional effects between the travel patterns of male and female household heads are explored. To this end, the relatively new method of latent class transition analysis is used. The results show that, over time, travel pattern membership of the male household head influences travel pattern membership of the female household head and vice versa. Given that the effects are controlled for a range of individual and shared household characteristics, these results suggest that social norms at the household level play an important role. The paper concludes with an outlook on how the developed framework can be extended in the future.