Train Commuters Research Articles

Hello, stranger? Pleasant conversations are preceded by concerns about starting one.

Connecting with others makes people happier, but strangers in close proximity often ignore each other. Prior research (Epley & Schroeder, 2014) suggested this social disconnection stems from people misunderstanding how pleasant it would be to talk with strangers. Extending these prior results, in a field experiment with London-area train commuters, those assigned to talk with a stranger reported having a significantly more positive experience, and learning significantly more, than those assigned to a solitude or control condition. Commuters also expected a more positive experience if they talked to a stranger than in the solitude or control conditions. A second experiment explored why commuters nevertheless avoid conversation even when it is generally pleasant. Commuters predicted that trying to have a conversation would be less pleasant than actually having one because they anticipated that others would be uninterested in talking. These experiments clarify the precise aspects of social interaction that may be misunderstood. People may avoid pleasant conversations with strangers because of miscalibrated concerns about starting them. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Stress and Adaptation Among Mumbai Local Train Commuters

Stress and Adaptation Among Mumbai Local Train Commuters

Modelling the Relationships between Train Commuters’ Access Modes and Traffic Safety

Walking, cycling, and feeder bus/tram for first- and last-mile (FLM) train access are often considered to have better health benefits, lower cost, and less environmental impacts than driving. However, little is known about the road safety impacts of these FLM access modes, particularly at a network level. This paper aims to investigate the impacts of train commuters’ access modes on road safety in Victoria, Australia. Macroscopic analyses of crash outcomes in each zone (i.e., Statistical Area Level 1) were performed using negative binomial (NB) and spatially lagged X negative binomial (SLXNB), accounting for potential indirect effects of mode shares in adjacent zones. This macroscopic analysis approach enabled the consideration of the safety effects across the network. The results showed that the SLXNB models outperformed the NB models. Commuting by train, either with walking or car as FLM access mode, was negatively associated with both total and severe crashes. In addition, commuting by train with feeder bus/tram access mode was negatively associated with severe crashes. Interestingly, commuting by train with cycling access mode was negatively associated with total crashes, with a larger effect when compared to walking and car access modes. Overall, the results suggested promoting active transport as FLM train access mode would lead to an improvement in road safety.

Working-class Commuters and Innovative Use of Associational Power: The Case of Mamelodi Train Sector in South Africa

The article analyses the power resources of working-class train commuters in Tshwane, South Africa. I examine the organisational strategy of Mamelodi Train Sector (MTS), considering the crisis of representation characteristic of the South African labour movement currently. With changing composition of membership in the Congress of South African Trade Unions, the article begins with the question, what strategies and avenues are there for both unions and unorganised members of the working class? Through the case study of MTS, I suggest a need to rethink power resources and strategies in order to appreciate various non-union ways in which workers continue to organise under conditions that are at times hostile to unions. Drawing on the Power Resources Approach, I argue that MTS can utilise its strategic site of operations and associational power to link unorganised workers with relevant unions. Through its on-train organising, MTS strategically uses its associational power to achieve two things: 1) to empower non-unionised workers, and 2) to influence local-level politics during the morning and afternoon commutes. KEYWORDS: Mamelodi Train Sector; train; comrades’ coach; associational power; political agency

How transport policy shapes commuting patterns: The case of the Bratislava sub-urban area

We analyse the commuting patterns in Bratislava’s fast growing sub-urban region with sub-optimally developed infrastructure. A standardized discrete choice model is used to estimate the demand for individual car transport as well as public buses and trains, and to obtain corresponding elasticities with respect to travel costs, times and income. We find a low rate of substitution between the available modes of transport. The direct price elasticity for public modes of transport is in accordance with the often-quoted rule of thumb of −0.3. Negative income elasticities of the demand for buses and trains, together with a low direct price elasticity for car transport can be hard to overcome when looking for a solution for the current traffic problems in the region. We use modelled demand to predict the effects of two recent draft policies – the new parking system in Bratislava city and the construction of highway D4R7. In the case of the first policy, we expect a massive reduction in car use due to increased costs for car commuters. On the other hand, the new highway would only have a limited impact on mode choice and could reduce the number of train commuters.

Do commuters adapt to in-vehicle crowding on trains?

In-vehicle crowding on public transportation is a serious problem that transportation planners must address. Recent studies have emphasized that in-vehicle crowding impacts travelers’ stress and health, while other studies have investigated how daily travel affects subjective well-being (SWB). Based on the findings of these studies, we provide useful insights into the value of a reduction in crowding in terms of SWB. The other factor we should consider is adaptation, as the effects of travel discomfort disappear after travelers become accustomed to them. In this paper, we analyzed the direct and stress-related indirect effects of dissatisfaction with in-vehicle crowding on life satisfaction, focusing on whether these effects differ by the length of time commuters have been using trains. Using a sample of 8296 train commuters in Tokyo, we found that (1) dissatisfaction with in-vehicle crowding directly lowers life satisfaction among some groups of short-term train commuters and (2) dissatisfaction with in-vehicle crowding indirectly lowers life satisfaction through stress and health, regardless of whether commuters have used trains for more or less than one year. These results revealed the importance of focusing on the stress-related indirect effects of dissatisfaction with crowding, while direct effects on SWB exist only among some commuters. Our results demonstrated the possibility of adaptation to direct effects.

Daily Experiences of Commuting Strain and Self-Control at Work and at Home

Abstract. The study investigates how commuting strain affects daily self-control capacities at work and at home. Irritability (i.e., increased readiness to express negative emotions when facing frustration) and concentration (i.e., a cognitive control capacity that relies on attention) were used as indicators of (impaired) self-control. Based on 5-day diary data from N = 185 train commuters, we found that on days with a strenuous ride from home to work, commuters indicated higher irritability and lower concentration capacity at work. On days with higher strain during the work-to-home ride, commuters reported to be more irritable back home. Moreover, commuters with low emotional stability turned out to be more affected by commuting strain but only if considering self-control impairment at home.

Technological change and sociocultural models in China: A case study of train commuters in Beijing

ABSTRACT China’s mobility turn has created the world’s largest public rail system, contributing extensively to citizens’ economic, social, and spatial mobility. Concurrently, this technological transformation has introduced many opportunities for individuation, which could potentially challenge the social, collectivistic, and Confucian foundations of China’s sociocultural and political ideology. While the notion that ‘mobility produces culture’ is readily accepted, research on train mobility in China is rare. In this study, we use Albert Bandura’s Model of Triadic Reciprocal Causation to conceptualize mobility as agency. We employ Hermeneutic Content Analysis, a mixed methods framework, to study how this rapidly evolving mobility environment connects to the lives of 31 regular train users living in Beijing. Studying agency in China enables us to systematize the sociocultural models within which mobility practices are embedded and how they manifest. We find that our interviewees embed agentive practices in a cultural model that is intertwined with collectivistic aspirations of the country. Technological developments are thus integrated into existing sociocultural models and political expectations, contradicting existing debates on the fracturing impact of disruptive technologies.

‘“It should allow me to opt in or opt out”: Investigating smartphone use and the contending attitudes of commuters towards geolocation data collection

A valuable body of literature critiques the ways in which data generated by individuals through their smartphone and mobile media use are collected and controlled by governments, state-based institutions and corporations. However, alongside this much-needed critical scholarship, it is necessary to identify the specific attitudes of users towards locational data collection activities and, by extension, the differing levels of socio-technical literacy that exist among smartphone users. This article presents evidence of the attitudes of train commuters about the geolocation mapping of their movement via smartphone Wi-Fi signals. Involving significant methodological challenges, the study used Simple Observation combined with a three-question survey of 100 commuters completed at a major train station in Melbourne, Australia, over a three-day period. Based on the evidence collected and analysed, the findings show that attitudes are grouped into six categories: (1)in favour, (2)in favour with guarantees, (3)sceptical, (4)staunchly opposed, (5)confused, and (6)apathetic. We propose that publicly visible initiatives to raise awareness about the collection and utilisation of smartphone data are essential to inform citizens about their locational privacy, especially given the continuing spread of sensor-based monitoring systems in public spaces and so-called smart cities.

Commuter travel cost estimation at different levels of crowding in a suburban rail system: a case study of Mumbai

This research values travel attributes such as waiting time, in-vehicle time and crowding levels using behavioural data obtained from Mumbai local train commuters through a stated preference experiment. Actual on-board crowding images are considered to perceive the crowding more realistically by the train users. A multinomial logit modelling technique is used for estimating commuter travel cost (time) at different crowding levels. Results show that there is an increase in perceived in-vehicle travel time with the increase in crowding level. Traveling in a crowded seating condition increases the travel cost by 0.81 min per 1 min travel. A crowded seat leads the user to perceive an 81% increase in in-vehicle travel time, whereas this perception increases by 282% more during travel in super dense crush crowding compared to normal travel conditions. The generalized travel cost increases to a maximum in the super dense crush crowding. An effect analysis was carried out to understand the sensitivity of gender, age, income, and trip length on travel attributes. Female users tend to perceive more decrease in utility due to crowding than male users. A reduction of 60% in seating capacity will lower the perceived travel cost per minute by 43% during peak hours of travel. Essentially, a reduction in seat capacity will increase the standee capacity which in turn offers more comfort to standees while standing in super dense crush load condition. Presented discussions in this research are important to policy-makers and planners in the Mumbai Railway Vikas Corporation to monitor, measure and develop programs for the local train operation service quality. The study findings will be useful for developing a policy framework to deal with issues related to the level of service improvement for the suburban rail system in India and other developing economies.

Temporal framing of stated preference experiments: does it affect valuations?

In this paper, we explore how valuations of trip attributes by train commuters differ between a short-run (departure time choice) and a long-run (travel routine choice) context using a unique SP experiment explicitly designed for this purpose. In the short-run version of the SP experiment, the respondents receive information about available travel options shortly before they had planned to travel. In the long-run version, the respondents receive information about available travel options one month ahead of the planned travel. The short-run context concerns temporary changes in available travel options, while the long-run context concerns permanent changes. We find significantly higher valuations of trip attributes in the long-run context. Moreover, our results indicate that the usual arrival time at work as well as the intrinsically preferred arrival time at work serve as reference points in the short-run as well as the long-run choice context, with the former dominating in the short-run context and the latter in the long-run context.

Commute quality and its implications for commute satisfaction: Exploring the role of mode, location, and other factors

The quality of a worker’s commute significantly impacts her well-being. We seek to add to the nascent literature on this topic by examining how travel mode, location, and other personal characteristics are associated with perceived commute quality and then by exploring implications for commute satisfaction. We use data from the annual Campus Travel Survey of students and employees at the University of California, Davis and focus on three dimensions of the commute experience: how stressful the commute to campus is, whether travel time is seen as wasted time, and the degree to which commuters like their travel mode. Our analysis shows that commute quality differs by residential location, commute mode, student versus employee status, and gender. Overall, bicycle commuters and train commuters report the highest quality commutes, all else equal; bus riders report the lowest quality commutes; the results for those traveling to campus by car are somewhere in the middle. We also find that all three dimensions of perceived commute quality are strongly associated with overall commute satisfaction. These results point to several different strategies for employers like UC Davis that aim to improve commute quality in order to enhance well-being: improve the quality of each mode, encourage a shift to modes offering higher quality commutes, identify “mis-matched” employees who are not using the mode that would yield the highest commute satisfaction, use social marketing techniques to change perceptions of and preferences for commute options, and increase housing near work sites to enable more commuters to live within bicycling distance.

Commuter exposure to PM2.5, BC, and UFP in six common transport microenvironments in Sacramento, California

This study was designed to estimate and compare the air pollution exposures experienced by commuters in six common transportation modes utilized by California residents, and to evaluate the impact of practical exposure mitigation strategies in reducing commute exposures. We measured concentrations of fine particle matter (PM2.5), black carbon (BC), and ultrafine particles (UFP) for 161 commutes between April 2014 and November 2015 in Sacramento, CA. We collected measurements for six modes including single occupancy vehicles, high occupancy vehicles (multiple occupants), buses, light rail, train, and bicycling. The largest average concentrations for most pollutants were measured during train commutes and the lowest average concentrations were observed during light-rail commutes. Mitigation options were explored for personal vehicles, bicycling, and train commute modes. We found that ventilation settings of personal vehicles can reduce in-vehicle PM2.5, BC, and UFP concentrations by up to 75%. Similarly, bicycle route choice can reduce exposures by 15–75% with the lowest concentrations observed during commutes on dedicated bicycle paths away from traffic sources. Train commuters experienced UFP concentrations an order of magnitude greater when the locomotive engine was pulling the rail cars versus pushing the rail cars. We found that UFP concentrations during bus, bicycling, and train commutes were 1.6–5.3 times greater than personal vehicle commutes, while light rail commutes had 30% lower UFP concentrations than personal vehicle commutes. The largest exposure per mile occurred during bicycle commutes with PM2.5, BC, and UFP exposures of 1.312 μg/mile, 0.097 μg/mile, and 3.0 × 109 particles/mile, respectively. Train commutes experienced the largest exposure per mile of all of the combustion-derived transportation commute modes. BC accounted for 5–20% of total PM mass across all commute modes with an average fraction of ∼7% of PM2.5.

Exposure to ultrafine particles in different transport modes in the city of Rome

There is evidence of adverse health impacts from human exposure to particulate air pollution, including increased rates of respiratory and cardiovascular illness, hospitalizations, and pre-mature mortality. Most recent hypotheses assign an important role to ultrafine particles (UFP) (<0.1 μm) and to associated transition metals (in particular Fe). In a large city like Rome, where many active people spend more than one hour per day in private or public transportation, it may be important to evaluate the level of exposure to harmful pollutants which occurs during urban travelling. In this context, the aim of this work was to examine the relative contribution of different transport modes to total daily exposure.We performed experimental measurements during both morning and evening traffic peak hours throughout the winter season (December 2013–March 2014), for a total of 98 trips. Our results suggest that the lowest UFP exposures are experienced by underground train commuters, with an average number concentration of 14 134 cm−3, and are largely a reflection of the routes being at greater distance from vehicular traffic. Motorcyclists experienced significantly higher average concentrations (73 168 cm−3) than all other exposure classes, and this is most likely a result of the presence of high-concentration and short-duration peaks which do not occur when the same routes are traveled by car. UFP concentrations in subway train environments were found to be comparable to urban background levels. Still, in underground trains we found the highest values of PM10 mass concentration with a maximum value of 422 μg/m3. PM10 concentration in trains was found to be four and two times higher than what was measured in car and motorbike trips, respectively. Transport mode contribution to total integrated UFP daily exposure was found to be 16.3%–20.9% while travelling by car, 28.7% for motorbike trips, and 8.7% for subway trips. Due to lower exposure times, commuting by car and motorbike is comparable to other daily activities in terms of exposure. Our data can provide relevant information for transport decision-making and increase environmental awareness in the hope that the information about inhaled pollutants can translate into a more rational approach to urban travelling.

A Mathematical Model for Purchase Behavior of Train Commuters at Kiosks during Morning Rush Hour

A Mathematical Model for Purchase Behavior of Train Commuters at Kiosks during Morning Rush Hour

Train commuters’ scheduling preferences: Evidence from a large-scale peak avoidance experiment

We study the trip scheduling preferences of train commuters in a real-life setting. The underlying data have been collected during large-scale peak avoidance experiment conducted in the Netherlands, in which participants could earn monetary rewards for traveling outside peak hours. The experiment included ca. 1000 participants and lasted for multiple months. Holders of an annual train pass were invited to join the experiment, and a customized smartphone app was used to measure the travel behavior of the participants. We find that compared to the pre-measurement, the relative share of peak trips decreased by 22% during the reward period, and by 10% during the post-measurement. By combining multiple complementary data sources, we are able to specify and estimate (MNL and panel latent class) departure time choice models. These yield plausible estimates for the monetary values that participants attach to reducing travel time, schedule delays, the number of transfers, crowdedness, and unreliability.

Train Commuters' Scheduling Preferences: Evidence from a Large-Scale Peak Avoidance Experiment

We study the trip scheduling preferences of train commuters in a real-life setting. The underlying data have been collected during large-scale peak avoidance experiment conducted in the Netherlands, in which participants could earn monetary rewards for traveling outside peak hours. The experiment included ca. 1000 participants and lasted for about 6 months. Holders of an annual train pass were invited to join the experiment, and a customized smartphone app was used to measure the travel behavior of the participants. We find that compared to the pre-measurement, the relative share of peak trips decreased by 22% during the reward period, and by 10% during the post-measurement. By combining multiple complementary data sources, we are able to specify and estimate (MNL and panel latent class) departure time choice models. These yield plausible estimates for the monetary values that participants attach to reducing travel time, schedule delays, the number of transfers, crowdedness, and unreliability.

The happy commuter: A comparison of commuter satisfaction across modes

Understanding how levels of satisfaction differ across transportation modes can be helpful to encourage the use of active as well as public modes of transportation over the use of the automobile. This study uses a large-scale travel survey to compare commuter satisfaction across six modes of transportation (walking, bicycle, automobile, bus, metro, commuter train) and investigates how the determinants of commuter satisfaction differ across modes. The framework guiding this research assumes that external and internal factors influence satisfaction: personal, social, and attitudinal variables must be considered in addition to objective trip characteristics. Using ordinary least square regression technique, we develop six mode-specific models of trip satisfaction that include the same independent variables (trip and travel characteristics, personal characteristics, and travel and mode preferences). We find that pedestrians, train commuters and cyclists are significantly more satisfied than drivers, metro and bus users. We also establish that determinants of satisfaction vary considerably by mode, with modes that are more affected by external factors generally displaying lower levels of satisfaction. Mode preference (need/desire to use other modes) affects satisfaction, particularly for transit users. Perceptions that the commute has value other than arriving at a destination significantly increases satisfaction for all modes. Findings from this study provide a better understanding of determinants of trip satisfaction to transport professionals who are interested in this topic and working on increasing satisfaction among different mode users.

Commuter Exposure to Air Pollution in Newcastle, U.K., and Mumbai, India

AbstractThe results of a study on commuter exposure to carbon monoxide (CO) and PM10 during transit in the several commonly popular modes of transport in Mumbai, India, and Newcastle, U.K., are presented in this paper. In Mumbai, real-time exposure concentrations were measured while commuting along a route by bus, train, air-conditioned taxi, and a non-air-conditioned private car. In Newcastle, real-time exposure concentrations were measured while traveling by electric vehicle, public bus, and bicycle along a route. Average heart rate while commuting was monitored and subsequently simulated in a submaximal exercise test to give minute ventilation (VE) associated with each transport mode. The study in Mumbai has indicated that commuters traveling on buses and private non-air-conditioned cars are exposed to very high levels of air pollution compared with the train commuters. In Newcastle, electric vehicles and bicycles displayed the lowest exposure concentrations relative to buses. Higher exposure concentra...

Approaches to Waiting in Mobility Studies: Utilization, Conceptualization, Historicizing

Mobility requires waiting, especially in intermodal transportation systems. People must wait in airports, stations, and vehicles; at bus stops; in queues at registration desks and luggage checks; at boarding; and elsewhere. Waiting is part of the public transportation routine. As Ohmori and Harata report, an average commute time for train commuters in Tokyo is sixty-nine minutes.