Models of Accident Risk and Fatigue in Railroad Operations

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neighborhood map and marked upon it the destinations to which they regularly walk/bike. Correspondingly, children were asked to
elaborate on environmental and/or social elements that may affect their experience of walking/biking in the neighborhood.
Results: Children from the traditional neighborhood described a higher number and greater variety of walking destinations (19 versus 11),
while very few biking destinations were reported by children from both neighborhoods types (3 in the traditional and 4 in the suburban
neighborhood). Low traffic-related safety was described as a common barrier to walking in the traditional neighborhood, while low
personal safety was more commonly reported in the suburban neighborhood. In addition, lack of biking infrastructure was described as a
common barrier in the traditional neighborhood, while social norms that are unsupportive of biking were commonly described in the
suburban neighborhood.
Conclusions: The results of this and our previous study suggest that while children in suburban neighborhood bike more frequently, they
have only a few biking destinations (as few as in traditional neighborhoods). This implies that in addition to biking infrastructure, it is
important to provide more biking destinations by enhancing mixed land uses. Furthermore, the results of this study highlight the
importance of the social-community environment in enhancing children's walking and biking, especially in suburban neighborhoods.
http://dx.doi.org/10.1016/j.jth.2016.05.073
A43
Testing Social Norms As an Incentive to Active Transportation Behavior
William Riggs
California Polytechnic State University, San Luis Obispo, CA, USA
Abstract
Background: The ability to influence active transportation behavior offers an opportunity to address societal issues of inflection such as
transportation congestion, air quality, and public health issues such as obesity. As a result a body of working is beginning to explore the
behavioral dimensions that drive travel, including both social and behavioral norms. Research suggests that social forces may play an equal
or paramount role to price / economic levers and that the psychological pull of social but more work is needed evaluate how market vs.
social nudges work together to influence transportation decisions.
Methods: To evaluate this a group of roughly 500 participants were offered differing incentives in four otherwise identical trials. These
incentives included various monetary amounts, a free gift or a social nudge tapping into altruistic values, in our case benefits to the
environment.
Results: After tests for homogeneity, the results indicated that the social nudge had a high degree of effectiveness, as compared to both the
financial incentives and gifts. Furthermore the results indicated that mixing market and social norms caused both to be less effective.
Conclusions: These findings that travel incentive programs that focus solely on fiscal may be missing out on a significant opportunity. A
focus on social norms and value may provide a tool to facilitate greater changes in travel behavior that can nudge individuals to more
healthy and climate-sensitive modes of travel such as walking, biking and transit.
http://dx.doi.org/10.1016/j.jth.2016.05.074
SOT-8 High Speed Rail
A44
Models of Accident Risk and Fatigue in Railroad Operations
Patrick Sherry
1
, Karen Philbrick
2
1
University of Denver, CO, USA
2
MTI, CA, USA
Abstract
Background: Fatigue is one of the most critical safety issues the railway industry faces today. Fatigue can result in loss of alertness,
impaired judgment, slower reaction time, increased errors, increased risk-taking, and reduced motivation. Fatigue can negatively affect
A. Macmillan, J. Woodcock / Journal of Transport & Health 3 (2016) S4–S61S30

performance resulting in increased errors and workplace accidents and a detrimental impact on safety. Fatigue within the transportation
industry is particularly challenging due to the fact that accidents on the job can have detrimental and fatal effects. The US DOT has adopted
a biomathematical model to be used in the prediction of the impact of extended work hours on accident likelihood. Models of accident risk
in the UK have been developed using a slightly different methodology to categorize shifts as high or low risk for accidents. To address
some of these discrepancies a sample of N¼100 work schedules of employees of a large Eastern commuter railroad were examined to
calibrate two of the models.
Methods: The present study examined the two main biomathematical models (FAST and FAID) currently under consideration in the USA. A
sample of N¼100 work schedules of employees of a large Eastern commuter railroad were analyzed and submitted to each model.
Resulting accident risk predictions were produced for each model. Regression analysis was used to identify intersecting risk cut points for
accident thresholds.
Results: Asignificant linear relationship was found between the two models (r ¼4.90). A cutoff score of 60 on the FAID model cor-
responded to a FAST score of 70 following the linear transformation of the FAID score. Bivariate correlations generated from FAST-FAID
scores were found to be statistically significant at the p o.001 level accounting for 53% of the explained variance. The FRA has determined
that the FAST model is related to injuires and human factor caused accitidents when scores fall below 70 on the model. The FAID model
showed a similar relationship yet with a more conservative threshold for fatigue.
Conclusions: The two models are highly related and can be used to predict accident risk. Caution should be used in applying these models
to actual operational settings. Nevertheless, these models provide the best scientific approach to understanding the effects of shiftwork,
and associated fatigue, to increase the likelihood of safe rail operations.
http://dx.doi.org/10.1016/j.jth.2016.05.075
A45
Tracking and Identifying Areas of Stress in RAIL Commuter Journeys Though Eye-Tracking and
DATA Fusion
Amy Guo, Graeme Hill, Joan Harvey
Newcastle University, Newcastle upon Tyne, United Kingdom
Abstract
Background: It is known that stressful situation can cause changes in physiological responses, such as increases in heart rate and breathing
rate. This paper describes an experimental approach to monitor rail commuters’travelling experience and reveal issues and contexts that
cannot be identified through traditional market research methods, such as questionnaires and focus groups.
Methods: The study utilised eye tracking cameras, gyro sensor, accelerometer, heart rate monitor and GPS to capture the commuters’eye
movement and orientation, heart rate variety, elevation and location. The approach enabled the physical and non-physical stressors to be
identified and context applied to changes in stress levels and causes thereof.
Results: A total of 15 female and 26 male commuters, aged from 20 to 60 (mean¼42.8, SD ¼12.7), participated in the study; 41 peak-hour
commuting journeys and 39 off-peak hour journeys were followed and monitored. The duration of the journeys ranged from 12 minutes
to 3 hours and 51 minutes depending on the participant and journey. An interview with each participant was carried out upon completing
the journeys. Information on weather, coach choice, condition of the coach, seating availability and choice, reason for journey, luggage (e.g.
carrying a bike), journey's punctuality and length of delay was recorded by researchers as well as reported by participants. Off-peak
journeys were used as the baseline to filter out the typical peak-hour factors from other co-exist factors when analysing the changes in
stress and anxieties. More in-depth and sophistic statistical analysis are undergoing and will be included in the presentation.
Conclusions: By transforming the collected second by second data into a continual proxy for the actual activity of the participant (e.g.
sitting or walking) and then combining this with the journey information, it is possible to show results unveiling the hidden causes of
commuting related stress and hence identify possible solutions to mitigate the stress and provide recommendations to transport operators
on how the experience could be improved. The results reveal the roles various sensors have played and how they could be easily employed
in future customer satisfaction studies.
http://dx.doi.org/10.1016/j.jth.2016.05.076
A. Macmillan, J. Woodcock / Journal of Transport & Health 3 (2016) S4–S61 S31