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Perceived risk and modal choice: Risk compensation in transportation systems
Abstract
A transportation mode choice analysis is performed that examines behavioral responses to perceived risk in the choice of mode for daily commute trips. This methodology provides a technique for examining, by means of disaggregate individual level data, risk-compensating effects in transportation systems. Various measures of perceived risk are examined for explaining modal choice. Other studies have described how safety regulations have resulted in increases in "driving intensity." This study defines one component of driving intensity to be the increased probability of commuting by automobile. The results show that modal shifts occur when risk perceptions for a given mode are reduced. To demonstrate potential risk-compensating effects within the transportation system, an estimate of changes in accident fatalities due to commuting is derived using rough estimates of fatalities per person-mile travelled. It is shown that a given change in the perceived risk of commuting by automobile results in a less than proportionate change in net commuting fatalities. The relative magnitude is dependent on how objective reductions in risk translate into perceived reductions in risk. This study also shows that perceived safety improvements in bicycle transportation have an aggregate elasticity value that is greater than one. This means that bicycle safety improvements attract proportionately more people to bicycle commuting (i.e. a 10% increase in safety results in a greater than 10% increase…
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“The presence of human drivers on the roads will also pose another - more profound - challenge to driverless vehicles, owing to the likelihood that human drivers will quickly learn to take advantage of the programmed behaviour of their driverless counterparts.”
From When human beings are like drunk robots: Driverless vehicles, ethics, and the future of transport (2017) · cites this paper as Noland, 1995
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Metadata
- Authors
- Noland, R. B.
- Affiliations
- University of California, Irvine (US)
- Corresponding author
- Noland, Robert B.
- ORCID
- Noland, Robert B.
- Venue
- Accident Analysis & Prevention
- Publisher
- Elsevier BV
- Published
- 1995-08
- Volume
- 27
- Issue
- 4
- Pages
- 503-521
- ISSN
- 0001-4575 (ISSN-L)
- OpenAlex
- W2079641705
- Cited by
- 128
- References
- 33
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 3 · 2023: 10 · 2022: 5 · 2021: 7 · 2020: 6 · 2019: 6 · 2018: 6 · 2017: 4 · 2016: 7 · 2015: 4 · 2014: 4 · 2013: 6 · 2012: 8
- FWCI
- 7.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Accident Analysis & Prevention (publishedVersion)
- PubMed (publishedVersion)
- Funders
- University of Pennsylvania
- Topics
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Traffic and Road Safety
- Social Sciences › Transportation › Transportation Planning and Optimization
- Social Sciences › Transportation › Urban Transport and Accessibility
- Keywords
- risk perception, risk compensation, mode choice, commuting, bicycle commuting, cyclist safety, accident mortality, modal shift, safety regulations, transport safety
- MeSH terms
- Accidents, Traffic, Attitude to Health, Choice Behavior, Female, Humans, Male, Probability, Psychological Theory, Surveys and Questionnaires, Risk-Taking, Safety, Transportation, Logistic Models
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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