SSCISCOPUSQ3
Journal of Transportation Safety & Security
TAYLOR & FRANCIS INC, United Kingdom
Journal of Transportation Safety & Security is an academic journal published by TAYLOR & FRANCIS INC (United Kingdom). Identifiers: ISSN 1943-9962, eISSN 1943-9970. Indexed in SSCI, SCOPUS. Metrics: JIF 2.6, CiteScore 6.0, SJR 0.775, SNIP 1.16. Subject areas: TRANSPORTATION. tlooto lists 837 papers from this journal.
CiteScore
6.00
Scopus citation metric
SJR
0.775
SCImago rank
SNIP
1.16
Source normalized impact
Percentage rank
-
JIF percentile rank
Journal profile
- ISSN
- 1943-9962
- eISSN
- 1943-9970
- Abbreviation
- J TRANSP SAF SECUR
- Publisher
- TAYLOR & FRANCIS INC
- Country
- United Kingdom
Web of Science categories
SSCITRANSPORTATION
Scopus ASJC categories
3311 Safety Research3313 Transportation
Keywords
Transportation
Papers in this journal
Recent papers
- Investigating passengers’ evacuation behavior in a burning metro train carriage: An immersive virtual reality experiment
2026
- Modeling motor and non-motorized vehicle conflicts at roundabouts: Integrating trajectory fluctuation and kinematic metrics
2026
- Uncovering crash narratives: enhancing safety reporting for underprotected road users in transit bus collisions
2026 · 1 citations
- Impact of reflected light on driving behavior: A driving simulation study on expressway
2026
- Identifying arterial wrong-way crash hotspots in Central Florida: Improvement and transferability of corridor-level analysis and modeling framework
2026
Most cited papers
- Exploring the Relationship Between Average Speed, Speed Variation, and Accident Rates Using Spatial Statistical Models and GIS
2013 · 152 citations
- Alternative Ordered Response Frameworks for Examining Pedestrian Injury Severity in New York City
2014 · 114 citations
- Interactions between cyclists and automated vehicles: Results of a photo experiment*
2019 · 96 citations
- Way-finding lighting systems for rail tunnel evacuation: A virtual reality experiment with Oculus Rift®
2016 · 91 citations
- Crash severity analysis of rear-end crashes in California using statistical and machine learning classification methods
2018 · 84 citations