A stop safety index to address pedestrian safety around bus stops

Mehmet Baran Ulak*, Ayberk Kocatepe, Anil Yazici, Eren Erman Ozguven, Ashutosh Kumar

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

22 Citations (Scopus)
439 Downloads (Pure)


Despite the decline in the numbers of crashes and fatalities in the U.S. since 1990, pedestrian crashes have been steadily increasing and reached its 28-year peak in 2018. This increase led to initiatives such as Vision-Zero in response to this deterioration in pedestrian safety. In spite of the severe outcomes of pedestrian crashes, guidelines are still not fully capable of alleviating pedestrian safety issues and to formulate safety performance functions; mainly due to the scarcity of pedestrian data, particularly the pedestrian counts. However, pedestrian safety is a critical concern; hence safety of pedestrian facilities is also needed to be quantified. With this need in mind, this study proposes a safety index for public transportation bus stops which are facilities that are heavily utilized by the pedestrians. For this purpose, this paper first shows that there is a significant spatio-statistical correlation between the bus stop locations and pedestrian-involved crashes. Then, a bus stop safety index (SSI) is proposed in order to quantify and assess pedestrian safety around bus stops. Finally, a regression tree model is also developed for SSI scores (in a fashion similar to safety performance functions) in order to make the SSI available to practitioners who do not have access to relevant software and pedestrian crash data. Overall, the developed SSI measure can be used as a screening metric which can rank the pedestrian safety around the bus stops, and help identify high-risk locations in a proactive manner before the pedestrians become crash statistics.
Original languageEnglish
Article number105017
Number of pages14
JournalSafety science
Publication statusPublished - Jan 2021


  • UT-Hybrid-D
  • Bus stop safety index
  • Pedestrian safety
  • Public transportation
  • Spatio-statistical analysis
  • Decision tree modeling


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