Enhancing non-motorized safety by simulating non-motorized exposure using a transportation planning approach : final report.

Details

• Creators:
  Eluru, Naveen ; Yasmin, Shamsunnahar ; Bhowmick, Tanmoy ; Rahman, Moshiur
• Corporate Creators:
  University of Central Florida. Department of Civil, Environmental and Construction Engineering
• Corporate Contributors:
  Safety Research Using Simulation (SAFER-SIM) University Transportation Center ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; Florida. Department of Transportation
• Subject/TRT Terms:
  • Accident exposure
  • Crash risk forecasting
  • Crash severity
  • Cyclists
  • Injury severity
  • Nonmotorized transportation
  • Pedestrian safety
  • Pedestrians
  • Policy analysis
  • Simulation
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• Resource Type:
  Tech Report
• Geographical Coverage:
  United States;Florida
• Edition:
  Final report
• Corporate Publisher:
  Safety Research Using Simulation (SAFER-SIM) University Transportation Center
• Abstract:
  Safety researchers and analysists have employed land use and urban form variables as surrogates for ; traffic exposure information (pedestrian and bicyclist volumes and vehicular traffic). The quality of these ; crash prediction models is affected by the lack of “true” non-motorized exposure data. The current ; research effort is focused on developing a transportation planning simulation framework to generate ; exposure information for crash prediction models. Specifically, the research effort is focused on evaluating ; non-motorist exposure measures in terms of demand at a planning level. The evaluated exposure ; measures are incorporated in examining non-motorist safety, which would allow us to devise more ; evidence-based policy implications for improving overall safety and activities related to non-motorized ; modes of travel. The proposed research approach recognizes that non-motorized safety is affected by ; vehicular volumes and non-motorized activity at a macro-level in the urban region. The vehicular and nonmotorized ; exposure measures are generated to enhance the vulnerable road user crash prediction ; models. In identifying non-motorist exposure measures, we develop aggregate-level demand models to ; identify critical factors contributing to non-motorist generators and attractors at a zonal level. In ; evaluating non-motorist safety, we estimate four different aggregate level models: (1) zonal-level crash ; count model for examining pedestrian-motor vehicle crash occurrences, (2) zonal-level crash count model ; for examining bicycle-motor vehicle crash occurrences, (3) zonal-level crash severity model for examining ; pedestrian crash injury severity by proportions, and (4) zonal-level crash severity model for examining ; bicycle crash injury severity by proportions. These models are estimated as a function of zonal level ; sociodemographic characteristics, roadway/traffic attributes, built environment, land-use characteristics, ; and exposure measures identified from demand models. The formulated demand models are estimated ; by using 2009 National Household Travel Survey data and the crash models are estimated by using the ; Signal Four Analytics crash database for the year 2010 for the Central Florida region. Model estimation ; results are further augmented by a validation exercise. To demonstrate the implication of the estimated ; models, we also perform policy analysis for ten different scenarios, including changes in traffic volume ; within the vicinity of central business district, reduction in zonal-level speed limit, increasing walking ; facilities, and restrictions on the number of traffic lanes. From the policy scenario analysis, we identify ; beneficial changes to existing infrastructure and traffic operation for improving non-motorized road user ; safety at a planning level. The research methodology as proposed in our study recognizes that zonal-level ; attributes are likely to influence non-motorist exposure. At the same time, non-motorist exposure along ; with the zonal-level attributes are critical factors in developing non-motorist safety models.
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• Format:
  PDF
• Funding:
  DTRT13-G-UTC53
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/32653/dot_32653_DS1.pdf
• File Type:
  [PDF - 3.30 MB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:8f6d43b33ab3f61d090f1789995c4b35ee3c7abc56f61e431e93ab286f1181e1fa90e1eb372ad3edbe1f299a2372af19a3f92cb85880b79e477b5853e12187c6