Jessica B. Cicchino

ORCID: 0000-0003-4337-518X
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About
Contact & Profiles
Research Areas
  • Traffic and Road Safety
  • Human-Automation Interaction and Safety
  • Urban Transport and Accessibility
  • Older Adults Driving Studies
  • Injury Epidemiology and Prevention
  • Automotive and Human Injury Biomechanics
  • Safety Warnings and Signage
  • Autonomous Vehicle Technology and Safety
  • Traffic Prediction and Management Techniques
  • Traffic control and management
  • Transportation and Mobility Innovations
  • Child and Animal Learning Development
  • Vehicle emissions and performance
  • Action Observation and Synchronization
  • Primate Behavior and Ecology
  • Smart Parking Systems Research
  • Agriculture and Farm Safety
  • Language Development and Disorders
  • Human Mobility and Location-Based Analysis
  • Physical Activity and Health
  • Human-Animal Interaction Studies
  • Insurance and Financial Risk Management
  • Transportation Planning and Optimization
  • Hearing Impairment and Communication
  • Infrastructure Maintenance and Monitoring

Insurance Institute for Highway Safety
2016-2025

University of Michigan
2016

Carnegie Mellon University
2004-2010

10.1016/j.aap.2022.106686 article EN Accident Analysis & Prevention 2022-05-14

10.1016/j.jsr.2018.05.006 article EN Journal of Safety Research 2018-05-19

10.1016/j.trf.2017.11.015 article EN Transportation Research Part F Traffic Psychology and Behaviour 2017-12-22

The objective of this study was to examine the effectiveness blind spot monitoring systems in preventing police-reported lane-change crashes.Poisson regression used compare crash involvement rates per insured vehicle year crashes 26 U.S. states during 2009-2015 between vehicles with and same models without optional system, controlling for other factors that can affect risk.Crash were 14% lower (95% confidence limits -24% -2%) among than those without.Blind are effective when considering all...

10.1080/15389588.2018.1476973 article EN Traffic Injury Prevention 2018-06-21

Objective Although partial driving automation systems are usually discussed as convenience features, consumers sometimes consider them to be safety features. The goal of this study was assess if reduces rear-end and lane departure crashes beyond like automatic emergency braking (AEB) prevention (LDP).

10.1080/15389588.2024.2448511 article EN Traffic Injury Prevention 2025-02-21

Objective E-scooter use has grown rapidly in the United States. Its rise popularity coincided with promotion of cycling many cities, but more needs to be known about how these transportation modes compare determine if should serve as an appropriate benchmark for policy decisions and safety expectations regarding e-scooters.Methods We examined characteristics adults seeking treatment a Washington, DC, emergency department (ED) injuries associated riding e-scooters during 2019 (n = 99) or...

10.1080/15389588.2021.1913280 article EN Traffic Injury Prevention 2021-05-07

Objective Automatic emergency braking (AEB) and forward collision warning (FCW) are effective at preventing rear-end crashes, but they may perform better in some crash scenarios than others. The goal of this study was to estimate the effects front prevention systems equipped passenger vehicles crashes where another vehicle, a medium/heavy truck, or motorcycle is struck compare effectiveness by vehicle type.

10.1080/15389588.2024.2321910 article EN Traffic Injury Prevention 2024-03-11

Information about drivers' experiences with driver assistance technologies in real driving conditions is sparse. This study characterized interactions forward collision warning, adaptive cruise control, active lane keeping, side-view assist, and departure warning systems following real-world use.Fifty-four Insurance Institute for Highway Safety employees participated drove a 2016 Toyota Prius, Honda Civic, 2017 Audi Q7, or Infiniti QX60 up to several weeks. Participants reported mileage...

10.1080/15389588.2017.1297532 article EN cc-by-nc-nd Traffic Injury Prevention 2017-03-24

Level 2 driving automation has the potential to reduce crashes; however, there are known risks when using these systems, particularly as they relate drivers becoming disengaged from driving. This paper provides data-driven recommendations for design best currently available methods encourage driver engagement and communicate where how a system can safely be used. Our pertaining concern management systems that monitor signs of disengagement return loop multimodal escalation process with...

10.1177/1555343420983126 article EN Journal of Cognitive Engineering and Decision Making 2021-01-20

Effective 9 January 2017, the default speed limit on Boston streets was reduced from 30 mph to 25 mph. This study evaluated effects of reduction speeds in Boston.Vehicle were collected at sites where lowered, and control Providence, Rhode Island, remained unchanged, before after change Boston. A log-linear regression model estimated vehicle associated with reduction. Separate logistic models changes odds vehicles exceeding mph, 35 lower limit.The a 0.3 % mean (p=0.065), reductions 2.9%, 8.5%...

10.1136/injuryprev-2018-043025 article EN Injury Prevention 2019-01-13
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