Research
- Aging Drivers
- Cannabis and Driving
- Commercial Motor Vehicle
- Railroad
Commercial Motor Vehicle
This research addresses commercial motor vehicle driver crashes by using technology to measure driver practices associated with speeding, non-seatbelt use, distraction, and work-zone safety. Data is collected on behaviors and the effectiveness of delivering interventions in real-time.
Research Projects
Use of Real-Time Driver Alerts to Improve CMV Safety
TREDS, in partnership with Drivewyze, is piloting novel in-cab Electronic Logging Device-based safety alerts for active work zones across California. Real-time work zone data is used to notify commercial drivers about upcoming hazardous road conditions, encouraging safer and more attentive driving in high-risk areas. The goal is to reduce speeding and hard braking, and to improve safety for all road users.
Use of Artificial Intelligence Supported Cameras to Improve CMV Safety
TREDS has partnered with Acusensus in the use of AI technology to anonymously identify and characterize the prevalence of unsafe driving practices among CMV drivers. These behaviors include speeding, handheld device use, and non-seatbelt use. Additionally, the effectiveness of immediate roadside targeted messaging to mitigate these risky behaviors will be measured.
For more information
Please click the button below to submit your inquiry. You can also email treds@ucsd.edu or contact us at 1.858.534.8386 with your questions.
