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Cooperative Safety Based on Naturalistic Driving Data
https://orcid.org/0000-0001-8210-8215
https://orcid.org/0000-0001-9811-496X
This study investigates a driving behavior referred to as the cooperative safety concept that assumes for strings of conventional vehicles traveling in nighttime or conditions with reduced visibility during a stable flow condition, the leading vehicles would bear much of the navigational challenges and risks while the following vehicles enjoy reduced driving workload and improved navigation safety. The study includes a comprehensive investigation of the safety risk levels and driver behaviors at intersections and freeway ramp locations in an attempt to verify this phenomenon using data from the large-scale Second Strategic Highway Research Program (SHRP 2) naturalistic driving study database. Overall, the driver behavior analysis showed that drivers following other vehicles tended to travel at lower speeds but with more acceleration activities than other vehicles. In addition, lighting during nighttime appeared to help alleviate the behavioral differences between the two types of travelers and resulted in more dispersed merging, diverging, and lane-changing behaviors. The safety event data analysis showed that higher traffic levels tended to correlate with more safety events in general but significantly fewer single-vehicle events. In addition, higher traffic levels correlated with a significantly lower likelihood of crashes in general when a safety event occurred. In the SHRP 2 data, safety events included crashes, near crashes, and statistically selected baseline events recorded during the data collection. The findings of this study, including in particular the event analysis, indicated that vehicles following other vehicles in a free-flow condition tended to drive slower and have lower safety risks in terms of crashes in general and single-vehicle crashes in particular. This knowledge can have significant implications for applications such as advanced lighting systems, cooperative vehicle features, and smart traffic control strategies.
Cooperative Safety Based on Naturalistic Driving Data
https://orcid.org/0000-0001-8210-8215
https://orcid.org/0000-0001-9811-496X
This study investigates a driving behavior referred to as the cooperative safety concept that assumes for strings of conventional vehicles traveling in nighttime or conditions with reduced visibility during a stable flow condition, the leading vehicles would bear much of the navigational challenges and risks while the following vehicles enjoy reduced driving workload and improved navigation safety. The study includes a comprehensive investigation of the safety risk levels and driver behaviors at intersections and freeway ramp locations in an attempt to verify this phenomenon using data from the large-scale Second Strategic Highway Research Program (SHRP 2) naturalistic driving study database. Overall, the driver behavior analysis showed that drivers following other vehicles tended to travel at lower speeds but with more acceleration activities than other vehicles. In addition, lighting during nighttime appeared to help alleviate the behavioral differences between the two types of travelers and resulted in more dispersed merging, diverging, and lane-changing behaviors. The safety event data analysis showed that higher traffic levels tended to correlate with more safety events in general but significantly fewer single-vehicle events. In addition, higher traffic levels correlated with a significantly lower likelihood of crashes in general when a safety event occurred. In the SHRP 2 data, safety events included crashes, near crashes, and statistically selected baseline events recorded during the data collection. The findings of this study, including in particular the event analysis, indicated that vehicles following other vehicles in a free-flow condition tended to drive slower and have lower safety risks in terms of crashes in general and single-vehicle crashes in particular. This knowledge can have significant implications for applications such as advanced lighting systems, cooperative vehicle features, and smart traffic control strategies.
Cooperative Safety Based on Naturalistic Driving Data
https://orcid.org/0000-0001-8210-8215
https://orcid.org/0000-0001-9811-496X
This study investigates a driving behavior referred to as the cooperative safety concept that assumes for strings of conventional vehicles traveling in nighttime or conditions with reduced visibility during a stable flow condition, the leading vehicles would bear much of the navigational challenges and risks while the following vehicles enjoy reduced driving workload and improved navigation safety. The study includes a comprehensive investigation of the safety risk levels and driver behaviors at intersections and freeway ramp locations in an attempt to verify this phenomenon using data from the large-scale Second Strategic Highway Research Program (SHRP 2) naturalistic driving study database. Overall, the driver behavior analysis showed that drivers following other vehicles tended to travel at lower speeds but with more acceleration activities than other vehicles. In addition, lighting during nighttime appeared to help alleviate the behavioral differences between the two types of travelers and resulted in more dispersed merging, diverging, and lane-changing behaviors. The safety event data analysis showed that higher traffic levels tended to correlate with more safety events in general but significantly fewer single-vehicle events. In addition, higher traffic levels correlated with a significantly lower likelihood of crashes in general when a safety event occurred. In the SHRP 2 data, safety events included crashes, near crashes, and statistically selected baseline events recorded during the data collection. The findings of this study, including in particular the event analysis, indicated that vehicles following other vehicles in a free-flow condition tended to drive slower and have lower safety risks in terms of crashes in general and single-vehicle crashes in particular. This knowledge can have significant implications for applications such as advanced lighting systems, cooperative vehicle features, and smart traffic control strategies.
Cooperative Safety Based on Naturalistic Driving Data
J. Transp. Eng., Part A: Systems
Li, Yingfeng “Eric” (author) / Gibbons, Ronald B. (author) / Kim, Bumsik (author)
2022-10-01
Article (Journal)
Electronic Resource
English
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