Rasmussen Breen (lyricpunch9)

Measures to protect vulnerable road users during low-speed maneuvers are required. For example, systems that use cameras to display the vehicle's rearview are popular. However, some vehicles are difficult to equip with a rear view camera system. To avoid a crash when driving in reverse, it is also effective to identify the presence of pedestrians via an audible warning using a device (e.g., clearance sonar). It may be cheaper to install than a rearview camera system. Installation cost is also important for the spread of equipment that reduces a crash. It is necessary to clarify the minimum specifications that balance cost and reduce crashes. Device specifications (e.g., detection distance and response delay) may affect the crash reduction rate. There should be a detection distance required for the sonar to have the same crash reduction effect as the rear view camera system. Thus, in this study, we conducted experiments and obtained data about how a vehicle moves and driver reactions to audible warnings when driving in reverse. Based on the acquired data, a numerical simulation was performed to determine whether a driver could avoid a crash under various circumstances. As a result, it was shown that the clearance sonar must have a detection distance of 0.8 m or more to expect the same effect as a rearview camera system. In other words, to expect sonar to have the same performance as a rearview camera, a detection distance of at least 0.8 m should be set as a specification.Ground-level traffic lights or safety signs have been introduced recently as a prevention measure for smartphone-related pedestrian accidents. However, quantitative evaluation of smartphone users' detection performance during distracted walking has been scarce. A laboratory experiment was conducted to evaluate the performance of detecting ground-level visual cues during the concurrent use of a smartphone while walking. Thirty-eight young smartphone users performed ground-level visual cue detection trials, 1) while walking upright on a treadmill without using a smartphone; 2) when conducting one-handed browsing while walking; and, 3) when conducting two-handed texting while walking. Visual cues were presented on the ground at 24 locations by a ceiling-mounted projector, and participants were asked to respond verbally when they perceived the appearance of each cue. Study results show that the concurrent use of a smartphone decreased the detection rate significantly (p less then 0.05) from 93.5 % to 76.3∼74.1 %, and increased the reaction time from 0.90 s to 1.04∼1.15 s. Among the 24 cue locations, cues that were presented closer to participants were detected significantly (p less then 0.05) more often and faster than cues that were shown at further locations. The results of this laboratory-based study imply that the ground-level signals might not be detected well by smartphone users, specifically when they were conducting more demanding tasks such as texting while walking. However, the laboratory conditions were confined to a specific usage environment; therefore, future research should be focused on the situation awareness of smartphone users under various usage scenarios and more realistic environments.The emergence of shared electric scooter (E-Scooter) systems offers a new micro-mobility mode in many urban areas worldwide. These systems have rapidly attracted numerous trips on various types of facilities such as sidewalks and bike lanes. After their burst of popularity, there are also growing safety concerns about E-Scooter riding. Consequently, a few cities have banned or temporarily suspended E-Scooters as severe crashes occurred. As an emerging micro-mobility mode, its safety performance is significantly understudied as compared to other travel modes such as cars and bicycles. The lack of crash records further prevents it from understanding the underlying mechanisms that drive the occurrences of E-Scooter crashes. selleck The overarching goal of this