Browsing by Author "Sturdevant, Jim"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Assessing the Effectiveness of In-Vehicle Highway Back-of-Queue Alerting System
    (The National Academies of Sciences, Engineering, and Medicine, 2021-01) Shen, Dan; Zhang, Zhengming; Ruan, Keyu; Tian, Renran; Li, Lingxi; Li, Feng; Chen, Yaobin; Sturdevant, Jim; Cox, Ed; Electrical and Computer Engineering, School of Engineering and Technology
    This paper proposes an in-vehicle back-of-queue alerting system that is able to issue alerting messages to drivers on highways approaching traffic queues. A prototype system was implemented to deliver the in-vehicle alerting messages to drivers via an Android-based smartphone app. To assess its effectiveness, a set of test scenarios were designed and implemented on a state-of-the-art driving simulator. Subjects were recruited and their testing data was collected under two driver states (normal and distracted) and three alert types (no alerts, roadside alerts, and in-vehicle auditory alerts). The effectiveness was evaluated using three parameters of interest: 1) the minimum Time-to-Collision (mTTC), 2) the maximum deceleration, and 3) the maximum lateral acceleration. Statistical models were utilized to examine the usefulness and benefits of each alerting type. The results show that the in-vehicle auditory alert is the most effective way for delivering alerting messages to drivers. More specifically, it significantly increases the mTTC (30% longer than that of 'no warning') and decreases the maximum lateral acceleration (60% less than that of 'no warning'), which provides drivers with more reaction time and improves driving stability of their vehicles. The effects of driver distraction significantly decrease the efficiency of roadside traffic sign alert. More specifically, when the driver is distracted, the roadside traffic sign alert performs significantly worse in terms of mTTC compared with that of normal driving. This highlights the importance of the in-vehicle auditory alert when the driver is distracted.
  • Thumbnail Image
    Item
    Implementation and Performance Evaluation of In-vehicle Highway Back-of-Queue Alerting System Using the Driving Simulator
    (IEEE Xplore, 2021-09) Zhang, Zhengming; Shen, Dan; Tian, Renran; Li, Lingxi; Chen, Yaobin; Sturdevant, Jim; Cox, Ed; Electrical and Computer Engineering, School of Engineering and Technology
    This paper proposes a prototype in-vehicle highway back-of-queue alerting system that is based on an Android-based smartphone app, which is capable of delivering warning information to on-road drivers approaching traffic queues. To evaluate the effectiveness of this alerting system, subjects were recruited to participate in the designed test scenarios on a driving simulator. The test scenarios include three warning types (no alerts, roadside alerts, and in-vehicle auditory alerts), three driver states (normal, distracted, and drowsy), and two weather conditions (sunny and foggy). Driver responses related to vehicle dynamics data were collected and analyzed. The results indicate that on average, the drowsy state decreases the minimum time-to-collision by 1.6 seconds compared to the normal state. In-vehicle auditory alerts can effectively increase the driving safety across different combinations of situations (driver states and weather conditions), while roadside alerts perform better than no alerts.