AIDC project number:
PI: Vinod Vasudevan, University of Alaska Anchorage
Co-PI: Shawn Butler, University of Alaska Anchorage
Data on driver behavior under various circumstances is essential both for understanding traffic and for quantifying traffic safety. Traditional approaches of data collection (such as using driving simulators and video-graphic method) possess various drawbacks. Therefore, innovative ways of data collection need to be explored to gather continuous data of vehicle interactions with the driving environment. Recent advances in technology make instrumented vehicles (IV) affordable and. In such an experimental setup, a portable data acquisition system (PDAQS) is equipped with various sensors, including LiDAR, to capture driver behavior when driving the vehicle as naturally as possible. A PDAQS helps to observe instantaneous vehicle information and driver behavior accurately for longer road sections and durations. Also, such a PDAQS can be used as a probe unit to capture the drivers' driving behavior around the IV. The data that can be obtained accurately at high frequency include changes in headways and speeds and interactions among various road users on the road. Based on preliminary research findings, a PADQS can also capture high-quality data of non-motorized road user behaviors. It is proposed to develop a PDAQS setup and to conduct studies related to understanding road user interactions. Since the installation is portable, the same structure can be moved across different vehicles and locations (such as urban, rural, and different states.) to capture driving and environment data for various conditions. The tasks include developing the hardware, developing software programs to extract useful data, and carrying out a project to study motorists' behavior in extreme weather. The PDAQS will facilitate collecting valuable data that will help address both safety and mobility issues more efficiently in regions, such as rural regions within the Pacific Northwest, where a greater understanding of driver behavior lack.