A First Investigation of Truck Drivers’ On-the-Road Experience Using Cooperative Adaptive Cruise Control

Shiyan Yang, Steven E. Shladover, Xiao-Yun Lu, John Spring, David Nelson and Hani Ramezani

Institute of Transportation Studies, Research Reports, Working Papers, Proceedings from Institute of Transportation Studies, UC Berkeley

Abstract: Cooperative Adaptive Cruise Control (CACC) is a driver assist technology that uses vehicle-to-vehicle wireless communication to realize faster braking and acceleration responses in following vehicles and shorter headways compared to Adaptive Cruise Control (ACC). This technology not only enhances road safety, but also offers fuel saving benefits as a result of reduced aerodynamic drag. The amount of fuel savings is dictated by the following distances and the driving speeds. So, the overarching goal of this work is to explore truck drivers’ preferences and behaviors when following in “CACC mode,” an area that remains largely unexplored. While in CACC mode, the brake and engine control actions are automated. A human factors study was conducted to investigate truck drivers’ experiences and performance using CACC at shorter-than-normal vehicle following time gaps. The “On-the-road” experiment required commercial fleets drivers to operate the second and third trucks in a three-truck string on the freeways for 160 miles in Northern California. The experiment was in mixed normal traffic without any on-site assistance of authorities, such as state police. All trucks were equipped with CACC systems and unloaded trailers. F ive different time gaps between 0.6 and 1.8 seconds were tested. Factors such as cut-ins by other vehicles, road grades, and traffic conditions influenced drivers’ experience using CACC. Other factors like time gap setting, individual differences, and route section affected drivers’ usage of CACC. These findings reveal truck drivers’ acceptance of the deployment of CACC in their truck fleets and provide useful information for decision making to promote CACC usage in the trucking industry.

Keywords: Engineering (search for similar items in EconPapers)
Date: 2018-06-25
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