Real-Time Analytics of Transportation Data Lab

About the research

Connected vehicle technologies are being developed to enable safe, interoperable networked wireless communications among vehicles (V2V), the infrastructure (V2I), and travelers’ personal communication devices (V2X). These technologies are intended to reduce highway crashes; provide data for assessing the performance of the transportation system; provide continual access to accurate information on the operation of the system to travelers; and reduce unnecessary stops, delays, and emissions.

Advances in the field of autonomous/self-driving vehicles has shown potential for new and innovative applications that could change how state departments of transportation (DOTs) and other public agencies maintain roadways and roadside vegetation, roadway and roadside construction, among other applications. Mowing of medians and the right-of-way is an important vegetation management practice for the California Department of Transportation (Caltrans), but it is labor intensive and requires expensive and specialized equipment. Autonomous vehicles have the potential to improve worker safety and efficiency.

With the advent of autonomous vehicles, it may be possible to reduce worker exposure and risk by utilizing driverless tractors for mowing operations. In addition, cost savings are possible by utilizing one operator to control more than one mower. The objective of this project is to assess ease of use, safety, and appropriateness for Caltrans operations of non-line-of-sight, remote control technology for Caltrans vehicles and operations. As a minimum, the technical literature will be reviewed to ascertain the state-of-the-art for autonomous vehicle technologies for highway mowing operations. Based on this review, a draft specification will be developed defining the minimum requirements a DOT expects. In addition, the specification will be shared with potential vendors to assess their capability to provide an implementable product.