Automated Vehicle Reliance on Pavement Markings

[vc_row css_animation="" row_type="row" use_row_as_full_screen_section="no" type="full_width" angled_section="no" text_align="left" background_image_as_pattern="without_pattern"][vc_column][vc_row_inner row_type="row" type="full_width" text_align="left" css_animation=""][vc_column_inner][vc_column_text]The goal of this study was to collect input from stakeholders regarding how automated driving technologies might interact with highway infrastructure assets—which technologies interact with which assets and how the design, operation, and maintenance...

[vc_row css_animation="" row_type="row" use_row_as_full_screen_section="no" type="full_width" angled_section="no" text_align="left" background_image_as_pattern="without_pattern"][vc_column][vc_row_inner row_type="row" type="full_width" text_align="left" css_animation=""][vc_column_inner][vc_column_text]This report reflects the views of the authors only and does not reflect the views or policies of Transport Canada. Neither Transport Canada, nor its employees, makes any warranty, express or implied, or assumes...

[vc_row css_animation="" row_type="row" use_row_as_full_screen_section="no" type="full_width" angled_section="no" text_align="left" background_image_as_pattern="without_pattern"][vc_column][vc_row_inner row_type="row" type="full_width" text_align="left" css_animation=""][vc_column_inner][vc_column_text]This study was conducted for the National Cooperative Highway Research Program (NCHRP) Project 20-102(06) “Road Markings for Machine Vision” by the Texas A&M Transportation Institute, a member of The Texas A&M University System. The...