Various disruptions such as natural disasters, malevolent attacks, and emergencies are still inevitably posing threats on road network in driverless environment. However, most studies have focused on the impacts of micro mixed traffic flow characteristics, which cannot explicitly measure road network vulnerability in driverless environment. This paper develops a bi-objective framework to construct driverless environment based on travel demand. An improved accessibility-based methodology integrating traffic flow and driverless conditions evaluates the vulnerability of road network under disruptions. The proposed methodology was applied to highway network of Florida, in USA. Results demonstrate that the vulnerability of road network would be decreased with the increase of the penetration rate of autonomous vehicles.  When the penetration rate gets in the range of 40-80%, network vulnerability would significantly reduce, and they show linear relationship. Findings of this study could provide new sights into managing and planning driverless road network in future.

Network vulnerability;Automatic vehicle;Disruption;accessibility;Mixed traffic flow