  Connected Autonomous Vehicles (CAVs) are widely expected to improve traffic
safety and efficiency by exploiting information from surrounding vehicles via
V2V communication. A CAV typically adapts its speed based on information from
the vehicle it follows. CAVs can also use information from vehicles further
ahead within their communication range, and this results in improved traffic
safety and efficiency. In mixed traffic scenarios, however, this may not always
be possible due to the presence of human-driven vehicles that do not have
communication capabilities. Furthermore, as wireless vehicular networks are
unreliable, information from other vehicles can be delayed or lost, which
brings more challenges for CAVs in utilizing information from multiple leading
vehicles. A few studies have investigated the impact of CAVs where they use
information from multiple leading vehicles on traffic safety and efficiency,
but only in very limited scenarios (i.e., with a very small number of
vehicles).
  In contrast, this paper investigates the impact of CAV car-following control
based on multiple leading vehicles information on both mixed traffic safety and
efficiency in realistic scenarios in terms of imperfect communication, vehicle
modelling, and traffic scenario. Results show that exploiting information from
multiple, rather than a single, leading vehicles in CAV controller design
further improves both traffic safety and efficiency especially at high
penetration rates. In addition to proper tuning of CAV controller parameters
(control gains and time headways), the scale of the improvement depends on both
market penetration rate (MPR) and communication reliability. A packet error
rate (PER) of 70% leads to an increase in traffic efficiency by 4.18% (at 40%
MPR) and 12.19% (at 70% MPR), compared to the simple single leading vehicle
information based controller.
