Abstract—Applying new technologies to traffic engineering
studies has become more urgent due to the high cost and risk
associated with ordinary in-the-field testing. Augmented reality
(AR) is one of those technologies, in which virtual (computer-
generated) objects are added to the real scene in a way that the
user cannot distinguish between real and virtual objects in the final
scene. Adding virtual objects (people, vehicles, hazards, and other
objects) to the normal view can provide a safe realistic environ-
ment for testing driving performance under different scenarios.
This paper presents two systems, i.e., AR vehicle (ARV) and offline
AR simulator (OARSim) systems, and uses them to study the left-
turn driving behavior at an unsignalized intersection for drivers
with different characteristics. Two experiments were performed:
one using the ARV system installed in a vehicle and another using
the OARSim system installed in the laboratory. Quantitative mea-
surements of left-turn drivers’ behaviors were recorded. There
was no significant gender effect on all measured parameters in
both experiments. Older drivers selected larger gaps and used
smaller acceleration rates to turn left than younger drivers in both
experiments. The conservative driving attitude of older drivers
indicates the potential presence of reduced driving ability of the
elderly. While left-turn times using the ARV system were not sig-
nificantly affected by drivers’ age, older drivers took longer time
to complete the left-turn maneuver than younger drivers using the
OARSim did. Results from this study supported the feasibility and
validity of the proposed systems and showed promise for these
systems to be used as surrogates to in-the-field testing for safety
and operation aspects of transportation research.