  In this paper, we propose sensing-assisted beamforming designs for vehicles
on arbitrarily shaped roads by relying on integrated sensing and communication
(ISAC) signalling.Specifically, we aim to address the limitations of
conventional ISAC beam-tracking schemes that do not apply to complex road
geometries. To improve the tracking accuracy and communication quality of
service (QoS) in vehicle to infrastructure (V2I) networks, it is essential to
model the complicated roadway geometry. To that end, we impose the curvilinear
coordinate system (CCS) in an interacting multiple model extended Kalman filter
(IMM-EKF) framework. By doing so, both the position and the motion of the
vehicle on a complicated road can be explicitly modeled and precisely tracked
attributing to the benefits from the CCS. Furthermore, an optimization problem
is formulated to maximize the array gain through dynamically adjusting the
array size and thereby controlling the beamwidth, which takes the performance
loss caused by beam misalignment into account.Numerical simulations demonstrate
that the roadway geometry-aware ISAC beamforming approach outperforms the
communication-only based and ISAC kinematic-only based technique in the
tracking performance. Moreover, the effectiveness of the dynamic beamwidth
design is also verified by our numerical results.
