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A Survey on Cooperative Longitudinal Motion Control of Multiple Connected and Automated Vehicles
Leveraging Connected Highway Vehicle Platooning Technology to Improve the Efficiency and Effectiveness of Train Fleeting Under Moving Blocks
Future advanced Positive Train Control systems may allow North American railroads to introduce moving blocks with shorter train headways. This research examines how closely following trains respond to different throttle and brake inputs. Using insights from connected automobile and truck platooning technology, six different following train control algorithms were developed, analyzed for stability, and evaluated with simulated fleets of freight trains. While moving blocks require additional train spacing beyond minimum safe braking distance to account for train control actions, certain following train algorithms can help minimize this distance and balance fuel efficiency and train headway by changing control parameters
Distributed Model Predictive Control for Heterogeneous Vehicle Platoon with Inter-Vehicular Spacing Constraints
This paper proposes a distributed control scheme
for a platoon of heterogeneous vehicles based on the mechanism
of model predictive control (MPC). The platoon composes of a
group of vehicles interacting with each other via inter-vehicular
spacing constraints, to avoid collision and reduce communication
latency, and aims to make multiple vehicles driving on the same
lane safely with a close range and the same velocity. Each
vehicle is subject to both state constraints and input constraints,
communicates only with neighboring vehicles, and may not know
a priori desired setpoint. We divide the computation of control
inputs into several local optimization problems based on each
vehicle’s local information. To compute the control input of
each vehicle based on local information, a distributed computing
method must be adopted and thus the coupled constraint is
required to be decoupled. This is achieved by introducing the
reference state trajectories from neighboring vehicles for each
vehicle and by employing the interactive structure of computing
local problems of vehicles with odd indices and even indices. It
is shown that the feasibility of MPC optimization problems is
achieved at all time steps based on tailored terminal inequality
constraints, and the asymptotic stability of each vehicle to the
desired trajectory is guaranteed even under a single iteration
between vehicles at each time. Finally, a comparison simulation
is conducted to demonstrate the effectiveness of the proposed
distributed MPC method for heterogeneous vehicle control with
respect to normal and extreme scenarios
Resilience in Platoons of Cooperative Heterogeneous Vehicles: Self-organization Strategies and Provably-correct Design
This work proposes provably-correct self-organizing strategies for platoons
of heterogeneous vehicles. We refer to self-organization as the capability of a
platoon to autonomously homogenize to a common group behavior. We show that
self-organization promotes resilience to acceleration limits and communication
failures, i.e., homogenizing to a common group behavior makes the platoon
recover from these causes of impairments. In the presence of acceleration
limits, resilience is achieved by self-organizing to a common constrained group
behavior that prevents the vehicles from hitting their acceleration limits. In
the presence of communication failures, resilience is achieved by
self-organizing to a common group observer to estimate the missing information.
Stability of the self-organization mechanism is studied analytically, and
correctness with respect to traffic actions (e.g. emergency braking, cut-in,
merging) is realized through a provably-correct safety layer. Numerical
validations via the platooning toolbox OpenCDA in CARLA and via the CommonRoad
platform confirm improved performance through self-organization and the
provably-correct safety layer
Analyzing Attacks on Cooperative Adaptive Cruise Control (CACC)
Cooperative Adaptive Cruise Control (CACC) is one of the driving applications
of vehicular ad-hoc networks (VANETs) and promises to bring more efficient and
faster transportation through cooperative behavior between vehicles. In CACC,
vehicles exchange information, which is relied on to partially automate
driving; however, this reliance on cooperation requires resilience against
attacks and other forms of misbehavior. In this paper, we propose a rigorous
attacker model and an evaluation framework for this resilience by quantifying
the attack impact, providing the necessary tools to compare controller
resilience and attack effectiveness simultaneously. Although there are
significant differences between the resilience of the three analyzed
controllers, we show that each can be attacked effectively and easily through
either jamming or data injection. Our results suggest a combination of
misbehavior detection and resilient control algorithms with graceful
degradation are necessary ingredients for secure and safe platoons.Comment: 8 pages (author version), 5 Figures, Accepted at 2017 IEEE Vehicular
Networking Conference (VNC
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