1,416 research outputs found
On Constant Distance Spacing Policies for Cooperative Adaptive Cruise Control
Cooperative Adaptive Cruise Control (CACC) systems are considered as key
potential enablers to improve driving safety and traffic efficiency. They allow
for automated vehicle following using wireless communication in addition to
onboard sensors. To achieve string stability in CACC platoons, constant time
headway (CTH) spacing policies have prevailed in research; namely, vehicle
interspacing grows with the speed. While constant distance headway (CDH)
spacing policies provide superior potential to increase traffic capacity than
CTH, a major drawback is a smaller safety margin at high velocities and string
stability cannot be achieved using a one-vehicle look-ahead communication. The
hypothesis of this work is to apply CDH only in few driving situations, when
traffic throughput is of highest importance and safety requirements can be met
due to comparably low velocities. As the most relevant situations where CDH
could be applied, we identify starting platoons at signalized intersections. In
this paper, we illustrate this idea. Specifically, we compare CTH with CDH
regarding its potential to increase the capacity of traffic lights. Starting
with the elementary situation of single traffic lights we expand our scope to
whole traffic networks including several thousand vehicles in simulation. Using
real world data to calibrate and validate vehicle dynamics simulation and
traffic simulation, the study discusses the most relevant working parameters of
CDH, CTH, and the traffic system in which both are applied.Comment: In preparation for submission to IEEE Transactions on Intelligent
Transportation System
A Learning-based Stochastic MPC Design for Cooperative Adaptive Cruise Control to Handle Interfering Vehicles
Vehicle to Vehicle (V2V) communication has a great potential to improve
reaction accuracy of different driver assistance systems in critical driving
situations. Cooperative Adaptive Cruise Control (CACC), which is an automated
application, provides drivers with extra benefits such as traffic throughput
maximization and collision avoidance. CACC systems must be designed in a way
that are sufficiently robust against all special maneuvers such as cutting-into
the CACC platoons by interfering vehicles or hard braking by leading cars. To
address this problem, a Neural- Network (NN)-based cut-in detection and
trajectory prediction scheme is proposed in the first part of this paper. Next,
a probabilistic framework is developed in which the cut-in probability is
calculated based on the output of the mentioned cut-in prediction block.
Finally, a specific Stochastic Model Predictive Controller (SMPC) is designed
which incorporates this cut-in probability to enhance its reaction against the
detected dangerous cut-in maneuver. The overall system is implemented and its
performance is evaluated using realistic driving scenarios from Safety Pilot
Model Deployment (SPMD).Comment: 10 pages, Submitted as a journal paper at T-I
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A Survey on Cooperative Longitudinal Motion Control of Multiple Connected and Automated Vehicles
On Microscopic Modelling of Adaptive Cruise Control Systems
AbstractThe Adaptive Cruise Control (ACC) system, is one of the emerging vehicle technologies that has already been deployed in the market. Although it was designed mainly to enhance driver comfort and passengers’ safety, it also affects the dynamics of traffic flow. For this reason, a strong research interest in the field of modelling and simulation of ACC-equipped vehicles has been increasingly observed in the last years. In this work, previous modelling efforts reported in the literature are reviewed, and some critical aspects to be considered when designing or simulating such systems are discussed. Moreover, the integration of ACC-equipped vehicle simulation in the commercial traffic simulator Aimsun is described; this is subsequently used to run simulations for different penetration rates of ACC-equipped vehicles, different desired time-gap settings and different networks, to assess their impact on traffic flow characteristics
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