Abstract
Vehicle steering, braking and acceleration are subject to
friction forces arising from contact of the tyres with
the road surface. The contact force is both enabling and
limiting. The ratio of the contact friction to the force
of the tyres pressing on the road surface is described as
the coefficient of friction. The maximum coefficient of
friction for different surfaces characterizes the extent
of tyre grip.
Collision avoidance and collision mitigation systems
require information on tyre grip so as to accurately
calculate braking distances and evasive manoeuvres.
Estimating road slipperiness (skid resistance) during
driving has however proven difficult.
This dissertation discusses estimating the maximum
coefficient of friction (herein referred to as the
friction potential) together with determining road
conditions. Both estimations are based on multi-sensor
data fusion; that is, combining data from several
sensors. The presented sensor data fusion utilizes
various sensors from three main classes: 1) environmental
sensors, 2) sensors measuring vehicle dynamics and 3)
experimental tyre sensors. This work concentrates
particularly on methods for combining measurements of
vehicle dynamics with environmental sensor readings; for
example, wheel speed signals are linked to readings about
ice, snow or water on the road.
The methods were incorporated into a prototype passenger
car implementation, where testing yielded a reliable
estimate of friction potential for approximately 90% of
driving time. The estimate of friction potential was then
within 0.2 of reference values measured in braking tests.
These results encapsulate a proof of concept on asphalt
roads in some wet, snowy, icy and dry road conditions.
The advantages of friction estimation for collision
avoidance and collision mitigation systems are analysed
using mainly simulations. A correct initial estimate of
the friction potential enables the systems to improve
traffic safety efficiently also in slippery road
conditions. However, the range of available environmental
sensors does not cover long braking distances.
Together with the simulations, the work introduces a new
method for collision avoidance calculations and timing
the activation of collision mitigation. The method is
based on a large number of pre-calculated vehicle
trajectories.
Original language | English |
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Qualification | Doctor Degree |
Awarding Institution |
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Supervisors/Advisors |
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Award date | 12 Mar 2010 |
Place of Publication | Espoo |
Publisher | |
Print ISBNs | 978-951-38-7382-0 |
Electronic ISBNs | 978-951-38-7383-7 |
Publication status | Published - 2010 |
MoE publication type | G5 Doctoral dissertation (article) |
Keywords
- friction
- sensor
- data fusion
- collision avoidance
- collision mitigation
- environmental sensing
- tyre
- road
- conditions
- trajectory
- curvature-velocity
- ADAS