Development and Evaluation of a Novel Traffic Friendly ... · Novel Traffic Friendly Commuter...
Transcript of Development and Evaluation of a Novel Traffic Friendly ... · Novel Traffic Friendly Commuter...
Development and Evaluation of a Novel Traffic Friendly Commuter Vehicle
Rajesh Rajamani
Department of Mechanical Engineering
University of Minnesota
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Highway Congestion
Traffic congestion is a significant - and growing -problem in the country’s major metropolitan areasSome statistics
– Average traffic delay due to congestion grew 235% between 1982-1997
– Uncongested travel fell from two-thirds of travel in 1982 to one-third travel in 1997
– The increase in traffic demand every year exceeds the increase in capacity due to new construction
Traffic congestion will continue to become worse
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Approaches to Addressing Highway Congestion
What solutions do researchers in the automotive industry and researchers in the vehicle dynamics community offer to highway congestion?
– Automated highway systems
– Intelligent adaptive cruise control systems
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Automated Highway Systems
AHS lanes will have three times the capacity of regular highway lanes -Vehicles will travel together in closely-packed “platoons”.Dedicated to automated vehicles -regular passenger cars will have to be specially instrumented to travel on AHS lanes.
AHS is “dual mode” transit– Your instrumented car can travel on AHS and can also
take you on regular roads
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Automated Highway Systems
NAHSC demonstration in 1997Demonstration operated continuously several hours a day for 3 weeks– Passenger rides given to over a 1000 visitors
Video
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Automated Highway Systems
A variety of challenges need to be addressed before AHS can become a reality– technical – economic– social– legal
The AHS concept received a setback with the demise of the NAHSC
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Adaptive Cruise Control
Without preceding vehicleMaintain constant speed
With preceding vehicleMaintainsafe distance
radar
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Adaptive Cruise Control
Typical ACC System– Constant time-gap (CTG) spacing between
vehicles
Research Questions– Should ACC systems be designed to maintain a
constant time-gap between vehicles ? – Can traffic capacity and safety be simultaneously
improved by clever ACC design ?
L
hv
hvL +Desired spacing =
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Narrow Commuter Vehicles
Motivation– Double highway capacity by using a half-width lane
instead of a regular highway lane– Motorcycles
take up less space on the highwayneed less space for parkingare fun to driveare energy efficient
Can we develop a narrow vehicle that can– provide the benefits of a motorcycle– the safety of a car– be as easy to drive as a car ?
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Narrow Commuter Vehicles
A narrow vehicle needs to tilt into a curve for stability
Front Viewθ
mg
mVR
2
h
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Project Objective
Develop an automatic control system that
– Keeps the vehicle balanced while it is traveling straight
– Tilts the vehicle into a curve during cornering
– Reduces acceleration experienced by the driver
– Always maintains vehicle stability
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Some interesting prototype narrow vehicles
The Volkswagen 1-liter car
Volkswagen’s objective: Develop a prototype vehicle that can provide 100 km/liter (250 miles / gallon !)
• Solution: A narrow vehicle two-seater platform, aerodynamic design, lightweight carbon-fiber reinforces composite body
• Very agile handling, provides driving pleasure combined with a fuel economy never seen before
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Some other interesting prototype narrow vehiclesIntroduction
Control system
Prototype
Simulation
Experiments
Conclusion
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Fig. 1 Ford “Gyron” (1961)
Fig. 2 GM “Lean Machine” (1983)
Fig. 4 “Carver” (2003)
Fig. 3 Daimler “Life Jet” (1997)
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Introduction
Control system
Prototype
Simulation
Experiments
Conclusion
Control system - Dynamic Model
z
Tc.g.
β
θ
mgRz
Ry
y
h2θ&
Vy ψ&&& +
hθ&&
θβ
y’
z’
h
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y
ψY
X
a) top view b) front view
θ
Fig. 5 Degrees of freedomFig. 6 Bicycle model
(1)ThFFhmghmhmI
FlFlI
mgFFhmmhVmym
rfx
rrffz
rf
++−+−−=
−=
++=−++
)cos()()sin())cos()cos()sin((
)sin()sin()cos( 2
θθβθθθθθ
ψ
βθθθθψ
&&&&&
&&
&&&&&&
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Introduction
Control system
Prototype
Simulation
Experiments
Conclusion
Control system – Driver Model
Driver Model: Look-ahead-error based model (Guldner et al. 1996)
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ds
e2ds
e1e1
e2
Desiredtrajectory
Look-ahead error
Fig. 7 Look ahead error
*)(*_ 21 ff
erroraheadLook
dseekinputDriver δ++−=−−43421
(2)
* Parameters can be defined as a function of velocity to account for driver steering behavior change due to velocity variations.
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Tilt Control Systems
Direct tilt control (DTC)– An independent actuator is used to
provide tilt torque– Tilt and lateral dynamics can be
independently controlled– For low speed operation (less than 5 m/s
or 11.18 mph).
Steering tilt control (STC)– Steering angle is used to control both tilt
and lateral position– Challenge: One control input, two control
tasks– For high speed operation (higher than 10
m/s or 22.37 mph).
Possible actuation systems
DriverVehicle
STC
Throttle
Brake
Driver steering
θ
Actual steering
Throttle
DriverVehicle
DTC
Brake
Driver steering
θ and alatTilt
torque
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Introduction
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Prototype
Simulation
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Conclusion
Introduction – Proposed control systemSa
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4 mph 10 mph 55 mph0 mph
Vehicle Speed
High speed controller
(STC)
Low speed controller
(DTC)
Tilt brake
31 2
Fig. 8 Control scheme
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Direct Tilt Control (DTC)
a) Simple approach (stand alone):
RgV
gV
des
2
==ψθ&
MG
hFf + Fr
mg
θ
FN
ghmIIVy rotationrotwheelwheel
des
)/()(2)( __ ψωψθ ψ &&&& −−+
=
b) Proposed approach I (stand alone):
- Accounts for lateral acceleration of vehicle in addition to centripetal acceleration.
- Accounts for gyroscopic moment due to rotating wheels.
- Results in a significant reduction in transient tilt torque requirement.
- Results in zero tilt torque requirement at steady state.
Moments at c.g.
θθθ &21 )( kkT des −−−=
c) Proposed approach II (Integrated):))(()_( 21 ffsdes edekksinputDriverks δθ ++−==
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Steering Tilt Control (STC)
Steer-by-wire system– Driver steering input is modified before being used
to steer the wheels– Driver input is interpreted as a desired tilt angle
With appropriate definitions, leads to the same steady state value of steering angle
DriverVehicle
STC
Throttle
Brake
Driver steering
θ
Actual steering
))(()_( 21 ffsdes edekksinputDriverks δθ ++−==
44344214444 34444 21&&
statesteady
des
transient
desdesdesekkk )(
43 )()( θθνθθθθθδ −−+−+−=
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Control system - Combined system (SDTC)
Fig. 12 SDTC
• Both STC and DTC used in parallel.
-DTC active at low vehicle speed.
-STC active at high vehicle speed.
Driver steering
DriverVehicle
STC
Throttle
Brake
θ
Actual steering
DTC
θ
Tilt torque
β
α
SDTC
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Introduction
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0 5 10 15 20 25
0
0.2
0.4
0.6
0.8
1
Velocity [m/s]
Mag
nitu
de
α
β
Vo Vf
Fig. 13 Weighting functions
⎪⎪⎪
⎩
⎪⎪⎪
⎨
⎧
>
<<⎥⎥⎦
⎤
⎢⎢⎣
⎡+
−−
+
<
=
f
fofo
o
o
VVif
VVVifVVVV
VVif
0
)2
))()(sin(1
21
1
ππα
αβ −= 1
])([
)()]())([
21
43
θθθα
θθθθθθβδ
&
&&
kkT
dtkkk
des
desidesdes
−−−=
−+−+−= ∫
(9)
(10)
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Control system - Tilt BrakeIntroduction
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ConclusionStart
V
Brake offθdes = ks*driver_input
V > Vmin ?
|driver_input| < ε1 ?
f fdesdes kk δθθθθδ +−+−= )()( 43&&
Brake onθ = 0
δ = driver_input
V < Vmin ?
θdes = 0
|θ| < ε2 ?
Brake onδ = driver_input
No
driver_input
V
θ
No
No
Yes
Yes
Yes
Yes
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Fig. 14 Tilt brake algorithm
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Prototype
Fig. 15 Second generation prototype
Introduction
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Prototype
Simulation
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Conclusion
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Introduction
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Prototype - DesignSa
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• Engine: 125cc Yamaha
• Longitudinal acceleration: + 0.7 g
• Tilt limit: +30o
• Bump limit: +15o (0.1 m)
• Steering limit +30o
• Rake angle: 9.5o
• Front wheel trail: 0.06 m
Vehicle Specifications
Fig. 16 Vehicle dimensions
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Introduction
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Prototype - Tilt mechanismSa
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Fig. 17 Vehicle tilt mechanism
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Introduction
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Prototype - Tilt Mechanism actuation
Fig. 18 Tilt motor
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Introduction
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Conclusion
Prototype - Steering Mechanism
(a) Direct steering (b) Steer-by-wire
Fig. 19 Steering system
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Introduction
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Conclusion
Prototype - Tilt Brake System
Fig. 20 Tilt brake
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Introduction
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Prototype - InstrumentationSa
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PC - 104
IBM computer
Tilt servomotorIncremental encoder 1
Steering servomotor
Tilt brake
electromagnet
Incremental encoder 2
Absolute
encoder
Hall effect sensor
Xbow IMU
Driver input
Tilt angle
Steering angle
Speed
ay, ax, az
yaw, pitch, roll
Sensors
States
Ref. input
Actuators
Control inputs
Fig. 21
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Introduction
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Conclusion
Simulation – DTC (Simple Vs. Proposed)
Operating conditions:
• Vehicle velocity: 5 m/s (11 mph).
• A desired trajectory of a straight line for the first 50 seconds followed by a
circular path of radius 8 m (26 ft).
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Fig. 22 Tilt torque requirement
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Introduction
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Simulation – SDTC
The SDTC system was simulated for:
• Vehicle velocity varying between 1 m/s (2.24 mph) and 25 m/s (55.92 mph).
• A desired trajectory of a straight line for the first 50 seconds followed by a
circular path of radius 500 m (1640.42 ft).
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0 20 40 60 80 100 120 140-5
0
5
10
15
20
25
30
t [sec]
y[
]
1
Vel
ocity
[m/s
] STC
Transition
DTC
Fig. 29 Velocity profile of vehicle
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SDTC Simulation
Trajectory tracking
0 200 400 600 800 1000 1200 1400-200
0
200
400
600
800
1000
1200
x [m]
y [m
]
Actual trajectoryDesired trajectroy
A
Circular path
Straight path
Zoomed view of ‘A’
832 832.2 832.4 832.6 832.8 833 833.2
7.4
7.6
7.8
8
8.2
8.4
8.6
x [m]y
[m]
Actual trajectoryDesired trajectroy
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Simulation – SDTC Introduction
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Transition DTCSTC
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0 20 40 60 80 100 120 140 160 180 200-10
-8
-6
-4
-2
0
2
4
6
8
10
Tilt
torq
ue [N
m]
t [sec]0 20 40 60 80 100 120 140 160 180 20
-1
0
1
2
3
4
5x 10-3
t [sec]
[rad]
[N-m
]
0
Fig. 32 SDTC - Tilt torque (T) Fig. 33 SDTC - Steering input (δ)
DriverModel
DTC
Roadδ
PLANTSTC T
θ
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Simulation – SDTC Sa
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Tilt Zone 1.4 m
Track Width 1 m
Allo
wa b
le E
rro r
0.2
m
All o
wa b
le E
rro r
0.2
m
Half Lane 1.8 m
0 50 100 150-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
t [sec]
Sta
tes
Vehicle tilt [rad]
Position error [m]
Heading error [rad]Look ahead error [m]
Fig. 30 SDTC – Lateral states Fig. 31 Allowable position error
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Introduction
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Experiments
Validate the tilt stability and trajectory tracking.• Turn maneuver experiments
• Lane change maneuver experiments
Validate the tilt brake system.• Sinusoid steering input experiments
Vehicle handling investigation.• Under steering experiment
• Neutral steering experiments
• Constant yaw rate experiments
System limits.• Steering subsystem vibration
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Introduction
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Experiments - General stabilitySa
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Fig. 34 Tilt stability
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Experiments – Trajectory tracking Sa
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Fig. 35 Slalom course
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Experiments – Turing maneuver Sa
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Fig. 36 Desired tilt angle tracking
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Experiments – Turning maneuver Sa
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Fig. 37 Vehicle yaw rate
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Experiments – Lane change maneuver Sa
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Fig. 38 Desired tilt angle tracking
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Experiments – Lane change maneuver Sa
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Fig. 39 Vehicle yaw rate
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Experiments – Tilt brake validationSa
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Fig. 40 Tilt angle tracking and tilt brake status
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Experiments – Tilt brake validationSa
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Fig. 41 Vehicle yaw rate
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Experiments – Neutral steeringSa
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Fig. 42 Neutral steering
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Experiments – System limitationsSa
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Fig. 43 Steering subsystem instability
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Experiments – System limitationsSa
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0 2 4 6 8 10 12 14 16 18-10
-5
0
5
10
15
20
25
time [s]
Steering motor current rating [Amp]
Steering motor current [Amp]
Desired tilt [deg]
Actual tilt [deg] Speed [mph]
0 2 4 6 8 10 12 14 16 18-10
-5
0
5
10
15
time [s]
oscillation
Steering motor current rating [Amp] Steering motor current [Amp]
Actual steering [rad]
Desired steering [rad]
(a) Steering motor current (b) Actual steering
Fig. 44 Steering subsystem instability
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Conclusion
A control system that stabilizes an NTV from start up to highway speed while accurately following a desired trajectory was successfully designed.
– A DTC system that is suited for an integrated SDTC (STC + DTC) system was proposed.
– A method for smoothly shifting control efforts between the STC and DTC system was developed.
– A Tilt brake system and algorithm was developed for low speed operation.
A new stand alone DTC system with minimal transient torque requirement and zero steady state torque requirement was developed.
A second generation tilting vehicle was fabricated and the proposed compound control system was successfully implemented.
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Limitations
• Actuator saturation
Future work
• Replace steering system motor with at least 10 Amp motor and investigate high speed performance.
• Driver Haptic feedback.
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ConclusionSa
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Acknowledgement:
This project was partly supported by funds from the National Science Foundation under Grant CMS-0411455 and by funds from the ITS-Institute, University of Minnesota.
Research Team:
Samuel Kidane
Lee Alexander
Patrick Starr
Rajesh Rajamani
Max Donath