Veh Dynamics

State of the Art Study of DAVINCI Project

Delft, 20 August 2000

Author Ir. Jiri Sika Faculty of Design, Engineering and Production, Vehicle Technology Section, Delft University of Technology

Thesis supervisor Prof. dr. ir. J.P. Pauwelussen Faculty of Design, Engineering and Production, Vehicle Technology Section, Delft University of Technology

State of the Art Study DAVINCI Project 2

Table of contents 1. Introduction to study of the art ..................................................................... 4 2. Introduction to vehicle dynamics ................................................................. 5 2.1. Classical vehicle dynamic equation of motion ............................................................ 5 2.1.1. General kinematics consideration in the study of the dynamics of ground vehicles......... 5 2.2. Dynamics fundamentals of vehicles - Vehicle subsystems ......................................... 6 2.2.1. Transfer of forces between tires and roadway................................................................ 6 2.2.2. Longitudinal force.......................................................................................................... 6 2.2.3. Terminology and axis system ........................................................................................ 7 2.2.4. The pneumatic tire characteristic ................................................................................... 7 2.2.5. Rolling resistance .......................................................................................................... 8 2.2.6. Tire characteristics ........................................................................................................ 8 2.2.7. Aerodynamic forces....................................................................................................... 9 2.2.8. Motor vehicle drive ...................................................................................................... 10 2.3. Longitudinal dynamics.............................................................................................. 11 2.3.1. Lumped mass.............................................................................................................. 11 2.3.2. Axis system................................................................................................................. 11 2.3.3. Basic equation............................................................................................................. 11 2.3.4. Climbing ability, maximum starting acceleration ........................................................... 12 2.3.5. Braking........................................................................................................................ 12 2.4. Lateral dynamics...................................................................................................... 14 2.4.1. Steady state turning..................................................................................................... 14 3. Automatic Driving ........................................................................................ 19 3.1. Main assumption...................................................................................................... 19 3.2. Other projects - overview ......................................................................................... 20 3.2.1. Japanese .................................................................................................................... 20 3.2.2. Dutch .......................................................................................................................... 20 3.2.3. Germany ..................................................................................................................... 20 3.2.4. Italy ............................................................................................................................. 20 3.2.5. USA ............................................................................................................................ 20 4. Sensing the Environment............................................................................ 21 4.1. Chassis Systems...................................................................................................... 21 4.1.1. Adaptive Cruise Control............................................................................................... 21 4.1.2. EPAS & EHPS ............................................................................................................ 22 4.1.3. Electromechanical Brakes (EMB): ............................................................................... 22 4.1.4. ABS braking ................................................................................................................ 22 5. Communication - Multiplex wiring system................................................. 24 5.1. Introduction .............................................................................................................. 24 5.1.1. Encoding techniques ................................................................................................... 25 5.1.2. Physical layers ............................................................................................................ 25 5.1.3. Protocols ..................................................................................................................... 26 5.2. CAN architecture...................................................................................................... 26 5.2.1. The CAN Protocol ....................................................................................................... 26 5.2.2. Higher Layer Protocols (HLP) ...................................................................................... 26 5.2.3. CAN Products ............................................................................................................. 27 5.2.4. User Groups................................................................................................................ 27 5.2.5. Distributed Control Systems ........................................................................................ 27

3 The Netherlands TRAIL Research School , June 2001

5.2.6. Why choose CAN ........................................................................................................ 27 6. Davinci experimental model car ................................................................. 29 6.1. Motivation .................................................................................................................29 6.2. Goals ........................................................................................................................29 6.2.1. Dynamics of Vehicle Rollover and Handling Analysis ................................................... 29 6.2.2. Dynamics of Anti-lock Braking Systems ....................................................................... 29 6.3. Description of vehicle................................................................................................29 6.4. Davinci experimental car...........................................................................................32 6.5. Schematic of systems ...............................................................................................32 7. Logistic modeling of automated guided vehicles ..................................... 33 7.1. Introduction...............................................................................................................33 7.2. Structured integral logistic control .............................................................................33 7.3. Basic model for vehicle control .................................................................................33 8. Literature....................................................................................................... 35


1. Introduction to study of the art Project Davinci starts with a state of the art study on automated vehicle guidance concepts and all

primary functions a vehicle had to fulfil within a transport environment, covering the normal vehicle functions and additional transport functions such as loading, unloading, coupling, de-coupling, positioning. That all should allow manufacturers and suppliers to develop integrated control systems in a more efficient and effective way, with guaranteed safety, reliability and optimal functionality.

The study of vehicle dynamics has traditionally focused on steady-state analysis, which provided adequate design equations. Braking, turning, acceleration, and ride are among the most essential properties of a motor vehicle and, therefore, should be well understood by every automotive engineer. Achievement this goals requires a better understanding of a vehicle as a system, so that qualities and performance can be predicted at an early stage of the design.

Next chapter introduce the basic mechanics of vehicle dynamics performance in the longitudinal (acceleration and braking modes), ride (vertical and pitch motions), and handling (lateral, yaw, and roll modes).


2. Introduction to vehicle dynamics 2.1. Classical vehicle dynamic equation of motion

2.1.1. General kinematics consideration in the study of the dynamics of ground vehicles

Over past decades analytical methods have been developed for predicting many aspects of automotive performance. Understanding vehicle dynamics can be accomplished at two levels - the empirical and the analytical.

The empirical understanding derives from trial and error by which one learns which factors influence vehicle performance, in which way, and under what conditions. The analytical approach attempts to describe the mechanics of interest based on known law of physics so that an analytical model can be established. In the simpler cases these models can be represented by algebraic or differential equations that relate forces or motion of interest to control inputs and vehicle or tire properties. These equations than allow one to evaluate the role of each vehicle property in the field of interest.

In order to reduce the intractability of the complex dynamics of ground vehicle motion, the classical vehicle dynamics field assumes the car body to act as a mass with six degrees of freedom (DOF). These degrees of freedom are then studied separately under the assumption that at any time only a subset of these six degrees of freedom will represent the dominant motion.

Heave and pitch, the names describing the vertical motion and in-plane angular motion within the vertical plane, are usually separated and studied as “ride”. Lateral motion and yaw, describing the angular motion in the horizontal plane, are studied in “handling”. Longitudinal acceleration and braking are studied separately usually under the title “road loads”.

The study of ride evaluates the passenger’s response to road/terrain irregularities with the objective of improving comfort and road isolation while maintaining wheel/ground contact. Suspension system design is mostly based on ride analysis. Handling evaluates the dynamics of the car in response to driver’s steering input. It includes cornering, directional stability, roll-over, and load transfer. The objective of the analysis is to improve the ability of the car to follow the desired steering input curve. Steering and suspension mechanisms are designed based on handling analysis. In road load studies, the longitudinal dynamics of motion are analyzed with the aim of improving the acceleration and braking responses of the vehicle. Engine and power-train characteristics are determined based on road load studies.

Several other important topics can be encountered in the study of vehicle dynamics, such as, tire dynamics or engine and powertrain dynamics. The analysis of powertrain dynamics including the dynamics

Fig. 0 The ISO vehicle dynamics axis system

PitchLateral

Vertical

Yaw

C.G.Roll

Longitudinalx

z

y


of the clutch, transmission system, and final drive, includes the interaction between the engine, powertrain, wheel, tire, and terrain with the objective of improving the longitudinal time response of the vehicle.

In particular tire dynamics is a field of critical importance in vehicle performance. The study of tire dynamics in the scope of vehicle dynamics attempts at developing mathematical and computer models that predict the dynamics of the pneumatic tire as a part of vehicle dynamic behavior.

The challenge that faces vehicle dynamists today is not only in merely understanding the complex non-linear dynamics of these areas but also in using modern CAD/CAE/CAM tools to integrate their design and computer controls in order to produce a highly responsive, comfort- able, and safe ground vehicle.

2.2. Dynamics fundamentals of vehicles - Vehicle subsystems

The proper function of the dynamic system motor vehicle - whether it is easy to handle, safety etc. can be explained by the interaction between sub-systems. The goal of this section is to explain the dynamics of a vehicle as a connection of subsystems based on theoretical and experimental consideration.

2.2.1. Transfer of forces between tires and roadway

The most important relationship for the vehicle dynamics. The reaction of the tire to rapid changes in kinetic values will only be taken into a consideration in a simplified way in respect to the lateral tire force.

A model of the system for the wheel and the contact forces is shown in this figure.

The tires and wheels to change the vehicle direction of motion must exert lateral forces. Mainly the wheel running at a slip angle accomplishes this lateral guidance function. The lateral sliding velocity vM.tan leads to a force system that can be represented by the lateral force S and the aligning torque Ms at the tire contact point.

With the introduction of the pneumatic trail or tire offset ns the aligning torque can also be described using the lateral force.

2.2.2. Longitudinal force

For the longitudinal force U the longitudinal slip, determined by the relative speed between the wheel and the roadway, is decisive

M

MB v

rvs Ω−= 1)

The form of this slip that increases very fast to the maximum and shows a decrease afterwards. Shape of this curve remains principally the same but different level for other road conditions.

Fig. 1 Model of vehicle wheel

ePU

x

z

MvM

r

W


2.2.3. Terminology and axis system

2.2.4. The pneumatic tire characteristic

The tire serves essentially three basic functions: It support the vertical load, while cushioning against road shocks It develops longitudinal forces for acceleration and braking It develops lateral forces for cornering

Fig. 2 Longitudinal friction coefficient

µdry road

wet road

ice

slip 100 %

V

V

-V

V

V

V

VM

F

F

F

FR

Y

Y

Y

Z

Z

S

S

S

X

X

X

C

C

γ

Ω

ψ

α

Fig. 3 Forces and moments at single wheel

Tractive force

Spin axis


2.2.5. Rolling resistance

The other important vehicle resistance is the rolling resistance of the tires. The deformation of the tire is associated flexing produces a rolling resistance which must be overcome even if the tire is only rolling

refR = 2)

Coefficient of rolling resistance of a single tire

Considering the vehicle as a whole, the total rolling resistance in the sum of the resistances from all the wheels:

WfRRR rxrxfx =+= 3)

The coefficient of rolling resistance is a dimensionless factor that expresses the effects of the complicated and interdependent physical properties of tire and ground. Factors affecting this coefficient are:

Tire temperature; tire inflation pressure versus load, velocity, tire material and design, tire slip.

2.2.6. Tire characteristics

We can usually distinguish the six force and moment components form the tire outputs. Many combination of inputs and outputs quantities are possible, each depending on a purpose of the tire model. Besides the vertical force Fz to carry the vehicle weight, the lateral force Fy and the longitudinal force Fx are most important, as they are needed to describe cornering and braking capabilities of the vehicle.

10 20 30 40 50 60 70 80 90 100

100

200

300

Total road load

Aerodynamic drag

Rolling resistance

Speed (mph)

Roa

d lo

ad fo

rce

(lb)

Fig. 4 Road load plot for a typical passenger car


The moment My represents the moment about the wheel axis, Mz the self-aligning moment and Mx the overturning moment. These forces and moments are acting from road to tires and these tires to rim.

Next figure represents characteristic of a radial tire for a constant normal force. Possible limit curves for the maximum coefficient of friction where entered in the graph. These tire characteristics show mainly the force relationship to be expected in the regular driving range disregarding the curve branches which run inward beginning at their maximum U/P. In this situation the wheel cannot transfer any higher longitudinal force and will quickly lock up or spin at higher braking or driving torque.( Fig.7)

2.2.7. Aerodynamic forces

The shape of the body determines the lift and drag coefficients. On the next picture is described an influence of wind from the direction with angle .

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.80.6 1

1

2

3

5

710

Fig.7 Tire forces at constant vertical load

α µmax

(x’,y’)

V

P

Projection of wheel axis

Contact area

Wheel centre plane

Fig.5 Top view of the contact area

y

x

x’

y’

V

C

O

p w

a

z

c

(u,v)


2.2.8. Motor vehicle drive

The considerations are limited to the aspects of combustion engines are used for propulsion of motor vehicles.

Figure shows the most important relationship for a diesel engine.

Fig.9 Performance a diesel engine

n [min ]-1

-1 -1

M [nM] p [kW]

m [gkW h ]

t

e

Fig.7 Areodynamic forces

y

y

y

x

xx

x x

vMW

MW

WW

b/2

b/2

MW

W

W

MW

z

z

z l/2l/2

resτ


2.3. Longitudinal dynamics

2.3.1. Lumped mass

A motor vehicle is made up of many components distributed within its exterior envelope. All these components move together and can be represented as one lumped mass located at its center of gravity (CG) with appropriate mass and inertia properties. For acceleration, braking and most turning analysis this is sufficient. For ride analysis we usually assign wheel as a separate lumped mass. In that case lumped mass representing the body is the sprung mass and the wheels are denoted as unsprung masses.

2.3.2. Axis system

The equations of motion employed in vehicle studies are related to a set of body -fixed axes. The origin of the axes is usually located at the center of the mass of the total vehicle. The fifth wheel is convenient location for the origin of both tractor and semi-trailer axes in the case of an articulated semi -trailer vehicle.

Road vehicles are controlled by forces and moments developed at the interface between tire and road. The nature of these forces and moments is such that it is convenient to consider the equation of motion in two phases.

The lateral and yawing motions cause the tires to generate angles of relative velocity against the road, as well as the equations in side slip and yaw are first order equations. Roll, bounce, and pitch movements effect the springs and dampers of the suspension which act in series with the tire springs in addition slip angle properties and thus the equations of motion are the second order.

2.3.3. Basic equation

The behavior of vehicle when driving straight ahead or at very small lateral acceleration values is defined as the longitudinal dynamics. The calculation and evaluation of acceleration, braking, climbing ability and top speed can be accomplished with a plane model. All factors that also cause considerable asymmetry when driving straight ahead (side wind, extremely one side load) belong to the lateral dynamics.

Three equation form Newton’s law:

( ) ( ) ( ) ySRFFFFRRRRRFF MWhUUelPelPJJ +⋅+−−−−⋅=Ω+Ω !!

SLFRX GWUUma ϑsin⋅−−+=

SZFR GWPP ϑcos0 ⋅−++=

PU

e

ΩΩ

r Gw

M MBA

Z

Z v ax x

vs

Fig. 12 Forces and moments at single wheel

Fig.11 Vehicle longitudinal dynamics

f

f

ff

f

rr

r

r

r

h

P

P U

U l

l

l

l

e

e

G

z

Ω

Ω

υs

Sy

r

a v

W

W

MW


Three additional equations can be derived for each individual wheel.

From these equation with equal rolling resistance coefficients for all wheels an equation for the longitudinal motion could be derived.

2.3.4. Climbing ability, maximum starting acceleration

The relation between the engine torque M and the drive moments at the wheels are determined by the properties of the drive train. (Fig.13)

Assuming that the vehicle drive is able to deliver the driving force required to overcome an ascending slope the climbing ability is limited by the longitudinal force coefficient between the tires and the roadway.

2.3.5. Braking

Essential to the understanding of the technology of the modern automotive vehicle braking seem to be knowledge of:

- tire-to-road interface - vehicle dynamics during braking - components of the brake system Tire-to-road interface

Function of the normal force on the wheel and the coefficient of friction. This coefficient of friction, it is not a cons. It is a function of factors: road surface, relative log. slip tire-to-road. A further limitation of the driving range is the maximum longitudinal deceleration determined by the longitudinal force coefficient.

Vehicle dynamics from Newton’s second law

From Newton’s second law we can also obtain equations for the time for a velocity change and the distance

SWXW GUXam υsin−+=

SWGPZ υcos0 −+=

( )PfUrMMJ RBA +−−=Ω!

whx WF µ=

( )RFRLSBFAFBFAFRRFF

x PPfWGr

MMr

MMr

Jr

Jma 22sin22 22 +−−−

−

+

−

=Ω

+Ω

+ ϑ!!

Fig.14 Vehicle dynamics during braking

R

R

FFW

W

WWcosu

W/gDW

DC.G.

xf

xf

xr

f

u

r

xr

h

A

Ah


xrxfx FFDg

WF +==∑

LhL

hFW

Fp

xnfsf

xmf

µµ

−

+

=1

LhL

hFWF

p

xnrsf

xmr

µµ

−

+

=1

traveled during a velocity change.

During braking, the dynamic load transfers.

Two another equations are important

Maximum friction force in the longitudinal direction on the front wheels

Maximum friction force in the longitudinal direction on the rear wheels

For the case that the angle u=0 and aerodynamic drag is negligible than:

The force on the front wheel

The force on the rear wheel

These equals indicate that the maximum braking force is on the front wheels and is dependent on the breaking force on the rear wheel, due to the load is transferred forward.

ufuWDFFDgWMaF raxrxtxx cossin ++++===∑

aa

xd DLh

Dg

WhlW −

=

−+= a

axfspxmf D

Lh

LghWDWF µ

+−= a

axrsxmr D

Lh

LghWDWF µ


List of symbols ax longitudinal vehicle acceleration ay lateral vehicle acceleration fR rolling resistance force coefficient G vehicle weight GW wheel weight h, ho, ha components of CG position l, lF, lR wheel base, front and rear distance of CG M vehicle mass mw wheel mass MA, MB drive moment , brake moment MS aligning torque MWx,y,z aerodynamic moment P normal force R rolling radius S lateral force U longitudinal tire force V velocity of CG vx longitudinal velocity of vehicle DA drag force slip angle wheel camber in respect to car body J wheel moment of inertia s angle of road slope aerodynamic angle yaw velocity wheel spin velocity

2.4. Lateral dynamics

Models that allow the lateral forces and the yawing of the vehicle to be described must be used for theoretical studies on cornering, transient steering manoeuvres as well as the directional stability when driving straight ahead. Inclusion of the body motion is in interaction with the wheel suspension. The nonlinear behaviour of the tires, the effects of the drive and steering system lead to very complex models with the help of which an attempt can be made to simulate the vehicle handling over a period of the time. However, a few of the basic considerations can be shown well using a linearized model.

2.4.1. Steady state turning

Low speed turning

The first step to understanding cornering is to analyze the low -speed turning behavior. At low speed the tires need not develop lateral forces. They roll with no slip angle, and the vehicle must negotiate a turn as illustrated in Figure 2.4.1 – 1.

( )2/tRL

O +≅δ ( )2/tR

Li −≅δ (19) (20)

For the proper geometry in the turn (small angles), the steer angles are given by : The average angle of the front wheels again assuming small angles) is defined as the Ackerman Angle:


Figure 2.4.1. - 1 Geometry of turning vehicle

L

t

R

δδo i

Turn center

High - speed cornering Much higher importance for our purpose of investigation vehicle lateral dynamics, because at high speed will be present lateral acceleration.

The lateral force, denoted by Fy, is called the cornering force when the camber angle is zero. At a given tire load, the cornering force grows with slip angle. At low slip angle (5 deg. and less) the relationship is close to linear.

ααCFy = (21) C is the cornering stiffness and is dependent on many variables. Tire size and type (radial versus bias-ply construction), number of plies, cord angles, wheel width, and tread are significant variables.

Slip angle

F

F

y

y

Direction of travel

cα

α

α

Slip angle

Late

ral f

orce

Figure 2.4.1 - 2 Tire cornering corce properties


bcFF yryf /=

The steady state cornering equations are derived from the application of Newton's second law. For purposes of analysis, it is convenient to represent the vehicle by the bicycle model shown in Figure 2.4.1 – 3.

For a vehicle traveling forward with a speed of V, the sum of the forces in the lateral direction is:

∑ =+= 2/2MVFFF yryfy (22) Also for the vehicle to be in a moment equilibrium about the center of gravity, the sum of the moments from the front and rear lateral forces must be zero.

0=− cFbF yryf (23) (24) Substituting back

( ) ( )cLFbLFbcbFbcFRMV yfyryryr ==+=+= //1//2 (25)

with the required lateral forces known, the slip angles at the front and rear wheels are also established.

)/(/ 2 RVLMbFyr = (26)

LcWW f.=

LMgbWr = (27) (28)

( )gRCVW fff αα /2= (29)

and

( )gRCVW rrr αα /2= (30)

Figure 2.4.1 - 3 Cornering of a bicycle model

L R

f

r

b

c

α

δ

α


From geometry of the vehicle be seen that:

rfRL ααδ −+= /3.57 (31) after substitution for fα and rα

r

r

f

f

CVW

CVW

RL

αα

δ22

3.57 −+= gRV

CW

CW

RL

r

r

f

f2

3.57

−+=

αα

δ (32) (33)

Under-steer gradient The equation is often written in this form:

yKaRL += 3.57δ (34)

where K is under-steer gradient and ay is lateral acceleration

These equations are very important to the turning response properties. It describes how the steer angle of the vehicle must be changed with the radius of turn R, or the lateral acceleration.

The term (35)

r

r

f

f

CW

CW

αα

− (35)

determines the magnitude and direction of the steering inputs required. It consists of two terms, each of which is the ratio of the load on the axle to the cornering stiffness of the tires on the axle. It is called the Understeer gradient.


Three possibilities exist:

Neutral steer

rfr

r

f

f KCW

CW

αααα

=→=→= 0 (36)

Understeer

rfr

r

f

f KCW

CW

αααα

>→>→> 0 (37)

Oversteer

rfr

r

f

f KCW

CW

αααα

<→<→< 0 (38)

Characteristic speed

For an under-steer vehicle. Is the speed at which the steer angle required to negotiate any turn is twice the Ackerman Angle.

RLKay 3.57= (39)

than

RLVchar /3.57= (40)

Critical speed

In the over-steer case , a critical speed will exist above which the vehicle will be unstable.

KLgVcrit /3.57−= (41)


3. Automatic Driving 3.1. Main assumption

In fact, a wide spectrum of approaches can be envisioned for highway automation systems in which the degree of each vehicle's autonomy varies. On one end of the range would be fully independent or "free-agent" vehicles with their own proximity sensors that would enable vehicles to stop safely even if the vehicle ahead were to apply the brakes suddenly. In the middle would be vehicles that could adapt to various levels of cooperation with other vehicles (platooning). At the other end would be systems that rely to a lesser or greater degree on the highway infrastructure for automated support. In general, however, most of the technology would be installed in the car.

One approach would be to develop automated highways that feature a lane or set of lanes on which vehicles equipped with specialized sensors and wireless communications systems could travel under computer control at closely spaced intervals, perhaps in small convoys or "platoons." Vehicles could be temporarily linked together in communications networks, which could allow the continuous exchange of information about speed, acceleration, braking, obstacles, and so forth.

Small networks of computers installed in vehicles and along selected roadways, these vehicles could closely coordinate vehicles and harmonize traffic flow (for example, reducing speed fluctuations and traffic shock waves), maximizing highway capacity and safety.

This approach is closely connected with AGV project of Trail Research School A driver electing to use such an automated highway might first pass through a validation lane,

similar to today's high-occupancy-vehicle (HOV) or carpooling lanes. The system would then determine if the car would function correctly in an automated mode, establish its destination, and deduct any tolls from the driver's credit account. Improperly operating vehicles would be diverted to manual lanes. The driver would then steer into a merging area, and the car would be guided through a gate onto an automated lane. An automatic control system would coordinate the movement of newly entering and existing traffic. Once traveling in automated mode, the driver could relax until the turnoff. The reverse process would take the vehicle off the highway. At this point, the system would need to check whether the driver could retake control, then take appropriate action if the driver is asleep.

The alternative to this kind of dedicated lane system is a mixed traffic system, in which automated and no automated vehicles would share the roadway. This approach requires more-extensive modifications to the highway infrastructure, but would provide the biggest payoff in terms of capacity increase.

System System System Diffusion degree Speed headway

keeping Collision avoidance & lane keeping

Automated highway

Successful lab tests 1990 1995 2000

system introduction 2000 2000 2010 Majority use by commercial vehicles

2010 2010 2025

Majority use by all automobiles 2020 2030 2045

Mandatory use by all road vehicles 2050 2065 -


3.2. Other projects - overview

3.2.1. Japanese

The trend toward developing automated highways seems to be strong in Japan and Europe. The Japanese government is working with Japanese auto-makers on the technology in the Advanced Cruise Assist Highway System Research Association, which organized automated-highway demonstrations in 1995 and 1996. The European Community is also participating in this type of research focusing initially on enhancing the mobility of freight. The Dutch Ministry of Transport, Public Works, and Water Management is working with Daimler-Benz, BMW, Fiat, Renault, and Volkswagen in the Automated Highway System European Analysis. 3.2.2. Dutch

The same Dutch ministry plus the Dutch Organization for Applied Scientific Research (TNO) and the European Union are sponsoring a demonstration of their Automated Vehicle Guidance (AVG) System in mid-June in Rijnwoude, the Netherlands. 3.2.3. Germany

European Community involvement in this technology is progressing under the Telematics for Transport, Fourth Stage Research Program. One effort is CHAUFFEUR, a wireless radio link between two trucks (provided by Daimler Benz and IVECO), only the first of which will be operated by a driver. The trucks will drive very close to each other at highway speeds, using video imaging to keep lanes as well as video registration and infrared signals to maintain a safe distance. This technology is the first step toward truck platooning. Another European Community-supported development project is its anticollision, autonomous-support, and safety-intervention system, which is an adaptive-cruise-control program involving Jaguar, Volvo, Renault, and Rover. 3.2.4. Italy

In addition, Urban Drive Control is an effort to enhance traffic flow in cities and reduce pollution. With this technology, road beacons are used to calculate the favorable speed to improve traffic mobility that is then recommended to drivers or imposed automatically. Fiat, PSA, Jaguar, and Renault are supporting this technology, which is being tested in Turin, Italy. 3.2.5. USA

Clearly, incremental steps will be needed to make any progress toward fully automated highways. ITS America's Bishop offered several possibilities for early introduction. An alternative would be "the huge private freight terminals at ports, where trucks move products to and from large storage areas." The idea is to convert incentive (high-mobility) lanes such as HOV (Eidhoven) (carpooling) lanes or the new alternative fueled vehicle lanes to semi-automated vehicle lanes.


4. Sensing the Environment A vehicle might use several approaches to sense its environment. To keep lanes, steer, and

find location, magnetometers might be used to sense magnets buried in the roadbed. Alternatively, visual sensors might monitor highway-marking tapes installed on the roadway, or intelligent video-imaging systems could track painted lane-boundary stripes. Obstacle detection and collision avoidance could be handled by millimeter-wavelength radar or infrared laser-ranging systems, or perhaps advanced video-imaging systems. Eventually, it is expected that [sensor] data-fusion techniques would be used on advanced vehicles to minimize the amount of sensor technology each car would have to carry. Accelerometers coupled to various actuators in a vehicle could manage steering, braking, and throttle systems to maintain its proper velocity and position. The choice of wireless communication system would depend on the type of automation. I guess that one key to developing suitable vehicles is the early adoption of an open-system architecture the framework within which individual information, services, and functions (such as traffic monitoring and emergency support) can be developed. Many systems have been developed for purposes of person transportation and some of modern passenger cars have so complex electronic system as a jet plain. In this chapter various system are distinguished:

Control unitACC radar

EHPS

EHPS motor with control electronics

Control electronics

Control unit

ABS - production moduleABS motors

& SensorsActive tachometers

Brake actuators

Bateries for EMB

Fig. 24 Chassis system

CAN class C

4.1. Chassis Systems

The demand for enhancement and the performance of vehicles has led to the implementation of modern vehicle control systems, such as anti-lock brake systems (ABS); active yaw control systems (AYC) and vehicle dynamic control systems (VDC) into vehicles.

4.1.1. Adaptive Cruise Control

1. ACC - Radar 2. Control Unit Technology: Adaptive speed control, Robust radar sensors, Distance control, Speed measurement, 77 GHz microwave circuit Benefits: Driving-support system for highest convenience, Enhanced safety


4.1.2. EPAS & EHPS

(Electric Power-Assisted Steering & Electric-Hydraulic Power Steering): 1. EPAS/EHPS Technology: EPAS: Electronic power steering for cars, Electronic steering aid with integrated electronics EHPS: Electronic power steering for heavy-duty vehicles: - Torque sensors - Power pack Benefits: Up to 5% lower fuel consumption, Low logistics costs, Low maintenance, Improved drive-ability, Shorter adaptation time, Flexible installation 4.1.3. Electromechanical Brakes (EMB):

1.Control Unit Technology: Multiprocessor system, Fail-safe architecture Benefits: High reliability, High flexibility: software solutions for all brake functions 2. Batteries for EMB Technology: Redundant energy concept: 2 batteries, Power management Benefits: High reliability, Automatic check function 3. Brake Actuators Technology: Brushless DC motor, integrated control unit Benefits: Maintenance-free, Easy to install , Wheel-selective control of brake force 4. Brake Pedal Unit Technology: Pneumatic-mechanical generation of pedal force, 3 redundant sensors Benefits: Free-adjustment pedal characteristics, Flexible ergonomics 4.1.4. ABS braking

1. ABS as production module Technology: Control electronics, relays, and valve coils in a single housing Benefits: Shorter production times 2. ABS Motors Technology: Precisely-defined interface, High-volume production Benefits: Optimal system integration, Flexibility


3. Sensors Technology: Active or inductive sensors Benefits: Variety of types, Compact size 4. Active Tachometer Technology: Differential Hall IC, Output signal used by ABS, driver information systems, or speedometer Benefits: Captures wheel speeds down to zero, Flexible installation geometry and system integration , Extremely accurate-even at low speeds


5. Communication - Multiplex wiring system 5.1. Introduction

The SAE Vehicle Network for Multiplexing and Data Communication has defined three classes of vehicle data communication network:

Class A - a potential multiplex system where vehicle-wiring system is reduced by the transmission and reception of multiple signals over the same signal bus between nodes.

Class B - a potential multiplex system where data are transferred between nodes to eliminate redundant sensors and other system elements. Nodes exist usually as stand-alone modules in conventionally wired vehicle.

Class C - a potential multiplex system where high data rate signals, typically associated with real time control systems, such as ABS, ESP or engine control are sent over the signal bus to facilitate distributed control and to further reduce vehicle wiring.

Control unitACC radar

EHPS

EHPS motor with control electronics

Control electronics

Control unit

ABS - production moduleABS motors

& SensorsActive tachometers

Brake actuators

Bateries for EMB

Fig. 25 CAN Networking in vehicle

CAN class C

Vehicle network messages are short (3-12 eight-bit byte) and consist of three parts


Chart of typical Vehicle Multiplexing Requirements Class A Class B Class C

Repetitive Allowed Yes Yes Bursty Yes Yes Yes Handshaking Yes Yes Yes Status Yes (Node) Yes Yes Acknowledgment Yes (in frame) No Beneficial Data consistency No No Beneficial Number of nodes ~100 10 to 30 10 to 30 Reliability Better Better Better Open system Truly Qualified Qualified Priority Latency <50 ms <20 ms <5 ms Oscillator % Allowed (20) 2.0 0.01 Wake-up time 10s 4 ms 4 ms Standby current <100 <15 mA <15 mA Gates/node <1000 <40k+ MPU <100k+ MPU

5.1.1. Encoding techniques

Pulse-Width Modulation (PWM) Variable Pulse-Width Modulation (VPWM) Standart 10 bit NRZ Bit-stuf NRZ L-Manchester (L-MAN) E-Manchester (E-MAN) Modified Frequency Modulation (MFM) 5.1.2. Physical layers

IdentifierField Data

FieldCRCField

ControlField

DLCRTR

0-64 15 1 1 1 7 341 11 1 2

Start of Frame

InterSpace Frame

End of Frame

Transmitter Receiver

Fig. 26 Frames of physical layer


5.1.3. Protocols

Protocol description:

A-BUS CAN SAE token slot TTP VAN

SAE class Class B & C

Class B & C Class C Class B & C

Affiliation VW ISO Bosch GM UNI Wien Proposed ISO Application Auto in-

vehicle Auto in-vehicle

Auto in-vehicle Auto in-vehicle Auto in-vehicle

Transm. Med. Single wire

Twist. pair/fib.opt.

Twist. pair/fib.o. Twist. pair/fib.o. Twisted pair

Bit encoding NRZ NRZ with bit-stuff.

NRZ with bit-stuff. MFM L-MAN,E-MAN

Media access Connection

Connection Token slot Time-triggered Connection

Error detection Bit only CRC CRC CRC CRC Data field length 2 bytes 0-8 bytes 0-256 bytes 2-8 bytes 0-8 bytes In-mess. ackn. Yes Yes Yes Max. bit-rate 0.5 Mbps 1 Mbps 2 Mbps 1 Mbps User definable Max. bus length 30m >40 30m 20m 20 Max. n. of nodes 32 >16 32 Not specified 16 Hardware avail. Yes Yes No No Yes

5.2. CAN architecture

The CAN protocol is an ISO standard (ISO 11898) for serial data communication. The protocol was developed aiming at automotive applications. Today CAN has gained widespread use and is used in industrial automation as well as in automotive and mobile machines. The CAN standard includes a physical layer and a data-link layer that defines a few different message types, arbitration rules for bus access and methods for fault detection and fault confinement 5.2.1. The CAN Protocol

The CAN protocol is defined by the ISO 11898 standard and can be summarized like this: • The physical layer uses differential transmission on a twisted pair wire. •A non-destructive bitwise arbitration is used to control access to the bus. • The messages are small (at most eight data bytes) and are protected by a checksum. • There is no explicit address in the messages, instead, each message carries a numeric value which controls its priority on the bus, and may also serve as an identification of the contents of the message. • An elaborate error handling scheme that results in retransmitted messages when they are not properly received. • There are effective means for isolating faults and removing faulty nodes from the bus. 5.2.2. Higher Layer Protocols (HLP)

The CAN protocol itself just specifies how small packets of data safely may be transported from point A to point B using a shared communications medium. It (quite naturally) contains nothing on topics such as flow control, transportation of data larger than can fit in a 8-byte message, node addresses, establishment of communication, etc. These topics are covered by a HLP (higher layer protocol). The term HLP is derived from the OSI model and its seven layers. Higher layer protocols are used in order to • Standardize startup procedures including bitrate setting


• Distribute addresses among participating nodes or kinds of messages • Determine the layout of the messages • Provide routines for error handling on system level 5.2.3. CAN Products

At the low level there are, in principle, two kinds of CAN products available on the open market, CAN chips and CAN development tools. At a higher layer another two kinds of products are relevant, CAN modules and CAN design tools. A wide variety of these are now available on the open market. 5.2.4. User Groups

One of the more efficient ways to increase your long-term performance within the CAN area, is to participate in the work carried out within a users' groups that works well. Even when you are not actively contributing to the work, the user's groups are in general good sources of information. Visiting conferences is another good way of getting comprehensive and relevant information. 5.2.5. Distributed Control Systems

The CAN protocol is a good basis when designing Distributed Control Systems. The CAN arbitration method ensures that each CAN node just has to deal with messages that are relevant for that node. A Distributed Control System can be described as a system where the processor capacity is distributed among all nodes in a system. The opposite can be described as a system with a central processor and local I/O-units. 5.2.6. Why choose CAN

Mature standard The CAN protocol has been around for a little more than ten years (since 1986). There are now a lot of CAN products and tools available on the open market. Hardware implementation of the protocol The CAN protocol is implemented in silicon. This makes it possible to combine the error handling and fault confinement facilities of CAN with a high transmission speed. The method used for distributing messages to the right receiver(s) contributes to gaining a good use of the available bandwidth. Simple transmission medium A common transmission medium is a twisted pair of wires. A CAN system can also work with just one wire. In some applications different kinds of links, opto-links or radio links, are better suited. Though there is a transmission hardware standard (twisted pair), it is not uncommon to use different transmission solutions depending on system requirements. Excellent error handling The error handling of CAN is one of the protocol's really strong advantages. The error detection mechanisms are extensive, and the fault confinement algorithms are well developed. The error handling and retransmission of the messages is done automatically by the CAN hardware. Fine fault confinement A faulty node within a system can ruin the transmission of a whole system, e.g. by occupying all the available bandwidth. The CAN protocol has a built in feature that prevents a faulty node from blocking the system. A faulty node is eventually excluded from further sending on the CAN bus.


Protocol This is a brief introduction to the CAN protocol. We do not claim completeness; if you want to know everything you should obtain the specification. The CAN bus The CAN bus is a broadcast type of bus. This means that all nodes can "hear" all transmissions. There is no way to send a message to just a specific node; all nodes will invariably pick up all traffic. The CAN hardware, however, provides local filtering so that each node may react only on the interesting messages. The bus uses Non-Return To Zero (NRZ) with bit stuffing. The modules are connected to the bus in a wired-and fashion: if just one node is driving the bus to a logical 0, then the whole bus is in that state regardless of the number of nodes transmitting a logical 1.


6. Davinci experimental model car 6.1. Motivation

The design of ground vehicles operating in automated mode in general is becoming an increasingly complex multi-disciplinary engineering task. To facilitate the realization of the big potential for control applications we are going to design and build a scaled experimental vehicle model. This all-electric vehicle would eventually be equipped with sensors, electric actuators, and real-time control and communication hardware and software, which would allow it to operate in automated mode. Electric actuators will be used for steering, propulsion and braking, as well as active suspension and roll control. On board digital computers control forces and moments generated by electric motors and actuators that greatly influence the dynamic motion of the vehicle. Furthermore, combined with intelligent sensors and on-board wireless communication hardware, these controllers and actuators will be able to operate the vehicle as part of an electronically connected convoy, in which multiple vehicles are combined in a formation to accomplish a task that can not be carried out by individual vehicles.

Analytical as well as physical tools are used to study and evaluate the dynamics of ground vehicles:

The analytic tools envelop classical dynamics, linear and nonlinear system theory, classical and modern control theory, stochastic control, and computer simulation tools. These analytic tools provide the designer with design formulas and equations that are then simulated on digital computers to provide the final design.

The physical tools may consist of Shakers, road simulators, scaled models of the vehicle and other devices that, using modern data acquisition and control computers, reproduces road effects. These tools provide an experimental evaluation of the final prototype design. Computer controlled instrumentation are an integral part of these tools and when integrated with simulation we have the so-called hardware in the loop simulation. The discussion of physical simulation tools, as important and insightful as these tools may be, is discussed in this capture. 6.2. Goals

6.2.1. Dynamics of Vehicle Rollover and Handling Analysis

-investigate the quasi-linear response of a car to a front wheel steering during obstacle avoidance maneuver. (We are going to subject this car a lane change test, slalom test and steady turn test) -investigate the effect of adding a rear steering system to the car. What effect does this strategy have on stability? Over steer? Under-steer? -investigate influence of a flexible payload and investigate the contribution of payload motion to the forces that may cause rollover 6.2.2. Dynamics of Anti-lock Braking Systems

-to study the effect of the two different strategies (ABS) on the stopping distance of the car -to design a control system that make the yaw rate of the vehicle equal to the rate of the nominal motion (VDC yaw rate control) 6.3. Description of vehicle

Actively controlled, remotely traced scaled lightweight prototype vehicle, which serve as an experimental platform for systems and control engineering research in Delft university project Davinci.

The final form of vehicle should be equipped: 4-wheel-independent drive-by-wire with one rotary electric motor at each wheel, 4-wheel-independent steer-by-wire with one linear electric actuator for each of the four wheels 4-wheel-independent brake-by-wire through the regenerative operation of the electric motor at each wheel


4-wheel-independent active suspensions with one linear electric actuator, actuated torsion bar or DAS roll over control system at each wheel. Each of the four wheels is driven through a chain-linked direct hookup by a Permanent Magnet

DC motor, which is in turn powered by a motor controller. Each of the four wheels is independently steered by a linear electric actuator of the ball-screw

type, which is in turn powered by a servo amplifier. The driver commands to the servo amplifiers for the steering and drive are provided by wire. The speed of each of the four wheels is measured through a sensor.

A built-in actuator characterizes this type of suspension. This actuator generates control forces

(calculated by a computer) to repress the above-mentioned roll and pitch motions. In addition the road holding has been improved because the dynamic behavior of the contact forces between tires and road has been controlled better, due to the absence of the low frequency resonance of the vehicle body (typically 1÷2 Hz). Locking the actuator in place as soon as it reaches its desired position, so that the batteries will not have to support the weight of the vehicle will reduce power consumption. In addition, these systems can improve the comfort considerably by the ability to control the vibrations of the sprung mass (vehicle body) in an active way. At the moment, hydraulically driven active suspension systems have been developed. These systems are only available on very few cars because they are costly (especially by using high response actuators) and have a high energy consumption.

To solve the problem of the high energy consumption a new active suspension system has been

invented at the Delft University of Technology that reduces the required energy level to a minimal amount. This new system is denoted by Delft Active Suspension (DAS) and has been developed towards a working prototype. The current prototype can be considered as an add-on system and is fully described and evaluated in the presentation Venhovens, P.J.Th., Knaap, A.C.M. van der, Delft Active Suspension (DAS), Background Theory and Physical Realization.

Actuator

Fig. 30 Active suspension system


However integration of DAS into existing suspension concepts results in a relatively simple and

compact practical realization. The essence of the invention is that the effective length of a mechanical lever with which a preloaded spring is connected to the wheel-axle can be adjusted by means of a servomotor. During this adjustment the length of the spring does not change (the spatial motion of the spring generates an imaginary cone), so the needed actuator force is very small. In this special manner, the desired control forces are generated in the wheel suspension with the major advantage that electric motors can be used for driving the system. This results in a more cost effective and simpler system than the currently available alternatives.

Third possibility is actuated torsion bar. The car has two electric active roll bars fitted, one per

axle, these are powered by a geared DC motor. Sensors control the moment they apply via the suspension and the front and rear are controlled individually.

The whole system is controlled by an on-board advanced system for real-time control system

(industrial-grade Pentium-II), which is equipped with A/D inputs, D/A outputs and digital encoder inputs and is running some real-time control software. Our experiments will be ideal for implementing and evaluating feedback strategies such as PID, LQG, fuzzy, neural nets, and adaptive and nonlinear controllers. Each module allows us to interchange components easily to attain maximum outcome.

All our experiments will be controlled via some Windows based real-time control software. This software should allow us to run and modify SIMULINK generated code in real-time or some other simulation software. This software could be executed on a standalone system or on a PC in a network. Power is provided by two 12V batteries, which are connected in series.

In addition, this prototype would have on-board transponders for communication with a base

station, as well as ranging sensors for measuring relative distance and orientation to other vehicles. The ranging sensors will enable experiments in autonomous operation, using the built-in

actuators to automatically activate the propulsion, braking, and steering subsystems of the vehicle. In fact autity will be a modeling level, this level of autonomy of vehicle determine the number of systems and sensors inside the car which are needed and define how must be equipped the environment.

Finally we could equipped this prototype with some navigation system (to install GPS on board)

and some ranging sensors. Low-power infrared laser and a couple of CCD chips to acquire a stereoscopic view. It could detect vehicle around it and also compute its distance from them.

DAS

Fig. 31 DAS suspension system


6.4. Davinci experimental car

This is a schematic of the research vehicle we could use to test our merging control strategies. Transducers feed data about the cars current state into an ECU. Using this information the car then calculates the optimal settings for steering actuators to give the optimum balance between ride comfort and vehicle handling.

6.5. Schematic of systems

Control architecture

Fig. 34 Control architecture of Davicar

Driverinterface

Integrated chassis controllerSteer, Suspension,Brake, Engine

Brakecontroller

Steering controller

DC motormanagement

CAN bus

Sensorinputs

Sensorinputs

Sensorinputs

Sensorinputs

Actuatorsoutputs

Actuatorsoutputs

Actuatorsoutputs

Actuatorsoutputs

VDC algoritmus serverECU

Adaptive cruise control

Roll over control


7. Logistic modeling of automated guided vehicles 7.1. Introduction

Freight transport by automated Guided Vehicles (AGVs) using dedicated infrastructure is becoming an important part for traditional transport in some highly populated and in industrialized areas. An example of such a project is the design of an underground freight transport system in the area of Amsterdam Airport Schiphol and flower auction Aalsmeer, which is designed to be operational in 2004. Automated Guided Vehicles The project of the underground freight transport in Schiphol is just one example of many initiatives for autonomous freight transport systems that are currently being studied. Because such a system needs to compete with traditional forms of transport, and because the cost of transportation and the value of the cargo are usually high, the demands for speed, flexibility, reliability, predictability, and safety are extremely high. 7.2. Structured integral logistic control

Today, flexibility, cooperation and scalibility have to be inherent qualities of a logistic control system because of the globalization of logistics, rapid changing markets and rise of new types of services and technologies. Therefore we are developing a general applicable, distributed, integrated coordination engineering system. The logistic concept used for this system is hierarchical and flexible. It consists of the following layers: customer interface inter-terminal logistics terminal logistics concurrent use of infrastructure vehicle control The system consists of three subsystems, SERVICES, TRACES and FORCES. In this project, the service control engineering system, called SERVICES, will be developed. SERVICES coordinates the services providing and interacts with the client. This will involve the translation of client orders into internal operation at micro level. 7.3. Basic model for vehicle control

The implementation of vehicle control is based on the TRACES (Transport Control Engineering System). In TRACES, vehicles are autonomous, and they find their way through the infrastructure on the basis of so-called scripts. Scripts are programs written in the TRACES control language that allow the AGV to drive along a path and to claim infrastructure whenever necessary. The infrastructure is divided into tracks. In the script, driving allowance for these tracks is given one by one. Figure 1 shows a Simple++ building block for a single-track level road-junction, without the possibility to turn. A single semaphore Sx, with threshold 1 (which means that a single ticket is available) is guarding the crossing. The physical dimensions of the crossing are at least half the width of an AGV

at both sides of the heart of the crossing. The ticket is claimed at such a time before entering the crossing that the vehicle can always stop whenever the semaphore cannot be claimed. This point in time is the called the “NEAR event”, and it is time-dependent. The ticket is returned when the vehicle’s rear exits the crossing. The blocks for the four scripts (for passing in a down-up, left-right, left-up, and down-right direction) are shown as well. The building block for a crossing can be used in a script of a higher-level domain or system. The connector triangles on all four sides of the block are used for this. For an example of a short script that uses the LR script of this building block, see figure 2. Please note that the

OLSScript

OLSScript

OLSScript

OLSScript

Sx

Infra Reset

LU DR

DU

XB

XD

CX

LRAX

Fig. xx Single track level crossroads


exact tracks that have to be followed to make a turn are not part of this building block: the attention is focused on the logical lay-out of the block, and not on the exact implementation of the tracks. In addition to these statements, the TRACES language has all the constructs of a generic programming language. The claiming process is implemented by using a specific type of semaphore, which allows vehicles to test, claim and free tickets for guarding the number of vehicles that are present in a domain or on a track or crossing at the same time. Vehicles only communicate with fixed ground stations for the semaphore claiming processes; they do not communicate with each other. A so-called script engine executes the script, which is actually a kind of computer program. The execution of the script is time-critical. Whenever a ticket cannot be obtained, the execution of the script halts, and as a result, the AGV may have to halt as well. One of the design parameters was how to guard the distance between AGVs. In train systems for instance, it is common to divide the infrastructure into fixed blocks in which only one train is allowed. In the implementation, the distance between AGVs has been based on a separate distance control, and not on the claiming of tickets for fixed blocks of infrastructure. Fixed blocks do not adapt to different speeds of the AGV (the lower the speed, the smaller the blocks can be), and the fixed concept usually leads to large spaces between succeeding AGVs. The question now becomes how to connect distance control and TRACES control to the vehicle control. For this, the concept of allowed

driving distance has been defined. Each time a "drive along track XYZ" command is being received by the vehicle control module, the driving route graph is extended, and the length of track XYZ is added to the possible driving distance. The allowed driving distance of the AGV is the minimum of the possible driving distance and the distance to the predecessor that follows the same route graph. The interrelation between the TRACES module, the distance control module, and the vehicle control module is shown in figure 3. To realistically simulate the interaction between the three modules, the vehicle behavior has to be modeled in a realistic way as well. When large numbers of vehicles crisscross in a complex infrastructure, acceleration and deceleration can have a profound effect on the performance of different scripts, because the allowed distance and the timing of events is largely dependent on the speed of the AGV. In most simulation languages, however, acceleration and deceleration can not be modeled at all, and an AGV halts immediately, and the simulation corrects for the deceleration time by halting the vehicle for some time. The same is done for accelerating: the vehicle waits for the acceleration time, and starts moving at top speed.

TRACES

Vehicle control:accelerationdeceleration

distance to predecessor

allowed distancefrom script

NEAR, PASSED events request ( distance)

Fig. XX distance vehicle control

Distance control


8. Literature Bakker, E., Pacejka, H.B., Lidner L., A new tire model with an application in vehicle dynamics Studies. SAE Paper 890097 (1989). Bauer, M., Tomizuka M., 1996, Fuzzy logic traction controllers and their effect on longitudinal vehicle platoon systems, Vehicle system dynamics, 25, 277-303. Crolla, D.A., 1996, Vehicle dynamics - theory into practice. Proc, IMechE, Part D, Journal of Automobile Engineering, Vol 210, No D2, pp 83-94. Crolla, D.A., 1997, Active suspension control - review of recent applications. In "Smart Vehicles" (ed. J.P. Paulwelussen and H.B. Pascejka), Swets and Zeitlinger, The Netherlands, 183-202. Ellis, J. R., Vehicle Handling Dynamics, 1993. Evers, J.J.M., Ottjes, J.A., Duinkerken, M.B., SMAGIC: Voertuiggeleiding als Systeem van Automaten. Document S-TRA/ALL-0006, TRAIL Research school, Delft, 1997 (in Dutch). Evers, J.J.M., Ottjes, J.A., Duinkerken, M.B., Lindeijer, D.G., New Logistics Control and Technical Automation: R&D Y- 2000, Delft University of Technology. Evers, J.J.M., Wielen van der G.J., Duinkerken, M.B., Ottjes, J.A., The jumbo container terminal: quay transport during ship loading, TRAIL Research school, Delft University of Technology. Fairley, R., Software Engineering Concepts, McGraw-Hill, 1985 (section 7.7). Garrott, R.W., Concepts in vehicle dynamics and simulation, Society of automotive Engineers, 1992. Garrott, R.W., Vehicle dynamics and simulation, Society of automotive Engineers, 1993. Gillespie, T.D., Fundamentals of Vehicle dynamics, Society of Automotive Engineers, 1992. Hessburg, T., Masayoshi Tomizuka, Fuzzy Logic Control for Lane Change Maneuvers in Lateral Vehicle Guidance University of California, Berkeley, October 1995. Hedrick, J.K., McMahon, D.H., Swaroop, D., Vehicle Modeling Control AHS, PATH/ITS University of California, Berkeley, November 1993. Hoover, S.V., Perry, R.F., Simulation: A Problem Solving Approach, Addison-Wesley, 1989. Johnson, E., Tires and handling, Society of Automotive Engineers Lugner, P., Horizontal Motion of Automobiles. Maciuca, D., Design, Modeling and Control of Steering and Braking for an Urban Electric Vehicle, Maurice, J.P., - Title: Short Wavelenght and Dynamic Tyre Behavior under Lateral and Combined Slip Conditions, 1999. Meihua Tai, Jeng-Yu Wang, Pushkar Hingwe, Chieh Chen, Masayoshi Tomizuka, Lateral Control of Heavy Duty Vehicles for Automated Highway Systems, University of California, Berkeley, February 1998. Mitschke, M., Dynamik der Kraftfahrzeuge, Bd. A Antrieb und Bremsung, 1982 (in German).


Mitschke, M., Dynamik der Kraftfahrzeuge, Bd. B Schwingungen Springer Verlag, Berlin, 1986. Mitschke, M., Dynamik der Kraftfahrzeuge, Bd. C Fahrverhalten Springer Verlag, Berlin, 1990. Pasterkamp, W.R., The Tyre as Sensor to Estimate Friction, Delft University Press, 1997. Pauwelussen, J.P., Vehicle performance - 1998. Pauwelussen, J.P., Truck tyres in use and testing methods European Tyre School. Pauwelussen, J.P., Modelling of the pneumatic tyre and its impact on vehicle behavior, European Tyre School. Polydoros, A., Dessouky, K., Pereira, J.M.N., Chung-ming Sun, Kuo-chun Lee, Papavassiliou, T.D., Li, V.O.K., Vehicle to Roadside Communications Study, PATH/ITS University of California, Berkeley, June 1993. Sampson, D.J.M., McKevitt, G., Cebon, D., The development of an active roll control system for heavy vehicles, 1999. Schielen, W.O., Dynamics of high - speed vehicles, 1982. Sheikholeslam, S., Desoer, Ch.A., Longitudinal Control of a Platoon of Vehicles I: Linear Model, PATH/ITS University of California, Berkeley, August 1989. Roppenecker, G., Wallentowitz, H., 1993, Integration of chassis and traction control systems, Vehicle system dynamics, 22, 283-296. Wallentowitz, H., 1997, Longitudinal control and interaction with other systems. In "Smart Vehicles" (ed. J.P. Paulwelussen and H.B.Pacejka), Swets and Zeitlinger, The Netherlands, 252-280. Tomizuka, M., Hedrick J., 1995, Advanced control methods for automotive applications, Vehicle system dynamics, 24, 449-468. El-Demerdash, S., Crolla D., 1996, Effect of non-linear components on the performance of hydropneumatic slow active suspension system. Proc IMechE Part D Journal of Automobile Engineering, 210(1). Narendran, V., Hedrick J., 1994, Autonomous lateral control of vehicles in an automated highway system, Vehicle system dynamics, 23, 307-324. Shladover, S., 1995, Review of the state of development of advanced vehicle control systems. Vehicle system dynamics 24,551-595. Vehicle dynamics and rollover propensity research, Society of automotive Engineers, 1992. Watkins, K.,Discrete Event Simulation in C., McGraw-Hill, 1993. Walrand, J., Hsu, I., Pei-Shan, Communication Requirements and Network Design for IVHS, PATH/ITS University of California, Berkeley, November 1993.

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