CHAPTER I
INTRODUCTION
1.1 Background of Project
The cars of tomorrow [8] will be more and more equipped with Advanced Driver Assistance Systems ADAS to support the driver in the driving task. One of
the ADAS is the Adaptive Cruise Control ACC. Pauwelussen and Minderhoud in [8] noted that the ACC could be defined as an extension of the Cruise Control CC
and maintains, next to a certain set speed, a certain set distance with respect to the lead vehicle.
The conventional CC only has control over the engine, which means that it cannot switch gears and it cannot break. This means that it is only used on roads
where the velocity of the car is somewhat constant, for example on highways. The driver cannot relax too much though, since the CC does not care about vehicles in
front. This is what the ACC is trying to solve.
The ACC takes both a desired maximum velocity and a desired minimum distance as input values from the driver. As long as no vehicle in front is closer than
the desired distance, the ACC functions exactly as a CC. If a vehicle in front comes closer than the desired minimum distance the ACC will adapt the velocity to follow
the vehicle. In order to keep this set distance, the ACC is able to accelerate and decelerate the vehicle. The acceleration and deceleration of the system is limited,
2 because of comfort reasons and by law [8]. This means that the driver has to
intervene if the system is not able to achieve the required needs [8]. Ideally, the driver only has to control the steering and only interrupt the ACC at takeovers or
situations that might lead to accidents [9].
The ACC is mainly a comfort system that takes over the car-following task, but the driver remains responsible for steering and collision avoidance. If the
deceleration of the ACC is not sufficient enough to avoid a collision, the ACC warns the driver with a warning sound [8]. This system is usually used on the highway,
where it is common to cruise at a constant velocity for long periods of time, as a relief for the driver [9].
These system [11], use radar to measure the distance from the vehicle they are in to the car ahead and its speed relative to theirs. If a car crosses into the lane
ahead, and the distance is now less than the preset minimum, the system applies the brakes, slowing the car with a maximum deceleration until it is following at the
desired distance [11]. If the leading car speeds up or moves out of the lane, the system opens the throttle until the trailing car has returned to the cruise control speed
set by the driver [11].
The advanced features of ACC systems include the ability to track a car in the lane ahead using forward looking radar. If the distance to a vehicle in front is below
a pre-set value, the ACC system is designed to slow the car down, using brakes if required, to track the speed of the vehicle in front, then returning the car to its pre-set
speed once the lane ahead is clear. Next, an intelligent lane prediction using steering angle and yaw rate sensors predict curves in the road, and to ensure that any vehicle
ahead being tracked is in the same lane as the car itself.
One of the potential advantages of ACC is the foundation that it provides for next generation advancements in collision avoidance systems that are expected to
include radar and cameras. ACC is also anticipated to be beneficial in cities and towns with heavy urban stop-and-go traffic by functioning at low stopstart speeds in
city traffic. It is expected to have the ability to stop the car completely when sitting
3 in traffic, re-starting and following the car in front when the traffic begins to move
again. Potential Key benefits of ACC are reduction in accident rate for vehicles fitted with collision avoidance type systems, reduction in driver fatigue and increase
in fuel efficiency due to very gradual speed increase decrease in traffic.
The controller developed for ACC consists of PID controller and Stateflow. The PID controller is a closed loop controller; designed to make the throttle decisions
control. The controller is created using parameters to allow easy modification tuning of the operation of the controller. This controller also included the
Stateflow chart that is used to address design challenges that often occur when developing and implementing embedded software.
Matlab is the main software used for computation, model implementation, and simulation. The Matlab simulation tool Simulink, which is used for modeling
and simulating dynamic systems, has been playing a major role during this work [12].
MATLABSimulink is a high- level technical computing language and object orientated environment for algorithm development, data visualization, data analysis,
and numerical computation. MATLABSimulink allows the development of a solution to technical computing problems faster than with traditional programming
languages, such as C, C++, and Fortran. The easy of development along with the extensive toolboxes and functions available were the major reasons for selecting
MATLABSimulink as the simulation environment.
The simulation environment starts as an overview of the implementation of the PID controller to the CC model. Next, the second model about the ACC model
incorporates the high- level system blocks representing, the signal input, vehicle dynamics, distance and velocity controller will be designed to get the performances
of the proposed controller.
The goals for the simulation environment were to be able to create the test cases based on 10 high- level requirements. To ensure that the controllers meet those
4 requirements, we need to build test cases that check the design against each
requirement. The simulation environment is flexible and if someone is interested in testing out another ACC algorithm, the controller is a single function that can be
replaced easily.
Simulink software models, simulates, and analyzes dynamic systems. It enables user to pose a question about a system, model the system, and see what
happens. With Simulink, we can easily build models from scratch, or modify existing models to meet our needs. Simulink supports linear and nonlinear systems,
modeled in continuous time, sampled time, or a hybrid of the two systems can also be multirate-having different parts that are sampled or updated at different rates.
1.2 Objectives of Project
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