This paper presents a method for trajectory generation using convex optimization to find a feasible, obstacle-free path for a road vehicle. Consideration of vehicle rotation is shown to be necessary if the trajectory is to avoid obstacles specified in a fixed Earth axis system. The paper establishes that, despite the presence of significant non-linearities, it is possible to articulate the obstacle avoidance problem in a tractable convex form using multiple optimization passes. Finally, it is shown by simulation that an optimal trajectory that accounts for the vehicle's changing velocity throughout the manoeuvre is superior to a previous analytical method that assumes constant speed.

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Trajectory generation for road vehicle obstacle avoidance using convex optimization

As roads become busier and automotive technology improves, there is considerable potential for driver assistance systems to improve the safety of road users. Longitudinal collision warning and collision avoidance systems are starting to appear on production cars to assist drivers when required to stop in an emergency. Many luxury cars are also equipped with stability augmentation systems that prevent the car from spinning out of control during aggressive lateral manoeuvres. Combining these
concepts, there is a natural progression to systems that could assist in aiding or performing lateral collision avoidance manoeuvres. 

A successful automatic lateral collision avoidance system would require convergent development of many fields of technology, from sensors and instrumentation to aid environmental awareness through to improvements in driver vehicle interfaces so that a degree of control can be smoothly and safely transferred between the driver and vehicle computer. A fundamental requirement of any
collision avoidance system is determination of a feasible path that avoids obstacles and a means of causing the vehicle to follow that trajectory.

This research focuses on feasible trajectory generation and
development of an automatic obstacle avoidance controller that integrates steering and braking action.

A controller is developed to cause a specially modified car (a Mercedes `S' class with steer-by-wire and brake-by-wire
capability) to perform an ISO 3888-2 emergency obstacle avoidance manoeuvre.

A nonlinear two-track vehicle model is developed and used to
derive optimal controller parameters using a series of simulations. Feedforward and feedback control is used to track a feasible reference trajectory. The feedforward control loops use inverse models of the vehicle dynamics. The feedback control loops are implemented as linear proportional controllers with a force allocation matrix used to apportion braking effort between redundant actuators.

Two trajectory generation routines are developed: a geometric method, for steering a vehicle at its physical limits; and an optimal method, which integrates steering and braking action to make full use of available traction. The optimal trajectory is obtained using a multi-stage convex optimisation procedure.

The overall controller performance is validated by simulation using a complex proprietary model of the vehicle that is reported to have been validated and calibrated against experimental data over several years of use in an industrial environment.

Development of a vehicle dynamics controller for obstacle avoidance

Lane-change is stressful operation for driver, especially when closing to the complex intersection. Accurate analysis the factor that relate to aggressive lane-change is foundation of any future driving safety research. Tracker was using for analyzing aggressive lane-changing behavior that based on amount of naturalistic on-road experiment using an UAV. Over two thousand lane-change video pieces have been recorded, then the selected features are extracted in to matrix. Also, the anonymous drivers and vehicle information is obtained according to license plates. Based on an advanced DBN deep learning algorithm, a relation model of lane-change behavior is constructed by considering the potential influence factors, including vehicle information, driver information, and the driving behavior. Finally, the accuracy of proposed model is validated by comparing to other common models, which approves our model’s superior accuracy, feasibility and concreteness.

Aggressive Lane-change Analysis Closing to Intersection Based on UAV Video and Deep Learning

Trends show that on board vehicle technology is becoming increasingly complex and that
this will continue to be the case. This complexity has enabled both driver assistance systems
and fully automatic systems to be introduced. Driver assistance systems include anti-lock
braking and yaw rate control, and these diﬀer from fully automatic systems which include
collision avoidance systems, where control of the car may be taken away from the driver.
With this distinct diﬀerence in mind, this work will focus on driver assist based systems,
where emerging technology has created an opportunity to try and improve upon the systems
which are currently available.
This work investigates the ability to simultaneously control a set of two lateral dynamics
using primarily the longitudinal wheels forces. This approach will then be integrated with
front wheel steering control to assess if any beneﬁts can be obtained.
To aid this work, three diﬀerent vehicle models are available. A linear model is derived for
the controller design stage, and a highly nonlinear validated model from an industrial partner
is available for simulation and evaluation purposes. A third model, which is also nonlinear,
is used to integrate the control structures with a human interface test rig in a Hardware in
the Loop (HiL) environment, which operates in real-time.
Frequency based analysis and design techniques are used for the feedback controller design,
and a feedforward based approach is used to apply a steering angle to the vehicle model.
Computer simulations are initially used to evaluate the controllers, followed by evaluation via
a HiL setup using a test rig. Using a visualisation environment in Matlab, this interface device
allows driver interaction with the controllers to be analysed. It also enables driver reaction
without any controllers present to be compared directly with the controller performance
whilst completing the test manoeuvres.
Results show that during certain manoeuvres, large variations in vehicle velocity are
required to complete the control objective. However, it can be concluded from both the
computer simulation and HiL results that simultaneous control of the lateral dynamics, based
on the longitudinal wheel forces can be achieved using linear control methods.

Control of vehicle lateral dynamics based on longitudinal wheel forces

This paper presents studies on differential braking-based Lane Departure Assistance System (LDAS). The dynamic threshold of Time to Lane Crossing (TLC), determined by vehicle heading error, speed, road adhesion and reaction time of human-machine system, is studied to activate driving assistance. Based on 2-DOF reference vehicle model and driver preview model, the desired yaw rate to avoid lane departure is calculated. To avoid loss of lateral stability during braking, strategies for the distribution of braking force are developed based on balanced longitudinal slip ratio, which aim to limit the slip ratio on all wheels. The Hardware in Loop (HIL) test bench is established to evaluate the rapid prototyping of LDAS. Results show that the proposed methods can confine the vehicle in lane effectively with lateral stability maintained and operate robustly, benefiting from timely assistance, model-independent control algorithm, and small and balanced slip ratio.

Lane departure assistance based on balanced longitudinal slip ratio differential braking control

A comparison is made between two vehicle control strategies for two different manoeuvres: a gentle and aggressive lane-change. Simulation results demonstrate that the choice of control objectives and selection of appropriate design approximations have a significant impact on the performance of the controller under these different manoeuvre conditions. A lateral control design trade-off between passenger comfort and collision avoidance capability is evident.

S.J. O'Neill

Papers

Performance comparison of collision avoidance controller designs