The Limited Integrator Model Regulator And its Use in Vehicle Steering Control

Unexpected yaw disturbances like braking on unilaterally icy road, side wind forces and tire rupture are very difficult to handle by the driver of a road vehicle, due to his/her large panic reaction period ranging between 0.5 to 2 seconds. Automatic driver assist systems provide counteracting yaw moments during this driver panic reaction period to maintain the stability of the yaw dynamics of the vehicle. An active steering based driver assist system that uses the model regulator control architecture is introduced and used here for yaw dynamics stabilization in such situations. The model regulator which is a special form of a two degree of freedom control architecture is introduced and explained in detail in a tutorial fashion whereby its integral action capability, among others, is also shown. An auxiliary steering actuation system is assumed and a limited integrator version of the model regulator based steering controller is developed in order not to saturate the auxiliary steering actuator. This low frequency limited integrator implementation also allows the driver to take care of low frequency steering and disturbance rejection tasks. Linear simulation results are used to demonstrate the effectiveness of the proposed method

The DRIVE-SAFE project: signal processing and advanced information technologies for improving driving prudence and accidents

In this paper, we will talk about the Drivesafe project whose aim is creating conditions for prudent driving on highways and roadways with the purposes of reducing accidents caused by driver behavior. To achieve these primary goals, critical data is being collected from multimodal sensors (such as cameras, microphones, and other sensors) to build a unique databank on driver behavior. We are developing system and technologies for analyzing the data and automatically determining potentially dangerous situations (such as driver fatigue, distraction, etc.). Based on the findings from these studies, we will propose systems for warning the drivers and taking other precautionary measures to avoid accidents once a dangerous situation is detected. In order to address these issues a national consortium has been formed including Automotive Research Center (OTAM), Koç University, Istanbul Technical University, Sabancı University, Ford A.S., Renault A.S., and Fiat A. Ş

Discrete-time Robust PD Controlled System with DOB/CDOB Compensation for High Speed Autonomous Vehicle Path Following

Autonomous vehicle path following performance is one of significant consideration. This paper presents discrete time design of robust PD controlled system with disturbance observer (DOB) and communication disturbance observer (CDOB) compensation to enhance autonomous vehicle path following performance. Although always implemented on digital devices, DOB and CDOB structure are usually designed in continuous time in the literature and also in our previous work. However, it requires high sampling rate for continuous-time design block diagram to automatically convert to corresponding discrete-time controller using rapid controller prototyping systems. In this paper, direct discrete time design is carried out. Digital PD feedback controller is designed based on the nominal plant using the proposed parameter space approach. Zero order hold method is applied to discretize the nominal plant, DOB and CDOB structure in continuous domain. Discrete time DOB is embedded into the steering to path following error loop for model regulation in the presence of uncertainty in vehicle parameters such as vehicle mass, vehicle speed and road-tire friction coefficient and rejecting external disturbance like crosswind force. On the other hand, time delay from CAN bus based sensor and actuator command interfaces results in degradation of system performance since large negative phase angles are added to the plant frequency response. Discrete time CDOB compensated control system can be used for time delay compensation where the accurate knowledge of delay time value is not necessary. A validated model of our lab Ford Fusion hybrid automated driving research vehicle is used for the simulation analysis while the vehicle is driving at high speed. Simulation results successfully demonstrate the improvement of autonomous vehicle path following performance with the proposed discrete time DOB and CDOB structure

Impact of Different Desired Velocity Profiles and Controller Gains on Convoy Driveability of Cooperative Adaptive Cruise Control Operated Platoons

As the development of autonomous vehicles rapidly advances, the use of convoying/platooning becomes a more widely explored technology option for saving fuel and increasing the efficiency of traffic. In cooperative adaptive cruise control (CACC), the vehicles in a convoy follow each other under adaptive cruise control (ACC) that is augmented by the sharing of preceding vehicle acceleration through the vehicle to vehicle communication in a feedforward control path. In general, the desired velocity optimization for vehicles in the convoy is based on fuel economy optimization, rather than driveability. This paper is a preliminary study on the impact of the desired velocity profile on the driveability characteristics of a convoy of vehicles and the controller gain impact on the driveability. A simple low-level longitudinal model of the vehicle has been used along with a PD type cruise controller and a generic spacing policy for ACC/CACC. The acceleration of the previous vehicle is available to the next vehicle as input, and the simulations are performed as Cooperative Adaptive Cruise Control of a convoy of vehicles. Individual vehicle acceleration profiles have been analyzed for driveability for two different velocity profiles that are followed in a stretch of 720 m between stop signs. The controller gains have been re-tuned based on the parameter space robust control PID approach for driveability and compared with the original gains. The US06 SFTP drive cycle has also been used for the comparison of the two different controller gain sets

Real time implementation of socially acceptable collision avoidance of a low speed autonomous shuttle using the elastic band method

This paper presents the real time implementation of socially acceptable collision avoidance using the elastic band method for low speed autonomous shuttles operating in high pedestrian density environments. The modeling and validation of the research autonomous vehicle used in the experimental implementation is presented first, followed by the details of the Hardware-In-the-Loop connected and autonomous vehicle simulator used. The socially acceptable collision avoidance algorithm is formulated using the elastic band method as an online, local path modification algorithm. Parameter space based robust feedback plus feedforward steering controller design is used. Model-in-the-loop, Hardware-In-the-Loop and road testing in a proving ground are used to demonstrate the effectiveness of the real time implementation of the elastic band based socially acceptable collision avoidance method of this paper

Dynamic Speed Harmonization

In the last decade, the accelerated advancements in manufacturing techniques and material science enabled the automotive industry to manufacture commercial vehicles at more affordable rates. This, however, brought about roadways having to accommodate an ever-increasing number of vehicles every day. However, some roadways, during specific hours of the day, had already been on the brink of reaching their capacity to withstand the number of vehicles travelling on them. Hence, overcrowded roadways create slow traffic, and sometimes, bottlenecks. In this paper, a Dynamic Speed Harmonization (DSH) algorithm that regulates the speed of a vehicle to prevent it from being affected by bottlenecks has been presented. First, co-simulations were run between MATLAB Simulink and CarSim to test different deceleration profiles. Then, Hardware-in-the-Loop (HIL) simulations were run with a Road Side Unit (RSU), which emulated a roadside detector that spotted bottlenecks and sent information to the Connected Vehicle about the position of the queue and the average speed of the vehicles at the queue. The DSH algorithm was also tested on a track to compare the performance of the different deceleration profiles in terms of ride comfort.Comment: 7 pages, 5 figure