Hsin-Han Chiang

The Heterogeneous Systems Integration Design and Implementation for Lane Keeping on a Vehicle

In this paper, an intelligent automated lane-keeping system is proposed and implemented on our vehicle platform, i.e., TAIWAN i TS-1. This system challenges the online integrating heterogeneous systems such as a real-time vision system, a lateral controller, in-vehicle sensors, and a steering wheel actuating motor. The implemented vision system detects the lane markings ahead of the vehicle, regardless of the varieties in road appearance, and determines the desired trajectory based on the relative positions of the vehicle with respect to the center of the road. To achieve more humanlike driving behavior such as smooth turning, particularly at high levels of speed, a fuzzy gain scheduling (FGS) strategy is introduced to compensate for the feedback controller for appropriately adapting to the SW command. Instead of manual tuning by trial and error, the methodology of FGS is designed to ensure that the closed-loop system can satisfy the crossover model principle. The proposed integrated system is examined on the standard testing road at the Automotive Research and Testing Center (ARTC)1 and extra-urban highways.

The automated lane-keeping design for an intelligent vehicle

In this paper, a vision-based lane-keeping automated steering system is proposed and is successfully verified in our vehicle platform, TAIWAN iTS-1. The proposed steering system can achieve the accurate detection of the complicated road environment information; and more, the closed-loop automated lane-keeping steering system with virtual look-ahead is stable under varying speed operation. Furthermore, to achieve more manlike driving behavior such as smooth tuning, a fuzzy gain schedule technology is proposed to concern with lateral offset and instant-speed of the vehicle, and hence, to compensate the feedback controller for adapting to the steering wheel command appropriately. The proposed steering system is demonstrated via TAIWAN iTS-1 on the standard testing road in automotive research and testing center (ARTC) and highway road.

Elucidating Vehicle Lateral Dynamics Using a Bifurcation Analysis

Issues of stability and bifurcation phenomena in vehicle lateral dynamics are presented. Based on the assumption of constant driving speed, a second-order nonlinear lateral dynamics model is obtained. Local stability and existence conditions for saddle-node bifurcation appearing in vehicle dynamics with respect to the variations in front wheel steering angle are then derived via system linearization and local bifurcation analysis. Bifurcation phenomena occurring in vehicle lateral dynamics might result in spin and/or system instability. A perturbation method is employed to solve for an approximation of system equilibrium near the zero value of the front wheel steering angle, which reveals the relationship between sideslip angle and the applied front wheel angle. Numerical simulations from an example model demonstrate the theoretical results

The Human-in-the-Loop Design Approach to the Longitudinal Automation System for an Intelligent Vehicle

This paper presents a safe and comfortable longitudinal automation system which incorporates human-in-the-loop technology. The proposed system has a hierarchical structure that consists of an adaptive detection area, a supervisory control, and a regulation control. The adaptive detection area routes the information from on-board sensors to ensure the detection of vehicles ahead, particularly when driving on curves. Based on the recognized target distance from the adaptive detection area, the supervisory control determines the desired velocity for the vehicle to maintain safety and smooth operation in different modes. The regulation control utilizes a soft-computing technique and drives the throttle to execute the commanded velocity from the supervisory control. The feasible detection range is within 45 m, and the high velocity for the system operation is up to 100 km/h. The throttle automation under low velocity at 10-30 km/h can also be well managed by the regulation control. Numerous experimental tests in a real traffic environment exhibit the systems validity and achievement in the desired level of comfort through the evaluation of international standard ISO 2631-1.

A Vision-Based Driver Nighttime Assistance and Surveillance System Based on Intelligent Image Sensing Techniques and a Heterogamous Dual-Core Embedded System Architecture

This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system framework on an embedded heterogamous dual-core platform. Therefore, this study develops and implements computer vision and sensing techniques of nighttime vehicle detection, collision warning determination, and traffic event recording. The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle. These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform. Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system.

Optimized Adaptive Motion Control Through an SoPC Implementation for Linear Induction Motor Drives

This paper proposes an optimized adaptive tracking control for a linear induction motor (LIM) drive taking into account the unknown end effects, payload, and uncertainties including the friction force. The dynamic model of a field-oriented LIM drive with the primary end effect is first investigated. On the basis of the backstepping control design, a sliding mode controller embedded with a practical fuzzy compensator is developed to confront the lumped uncertainties of the LIM drive. Moreover, to overcome the obstacle of the unknown bound of the lumped uncertainties in the overall system, an adaptive mechanism based on the sense of the Lyapunov stability theorem is derived to online adjust the fuzzy compensation gains. Moreover, to achieve the robust tracking performance in the presence of the difficulty arisen from the LIM drive accompanied with uncertain nonlinearities and/or external disturbances, the soft-computing technique is adopted for optimizing the designed controller parameters. A system-on-programmable-chip is employed to implement the developed system for the reason of raising the benefits of fast-prototyping and high-performance in industrial applications. The high performance of the proposed control scheme is validated through comparative experimental results.

Longitudinal and Lateral Fuzzy Control Systems Design for Intelligent Vehicles

In this paper, the longitudinal and lateral fuzzy control vehicle systems are considered separately due to the decoupling under the assumption of small varying velocity and steering angle. Firstly, the problem of longitudinal control system design is to concentrate on the car-following strategy and the single-input fuzzy logic controller (SFLC) is adopted here to achieve a safety-distance keeping between the preceding and following vehicles with the same velocity and acceleration. Besides, the pole-placement technique with proposed fuzzy gain scheduling (FGS) and observer design are developed to improve the lateral control of vehicles. The kernel of FGS is the inference rule base which provides a natural environment to incorporate engineering judgment and human knowledge for vehicle steering controller. Moreover, FGS can also be anticipated to handle the substantial nonlinearities in vehicle dynamics, the tire characteristics or asymmetry in mechanism. Finally, the simulation results show the efficiency of our approach

Embedded Driver-Assistance System Using Multiple Sensors for Safe Overtaking Maneuver

Advanced driver-assistance systems have recently become one of the most active topics related to intelligent vehicles. Such assistance facilitates vehicular operation by allowing drivers increased control and an enhanced driving experience, and it even comes in the form of automated assistance for autonomous vehicle operation. This paper presents a driver-assistance system that uses a low-cost embedded digital signal processor, with the overall system installed in a commercial vehicle. Based on driving information supplied by multiple sensors, such as a real-time vision system, a vehicle-to-vehicle communication system, and in-vehicle sensors, the proposed system can facilitate decision making and the performing of driving tasks while executing overtaking maneuvers. This paper developed a data fusion stage based on a collision warning algorithm in which the overtaken vehicle and other vehicles in the neighboring lane are accounted for to avoid collisions. The system employs fuzzy control in the steering and speed automation to emulate the driving tasks performed by humans. The applicability of the proposed system was examined in a real-road environment, and a set of experimental results demonstrate the feasibility of using the involved coordination strategies while conducting various driving maneuvers.

An Intelligent Knowledge-Based and Customizable Home Care System Framework with Ubiquitous Patient Monitoring and Alerting Techniques

This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

A bifurcation study of vehicle's steering dynamics

Issues of stability and bifurcation phenomena in vehicles steering dynamics are presented. Based on the assumption of constant driving speed, a second order nonlinear lateral dynamical model is obtained. Local stability and existence conditions for saddle node bifurcation appearing in vehicle dynamics with respect to the variation of the front wheel steering angle are then derived via system linearization and local bifurcation analysis. Bifurcation phenomena occurring in nonlinear vehicle lateral dynamics might result in spin and/or system instability. Perturbation method is employed to solve for an approximation of system equilibrium near the zero value of the front wheel steering angle, which reveals the relationship between sideslip angle and the applied front wheel angle. Numerical study of a simple example verifies the theoretical analysis.