Jau-Woei Perng

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.

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.

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

Limit cycle analysis of nonlinear sampled-data systems by gain-phase margin approach

This work analyzes the limit cycle phenomena of nonlinear sampled-data systems by applying the methods of gain–phase margin testing, the M-locus and the parameter plane. First, a sampled-data control system with nonlinear elements is linearized by the classical method of describing functions. The stability of the equivalent linearized system is then analyzed using the stability equations and the parameter plane method, with adjustable parameters. After the gain–phase margin tester has been added to the forward open-loop system, exactly how the gain–phase margin and the characteristics of the limit cycle are related can be elicited by determining the intersections of the M-locus and the constant gain and phase boundaries. A concise method is presented to solve this problem. The minimum gain–phase margin of the nonlinear sampled-data system at which a limit cycle can occur is investigated. This work indicates that the procedure can be easily extended to analyze the limit cycles of a sampled-data system from a continuous-data system cases considered in the literature. Finally, a sampled-data system with multiple nonlinearities is illustrated to verify the validity of the procedure.

Multi-sensor information integration on DSP platform for vehicle navigation safety and driving aid

Intelligent transportation systems (ITS) are the mainstream of the development of next-generation technologies. The project of Human-centered technology (HT)-ITS in Taiwan has launched R&D researches in driver assistance and safety warning systems. This paper demonstrates a part result that a multi-sensors integrated system to achieve the purpose of the vehicle navigation and safety warning assistance. Multi-sensors including a global position system (GPS), a laser range finder, and an inertia measurement unit (IMU), are equipped on the vehicle to realize the manipulation of collision warning (CW), dead-reckoning (DR), and the operation of comfort-meter. The maneuver of CW is developed based on the idea that warning or potential crash information generally can be graded such that the driver need not react to a discrete on/off alarm. DR is responsible to estimate the vehicle location and trajectory when GPS floats. The purpose of the comfort-meter is to examine whether the vehicle driving does conform to the comfortable standard or not. The current states of the vehicle will also be transmitted to the far-end monitoring center, and shown in the graphical user interface through wireless transmission in order to monitor the vehicle driving status. The processing unit is realized on an embedded platform, as well as these functions are verified on real-road testing.

GPS navigation based autonomous driving system design for intelligent vehicles

The main objective of this paper is to design and implement a real-time autonomous navigation system for intelligent vehicles by integrating a real-time kinematics differential global position system (RTK-DGPS) and a laser range finder. Firstly, a fuzzy logic algorithm for target position tracking is proposed to achieve the human driving concept. In addition, an actuator is equipped in the experimental vehicle TAIWAN iTS-1 so that the steering wheel can be controlled to let the vehicle follows a desired trajectory in digital maps. A laser range finder is used to detect obstacles in front of the vehicle for warning announcement and collision avoidance. A human machine interface is also built up to provide information from sensors. The performance and accuracy of the proposed system is verified by real-time experimental results.

The design of an intelligent real‐time autonomous vehicle, TAIWAN iTS‐1

Abstract Developed at National Chiao Tung University, TAIWAN iTS‐1 is the first smart car with active safety systems and comfortable autonomous driving in Taiwan. An adaptive vision‐based lane detection algorithm was proposed to help the lateral control unit to keep the car in its lane safely. It also carries a DSP system to generate warning signals for unintentional roadway departures. A laser radar measures the distance between the preceding car and TAIWAN iTS‐1. With this information, the longitudinal control unit performs intelligent cruise control and stop‐and‐go functions. The remote control function is realized on TAIWAN iTS‐1 for safety testing and military applications. Unlike most smart car studies, this paper considers not only driving safety demands but also non‐driving security. An active mobile surveillance system will inform the car owner when the car is illegally broken into, anytime and anywhere. For drivers and passengers, the perception of comfort is achieved by intelligent vehicle dynamic control. All functions integrated into TAIWAN iTS‐1 have been tested repeatedly on National Highway 3 and Expressway 68 in the Hsinchu area and the systems robustness has been successfully demonstrated in these real‐road experiments.

Limit cycle analysis of PID controller design

The main purpose of this paper is to predict limit cycles of nonlinear PID control systems with adjustable parameters by the approaches of stability equation, describing function and parameter plane. First, nonlinear elements are linearized by the classical describing function method. The stability of equivalent linearized system with adjustable parameters is then analyzed by using the stability equations and the parameter plane method. According to our study, the characteristics of limit cycles with PID control design in current literature can be improved. Finally, this approach is also extended to a sampled-data control system with broken line nonlinearity.

The design and implementation of a vision-based people counting system in buses

This system counts passengers through a single camera that is fixed at an overhead (zenithal) position. The proposed algorithm is designed to solve the problem of illumination, which can occur when the bus door opens or closes. A processing ratio of about 30 frames/s is necessary to overcome the extreme change in illumination. The system combines global positioning system data and standard time to establish the number of passengers at each bus stop at different periods of time and calculates the number of passengers and unoccupied seats to provide business-related information.