Dezhao Zhang

An Adaptive Longitudinal Driving Assistance System Based on Driver Characteristics

A prototype of a longitudinal driving-assistance system, which is adaptive to driver behavior, is developed. Its functions include adaptive cruise control and forward collision warning/avoidance. The research data came from driver car-following tests in real traffic environments. Based on the data analysis, a driver model imitating the drivers operation is established to generate the desired throttle depression and braking pressure. Algorithms for collision warning and automatic braking activation are designed based on the drivers pedal deflection timing during approach (gap closing). A self-learning algorithm for driver characteristics is proposed based on the recursive least-square method with a forgetting factor. Using this algorithm, the parameters of the driver model can be identified from the data in the manual operation phase, and the identification result is applied during the automatic control phase in real time. A test bed with an electronic throttle and an electrohydraulic brake actuator is developed for system validation. The experimental results show that the self-learning algorithm is effective and that the system can, to some extent, adapt to individual characteristics.

Enhanced eco-driving system based on V2X communication

The concept of Eco-driving is proposed to reduce the fuel consumption of vehicles while maintaining dynamic performance. MPC controller has been introduced to achieve comprehensive goals including safety, fuel consumption and comfort of driving. Yet the information of the surrounded vehicles and road conditions have not been fully utilized. An enhanced algorithm taking the driving style of preceding vehicle, host vehicle drivers and road information into account is proposed in this paper. It is tested by the results of simulation that the controller becomes more flexible and can reduce the fuel consumption of the controlled vehicle in different working conditions with the help of the enhanced algorithm.

A curving ACC system with coordination control of longitudinal car-following and lateral stability

The paper presents a curving adaptive cruise control (ACC) system that is coordinated with a direct yaw-moment control (DYC) system and gives consideration to both longitudinal car-following capability and lateral stability on curved roads. A model including vehicle longitudinal and lateral dynamics is built first, which is as discrete as the predictive model of the system controller. Then, a cost function is determined to reflect the contradictions between vehicle longitudinal and lateral dynamics. Meanwhile, some I/O constraints are formulated with a driver permissible longitudinal car-following range and the road adhesion condition. After that, desired longitudinal acceleration and desired yaw moment are obtained by a linear matrix inequality based robust constrained state feedback method. Finally, driver-in-the-loop tests on a driving simulator are conducted and the results show that the developed control system provides significant benefits in weakening the impact of DYC on ACC longitudinal car-following capability while also improving lateral stability.

Multi-objective driving assistance system for intersection support

An intersection driving assistance system is developed, which focuses on improvement of traffic efficiency and driving comfort, while maintaining a high level of driving safety. The system can receive traffic light information through wireless communication, and assist the driver with driving support or warning information using received information on time-dependent traffic signal status. The paper describes the system structure, the implemented assistance strategy, which combines three main functions of passing support, violation warning and rear-end collision warning, and the system prototype that has been built. Field experiments show that the proposed assistance system and strategy can ensure a high level of traffic safety, while at the same time improving driving comfort and traffic efficiency at intersections.

Study on robustness and feasibility of MPC based vehicular Adaptive Cruise Control system

Model Predictive Control (MPC) framework is becoming more and more attractive in designing vehicular Adaptive Cruise Control (ACC) system. However, benefiting from its advantage, e.g. close-loop optimality, MPC algorithm must overcome some of its practical problems, among which low robustness to model mismatch and computing infeasibility of control law are most critical. Aiming at MPC based vehicular ACC algorithm, this paper studies its robustness and computing feasibility issues for the purpose of applying the algorithm into vehicle products. In order to enhance its robustness to model mismatch, feedback correction method is adopted to compensate the predictive error of vehicular following model and improve its predictive precision on the system state. Constraint management method is employed to revise the cost function and soften the I/O constraints of predictive optimization problem, avoiding the computing infeasibility of control law caused by larger tracking errors. Series of simulations with a commercial truck model indicate that the adopted methods can effectively solve the low robustness and computing infeasibility problems of vehicular MO-ACC algorithm, laying a foundation for its implementation on vehicle products.

Double-Mode vehicular Electronic Throttle for driver assistance systems

Normally used electronic assistant throttle actuators for R&D of vehicle longitudinal driver assistance systems, such as ACC, may conflict with cars primary throttle system and have inconvenience in switch between ACC control and driver operating. In order to overcome the disadvantages abovementioned, this paper addresses the design, control and experiments of a Double-Mode Electronic Throttle (DMET) which can be operated by ACC and driver synchronously. First, based on the existing electronic throttle system the structure of the DMET is designed. Then, focusing on the time delay of the DMET, a gain-adaptive Smith predictor based on a identified transfer function is set to get better system dynamic performance. Furthermore, in order to achieve seamless switch between ACC control mode and driver operating mode, a dead zone restriction is introduced to the controller. Finally, the system performance in tracking ACC desired throttle angle and switching between two operating modes is confirmed by series of experiments.

Pneumatic electronic braking assistance system using high-speed valves

In order to satisfy the request of the driving assistance systems (DAS) for heavy duty vehicles, a high-speed valves based pneumatic electronic braking assistance system (PEBAS) is developed. A novel configuration of PEBAS is designed and its mathematical model is built by analyzing the operation of the air-flow inside the high-speed valve. Based on the model, a PWM (pulse width modulation) method is used to control the high-speed valves and its duty cycle is adjusted by a PI controller in order to track the desired braking pressure. The controller is optimized according to test results of the high-speed valves. Then, an HIL (Hardware in-the-Loop) platform is built to validate the performance of the system. Experiments show that the control error of the developed PEBAS is less than 5%.