Vehicle Adaptive Cruise Control And The Corresponding Macroscopic Traffic Flow Model

As an advanced Driver Assistant System (DAS), Adaptive Cruise Control (ACC) system is designed to release human drivers'mental load, reduce the car accidents, increase the driving comfort, decrease the fuel consumption and improve the traffic flow. In recent years, ACC system has received considerable attention from government, automobile companies, and research institutions.In the control module of ACC system, spacing policy and the control algorithm are the key factors to achieve system function and its real application, so they directly determine the dynamical responses of ACC systems. Establishing the macroscopic traffic flow model of ACC-equipped vehicles is not only beneficial to analyze the macroscopic dynamical characteristics of ACC flow, reflect the improvement of ACC system to the traffic flow, but also provides theoretical support for traffic management and control. This dissertation takes ACC system as the research object, investigate the spacing policy, the upper level control algorithm which aims at the longitudinal dynamics of inter-vehicle, the integrated control design including the longitudinal dynamics of inter-vehicle and the switch performance of throttle and brake, and the macroscopic traffic flow model of ACC flow, respectively. The main contributions of this dissertation are presented as follows:(1) A variable time headway policy which considers the velocity tendency of preceding vehicle is proposed, and the corresponding stability of spacing error is proved. By introducing the acceleration disturbance of preceding vehicle, the ability regarding forward-looking and anti-disturbance of spacing control is improved. Moreover, the introduction of saturation function makes time headway more reasonable and meanwhile improves the capacity of traffic flow. Compared to the traditional spacing policies, the proposed one can adapt the complex traffic scenarios, effectively balance the safety and car-following, and improve the dynamical performance of spacing control.(2) A multi-objectives upper level controller of ACC is proposed in MPC (Model Predictive Control) framework, which can satisfy safety, car-following, driving comfort and fuel efficiency. First, a high order state model which describes the longitudinal dynamics of inter-vehicle is established. Based on this model, the control objectives of ACC system are analyzed and transformed to the performance index and system constraints, respectively. Then the control algorithm is designed in MPC framework to satisfy these multi-objectives and constraints. It is shown that the proposed ACC upper-level control algorithm not only meets the safety and car-following requirements, but also outperforms the traditional algorithms by improving driving comfort and reducing fuel consumption.(3) A two-mode upper level controller of ACC in MPC framework is designed based on humans'driving habits. By analyzing the real microscopic traffic data from NGSIM, the control algorithm is designed to consist of steady following mode, fast approaching mode and fuzzy switch logic. Steady following mode is activated when the inter-distance falls round the desired value. The control algorithm proposed in (2) is utilized for this mode, with the purpose of following the preceding vehicle safely and steadily. Once the inter-distance becomes larger than the desired value, ACC vehicle switches to the fast approaching mode, which employs a time-optimal MPC algorithm. Then the controller design is transformed to be an online Mixed Integer NonLinear Programming (MINLP), which is solved by a nested two-loop algorithm based on Particle Swarm Optimization (PSO). In order to imitate human drivers' decision-making, the switching strategy between the two control modes is developed based on fuzzy inference It is shown that this two-mode upper level ACC algorithm can satisfy the multi-objectives of vehicle traveling, choose different control modes according to the current traffic condition, and therefore effectively reflect the humans'driving habits and increase the usage of ACC system.(4) An integrated control structure is proposed, which synthesizes the longitudinal dynamics of inter-vehicie with the mechanical characteristics of throttle and brake. Moreover, an integrated ACC algorithm with optimal switching between throttle and brake is designed in this control structure. First, the binary integer variables and logic constraints arc introduced to synthesize the dynamics of throttle and brake into one model framework, and then it is combined with the longitudinal dynamics of inter-vehicle, which leads to an integrated ACC model. Based on this integrated ACC model, the control algorithm is designed to satisfy not only safety, car-following, driving comfort and fuel efficiency, but also the optimal switching performance (the switching sequence and the control input of actuator) between throttle and brake. Therefore, the controller design is transformed to be an online MINLP, and it can be solved by the nested two-loop algorithm based on PSO, which is proposed in (3) mentioned above. Compared to the tradition threshold switching algorithm, this control algorithm can not only satisfy the multi-objectives of vehicle traveling, but also effectively reduce the switching between throttle and brake, avoid the mechanism abrasion caused by frequent switching between different actuators, and improve the dynamics of control input of actuators.(5) A macroscopic traffic flow model of ACC-equiiped vehicles is established. By synthesizing the ACC control algorithm and the principles of traffic flow, this macroscopic ACC model truly reflect the stability features and dynamical evolution laws of ACC flow, and effectively reveal the transmission characteristics of traffic wave. Based on this macroscopic ACC model, the characteristics of speed-density and flow-density are analyzed. It is proved that the usage of ACC system is beneficial to increase road capacity and service ability, therefore effectively improve traffic flow.