1. Analysis of Intelligent and Connected Vehicle Control under Communication Delay and Packet Drop
- Research Background
V2X technology helps overcome the performance constraints of intelligent vehicle in such aspects as perception, decision and control, which enhances driving safety, efficiency, comfort and economy, etc. Yet, inherent communication delay and packet drop impair the safety and performance of connected vehicle control. Understanding the influences of delay and packet drop on the lateral and longitudinal control of ICV is significant for the implementation of ICV.
- Research Achievements
The influence of delay and packet dropout on connected path-following control and vehicle-following control was studied by the joint-simulation of Simulink and CarSim, and results are as follows. Lateral error is in nonlinear positive correlation with delay and dropout rate. There are thresholds of delay, dropout rate and path frequency beyond which lateral error grows quickly, and within thresholds, lateral errors are not significant. With delays, steady-state speed errors are almost zero, and steady-state distance errors are almost linear. Error in dynamic process is in positive correlation with delay. With dropouts, steady-state distance error grows quickly with speed error after a certain dropout rate, and occasional dropouts in dynamic process lead to chatter of speed.
Field tests is conducted with the help of ICV test bed and LTE-V prototype, and results are as follows. The influence of randomness on control error is comparable to that of delay and packet drop. Large delay and dropout rate deteriorates lateral control performance by reducing response and leading to low frequency oscillation. Tracking error is not in strict positive correlation with delay or dropout rate due to their randomness. Timing of delay or dropout can impose greater influences on performance than their severity, when delay or dropout rate is large.
Leading Research Member: CHANG Xueyang
2. ICV Control Method Based on Bounded Countermeasure Information
- Research Background
In the future, the control system of intelligent and connected vehicles may suffer from the intrusion of countermeasure information in the internet of vehicles environment, affecting the safety of the vital vehicle control. Therefore, it is of practical significance to study the vehicle control method adapted to the countermeasure information to ensure the safety of vehicles. On the one hand, the traditional control method is not sufficient to guarantee the vehicle control safety in this case. On the other hand, there are still some problems in current researches regarding the control method towards countermeasure information, such as difficult solution under complex time-varying constraints, insufficient control performance optimization, and loose combination with vehicle control, all of which still need to be further studied.
- Research Achievements
In order to study the potential influence of uncertain bounded countermeasure information on vehicle state, the state accessibility of vehicles in this case is analyzed. By using the state feedback control law, the deviation between the actual trajectory and the reference trajectory can be decoupled from the selection of the reference trajectory, and the reachability analysis of the differential reachability set formed by the deviation can be made. Furthermore, by optimizing dynamic feedback control law, it can not only reduce and reshape the differential reachability set, but also leave more room for the control limit used for reference trajectory generation, which alleviates the trade-off between the existing feedback matrix and the control limit to a certain extent.
In order to ensure the safety of vehicle control under bounded countermeasure information, based on Reachability Analysis and with the help of Satisfiability Modulo Theories, the vehicle safety verification is carried out. Under the framework of Receding Horizon Control, an optimal control method suitable for vehicle control in infinite horizon is initiated. On the one hand, the reference trajectory optimal control strategy is obtained, which not only ensures the safety, but also takes into account the control performance. On the other hand, it can improve the applicability of the vehicle control method in more complex traffic scenarios. The simulation results of vehicle-following scenario and lane-changing scenario verify the effectiveness of the control method.
Leading Research Member: LIU Yicong