Most of the timed automata reachability analysis algorithms in the literature explore the state spaces by enumeration of symbolic states, which use time constraints to represent a set of concrete states. A time constr...Most of the timed automata reachability analysis algorithms in the literature explore the state spaces by enumeration of symbolic states, which use time constraints to represent a set of concrete states. A time constraint is a conjunction of atomic formulas which bound the differences of clock values. In this paper, it is shown that some atomic formulas of symbolic states generated by the algorithms can be removed to improve the model checking time- and spaceefficiency. Such atomic formulas are called as irrelevant atomic formulas. A method is also presented to detect irrelevant formulas based on the test-reset information about clock variables. An optimized model-checking algorithm is designed based on these techniques. The case studies show that the techniques presented in this paper significantly improve the space- and time-efficlency of reachability analysis.展开更多
To cater for the scenario of coordinated transportation of multiple trucks on the highway,a platoon system for autonomous driving has been extensively explored in the industry.Before such a platoon is deployed,it is n...To cater for the scenario of coordinated transportation of multiple trucks on the highway,a platoon system for autonomous driving has been extensively explored in the industry.Before such a platoon is deployed,it is necessary to ensure the safety of its driving behavior,whereby each vehicle’s behavior is commanded by the decision-making function whose decision is based on the observed driving scenario.However,there is currently a lack of verification methods to ensure the reliability of the scenario-based decision-making process in the platoon system.In this paper,we focus on the platoon driving scenario,whereby the platoon is composed of intelligent heavy trucks driving on cross-sea highways.We propose a formal modeling and verification approach to provide safety assurance for platoon vehicles’cooperative driving behaviors.The existing Multi-Lane Spatial Logic(MLSL)with a dedicated abstract model can express driving scene spatial properties and prove the safety of multi-lane traffic maneuvers under the single-vehicle perspective.To cater for the platoon system’s multi-vehicle perspective,we modify the existing abstract model and propose a Multi-Agent Spatial Logic(MASL)that extends MLSL by relative orientation and multi-agent observation.We then utilize a timed automata type supporting MASL formulas to model vehicles’decision controllers for platoon driving.Taking the behavior of a human-driven vehicle(HDV)joining the platoon as a case study,we have implemented the model and verified safety properties on the UPPAAL tool to illustrate the viability of our framework.展开更多
基金Supported by the National Natural Science Foundation of China （Grant Nos. 60203009, 60233020 and 60425204）, the NSF of Jiangsu Province （Grant No. BK2003408） and the National Basic Research 973 Program of China （Grant No. 2002CB312001）.
文摘Most of the timed automata reachability analysis algorithms in the literature explore the state spaces by enumeration of symbolic states, which use time constraints to represent a set of concrete states. A time constraint is a conjunction of atomic formulas which bound the differences of clock values. In this paper, it is shown that some atomic formulas of symbolic states generated by the algorithms can be removed to improve the model checking time- and spaceefficiency. Such atomic formulas are called as irrelevant atomic formulas. A method is also presented to detect irrelevant formulas based on the test-reset information about clock variables. An optimized model-checking algorithm is designed based on these techniques. The case studies show that the techniques presented in this paper significantly improve the space- and time-efficlency of reachability analysis.
基金supported by the National Key Research and Development Program of China under Grant No.2019YFB2102602。
文摘To cater for the scenario of coordinated transportation of multiple trucks on the highway,a platoon system for autonomous driving has been extensively explored in the industry.Before such a platoon is deployed,it is necessary to ensure the safety of its driving behavior,whereby each vehicle’s behavior is commanded by the decision-making function whose decision is based on the observed driving scenario.However,there is currently a lack of verification methods to ensure the reliability of the scenario-based decision-making process in the platoon system.In this paper,we focus on the platoon driving scenario,whereby the platoon is composed of intelligent heavy trucks driving on cross-sea highways.We propose a formal modeling and verification approach to provide safety assurance for platoon vehicles’cooperative driving behaviors.The existing Multi-Lane Spatial Logic(MLSL)with a dedicated abstract model can express driving scene spatial properties and prove the safety of multi-lane traffic maneuvers under the single-vehicle perspective.To cater for the platoon system’s multi-vehicle perspective,we modify the existing abstract model and propose a Multi-Agent Spatial Logic(MASL)that extends MLSL by relative orientation and multi-agent observation.We then utilize a timed automata type supporting MASL formulas to model vehicles’decision controllers for platoon driving.Taking the behavior of a human-driven vehicle(HDV)joining the platoon as a case study,we have implemented the model and verified safety properties on the UPPAAL tool to illustrate the viability of our framework.
