Adaptive Cruise Control: Hybrid, Distributed, and Now Formally Verified (CMU-CS-11-107)

Car safety measures can be most effective when the cars on a street coordinate their control actions using distributed cooperative control. While each car optimizes its navigation planning locally to ensure the driver reaches his destination, all cars coordinate their actions in a distributed way in order to minimize the risk of safety hazards and collisions. These systems control the physical aspects of car movement using cyber technologies like local and remote sensor data and distributed V2V and V2I communication. They are thus cyber-physical systems. In this paper, we consider a distributed car control system that is inspired by the ambitions of the California PATH project, the CICAS system, SAFESPOT and PReVENT initiatives. We develop a formal model of a distributed car control system in which every car is controlled by adaptive cruise control. One of the major technical difficulties is that faithful models of distributed car control have both distributed systems and hybrid systems dynamics. They form distributed hybrid systems, which makes them very challenging for verification. In a formal proof system, we verify that the control model satisfies its main safety objective and guarantees collision freedom for arbitrarily many cars driving on a street, even if new cars enter the lane from on-ramps or multi-lane streets. The system we present is in many ways one of the most complicated cyber-physical systems that has ever been fully verified formally.

[1]  André Platzer,et al.  Adaptive Cruise Control: Hybrid, Distributed, and Now Formally Verified , 2011, FM.

[2]  Chin-Woo Tan,et al.  An Efficient Lane Change Maneuver for Platoons of Vehicles in an Automated Highway System , 2003 .

[3]  Olaf Stursberg,et al.  Verification of a Cruise Control System using Counterexample-Guided Search , 2004 .

[4]  Matthias Althoff,et al.  Safety verification of autonomous vehicles for coordinated evasive maneuvers , 2010, 2010 IEEE Intelligent Vehicles Symposium.

[5]  Nancy A. Lynch,et al.  Strings of Vehicles: Modeling and Safety Conditions , 1998, HSCC.

[6]  Stefan Germann.  Modellbildung und modellgestützte Regelung der Fahrzeuglängsdynamik , 1997 .

[7]  Thanh-Son Dao,et al.  Optimized Lane Assignment Using Inter-Vehicle Communication , 2007, 2007 IEEE Intelligent Vehicles Symposium.

[8]  André Platzer,et al.  Quantified Differential Dynamic Logic for Distributed Hybrid Systems , 2010, CSL.

[9]  Datta N. Godbole,et al.  Automated Highway Systems , 1996 .

[10]  Masayoshi Tomizuka,et al.  Vehicle Lane Change Maneuver In Automated Highway Systems , 1994 .

[11]  Rolf Johansson,et al.  Nonlinear and Hybrid Systems in Automotive Control , 2002 .

[12]  Rajesh Subramanian,et al.  CICAS-V research on comprehensive costs of intersection crashes , 2007 .

[13]  Elias B. Kosmatopoulos,et al.  Collision avoidance analysis for lane changing and merging , 1999, IEEE Trans. Veh. Technol..

[14]  Nancy Lynch,et al.  Safety Verification for Automated Platoon Maneuvers: A Case Study , 1997, HART.

[15]  Randolph W. Hall,et al.  The Automated Highway System/Street Interface: Final Report , 2003 .

[16]  C.M. Clark,et al.  Distributed platoon assignment and lane selection for traffic flow optimization , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[17]  Sonia R. Sachs,et al.  Design Of Platoon Maneuver Protocols For IVHS , 1991 .

[18]  Hardi Hungar,et al.  Verification of cooperating traffic agents , 2006 .

[19]  Richard M. Murray,et al.  Periodically Controlled Hybrid Systems , 2009, HSCC.

[20]  Pravin Varaiya,et al.  Smart cars on smart roads: problems of control , 1991, IEEE Trans. Autom. Control..

[21]  Steven E Shladover,et al.  Effects of Traffic Density on Communication Requirements for Cooperative Intersection Collision Avoidance Systems (CICAS) , 2005 .