Control Challenges in the Vehicle Infrastructure Initiative (VII)

Transcription

1 Control Challenges in the Vehicle Infrastructure Initiative (VII) Hemant Sardar Automotive IEEE TCAC Workshop on Open Problems & Challenges in Automotive Control

2 Introduction Background of ITS Overview of VII & e-safety Status of current technologies Options for VII controllers Wrap-up & questions SASPENCE 2

3 Background Substantial work done in ITS over the past several years PATH program in California CALTRANS, US-DOT, UC-Berkeley, CMU, etc. Considerable body of research & publications Not all necessarily useful Past research: Single vehicle level sensor/data fusion demonstrated Robustness shown to specific types of noisy environments (internal & external) Issues with very large scale integration Stability issues from control standpoint Requires substantial investment in infrastructure to achieve basic levels of performance expected Open question on how this can be done 3

4 Vehicle Infrastructure Initiative (VII) Emerging Intelligent Transportation System (ITS) initiative Consortium includes FHWA, US-DoT, state DoTs, NA automotive industry Focus is on overall intelligent transportation infrastructure development Develop scaleable network for wide variety of applications Vehicle-to-vehicle (V2V) communication linkages Vehicle-to-infrastructure (V2I) communication linkages Can utilize V2V & V2I linkages for a variety of things Hazard prevention and mitigation Infrastructure health preventive maintenance Traffic flow management Real-time traveler information dissemination 4

5 European Union e-safety Initiative Initiative involves several EU agencies and companies E.U. wide multi-generational program with industry / government / academia participation Further along than US initiative Projects/subprojects identified Timelines & deliverables defined Several proof-of-concept demonstrations completed Focus on vehicle/occupant safety Infrastructure & building blocks are targeted towards hazard prevention and mitigation Projects targeted towards various aspects of safety including driver-vehicle interaction 5

6 EU e-safety e-safety building blocks (FP6 projects): PReVENT Preventive, Active & Passive Safety Applications Help drivers avoid/mitigate accidents through use of in-vehicle systems AIDE Adaptive Integrated -vehicle Interface Focus on automotive human-machine interaction () EASIS Electronic Architecture & System Engineering for Integrated Safety Systems Develop a standardized in-vehicle electronics architecture & system engineering approach for integrated safety systems GST Global System for Telematics enabling on-line safety services HUMANIST Human factors and ergonomic research applied to road transport Strong interaction with aspects of AIDE project 6

7 Pre-crash Systems, Reversible Protection Systems PReVENT Project 7 Intersection safety Foresighted Driving Warning & Assistance Systems

8 Development Status VII & e-safety are complementary initiatives Overall goals are somewhat different Several e-safety activities/building blocks can be dovetailed within VII & vice-versa Industry participating in areas of interest focus is on safety systems and technologies Active and passive technologies and their integration Involved in subprojects within PReVENT project: SASPENCE» Safe speed, safe distance INTERSAFE» Improved safety at intersections based on sensors & communications Other technologies also developed in-house (e.g. ACC, LDW, etc.) 8

9 Development Status Most of work is at driver/vehicle level Focus on information exchange from vehicle to driver Sensor/data fusion at single vehicle level Accomplished for specific technologies/demonstrators Vision & radar sensors Mostly done as proof-of-concept / technology demonstrator Several issues need to be ironed out at unit level Comprehensive assessment in noisy environments Issues (Human-machine interface) Rear Detection & Lane Change Assistance Lane Support Lane Change Blind Spot 9

10 Typical Block Diagram Single Vehicle Multiple Control Strategies Applied DRIVER SUBSYSTEM H (Tomizuka) Sliding mode (Tomizuka, Utkin) SASPENCE Road Optimal (Peng) Neural Networks (Pomerleau) Others (Kalman filters, etc.) Sensor / Data Fusion Disturbance rejection Stability Hierarchical control Modeling & validation 10

11 Single Vehicle ITS Controllers Single /dual control loop architectures developed For single loop architectures vehicle offset is typically the controlled parameter SASPENCE For dual loop schemes, lateral & yaw dynamics are typically controlled Yaw controller is slave to position controller Each scheme has advantages & disadvantages Computational & modeling overhead Bicycle models suffice for some More complex vehicle models required in other cases Disturbance/noise identification & rejection Explicit robustness to vehicle speeds achieved Robustness to uncertainties (vehicle & external) demonstrated, however not in comprehensive manner 11

12 VII Requirements VII requires higher level of integration Focus on developing V2V & V2I linkages Several questions TBD: Structure of system (master-slave, equal priority, etc.) Communications protocols Nature & type of information that should be available Etc. V2V Linkage 12

13 VII Requirements VII requires higher level of integration Focus on developing V2V & V2I communication linkages Several questions TBD: Structure of system Communications protocols Nature & type of information that should be available Etc. Infrastructure Elements V2I Linkage V2V Linkage 13

14 VII Hypothesis 14

15 VII Hypothesis 15

16 VII Hypothesis 16

17 VII Requirements (Assumed) High level requirements Multiple V2V & V2I linkages Vehicles arrive into and depart from the ITS system at random Note that most urban areas have traffic pattern data Can be utilized for optimizing system Can consider appropriate random distributions where applicable Markov process models for modeling arrival and departure Possible definition of steady-state Constant traffic flow rate between any two end-points along the ITS network for any given time window in-spite of: Failures at the individual vehicle level (unit) Failures in the infrastructure 17

18 Possible Control Structures CAN topology is one possible candidate Capable of very large scale integration Scalable Each vehicle is a node SASPENCE Each access/data collection point on the infrastructure is a node Data is broadcast by each node at network specified frequency Fusion of information gathered & processed by vehicle sensors Message priority is tagged to broadcast High priority messages get preference for transmission & action Topology is very fault tolerant if a node fails Top-down design FAA model 18

19 CAN Topology - Discussion However, CAN topology strictly allows for V2I linkages only Scope of V2V linkage needs to be carefully defined Passive sensors only (?) Limited data processing and control authority for ITS SASPENCE Supervisory controller will run on infrastructure Allows for large-scale data processing Can handle much larger computational burden For present case, assume V2V linkages are significantly weaker than V2I Small signal behavior v/s large signals analogy Design controller for large signals 19

20 Alternate VII Hypothesis Weak linkages 20

21 CAN Topology Determination of stability for system is more structured Can use previously researched methods for CAN topology to ensure system does not go unstable SASPENCE Need to ensure hierarchical structure is maintained Control scheme for supervisor will be of MIMO type Operator in the loop required for safety / policy reasons Probabilistic element to control structure Arrival and departure of vehicles is random Signaling of issue(s) from any node is random Assumption is that given present state, the past does not provide any additional information about the future states 21

22 CAN Supervisor Control Can define performance index to Minimize supervisor response time to an error signal Minimize deviation from steady-state: Minimize occurrence of error signals from other nodes given that original error signal occurred If initial response is not correct, there will be spill-over effect on other nodes Ability to manage failures without letting them cascade through the system J i = ( 2 T 2 T W t W + W e W ) e e e Can expand this PI to n occurrences and responses Note that there is a probabilistic component to the parameter e r (=µ 0 p ij ) r r r J = W e n t 2 e W T e + W r n e 2 r W T r 22

23 CAN Topology Controller Can define control scheme to minimize PI However: SASPENCE No best solution for this approach Initial assumptions will have strong influence on results Difficult to predict behavior as number of nodes and possible error states increase (rush hour traffic) Note that the FAA model does not work very well even today Heavily dependent on infrastructure capabilities Do not exist yet 23

24 Alternate Control Structure Hypothesis that information about adjacent vehicles is more important V2V is higher priority Strength of a linkage is based on distance and whether any other vehicles are within the δ nbd of a vehicle (adjacency) V2I linkage is done at lower priority & frequency Inform infrastructure of status Operator intervention needed to react to traffic situations Virtual linkages between vehicles on a road (V2V) Controller structured around keeping strength of V2V linkages between bounds for vehicles within a predefined δ nbd L min L V 2V L max 24

25 Alternate VII Hypothesis Weak linkages 25

26 Virtual Link Control Topology Need to define what constitutes a V2V linkage Virtual link that contains information of interest to both vehicles SASPENCE Could include information from multiple vehicle level ITS subsystems: ACC /LDW / VSC Other vehicle health monitoring (e.g. TPM) Virtual links are constantly formed and broken based on predefined criteria δ nbd envelope around vehicle based on known safety requirements (e.g. distance to stop, crash avoidance, etc.) Another vehicle getting in between i.e., adjacency requirement changes This is more of a bottom-up approach 26

27 Virtual Link Control Topology Control scheme is based on changing links Sliding mode type control structure may be more appropriate SASPENCE Intent to try and keep L v2v constant as much as possible Account for speeds of vehicles involved in virtual links This approach becomes quite complex and difficult to manage very quickly Links grow exponentially as number of vehicles involved increases Stability issues with approach need to be carefully analyzed Initially no need for significant change to infrastructure capabilities Subsystems development ongoing 27

28 Summary VII is an ITS initiative Multiple objectives and goals for participants Complementary to ongoing EU e-safety initiative SASPENCE Industry already developing several ITS sub-systems Focus is currently on single vehicle-driver interaction and information exchange Ongoing debate about top-down or bottom-up approach to very large scale integration in ITS Subsystems required for either approach are similar Require slightly different emphasis on capabilities 28

29 Summary Two possible control approaches discussed Each has advantages & disadvantages Not clear at this stage if either can be a viable option Issues to address for both: capability SASPENCE Assumption is that driver are capable and responsible Need to assess ability to game the system 29