embedded ad hoc distributed simulation for transportation system monitoring and control
DESCRIPTION
NSF EFRI ARES-CI Project PIs: Michael Hunter, Richard Fujimoto, Randall Guensler, Christos Alexopoulos, Frank Southworth. Presented at:. ITS Georgia 2009 Annual Meeting. EMBEDDED AD HOC DISTRIBUTED SIMULATION FOR TRANSPORTATION SYSTEM MONITORING AND CONTROL. - PowerPoint PPT PresentationTRANSCRIPT
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
EMBEDDED AD HOC DISTRIBUTED SIMULATION FOR TRANSPORTATION SYSTEM MONITORING AND CONTROL
NSF EFRI ARES-CI Project PIs: Michael Hunter, Richard Fujimoto, Randall Guensler, Christos Alexopoulos, Frank Southworth
Presented at:
ITS Georgia 2009 Annual Meeting
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Research Overview
OBJECTIVE - Reconfigurable, resilient, transportation system monitoring, forecasting & control
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Current Trends
Smart Vehicles On-board GPS, digital maps Vehicle, environment sensors Significant computation,
storage, communication capability
Not power constrained
U.S. DOT IntelliDrivesm
Provide connectivity among roadway users and the roadside
Improve safety, mobility, and environment
Dedicated Short Range Communications (DSRC)
5.850-5.925 GHz V2V, V2R communication 802.11p protocol 7 channels, dedicated safety channel 6- 27 Mbps Up to 1000 m range
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NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
In-Vehicle Data Module
In-VehicleSimulationControl
Updates
Traffic Sensors
IN-VEHICLE SIMULATION
Historical Data
Physical Data
Traffic Control
Region Wide Traffic Network
IN-VEHILCE SIMULATION
IN-VEHILCE SIMULATION
IN-VEHILCE SIMULATION
WWAN BS
WLAN APWLAN AP
Vehicle-to-Vehicle and Vehicle-to-Roadside Communication Architecture to Central Server
REGIONAL SERVER
REGIONALDISTRIBUTED SIMULATION
- Area wide traffic projection- Wide area control adjustments- Redirect mobile sensor- Adjust sensor polling
----
Traffic ControlAdjustmentsData Requests
In-VehicleSimulationPredictions
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NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Instrumentedtraffic signal
controller
Roadside-to-vehiclecommunicationVehicle-to-Vehicle
communication
In-Vehicle Simulations
Ad Hoc Distributed Simulation
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Ad Hoc Distributed Simulations
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Individual Vehicles Simulate Local Area of Interest
IN-VEHICLE SIMULATION
IN-VEHICLE SIMULATION
IN-VEHICLE SIMULATION
IN-VEHICLE SIMULATION
Ad Hoc Distributed Simulations
• An Ad Hoc distributed simulation is a composition of autonomous on-line simulators, each modeling its own “area of interest” independent of other simulators– Simulators may be stationary or mobile– Area of interest may vary over time
• Not a clean partitioning of physical system– Areas modeled by different simulators may overlap– Some areas may not be modeled at all
• Sensor network captures current system state
• Simulation used to project future system states
• Simulation-based system optimization
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Conventional vs. Ad Hoc
Conventional• Top-Down construction• Clean partition of state
space; static partition• Produce same results
as a single run
Processor1 Processor2
Processor3 Processor4
Ad Hoc• Bottom-Up construction• Ad Hoc partition of state
space; dynamic partition• Produce same statistical
results as replicated runs
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
State Prediction QuestionsState prediction problems:• Can a collection of localized simulations
provide accurate predictions of the overall system state?
• Static prediction: Given a current snapshot of the state of the system, what is the predicted, future state?
• Dynamic predication: Given a new snapshot of the state of the system, what is the (revised) prediction of future system state?
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Execution Mechanism
• System state: Space-Time Memory– Time stamp addressed memory– Stores current and predicted system state
• Autonomous simulators– Read current, predicted state from STM– Compute future state predictions – Provide updates to STM
• Optimistic synchronization (Rollback)– Prediction errors arise when
• Sensor readings do not match predictions• Predictions from other simulators change
– If error sufficiently large, roll back simulator and re-compute new projection
Roadside Server
In-Vehicle Simulations
Space-Time memory
(other levels of hierarchy, e.g., regional, traffic management center not shown)
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NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Synchronization• Simulators predict future state of system
based on on-line measurement• These predictions may be wrong due to
unexpected events (e.g., accidents)• If prediction does not match measured
state, roll back simulation, and re-compute new future state based on measured data
• If new predicted state very different from previously projected state, may trigger additional rollbacks (cascaded rollbacks)
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
12
Passing upstream traffic state to downstream• Non-congested condition
– Vehicle 1 detects volume decrease at 7:10PM– Vehicle 1 runs simulation & predicts volume on Link A will reach 270vph at 7:22PM– Server compares the data. Difference between 500vph & 270vph exceeds 200vph
threshold – Server sends rollback message to Vehicle 2 saying new flow rate is 270vph at 7:22PM– Vehicle 2 resumes its simulation with updated info
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Time
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Veh 1 prediction
Veh 2 prediction
Link jVehicle 1
Vehicle 2
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Veh 2 prediction
200vph
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NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
13
Passing downstream traffic state to upstream
Incident
Queue
Vehicle 1
Vehicle 2
• Congested condition– Average traffic flow: 500vph / Average speed 48km/hr– Incident at 7:10PM & speed drops to 2km/hr for 15min (Queue toward upstream)– Vehicle 2 detects the incident. This info needs to be delivered to vehicle 1– Vehicle 1 needs to represent this congested traffic condition– Reduce speed of vehicles on link A in its simulation to create congested condition
Reduce speed to create queue
Vehicle 1
Link j
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
14
Passing downstream traffic state to upstream
– Vehicle 2 detects incident at 7:10PM
– Vehicle 2 runs simulation predicting speed on Link A will reach 2kmph at 7:20PM
– Sends prediction to server
– Server sends rollback message to Vehicle 1
– Vehicle1 is rollbacked to 7:20PM with new data
Incident
Queue
Vehicle 1
Vehicle 2
Link j
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Automated Update using Rollback
Roll back simulator when• Prediction and measurement disagree• Predictions from other simulators change
A
B
DC
Measure increase in traffic flow at A
time
flow
rat
e
Rollback, re-compute flow at B
time
flow
rat
e
Rollback based on B, re-compute flow at C
time
flow
rat
e
Rollback based on C, re-compute flow at D
time
flow
rat
e
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Prototype Implementation• Simulators
– Custom traffic simulator• Cellular automata• Custom designed for ad hoc execution mechanism• Simplified models
– Commercial simulator• VISSIM• Detailed, “industrial strength” microscopic traffic
simulator
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Cellular Automata Simulator• Vehicle rules
– Acceleration– Deceleration– Randomized speed
change– Car motion
• Straight, turn probabilities
• Signal timing– Cycle– Left turn phase
• State: vehicle flow rate
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Initial Results
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Initial Test Network
• Test Configuration– 20 in-vehicle simulators, each simulates half of the network– 1 server (space-time memory)– Intel Xeon processors (2.0 to 3.2 GHz), 1 GB memory, running Redhat Enterprise
Linux 4 OS, 2.6.9-22.0.1 kernel; LAN interconnect• Test scenarios
– Steady state under three demand scenarios– Sudden influx of eastbound traffic at western most link
• Clients 1-10 roll back due to sensor data• Clients 11-20 roll back due to change in predictions of clients 1-10
– Compare ad hoc distributed simulation against replicated simulation experiment of entire network
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Steady State, Exit Link
• Constant input rate at edge of network throughout experiment• Measure flow rate on rightmost link at edge of network• Compare average (replicated trial), client average, single client
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20 client replicated average - 100 cars/hr 10 client distributed average - 100 cars/hrSample Distributed Client - 100 cars/hr 20 client replicated average - 300 cars/hr10 client distributed average - 300 cars/hr Sample Distributed Client - 300 cars/hr20 client replicated average - 500 cars/hr 10 client distributed average - 500 cars/hrSample Distirubted Client - 500 cars/hr
Simulation time
Pre
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k 10
100 veh/hr
300 veh/hr
500 veh/hr
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Increase Demand
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240 540 840 1140 1440 1740 2040 2340 2640 2940 3240 3540
Client 1-10 distributed average, Road 0 Client 1-10 distributed average, Road 5
Client 11-20 distributed average, Road 5 Client 11-20 distributed average, Road 10
20 client replicated average, Road 5 20 client replicated average,Road 10
• Cellular automata microscopic traffic simulator; single road w/ cross traffic• Initial input rate of 100 veh/hr; at time 1000, increase to 500 veh/hr• Clients 11-20 roll back when change occurs• If the simulators not coupled, clients 11-20 would not predict increase in flow until
higher traffic volume reached link 5
Simulation time
Pre
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Link 10
Link 5
Link 0
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Grid Network Test• Network
• Manhattan-style 10 x 10 grid - 100 equally spaced intersections (1320 ft. apart)
• Two-lane, two-way roads • Each intersection contains a shared through/right turn lane and a left
turn bay. • All intersections operate under a fixed-time, 4 phase, 120 sec cycle• Constant turn rates at each intersection - 85% through, 5% left, 10%
right• Main arterials are defined with a higher volume at the horizontal and
vertical midpoints of the network
• Experiment• Forty clients are distributed over the network• Each simulating a maximum 5 x 3 intersection grid in front of vehicle• Arrival rate on all boundary input roads initialized to a specified
value. • Model network under steady state and demand increase conditions• Improved algorithms
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Grid – Steady State
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Grid – Increase Demand
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Commercial Simulator
• Commercial simulator: VISSIM
• Scenario: evacuation of Georgia Tech campus
• Normal traffic demand at points A-J
• Traffic at point A increases from 100 to 600 veh/hr 1800 seconds into scenario
• Indicated link is bottleneck (highway overpass)
Study Area
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Traffic Flow (Overpass)
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Time
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Real World Three Minute Avgerage 10 Replicated Clients Three Minute Average
Simulation emulates the “real world,” provides data to in-vehicle (ad hoc) simulator
Ad hoc simulation predictions at bottleneck link compared to “real world” data
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
In-Vehicle Simulation
NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Conceptual Framework*• Point Sensors: loop detectors and video cameras• Server: polls and processes data from point sensor• TS*: subscribes to Server; provides real-time simulated,
mirror image of roadway’s current condition• TS-1, TS-2, TS-3: client simulations that provide possible
future roadway conditions
* Henclewood, D., M. Hunter, R. Fujimoto. Proposed Methodology For A Data Driven Simulation For Estimating Performance Measures Along Signalized Arterials In Real-Time, Proceedings of the 2008 Winter Simulation Conference, Miami, Florida, 2008.
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NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Experimental Design– 3 intersection network under semi-actuated control– 8 boundary detection points– Volume 1200 to 550 vehicle/hr– Named-Pipe used for communication between VISSIM
instances, with the aid of VISSIM’s COM module and C++– Detectors model under perfect detection - ID - and
realistic - RD - (i.e., 10% speed error, 2% loss)
Pipe-server Pipe-Client
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NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Results
• General Observations– In-vehicle Simulation appears capable of accurately reflecting real-world– However, instances are seen where real-world not consistently tracked,
particularly during peak flow
• Next Steps– Explore the impacts of VISSIM’s Calibration parameters – “perfect” calibration – Identify, quantify, and address factors that caused significant variation noted
during the peak demand period– Incorporate detector data from internal detectors– Incorporate probe data– Allow for changing roadway topology to reflect vehicle movement
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QL-1 QL-2QL-3 QL-4QL-5 QL-6QL-7 QL-8QL-9 QL-10QL-11 QL-12
Queue
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NSF EFRI ARES-CI PROJECTNSF AWARD NUMBER: 0735991
Embedded Ad Hoc Distributed Simulation for Transportation System Monitoring and Control
ITS Georgia 2009 Annual Meeting
Questions and Discussion
Contact Information – [email protected](404) 385-1243