capability-enhanced paramics simulation with developed api library lianyu chu, henry x. liu, will...
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Capability-Enhanced PARAMICS Simulation with Developed API Library
Lianyu Chu, Henry X. Liu, Will Recker
California Partners for Advanced Transit and Highways (PATH) University of California, Irvine
Presentation Outline
Introduction Methodologies Capability enhancements Development of advanced API modules Applications Conclusions
Introduction
Microscopic simulation– PARAMICS– VISSIM– AIMSUN2
… Applications
– Evaluations– Testing models / algorithms
…
Motivations
Replicate the real-world traffic operations– e.g. actuated signal control, HOV, etc.
Model / Evaluate ITS– e.g. VMS, adaptive signal control, ramp
metering, bus rapid transit, etc.
Test new models & algorithm– e.g. a control strategy combining several ITS
components
Two approaches
Modifying the source code API Programming
– API: Application Programming Interface
=> our practices of enhancing capabilities of PARAMICS via API
PARAMICS: high-performance, ITS-capable, user-programming micro-simulation package
Role of API
User
Developer
Output Interface
Input Interface
GUI Tools
Professional Community Oversight
Core Model API
(source: FHWA)
How PARAMICS API works
N
Y
Use
r-de
velo
ped
basi
c A
PI
mod
ules
Start
At every time step:
Callback
Override
Overload
End of simulation ?
Stop
Adv
ance
d A
PI
mod
ules
Other applications e.g. database
PARAMICS API Development: A Hierarchical Approach
Provided API Library
Basic controller
Basic API Modules
Advanced API Modules
Data Handling
Routing
Ramp
Signal
CORBA
Databases
Adaptive Signal Control
Adaptive Ramp Metering
Network Load Management...
Demand...
XML…
Current components of API-enhanced PARAMICS
Commercial Paramics Model
Dynamic Linking
Dynamic Linking
MOE
Actuated Signal
Ramp Metering
Loop data Aggregator
Path-based Routing
MyS
QL
Dat
abas
e
Advanced ATMIS Modules
Interface functions
Probe vehicle
Capability enhancements
1. Basic control modules
2. Traffic data collection and communication
3. Database connection
4. Overall performance measures
Basic control modules
Signal (Actuated signal control)– Dual-ring, 8-phase logic– Signal controller: Interfaces with advanced signal modules
Ramp metering– Fixed-time, time-of-day basis– “n-cars-per-green”basis – HOV bypass– Ramp metering controller: Interfaces with advanced metering
algorithms Path-based routing
– Specified vehicles follow a given path
Data collection and broadcasting
Data collection:– Loop detector data collection and aggregation in
each polling cycle, emulating the real-world loop data collection
– Probe vehicle data: link / section travel time data collection at certain time interval
Data broadcasting to shared memory, accessible through interface functions
Database connection
MYSQL: highly efficient database Purposes of this module:
– Storing intermediate data during simulation and simulation results
– Exchange data with other API modules / outside programs
Overall performance measures
PARAMICS: powerful in MOE data collection MOE API can collect:
– System performance– Freeway performance– Arterial performance
Statistical Measures- Mean- Variance- Etc.
Development of advanced modules
Advanced API modules
Basic API modules
Provided API New rate
New rate Old metering rate Loop data
PARAMICS simulation
Advanced ramp-metering algorithms
Ramp metering Controller
Loop Data Aggregator
Development of advanced modules (contd.)
Interface from loop data aggregator:– LOOPAGG loop_agg (char *detectorName)
Interfaces from ramp metering controller(1) Get current metering rate:
RAMP *ramp_get_parameters (char *rampnode)
(2) Set a new metering rate:
void ramp_set_parameters (RAMP *ramp, Bool status)
Developed advanced modules
Actuated signal coordination Adaptive ramp metering algorithms
– ALINEA, ZONE, BOTTLENECK, SWARM
PARAMICS-DYNASMART Demand-responsive Transit
Sample Applications
Signal– Hardware-in-loop, testing 170 controller– On-line signal control based on real-time delay
estimation
Ramp metering– Evaluating adaptive ramp metering algorithms
TMS master plan– Evaluating potential ITS strategies
User groups
Caltrans: Transportation planning & Traffic operation
California PATH headquarter at Berkeley UC Davis National University of Singapore Consultant companies:
– Dowling Associates– Cambridge Systematics
Conclusions
Our practices on developing a capability-enhanced PARAMICS simulation environment
Accessible to the core models of micro-simulation – simulation shell
Applicability of the same mechanism to other micro-simulators
More information
PCTSS website:http://www.its.uci.edu/~paramics/
PATH website:http://www.path.berkeley.edu/
Contact: PATH ATMS Center @ UC Irvine– Lianyu Chu: [email protected]– Henry Liu: [email protected]– Will Recker: [email protected]