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Capability-Enhanced PARAMICS Simulation with Developed API Library

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

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Capability-Enhanced PARAMICS Simulation with Developed API Library

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  1. 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

  2. Presentation Outline • Introduction • Methodologies • Capability enhancements • Development of advanced API modules • Applications • Conclusions

  3. Introduction • Microscopic simulation • PARAMICS • VISSIM • AIMSUN2… • Applications • Evaluations • Testing models / algorithms …

  4. 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

  5. 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

  6. User Input Interface Professional Community Oversight Output Interface GUI Tools Developer Role of API Core Model API (source: FHWA)

  7. How PARAMICS API works

  8. PARAMICS API Development: A Hierarchical Approach Signal Provided API Library Ramp Basic controller Routing Demand... Basic API Modules CORBA Data Handling Databases XML… Adaptive Signal Control Advanced API Modules Adaptive Ramp Metering Network Load Management...

  9. Current components of API-enhanced PARAMICS

  10. Capability enhancements • Basic control modules • Traffic data collection and communication • Database connection • Overall performance measures

  11. 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

  12. 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

  13. 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

  14. Overall performance measures • PARAMICS: powerful in MOE data collection • MOE API can collect: • System performance • Freeway performance • Arterial performance • Statistical Measures • Mean • Variance • Etc.

  15. Development of advanced modules

  16. 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)

  17. Developed advanced modules • Actuated signal coordination • Adaptive ramp metering algorithms • ALINEA, ZONE, BOTTLENECK, SWARM • PARAMICS-DYNASMART • Demand-responsive Transit

  18. 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

  19. User groups • Caltrans: Transportation planning & Traffic operation • California PATH headquarter at Berkeley • UC Davis • National University of Singapore • Consultant companies: • Dowling Associates • Cambridge Systematics

  20. 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

  21. 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: lchu@translab.its.uci.edu • Henry Liu: hliu@translab.its.uci.edu • Will Recker: recker@translab.its.uci.edu

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