1. Development of PARAMICS Plug-ins with Application Programming Interfaces Henry X. Liu, Lianyu Chu, Will Recker PATH / UC-Irvine

2. Presentation Outline Introduction Development Approach Basic Modules Advanced Modules Applications Conclusions

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

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

6. How PARAMICS API works

7. 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…

8. Capability enhancements 1. Basic control modules 2. Traffic data collection and communication 3. Database connection 4. Overall performance measures

9. Basic control modules Signal (Actuated signal control) – Dual-ring, 8-phase logic – Signal Coordination Ramp metering – Fixed-time, time-of-day basis – “n-cars-per-green”basis – HOV bypass Path-based routing – Specified vehicles follow a given path

10. 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

11. Database connection MYSQL: highly efficient database Purposes of this module: – Storing data during simulation and simulation results – Exchange data with other API modules / outside programs

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

13. Development of advanced modules

14. 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)

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

16. 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