1 Development of Capability-Enhanced PARAMICS Simulation Environment Lianyu Chu, Henry X. Liu, Will Recker California PATH ATMS Center University of California, Irvine

2 Introduction Microscopic simulation: – a software tool to model traffic system, including roads, drivers, and vehicles, in fine details. Micro-simulation models – CORSIM, PARAMICS, VISSIM, AIMSUN2… Micro-simulation applications – Model traffic network – Model and Evaluate ITS – Calibrate / optimize operational parameters of ITS strategies – Develop and test new traffic models, algorithms, control strategies

3 Introduction Why capability enhancements are needed – Complement missing functionalities of the current model – Modeling and evaluating ITS How to enhance – Working on source codes proprietary of a software – API Programming: a practical way for users API -- Application Programming Interface Requirement: an API library provided by micro-simulator

4 Role of API User Developer Output Interface Input Interface GUI Tools Professional Community Oversight Core Model API *source: from FHWA website

5 PARAMICS PARAMICS: PARAllel MICroscopic Simulation Developer: Quadstone, Scotland Features: – Large network simulation capability – Good graphical interface – Modeling the emerging ITS infrastructures – API Programming Purpose of this paper: – Enhancing capabilities of PARAMICS via API in order to better model and evaluate ITS

6 PARAMICS

7 How PARAMICS API works

8 Aspects of PARAMICS need to be enhanced Path-based Routing (a missing function) – PARAMICS: Link-based routing Traffic controller: – Actuated signal control (a missing function) – Ramp metering control (functionality enhancement for facilitating ITS modeling) Real-time traffic information (a missing function) – including the collection and aggregation of loop data and probe vehicle data Database connection (functionality enhancement) Performance measure (functionality enhancement)

9 Current framework of enhanced PARAMICS

10 PARAMICS API Development: A Hierarchical Approach

11 Basic modules: Path-based routing Required for the simulation of driver responses to the information supply and resulting route choice Logic: specified vehicles follow a given path Interface function:

12 Basic modules: Full-actuated signal controller NEMA Dual-ring, 8-phase logic:

13 Basic modules: Ramp metering controller Support HOV bypass Support the use of ramp detectors for metering control Interface functions for external algorithm modules to control metering Operation: n-cars-per-green basis (with n >= 1) Pre-timed control Support multiple timing plans

14 Basic modules: Loop data aggregator Emulating the real-world loop data collection – Aggregated loop data are used for real-time traffic control and off-line analysis Inputs: – loop detector name – aggregation interval (typically with 30 second interval) Outputs: – Data broadcasting to shared memory, accessible through interface functions – Reported to text files or database for performance analysis

15 Basic modules: Probe vehicle Emulating section travel time data collection through GPS equipped vehicles Inputs: – Sections of travel time collection – Sample rate of equipped vehicles – Aggregation interval Outputs: – Aggregated data broadcasting to shared memory, accessible through interface functions – Reported to text files or database for performance analysis

16 Basic modules: Database connection interface MYSQL: most popular and highly efficient Open Source SQL database This interface is developed using API functions of MYSQL. This interface allows us to operate the database via our developed PARAMICS API codes. Purposes of this module: – Storing intermediate data during simulation and simulation results – Exchange data with other API modules / outside programs

17 Basic modules: Performance measures PARAMICS has strong abilities on the collection of statistics / measurement data Current difficulties are: – With the increase of network size, the number of links, trips, intersections, and detectors increases drastically – Large amount of data are required to be processed after simulation runs for obtaining expected MOE. – Some MOE, such as on-ramp waiting time, cannot be extracted from output measurement data. – PARAMICS has a restriction on the number of output files to be opened during simulation under WINDOWS version. Use API to collect some generic overall MOE for evaluating ITS

18 Basic modules: Performance measures System performance – System efficiency: Vehicle miles traveled (VHT) – System reliability: standard deviation of average OD travel times Freeway performance – Mainline: average freeway travel speed and its variance – Ramp: total on-ramp delay and on-ramp queue spillback percentage Arterial performance – Average travel time of an arterial and its variance

19 Advanced modules: How to develop an advanced module

20 Advanced modules: How to develop an advanced module Interfaces with ramp metering controller – Set a new metering rate: void ramp_set_parameters (RAMP *ramp, Bool status) – Get current metering rate: RAMP *ramp_get_parameters (char *rampNode) Interface with loop data aggregator: – LOOPAGG loop_agg (char *detectorName) type Ramp { // ramp signal name and location char *rampNode; char *controllerLocation; // ramp control types and parameters int ControlType; float meteringCycle; }; type LOOPAGG { intdetectorIndex; floatAggregationTime; intlane; intg_vol; floatg_occ; floatg_spd; int*vol; float*occ; float*spd; };

21 Developed advanced modules Signal control – Adaptive signal – Actuated signal coordination Adaptive ramp metering algorithms – ALINEA – ZONE – BOTTLENECK – SWARM PARAMICS-DYNASMART Demand-responsive Transit

22 Sample applications Signal – Hardware-in-loop, testing 170 controller – Adaptive signal control based on real-time delay estimation Ramp metering – Evaluating adaptive ramp metering algorithms – Caltrans Freeway improvement projects I-10 freeway I-680 freeway Caltrans’ Traffic Management System master plan – Evaluating potential ITS strategies

23 Current API user groups UC Irvine Caltrans: – Transportation planning – Traffic operation California PATH program headquarter at Berkeley UC Berkeley UC Davis National University of Singapore Consultant companies: – Dowling Associates – Cambridge Systematics

24 Conclusions API can access the core models of micro-simulation. PARAMICS is a good simulation shell that users can replace its algorithms through API. We enhanced capabilities of PARAMICS and used the enhanced PARAMICS for modeling and evaluating ITS. The developed APIs have been used by Caltrans and our research & project partners in many projects. The same enhancement mechanism can be applicable to other micro-simulators, such as VISSIM, AIMSUN2, etc.

25 More information PCTSS website: PATH website: Contact: PATH ATMS UC Irvine – Lianyu Chu: – Henry Liu: – Will Recker: