California PATH task order 4143
Task 1: Real-time Traffic Information Estimation Through On-line Simulation
Researchers: Lianyu Chu
Time:  2001.8 – 2003.6
Project status: on-going

Project Summary:

This project will link PARAMICS simulation model with the real-world loop data. A freeway network can thus be simulated without having dynamic OD tables, which is difficult to obtain based on current theoretical methods.

Project Description:

This project includes the following sub-tasks:

1. Processing real-world loop data from ATMS testbed database in order to

(1)  Analyze the existence and quality of loop data.

(2)  Estimate speed based on single loop data.

(3)  Aggregate loop data at a given aggregation interval

2. Development of a composite demand loading model, used to release vehicles from origin zones to the network based on the traffic condition.

(1)  Under low-density traffic, vehicles are released to the network according to negative exponential distribution

(2)  Under high-density traffic, vehicles are released to the network according to normal distribution with the mean of a constant headway.

(3)  Under the traffic between low density and high density, we use a distribution factor to determine how much of traffic follows negative exponential distribution and how much of traffic follows normal distribution.

3. Development of an OD estimation model based on the method of the FREQ model because any a vehicle in simulation need to have OD information.

4. Development of traffic flow prediction models for predicting future traffic flow based on historical data. Two methods are developed, including Kalman filtering method and time series (ARIMA) method.

5. Implementing the on-line simulation system in PARAMICS via integrating all components / models described above.