IDEAS – Improving Demand Estimation with Activity Scheduling

The project at a glance

Start date:

01 Feb 2014
Duration in months:

36
Funding:

FNR AFR-PhD Grant (6947587)
Principal Investigator(s):

Francesco VITI

About

Simulation of traffic conditions requires accurate knowledge of travel demand. In a dynamic context, this entails estimating time-dependent demand matrices, which are a discretised representation of the dynamic origin-destination (OD) flows. This problem, referred to as Dynamic Demand Estimation (DDE) in literature, seeks for the best possible approximation of OD flows which minimises the error between simulated and available traffic data. Since DDE problem is usually underdetermined because of the high number of unknown variables, many researchers have dealt with the critical issue of decreasing the number of decision variables. IDEAS focuses on extending standard (Dynamic) Demand Estimation models in order to account for different activity purposes/ demand segments. The proposed framework allows estimating activity patterns using macroscopic data (traffic counts, link speeds, mobile phone data etc.). The goal of IDEAS is to solve the DDE in complex networks, identifying aggregate activity patterns. This not only allows to have a more reliable calibration traffic models, but also to have a more realistic demand forecasting, in which the engineer is able to observe the difference between estimated activity patterns the non-recurrent ones.