Trips-in-Motion Time Matrix to Identify Time Windows as an Input for Time-of-Day Modelling

Abstract

Time-of-day modelling is an additional step to the conventional four-step Travel Demand Models (TDMs). Here, the target is to obtain more detailed outputs over the temporal dimension. With this additional step, daily (24-hour) travel demand is distributed into a discrete number of time-windows. This paper aims to identify the most precise time windows that maximise the trips that fall within a given time-window and minimise the trip-tailing associated with it. The trips-in-motion method follows a more logical approach to capturing the entire trip duration. The Colombo Metropolitan Region Transport Masterplan database, developed in 2013, is analysed using Bentley Cube Voyager transport demand modelling software. The most precise starting timestamps of two-hour time windows were selected for the morning, mid-day, and evening peaks at 6:30 AM, 01:30 PM and 05:00 PM. This study has developed a systematic approach to identify time-windows as input for time-of-day based modelling. This attempt is an initial step to simulate the third-dimension of a trip, which is called the temporal dimension of TDMs. Finally, it is recommended to study the shift in peak periods with the change in time of demand, which would be the behavioural change most expected to occur post- COVID-19.

Keywords

• time of day
• travel demand model
• time window
• peak-time