A traffic flow simulator for short‐term travel time forecasting

Abstract

This paper presents an off-line forecasting system for short-term travel time forecasting. These forecasts are based on the historical

Application of automatic vehicle identification technology for real-time journey time estimation

“…Lam et al [9,10] have developed an off-line traffic forecasting system for Hong Kong. In this off-line system, a traffic flow simulator (TFS) has been calibrated for travel time estimation by making use of the Hong Kong Annual Traffic Census (ATC) data.…”

“…The followings are the proof of Eq. (9). By the assumption of multivariate normal distribution (MVN) of link travel times, the link travel times in the off-line system can be denoted as t $ MVNð t; KÞ and partitioned as…”

How to Provide Accurate and Robust Traffic Forecasts Practically?

“…For instance, most of literature foucs on traffc flow forecasting (Jiang & Adeli, 2004;Qiao et al, 2001;Abdulhai et al, 1999;Castillo et al, 2008;Chen & Chen, 2007;Dimitriou et al, 2008;Ding et al, 2002;Huang & Sadek, 2009;Ghosh et al, 2005Ghosh et al, , 2007Smith et al, 2002), travel time forecasting, and related analysis such as validation, optimization, etc. (Chan et al, 2003;Chang et al, 2010;Kwon, 2000;Kwon & Petty, 2005;Lam, 2008;Lam et al, 2002Lam et al, , 2008Lam & Chan, 2004;Lee et al 2009;Nath et al, 2010;Schadschneider et al, 2005;Tam & Lam, 2009;Tang & Lam, 2001;Yang et al, 2010).…”

Short-term prediction of traffic dynamics with real-time recurrent learning algorithms

“…Smart incident detection may require 1-min or shorter traffic states as inputs. Lam et al (2002) pointed out that the short-term traffic forecasting results can be used for validation of the regional and territory-wide transport models required in various transport studies, such as the freight transport study and parking demand study, and the development of traffic flow simulator to provide the offline short-term travel time and traffic flow forecasting database. Due to the complex nature of traffic time series with considerable fluctuations and noises, accurately capturing and predicting short-term traffic dynamics is more challenging than the long-term (e.g.…”