Approaches for Modelling Travel Time Uncertainty

Recent research outcomes have reasonably stated that network traffic is stochastic, hence traffic demand management policies like perimeter control and gating should embrace stochasticity in any form for efficiency. This work attempts to model Travel Time Distribution in terms of Travel Time Uncertainty (TTU), a stochastic quantity. The study advised splitting the traffic network into an appropriate number of subnetworks using a clustering technique to provide approximate spatial homogeneity since TTU is also contributed by spatial variability. Travel time in distinct time stamps is used to represent TTU initially since it is directly related to TTU, however the concerned models have proven deterministic behavior approximately. The study modelled the quantity using the Bureau of Public Road Link-function (BPR) with TTU and related factors. The redesigned model captured stochastic behavior and integrated heterogeneity nicely. The Modified BPR (MBPR) function addresses the hysteresis phenomena in trip time distribution versus traffic flow values, which few research have reported. TTU and deterministic descriptors allow for network-level stochastic research in this paradigm.