Abstract
This paper presents a new macroscopic multi-class dynamic network loading model called Dynamic Queuing Transmission Model (DQTM). The model utilizes ‘good’ properties of the Dynamic Queuing Model (DQM) and the Link Transmission Model (LTM) by offering a DQM consistent with the kinematic wave theory and allowing for the representation of multiple vehicle classes, queue spillbacks and shock waves. The model assumes that a link is split into a moving part plus a queuing part, and p that traffic dynamics are given by a triangular fundamental diagram. A case-study is investigated and the DQTM is compared with single-class LTM, single-class DQM and multi-class DQM. Under the model assumptions, single-class models indicate that the LTM and the DQTM give similar results and that the shock wave property is properly included in the DQTM, while the multi-class models show substantially different travel times for two vehicle classes. Moreover, the results show that the travel time will be underestimated without considering the shock wave property.
Highlights
In order to predict more realistically traffic flows and travel times on road networks, conventional static assignment models and Dynamic Traffic Assignment (DTA) models have been developed with a focus on their application on large-scale networks
The current study focuses on Dynamic Network Loading (DNL) models used in a planning context for large-scale applications, which are characterized by uncertainty about future data and do not require as precise a representation of traffic dynamics as the models used in real-time traffic management (Balijepalli et al 2014)
The first comparison concerns the single-class Link Transmission Model (LTM), Dynamic Queuing Model (DQM) Indy and Dynamic Queuing Transmission Model (DQTM), and Fig. 3 represents the travel times obtained for these three models, each route and each vehicle class
Summary
In order to predict more realistically traffic flows and travel times on road networks, conventional static assignment models and Dynamic Traffic Assignment (DTA) models (for an extensive overview, see Peeta, Ziliaskopoulos 2001) have been developed with a focus on their application on large-scale networks. Models based on the Kinematic Wave Theory (KWT) represented vehicle propagation as based on a fundamental diagram of traffic flow instead of a travel time function (Lighthill, Whitham 1955). It is relevant to mention some recent work on quasi-dynamic network loading models, which combine static traffic assignment with some dynamic phenomena such as queuing and spillbacks (Bliemer et al 2012) This model overcomes the drawback of static assignment via an approach that is consistent with the traffic flow theory instead of the travel time function, yielding a more accurate representation of queues and spillbacks in the static framework. This study proposes the development of a DNL model that is able to represent shock waves and multiple vehicle classes at the same time. The fifth section provides conclusions and directions for further research
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