Network user equilibrium or user optimum is an ideal state that can hardly be achieved in real traffic. More often than not, every day traffic tends to be in disequilibrium rather than equilibrium, thanks to uncertainties in demand and supply of the network. In this paper we propose a hybrid route choice model for studying non-equilibrium traffic. It combines pre-trip route choice and en-route route choice to solve dynamic traffic assignment (DTA) in large-scale networks. Travelers are divided into two groups, habitual travelers and adaptive travelers. Habitual travelers strictly follow their pre-trip routes which can be generated in the way that major links, such as freeways or major arterial streets, are favored over minor links, while taking into account historical traffic information. Adaptive travelers are responsive to real-time information and willing to explore new routes from time to time. We apply the hybrid route choice model in a synthetic medium-scale network and a large-scale real network to assess its effect on the flow patterns and network performances, and compare them with those obtained from Predictive User Equilibrium (PUE) DTA. The results show that PUE-DTA usually produces considerably less congestion and less frequent queue spillback than the hybrid route choice model. The ratio between habitual and adaptive travelers is crucial in determining realistic flow and queuing patterns. Consistent with previous studies, we found that, in non-PUE DTA, supplying a medium sized group (usually less than 50%) of travelers real-time information is more beneficial to network performance than supplying the majority of travelers with real-time information. Finally, some suggestions are given on how to calibrate the hybrid route choice model in practice to produce realistic results.
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Total delay equals the total vehicle-hour-traveled (VHT), subtracted by the total free-flow travel time of all vehicle trips taking the same routes as where VHT is computed.
We do not include the results from PUE because a gridlock occurs during the iterative procedure of DNL, and solving the issue of gridlock in the DTA algorithm is beyond the scope of the paper.
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Qian, Z.(., Zhang, H.M. A Hybrid Route Choice Model for Dynamic Traffic Assignment. Netw Spat Econ 13, 183–203 (2013). https://doi.org/10.1007/s11067-012-9177-z
- Dynamic traffic assignment
- Hybrid route choice
- Traveler heterogeneity