How do you model user behavior and route choice in dynamic traffic assignment?

1 User behavior and route choice

User behavior and route choice refer to how travelers decide when, where, and how to travel in a transportation network. These decisions depend on various factors, such as travel purpose, preferences, information, expectations, and constraints. User behavior and route choice affect the traffic flow patterns and dynamics in the network, and vice versa. Therefore, modeling user behavior and route choice is essential for DTA.

2 User equilibrium and stochastic user equilibrium

User equilibrium (UE) and stochastic user equilibrium (SUE) are two common assumptions of user behavior and route choice in DTA. UE assumes that all travelers are rational and choose the route that minimizes their travel cost, such as travel time or toll. SUE relaxes the UE assumption by allowing some travelers to choose suboptimal routes due to uncertainty, perception errors, or preference heterogeneity. Both UE and SUE imply that no traveler can improve their travel cost by switching to another route.

3 Dynamic user equilibrium and stochastic dynamic user equilibrium

Dynamic user equilibrium (DUE) and stochastic dynamic user equilibrium (SDUE) are extensions of UE and SUE to account for the time-varying nature of traffic conditions and travel costs. DUE assumes that all travelers are aware of the dynamic traffic conditions and choose the departure time and route that minimize their travel cost over the entire trip. SDUE allows for some travelers to have imperfect or incomplete information about the dynamic traffic conditions and choose their departure time and route based on their expectations and experience.

4 Assignment models and algorithms

Assignment models and algorithms are mathematical formulations and computational methods that aim to find the equilibrium or optimal solution of user behavior and route choice in DTA. Assignment models can be classified into deterministic or stochastic, static or dynamic, and discrete or continuous, depending on the assumptions and representations of the traffic flow, travel cost, and user behavior. Assignment algorithms can be classified into link-based or path-based, analytical or simulation-based, and iterative or non-iterative, depending on the solution approach and technique.

5 Calibration and validation

Calibration and validation are important steps to ensure the accuracy and reliability of the user behavior and route choice models in DTA. Calibration is the process of adjusting the model parameters, such as travel cost functions, demand matrices, or behavioral coefficients, to match the observed traffic data, such as traffic counts, travel times, or speeds. Validation is the process of testing the model performance and sensitivity to different scenarios, such as network changes, demand variations, or information provision.

6 Challenges and opportunities

Modeling user behavior and route choice in DTA is a challenging and evolving task that requires a balance between realism and simplicity, data availability and quality, and computational efficiency and robustness. Some of the current challenges and opportunities include incorporating behavioral dynamics, learning, and adaptation, accounting for multimodal and intermodal choices, capturing the effects of emerging technologies and services, such as connected and autonomous vehicles, ride-hailing, or mobility as a service, and integrating user behavior and route choice models with other models, such as land use, emissions, or safety.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?