Abstract
In many cases, the final path selection of travellers’ is not the shortest path, due to the limited computing power and high cost of path search. To solve the problem, this paper proposes a day-to-day (DTD) stochastic traffic flow assignment model that regulates the traffic flow based on the travel time (travel cost) and residual congestion of optional paths. The regulation mechanism is called the mixed regulation. Then, the authored proved the existence, uniqueness and stability of the model solution. The proposed model was verified through simulation on a Nguyen-Dupuis road network. The results show that traffic flows and travel times of all paths reached the equilibrium state, thanks to the DTD mixed regulation for 20~30 days. From the traffic flows and congestion degrees of different sections, it can be seen that our model with mixed regulation diverts the traffic flow to the sections with a low congestion degree, and encourages travellers to drive through the sections with a low traffic flow. In addition, the congestion degrees of the four most congested sections decreased by 5.8%, 4%, 7% and 1.2%, respectively, and the entire road network exhibited a slight downward trend in mean congestion degree. These results prove that our model can uniformize the traffic flow, improve the operation efficiency and alleviate the congestion of the road network. These findings shed new light on the control, guidance and planning of traffic flow in road networks.
Highlights
In the road network, the traffic flow is often unequilibrated under external or internal factors [1]
Based on non-Walrasian equilibria [19]–[21] and path congestion degree, this paper proposes a DTD stochastic traffic flow assignment model that regulates the traffic flow based on the travel time and residual congestion of optional paths
This paper proposes a DTD stochastic traffic flow assignment model based on mixed regulation
Summary
The traffic flow is often unequilibrated under external or internal factors [1]. Considering the impact of congestion charge on travellers’ path selections, Li and Guan [14] assumed that the charge is positively correlated with the travel time in congested section, and introduced the congestion charge policy to the DTD dynamic evolution model of traffic flow. The regulation mechanism is called the mixed regulation This simple and stable model can reasonably describe how some travellers choose the paths based on congestion information, and lead to the equilibrium of the traffic flow. The higher the value of φ, the more sensitive the congestion degree of the path, and the less random the traveler to choose the path On this basis, the DTD stochastic traffic flow assignment model based on residual congestion can be established as: pr (n).
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