Abstract
This paper studies the network capacity problem on signalized road network with reversible lanes. A Mixed Network Design Problem (MDNP) is formulated to describe the problem where the upper-level problem is a mixed integer non-linear program designed to maximize the network capacity by optimizing the input parameters (e.g. the signal splits, circles, reassigned number of lanes and O–D demands), while the lower-level problem is the common Deterministic User Equilibrium (DUE) assignment problem formulated to model the drivers’ route choices. According to whether one way strategy is permitted in practice, two strategies for implementing reversible roadway are considered. In the first strategy, not all lanes are reversible and the reversible roadways always hold its ability to accommodate the two-way traffic flow. In the second strategy, one-way road is allowed, which means that all the lanes are reversible and could be assigned to one flow direction if the traffic flow in both directions is severally unsymmetrical. Genetic Algorithm (GA) is detailedly presented to solve the bi-level network capacity problem. The application of the proposed method on a numerical example denotes that Strategy 2 can make more use of the physical capacity of key links (signal controlled links), thus, the corresponding network capacity outperforms it is of Strategy 1 considerably.
Highlights
To accommodate the increasing traffic flow in urban road network, measures, such as network construction, traffic signal coordination control et al are extensively used by the approach people
The NDP is considered in three forms, the first form is Continuous Network Design Problem (CNDP), which deals with the continuous capacity expansion of the existing streets, the second form is Discrete Network Design Problem (DNDP), which deals with adding new streets or lanes to the existing streets, and the third one is Mixed Network Design Problem (MNDP), which deals with both discrete and continuous network design variables (Miandoabchi, Farahani 2011)
The network capacity problems with the two reversible roadway strategies are modeled as a MNDP, where upper-level problem is a mixed integer non-linear program, which aims to maximize the network capacity by optimizing parameters, such as the signal splits, circles, reassigned number of lanes and O–D demands, while the lower-level problem is the common Deterministic User Equilibrium (DUE) assignment problem, formulated to compute the equilibrium traffic flows for each network design scenario
Summary
To accommodate the increasing traffic flow in urban road network, measures, such as network construction (widening links or building new roads), traffic signal coordination control et al are extensively used by the approach people. Through embedding the concept of reserve capacity, Chiou (2008) further proposed a CNDP to study the network capacity on signalized road network with link capacity expansions This problem is formulated such that the total travel demand is maximized while the total delays are minimized simultaneously. The network capacity problems with the two reversible roadway strategies are modeled as a MNDP, where upper-level problem is a mixed integer non-linear program, which aims to maximize the network capacity by optimizing parameters, such as the signal splits, circles, reassigned number of lanes and O–D demands, while the lower-level problem is the common Deterministic User Equilibrium (DUE) assignment problem, formulated to compute the equilibrium traffic flows for each network design scenario.
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