2016
DOI: 10.1111/mice.12236
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Robust Optimal Lane Allocation for Isolated Intersections

Abstract: Lane allocation including approach and exit lane numbers and lane markings of approach lanes plays an important role in improving the capacity of an intersection. Conventional approaches for optimizing lane allocation often ignore fluctuations in traffic demand (TD). This article presents a stochastic model for robust optimal lane allocation of an isolated intersection understochastic traffic conditions. This model is built in three steps. In the first step, an enhanced lane-based model in the form of a binary… Show more

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Cited by 19 publications
(9 citation statements)
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“…With the comparison with the deterministic linear programming model, it shows that the proposed stochastic programming model can reduce total vehicle delay and queue length, and improve throughput. Yu et al [38] proposed a robust optimization model for the integrated design of lane allocation and signal timing for isolated intersections. Hao et al [39] proposed a robust optimization model of signal timing for unsaturated intersections.…”
Section: Literature Reviewmentioning
confidence: 99%
See 1 more Smart Citation
“…With the comparison with the deterministic linear programming model, it shows that the proposed stochastic programming model can reduce total vehicle delay and queue length, and improve throughput. Yu et al [38] proposed a robust optimization model for the integrated design of lane allocation and signal timing for isolated intersections. Hao et al [39] proposed a robust optimization model of signal timing for unsaturated intersections.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Since the objective function is non-convex and nondifferentiable [23], [54], [55] and the model contains nonlinear constraints, it is difficult to solve by traditional optimization algorithms. A heuristic algorithm is often used to solve this problem [38], [56], [57]. Therefore, this model was figured out based on the genetic algorithm (GA) in this paper, and the procedure is shown below.…”
Section: B Constraints 1) Calculation Of the Vehicular Delaymentioning
confidence: 99%
“…Model [M2] can be solved by a mixed‐integer linear programming solver such as CPLEX (González et al., ; Maghrebi et al., ; Rashidi et al., ; Xie and Jiang, ; Zhao et al., ; Zockaie et al., ; Yu et al., ).…”
Section: Model Formulation and Algorithmmentioning
confidence: 99%
“…This design concept has been successful in designing individual signalized intersections [17]. Intersection capacity has been increased significantly if lane markings and traffic signal settings are optimized in a unified framework [18][19][20][21].…”
Section: Discrete Dynamics In Nature and Societymentioning
confidence: 99%