Stochastic Optimization for Sustainable Traffic Signal Control

Park, Byungkyu Brian; Yun, Ilsoo; Ahn, Kyoungho

doi:10.1080/15568310802091053

Cited by 66 publications

(30 citation statements)

References 5 publications

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“…For example, Li et al [21] analyzed the relationships between emissions, fuel consumption, vehicle delay, and the signal cycle length for an isolated intersection to optimize the green time and signal cycle length. Liao et al [22], Park et al [23], and Stevanovic et al [24] optimized the signal timing while minimizing fuel consumption and vehicle emissions with the aid of traffic simulation software. Their study provided a fresh approach by which to integrate existing state-of-the-art tools for reassessing and ultimately minimizing fuel consumption and emissions.…”

Section: Literature Reviewmentioning

confidence: 99%

Arterial Offset Optimization Considering the Delay and Emission of Platoon: A Case Study in Beijing

Ding

Chen

et al. 2019

Sustainability

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The effective setting of offsets between intersections on arterial roads can greatly reduce the travel time of vehicles through intersections. However, coordinated control systems of urban arterial roads often do not achieve the desired effect. On the contrary, they are very likely to increase the traffic congestion on arterial roads, resulting in more delays of the platoon with more exhaust emissions, if the coordinated control system does not have effective settings. Meanwhile, taking into account increasing environmental pollution, measures are needed to solve the conflict between environmental and traffic management. Thus, in order to ensure the smooth flow of urban arterial roads while considering the environment, this paper develops a bi-objective offset optimization model, with reducing delays of the platoon on arterial roads as the primary objective, and reducing exhaust emissions as the secondary objective. The proposed bi-objective model is based on the division of platoon operating modes on arterial roads, and more pollutant types, including NOx, HC, and CO, are considered when measuring environmental impact. Further, the modified hierarchical method, combining the branch and bound approach with the introductions of a relaxation coefficient, is employed to solve the model. By introducing a relaxation coefficient, the modified hierarchical method overcomes the defects of the traditional one. Finally, Xi Dajie Road in Beijing was taken as an example. The results showed that the bi-objective offset optimization model, considering both the delays and emissions of the platoon reduced delays by up to 20% and emissions by 7% compared with the existing timing plan. If compared with the offset optimization model considering delays only, such a model increases delays no more than 3% and reduces emissions by 6%.

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Section: Literature Reviewmentioning

confidence: 99%

Arterial Offset Optimization Considering the Delay and Emission of Platoon: A Case Study in Beijing

Ding

Chen

et al. 2019

Sustainability

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“…Alleviating emissions burden through traffic signal control has been of interest because of its cost-effectiveness and non-reliance on encouraging motorists to adjust their driving habits (e.g., driving at lower speeds) [6,7]. Former studies [6,8] stated that extra emissions and fuel consumption at signalized intersections are intimately associated with unnecessary stop-events and extra seconds of delay while idling. However, the general practice of optimizing signals to minimize delay does not necessarily minimize extra stops; hence emissions could increase [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…Former studies [6,8] stated that extra emissions and fuel consumption at signalized intersections are intimately associated with unnecessary stop-events and extra seconds of delay while idling. However, the general practice of optimizing signals to minimize delay does not necessarily minimize extra stops; hence emissions could increase [6][7][8]. Thereby, several studies [9][10][11] have been conducted to find a Pareto-optimal signal timings solution to balance delay and stops.…”

Section: Introductionmentioning

confidence: 99%

Impact of Various Operating Conditions on Simulated Emissions-Based Stop Penalty at Signalized Intersections

2021

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Sustainability has become one of the most important goals when optimizing traffic signals. This goal is achieved through utilizing various objective functions to reduce sustainability metrics (e.g., fuel consumption and emissions). However, most available objective functions do not distinguish between the reduction mechanism of various types of emissions. Further, such functions do not consider the compound impact of multiple operational conditions (e.g., road gradient) influencing emissions on the optimized signal plans. This study derives a new Environmental Performance Index representing a surrogate measure for emission estimates that can be used as an objective function in signal timings optimization to reduce emissions under various operational conditions. The Environmental Performance Index is a linear combination of delays and stops. The key factor of the Environmental Performance Index is the emissions-based stop penalty, which represents an emission stop equivalency measured in seconds of delay. This study also uses traffic simulation and emission models to investigate the compound impact of several operational conditions on the stop penalty. Results show that the stop penalty varies significantly with all the investigated conditions and that the stop penalty is unique for different types of emissions. These findings may have significant implications on the current practice of sustainable signal timing optimization.

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“…The required computational time was considerably high and the solution could be a local optima. Stochastic approximation methodologies were used for the simultaneous calibration of traffic flow model parameters (Park et al, 2009;Park and Kamarajugadda, 2007;Chien, 1982). The SPSA (Spall, 1998) has been widely used for the calibration of various traffic flow models.…”

Section: Introductionmentioning

confidence: 99%

Calibration of traffic flow models using a memetic algorithm

Paz

Molano

Martinez

et al. 2015

Transportation Research Part C: Emerging Technologies

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a b s t r a c tA Memetic Algorithm (MA) for the calibration of microscopic traffic flow simulation models is proposed in this study. The proposed MA includes a combination of genetic and simulated annealing algorithms. The genetic algorithm performs the exploration of the search space and identifies a zone where a possible global solution could be located. After this zone has been found, the simulated annealing algorithm refines the search and locates an optimal set of parameters within that zone. The design and implementation of this methodology seeks to enable the generalized calibration of microscopic traffic flow models. Two different Corridor Simulation (CORSIM) vehicular traffic systems were calibrated for this study. All parameters after the calibration were within reasonable boundaries. The calibration methodology was developed independently of the characteristics of the traffic flow models. Hence, it is easily used for the calibration of any other model. The proposed methodology has the capability to calibrate all model parameters, considering multiple performance measures and time periods simultaneously. A comparison between the proposed MA and the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm was provided; results were similar between the two. However, the effort required to finetune the MA was considerably smaller when compared to the SPSA. The running time of the MA-based calibration was larger when it was compared to the SPSA running time. The MA still required some knowledge of the model in order to set adequate optimization parameters. The perturbation of the parameters during the mutation process must have been large enough to create a measurable change in the objective function, but not too large to avoid noisy measurements.Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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Stochastic Optimization for Sustainable Traffic Signal Control

Cited by 66 publications

References 5 publications

Arterial Offset Optimization Considering the Delay and Emission of Platoon: A Case Study in Beijing

Arterial Offset Optimization Considering the Delay and Emission of Platoon: A Case Study in Beijing

Impact of Various Operating Conditions on Simulated Emissions-Based Stop Penalty at Signalized Intersections

Calibration of traffic flow models using a memetic algorithm

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