Stochastic Optimal-Control Approach to Automatic Incident-Responsive Coordinated Ramp Control

Sheu, Jiuh‐Biing; Chang, Mei‐Shiang

doi:10.1109/tits.2007.893327

Cited by 18 publications

(9 citation statements)

References 10 publications

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“…It has long been recognized that nonrecurring events can cause at least half of the total traffic congestion (6). Over the years, extensive effort has been invested in studying how to alleviate nonrecurrent congestion with automatic signal control methods (7)(8)(9). A few studies have focused on manual control operation.…”

Section: Literature Reviewmentioning

confidence: 99%

Performance Measures of Manual Multimodal Traffic Signal Control

Ding

2014

Transportation Research Record: Journal of the Transportation R

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Representatives of traffic control agencies (TCAs)—including police officers, firefighters, and other traffic law enforcement officers who override automatic traffic signal controls—are crucial to the mitigation of nonrecurrent traffic congestion caused by planned and unplanned events. An unanswered question is how well TCA officers perform compared with state-of-practice automatic traffic signal controls. This study assessed the performance of TCA manual multimodal traffic signal control during special events. First, an interview was designed to promote understanding of the control rules of TCAs and the practice of manual traffic signal control. Next, a simulation experiment was conducted to record control actions during multimodal traffic flows containing buses, pedestrians, and passenger cars. Third, a TCA performance index was developed through a comparison of manual control with actuated signal control and optimal control solutions from an online optimization model, which assumed the availability of rich vehicle information, to determine the best control strategies. The results show that manual traffic control can significantly improve control performance, even to the point of approaching the performance of the optimized timing plan. Large variations, however, were observed during the study.

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Section: Literature Reviewmentioning

confidence: 99%

Performance Measures of Manual Multimodal Traffic Signal Control

Ding

2014

Transportation Research Record: Journal of the Transportation R

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“…e variables that must be considered to obtain a better response rate include key requirements, competition priority, time urgency, and availability of necessary resource allocation. However, potential transportation and condition restrictions have hindered the provision of emergency services [13,[18][19][20]. Emergency dispatch coordinators and decision-makers often make wrong decisions during natural disasters.…”

Section: Introductionmentioning

confidence: 99%

Research on the Scheduling of Tractors in the Major Epidemic to Ensure Spring Ploughing

Chen

Zhang

et al. 2021

Mathematical Problems in Engineering

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When the outbreak of COVID-19 began, people could not go out. It was not allowed to provide agricultural machinery services in different places across regions to reduce the flow and gathering of people. Improvement of utilization efficiency of agricultural machinery resources is required through scientific scheduling of agricultural machinery. With seizing the farming season and stabilizing production as the goal, this paper studied the scientific scheduling of tractors within the scope of town and established agricultural machinery operation scheduling model with the minimization of total scheduling cost as the optimization objective. Factors such as farmland area, agricultural machinery, and farmland location information and operating time window are considered in this model to improve the accuracy of the agricultural machinery operation scheduling model. The characteristics of multiple scheduling algorithms are analyzed comprehensively. The scheduling requirements of agricultural machinery operation to ensure spring ploughing are combined to design the agricultural machinery scheduling algorithm based on the SA algorithm. With Hushu Street, Jiangning District, Nanjing City, as an example, a comparative experiment is conducted on the simulated annealing algorithm (SA) designed in this paper and the empirical algorithm and genetic algorithm (GA). The results suggest that the total cost of the scheduling scheme generated by the SA algorithm is 19,042.07 yuan lower than that by the empirical scheduling algorithm and 779.19 yuan lower than that by the genetic algorithm on average. Compared with the GA algorithm, the transfer distance, waiting cost, and delay cost of the SA algorithm are reduced by 11.6%, 100%, and 98.1% on average, indicating that the transfer distance of agricultural machinery in the scheduling scheme generated by the SA algorithm is shorter, so is the waiting and delay time. Meanwhile, it can effectively obtain the near-optimal solution that meets the time window constraint, with good convergence, stability, and adaptability.

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“…A more complex system with consideration of dynamic incident duration was developed in [16] which can be solved by the linear programming technique. In the research presented in [17,18], both lanechanging and queuing behaviour during the incident were incorporated into a modelling structure and solved by a stochastic optimal control system. Although these systems are based on different technologies, they all need a model to predict traffic conditions and use these predictions to accomplish the control process.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Ramp Control for Incident Response Using Dyna-QArchitecture

Lü

Zhao

Gong

2015

Mathematical Problems in Engineering

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Reinforcement learning (RL) has shown great potential for motorway ramp control, especially under the congestion caused by incidents. However, existing applications limited to single-agent tasks and based onQ-learning have inherent drawbacks for dealing with coordinated ramp control problems. For solving these problems, a Dyna-Qbased multiagent reinforcement learning (MARL) system named Dyna-MARL has been developed in this paper. Dyna-Qis an extension ofQ-learning, which combines model-free and model-based methods to obtain benefits from both sides. The performance of Dyna-MARL is tested in a simulated motorway segment in the UK with the real traffic data collected from AM peak hours. The test results compared with Isolated RL and noncontrolled situations show that Dyna-MARL can achieve a superior performance on improving the traffic operation with respect to increasing total throughput, reducing total travel time and CO2emission. Moreover, with a suitable coordination strategy, Dyna-MARL can maintain a highly equitable motorway system by balancing the travel time of road users from different on-ramps.

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Stochastic Optimal-Control Approach to Automatic Incident-Responsive Coordinated Ramp Control

Cited by 18 publications

References 10 publications

Performance Measures of Manual Multimodal Traffic Signal Control

Performance Measures of Manual Multimodal Traffic Signal Control

Research on the Scheduling of Tractors in the Major Epidemic to Ensure Spring Ploughing

Intelligent Ramp Control for Incident Response Using Dyna-QArchitecture

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