Online Calibration of Microscopic Road Traffic Simulator

Fang, Xuan; Tettamanti, Tamás; Piazzi, Arthur Couto

doi:10.1109/sami48414.2020.9108744

Cited by 6 publications

(6 citation statements)

References 14 publications

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“…NSGA-II is a multi-objective sorting genetic algorithm that combines elitism and does not require a priori selection of shared parameters. The highest-ranking topologies were selected for the next step using the tournament algorithm [ 21 ].…”

Section: Methodsmentioning

confidence: 99%

Dynamic Weight Agnostic Neural Networks and Medical Microwave Radiometry (MWR) for Breast Cancer Diagnostics

Galazis

Popov

et al. 2022

Diagnostics

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Background and Objective: Medical microwave radiometry (MWR) is used to capture the thermal properties of internal tissues and has usages in breast cancer detection. Our goal in this paper is to improve classification performance and investigate automated neural architecture search methods. Methods: We investigated extending the weight agnostic neural network by optimizing the weights using the bi-population covariance matrix adaptation evolution strategy (BIPOP-CMA-ES) once the topology was found. We evaluated and compared the model based on the F1 score, accuracy, precision, recall, and the number of connections. Results: The experiments were conducted on a dataset of 4912 patients, classified as low or high risk for breast cancer. The weight agnostic BIPOP-CMA-ES model achieved the best average performance. It obtained an F1-score of 0.933, accuracy of 0.932, precision of 0.929, recall of 0.942, and 163 connections. Conclusions: The results of the model are an indication of the promising potential of MWR utilizing a neural network-based diagnostic tool for cancer detection. By separating the tasks of topology search and weight training, we can improve the overall performance.

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Section: Methodsmentioning

confidence: 99%

Dynamic Weight Agnostic Neural Networks and Medical Microwave Radiometry (MWR) for Breast Cancer Diagnostics

Galazis

Popov

et al. 2022

Diagnostics

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“…We use the Non-dominated Sorting Genetic Algorithm II (NSGA-II) [20] to sort the network topologies. Then, the highest-ranking topologies are selected for the next step using tournament algorithm [21].…”

Section: Weight Agnostic Neural Networkmentioning

confidence: 99%

Dynamic Weight Agnostic Neural Networks and Medical Microwave Radiometry (MWR) for Breast Cancer Diagnostics

Li¹,

Galazis²,

Popov³

et al. 2022

Preprint

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Abstract Background and Objective: Medical Microwave Radiometry (MWR) is used to capture the thermal properties of internal tissues and has usages in breast cancer detection. Our goal in this paper is to improve classification performance and investigate automated neural architecture search methods. Methods: We investigate optimizing the weights of a weight agnostic neural network using bi-population covariance matrix adaptation evolution strategy (BIPOP-CMA-ES) once the topology is found. We compare it against a weight agnostic and cascade correlation neural network. Results: The experiments are conducted on a breast cancer dataset of 4912 patients. Our proposed weight agnostic BIPOP-CMA-ES model achieved the best performance. It obtained an F1-score of 0.9225, accuracy of 0.9219, precision of 0.9228, recall of 0.9217 and topology of 153 connections. Conclusions: The results are an indication of the potential of MWR utilizing a neural network-based diagnostic tool for cancer detection. By separating the tasks of topology search and weight training, we are able to improve the overall performance.

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“…The parameters in the simulation were calibrated and determined according to the data in the above section and the calibration method in Ref. [38]. Based on the calibration results, the driver's reaction time is around 600 ms, and with the transfer delay of the vehicle braking system, the total reaction time for the driver takes a value of 1 s in general.…”

Section: Simulation Model Parameters Selectionmentioning

confidence: 99%

“…In this paper, the SSAM-Based model under the influence of the left side hard shoulder is constructed using traffic conflict techniques, and the analysis method of the SSAM-Based model is referred to Ref. [38] to further compare the differences in vehicle conflicts on the left hard shoulder when used on one-way three-lane, four-lane, and five-lane highways based on safety and efficiency by summarizing the highway driving rules. The results show that for freeways with more than three lanes in one direction, the indexes MaxS and DeltaS are improved after installing the left hard shoulder than without the left hard shoulder.…”

Section: Theoretical and Practical Applicationsmentioning

confidence: 99%

Research on the Safety of the Left Hard Shoulder in a Multi-Lane Highway Based on Safety Performance Function

Zhao

et al. 2022

Sustainability

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The left hard shoulder plays an important role in the event of an emergency on the inside of a multi-lane highway, but past studies have not been able to clarify the criteria for its installation or quantify the safety impact of its installation on the left side. In order to study the influence of the left hard shoulder on the safety of vehicles traveling on multi-lane highways, based on past studies that only studied the situation of four-lane highways, this paper firstly constructs a multi-lane highway simulation model under different numbers of lanes based on the VISSIM traffic simulation and uses Surrogate Safety Assessment Model (SSAM) to study the conflict characteristics of multi-lane highway vehicles under different numbers of lanes. Based on the above findings, this paper introduces the Safety Performance Function (SPF) to construct a multi-lane freeway accident prediction model, calibrates the model by adding the indexes affected by the left side hard shoulder to the basic prediction mode, and uses the historical accident data of the Badou-Shihu section of the Guangdong Northern Second Ring Highway as the basis to study the differences in accident rates of the investigated section before and after setting the left hard shoulder. The study showed that the average Time to Collision (TTC) increased by 57.2%, Maximum Deceleration (MaxD) increased by 19.2%, and Delta Speed (DeltaS) increased by 15.3% after setting hard shoulders on the left side of multi-lane freeways, and traffic conflicts on multi-lane freeways were significantly reduced, and safety was improved considerably. In addition, the rear-end conflict rate decreased by 0.17%, 0.75%, and 4.6% after setting hard shoulders on the left side of one-way three, four, and five lanes, respectively, indicating that hard shoulders on the left side are the most effective in improving the safety of one-way five-lane freeways. The accident prediction results show that within the reasonable setting range of the left hard shoulder width (0~4 m), the accident rate decreases by about 1.5% for every 0.5 m increase if only the influence of the left hard shoulder width is considered. Without considering other factors, increasing the width of the hard shoulder on the left side can reduce the number of accidents. This indicates a significant safety improvement for a one-way five-lane highway after setting the hard shoulder on the left side, and the conclusion is consistent with the simulation results. In this paper, based on past research, the research object is extended to one-way three-, four-, and five-lane highways. The findings of this paper can help the road authorities develop specifications for installing hard shoulders on the left side of multi-lane freeways and adopt strategies to improve the traffic safety level of multi-lane freeways. In addition, the models and methods used in this paper can also help build a framework for future intelligent networked vehicle avoidance systems and promote the development of intelligent networked technologies.

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Online Calibration of Microscopic Road Traffic Simulator

Cited by 6 publications

References 14 publications

Dynamic Weight Agnostic Neural Networks and Medical Microwave Radiometry (MWR) for Breast Cancer Diagnostics

Dynamic Weight Agnostic Neural Networks and Medical Microwave Radiometry (MWR) for Breast Cancer Diagnostics

Dynamic Weight Agnostic Neural Networks and Medical Microwave Radiometry (MWR) for Breast Cancer Diagnostics

Research on the Safety of the Left Hard Shoulder in a Multi-Lane Highway Based on Safety Performance Function

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