Introduction to Real World Traffic
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10.1016/j.ijpe.2020.108009
The case study on a real-world traffic network comprised of 0.
The case study on a real-world traffic network comprised of 0.
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10.1109/ICPR48806.2021.9412506
Extensive experiments on a real-world traffic state dataset validate the effectiveness of our method by showing that GLT-GCRNN outperforms the state-of-the-art methods in terms of different metrics.
Extensive experiments on a real-world traffic state dataset validate the effectiveness of our method by showing that GLT-GCRNN outperforms the state-of-the-art methods in terms of different metrics.
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10.1504/ijspm.2021.117336
The model was built by adding complexity and the simulated results are analysed and compared for real-world traffic performance.
The model was built by adding complexity and the simulated results are analysed and compared for real-world traffic performance.
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10.1109/VTC2021-Spring51267.2021.9448868
Our simulation results based on a real-world traffic data set demonstrate the advantages of the proposed approaches.
Our simulation results based on a real-world traffic data set demonstrate the advantages of the proposed approaches.
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10.23919/ACC50511.2021.9482675
Despite the low-order system dynamics, the piecewise fuel/efficiency map, gear shifting, and real-world traffic/road situations bring system discontinuities/switchings and pure state constraints into the problem formulation, which make the problem highly nonlinear and nontrivial to solve.
Despite the low-order system dynamics, the piecewise fuel/efficiency map, gear shifting, and real-world traffic/road situations bring system discontinuities/switchings and pure state constraints into the problem formulation, which make the problem highly nonlinear and nontrivial to solve.
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10.1109/ICACI52617.2021.9435905
To validate the proposed system, experiments are performed on the real-world traffic data provided by the Aliyun Tianchi platform.
To validate the proposed system, experiments are performed on the real-world traffic data provided by the Aliyun Tianchi platform.
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10.1109/TMC.2020.2971470
The key problem in C-RAN optimization is to dynamically allocate BBUs and map them to RRHs under cost and quality constraints, since real-world traffic and mobility are difficult to predict, and there are enormous numbers of candidate RRH-BBU mapping schemes.
The key problem in C-RAN optimization is to dynamically allocate BBUs and map them to RRHs under cost and quality constraints, since real-world traffic and mobility are difficult to predict, and there are enormous numbers of candidate RRH-BBU mapping schemes.
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10.1016/J.TRPRO.2021.01.014
While the former is able to represent many details of traffic and model large-scale, real-world traffic situations with a co-evolutionary approach, the latter provides an environment for provable mathematical statements and results on exact user equilibria.
While the former is able to represent many details of traffic and model large-scale, real-world traffic situations with a co-evolutionary approach, the latter provides an environment for provable mathematical statements and results on exact user equilibria.
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10.1109/JIOT.2020.3040615
To evaluate the effectiveness of FlexSensing, we simulate the mobility of different vehicles involved in the scenario at different times of the day based on real-world traffic data collected from the city of Helsinki and select a real-time object detection application for a case study.
To evaluate the effectiveness of FlexSensing, we simulate the mobility of different vehicles involved in the scenario at different times of the day based on real-world traffic data collected from the city of Helsinki and select a real-time object detection application for a case study.
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10.1109/TITS.2020.2983763
We evaluate T-MGCN on two real-world traffic datasets and observe improvement by approximately 3% to 6% as compared to the state-of-the-art baseline.
We evaluate T-MGCN on two real-world traffic datasets and observe improvement by approximately 3% to 6% as compared to the state-of-the-art baseline.
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10.4233/UUID:746F5F73-1876-4371-B142-F0F3117DED6A
Research objectives To address this concern, further insights are needed in how drivers monitor automation in complex real-world traffic, and how their behaviour and performance change with long-term automated driving experience.
Research objectives To address this concern, further insights are needed in how drivers monitor automation in complex real-world traffic, and how their behaviour and performance change with long-term automated driving experience.
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10.1109/itsc48978.2021.9564456
Imitation learning on real-world data has the potential to improve the simulation of real-world traffic.
Imitation learning on real-world data has the potential to improve the simulation of real-world traffic.
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10.1109/TITS.2020.2972198
The optimal speed control strategy is evaluated in both a simulated traffic scenario and a real-world traffic scenario.
The optimal speed control strategy is evaluated in both a simulated traffic scenario and a real-world traffic scenario.
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10.1109/LCSYS.2020.3040690
Despite the low-order system dynamics, the piecewise fuel/efficiency map, gear shifting, and real-world traffic/road situations bring system discontinuities/switchings and pure state constraints into the problem formulation, which make the problem highly nonlinear and nontrivial to solve.
Despite the low-order system dynamics, the piecewise fuel/efficiency map, gear shifting, and real-world traffic/road situations bring system discontinuities/switchings and pure state constraints into the problem formulation, which make the problem highly nonlinear and nontrivial to solve.
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10.1007/978-981-33-4669-7_10
The solution approach is then tested on medium and large realistic instances generated from real-world traffic on Paris-Orly airport to show the benefit of our approach.
The solution approach is then tested on medium and large realistic instances generated from real-world traffic on Paris-Orly airport to show the benefit of our approach.
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10.1145/3465481.3470113
We evaluate the performance of our method with synthetically generated but realistic traffic as well as on real-world traffic from a Tor exit node on the Internet.
We evaluate the performance of our method with synthetically generated but realistic traffic as well as on real-world traffic from a Tor exit node on the Internet.
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10.1021/acs.est.1c00412
In this study, the emissions in real-world traffic from Euro VI-compliant HDTs were compared to those from older classes, represented by Euro V, using high-resolution time-of-flight chemical ionization mass spectrometry.
In this study, the emissions in real-world traffic from Euro VI-compliant HDTs were compared to those from older classes, represented by Euro V, using high-resolution time-of-flight chemical ionization mass spectrometry.
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10.1109/ICPR48806.2021.9412056
Extensive experiments on real-world traffic surveillance benchmarks demonstrate the real-time performance of the proposed model while keeping comparable accuracy with state-of-the-art.
Extensive experiments on real-world traffic surveillance benchmarks demonstrate the real-time performance of the proposed model while keeping comparable accuracy with state-of-the-art.
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10.1145/3472305.3472324
We demonstrate this claim by applying our methodology to real-world traffic from DNS servers that use partial prefix-preserving anonymization.
We demonstrate this claim by applying our methodology to real-world traffic from DNS servers that use partial prefix-preserving anonymization.
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10.1109/access.2021.3108801
We compared the performance of the proposed load balancer with iptables DNAT and loopback based on the RFC2544 performance standard, and also performed tests simulating real-world traffic patterns by using IMIX traffic streams.
We compared the performance of the proposed load balancer with iptables DNAT and loopback based on the RFC2544 performance standard, and also performed tests simulating real-world traffic patterns by using IMIX traffic streams.
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10.1080/21680566.2021.1916646
We evaluate the framework on the real-world traffic dataset and obtain a consistent improvement of 6.
We evaluate the framework on the real-world traffic dataset and obtain a consistent improvement of 6.
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10.1109/IWQOS52092.2021.9521328
Our testbed evaluations confirm that, by using the live video streams derived from real-world traffic cameras, Soudain ensures the real-time requirement and achieves up to 25% improvement on the detection accuracy, compared with multiple state-of-the-art alternatives.
Our testbed evaluations confirm that, by using the live video streams derived from real-world traffic cameras, Soudain ensures the real-time requirement and achieves up to 25% improvement on the detection accuracy, compared with multiple state-of-the-art alternatives.
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10.1007/978-3-030-72073-5_22
In a real-world traffic scene, objects can appear in different sizes and pose different details.
In a real-world traffic scene, objects can appear in different sizes and pose different details.
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10.1109/itsc48978.2021.9564849
The proposed prediction method is carefully evaluated with real-world traffic data collected on Hwy 55 in Minnesota.
The proposed prediction method is carefully evaluated with real-world traffic data collected on Hwy 55 in Minnesota.
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10.3390/ijgi10040248
This article proposes the ST-Discovery algorithm, a novel unsupervised spatio-temporal data mining algorithm that facilitates effective data-driven discovery of RC dependencies induced by the road network topology using real-world traffic data.
This article proposes the ST-Discovery algorithm, a novel unsupervised spatio-temporal data mining algorithm that facilitates effective data-driven discovery of RC dependencies induced by the road network topology using real-world traffic data.
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10.1109/BigDataService52369.2021.00018
In this paper, we analyze how FL impacts the performance of object detection in a real-world traffic environment.
In this paper, we analyze how FL impacts the performance of object detection in a real-world traffic environment.
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10.1109/ICASSP39728.2021.9413812
We then apply our model to a real-world traffic sensor dataset to study traffic patterns during different configurations of the traffic lights at an intersection.
We then apply our model to a real-world traffic sensor dataset to study traffic patterns during different configurations of the traffic lights at an intersection.
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10.1109/IJCNN52387.2021.9533301
We evaluated both models on a real-world traffic dataset captured by surround-view fisheye cameras mounted on top of a vehicle.
We evaluated both models on a real-world traffic dataset captured by surround-view fisheye cameras mounted on top of a vehicle.
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10.5220/0010405700650071
Traditional iteration based approach as well as estimators adopted from control theory are discussed, benchmarked, and validated on real-world traffic data.
Traditional iteration based approach as well as estimators adopted from control theory are discussed, benchmarked, and validated on real-world traffic data.
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10.3390/APP11073061
It is a challenging task for self-driving vehicles in Real-World traffic scenarios to find a trade-off between the real-time performance and the high accuracy of the detection, recognition, and tracking in videos.
It is a challenging task for self-driving vehicles in Real-World traffic scenarios to find a trade-off between the real-time performance and the high accuracy of the detection, recognition, and tracking in videos.
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10.1145/3447382
We evaluate our approach on a real-world traffic dataset from a major ISP and Mobile Network Operator.
We evaluate our approach on a real-world traffic dataset from a major ISP and Mobile Network Operator.
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10.1016/J.TRC.2021.103339
We present a machine learning approach using Long-Short Term Memory Neural Networks (LSTM-NN), trained over real-world traffic data during hurricane evacuation (hurricanes Irma and Matthew) using different combinations of input features and forecast horizons.
We present a machine learning approach using Long-Short Term Memory Neural Networks (LSTM-NN), trained over real-world traffic data during hurricane evacuation (hurricanes Irma and Matthew) using different combinations of input features and forecast horizons.
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10.1016/J.NEUCOM.2021.06.028
We use real-world traffic data from two locations (i.
We use real-world traffic data from two locations (i.
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10.1145/3447548.3467430
We evaluate our model on multiple real-world traffic datasets and superior performance is achieved over state-of-the-art baselines.
We evaluate our model on multiple real-world traffic datasets and superior performance is achieved over state-of-the-art baselines.
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10.1007/978-981-16-2241-0_3
Trace-driven experiments with real-world traffic data show that the proposed approach derives accurate traffic conditions with the average accuracy as 80%, based on only 50 probe vehicles’ intervention.
Trace-driven experiments with real-world traffic data show that the proposed approach derives accurate traffic conditions with the average accuracy as 80%, based on only 50 probe vehicles’ intervention.
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10.1016/J.MEASUREMENT.2021.109676
Traditional iteration based approach as well as estimators adopted from control theory were benchmarked and validated on real-world traffic data as well as via microscopic traffic simulation.
Traditional iteration based approach as well as estimators adopted from control theory were benchmarked and validated on real-world traffic data as well as via microscopic traffic simulation.
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10.1109/TITS.2021.3113608
We conduct extensive numerical experiments on several real-world traffic data sets, and our results demonstrate the effectiveness of LATC in diverse missing scenarios.
We conduct extensive numerical experiments on several real-world traffic data sets, and our results demonstrate the effectiveness of LATC in diverse missing scenarios.
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10.5220/0010501407350744
We generate a large dataset of 30 million cycles by approximately replicating real-world traffic arrival patterns from archived loop detector data in a microscopic traffic simulator.
We generate a large dataset of 30 million cycles by approximately replicating real-world traffic arrival patterns from archived loop detector data in a microscopic traffic simulator.
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10.1109/tits.2020.2991757
We successfully show the overall evaluation of these proving grounds in terms of their capability to accommodate real-world traffic scenarios.
We successfully show the overall evaluation of these proving grounds in terms of their capability to accommodate real-world traffic scenarios.
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10.1109/LSP.2020.3037527
Experiments on three real-world traffic datasets have verified the superiority of the proposed model.
Experiments on three real-world traffic datasets have verified the superiority of the proposed model.
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10.1109/MERCon52712.2021.9525670
A simple LSTM model, LSTM encoder-decoder model, CNN-LSTM model and a Conv-LSTM model were designed and evaluated using a real-world traffic volume dataset for multiple prediction horizons.
A simple LSTM model, LSTM encoder-decoder model, CNN-LSTM model and a Conv-LSTM model were designed and evaluated using a real-world traffic volume dataset for multiple prediction horizons.
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10.23919/IFIPNetworking52078.2021.9472804
Additionally, we collect a real-world traffic flow dataset to evaluate the effectiveness of the approach.
Additionally, we collect a real-world traffic flow dataset to evaluate the effectiveness of the approach.
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10.1109/TITS.2021.3062072
We carry out experiments on synthetic traffic grid and real-world traffic network of Monaco city to compare with the existing A2C and Q-learning algorithms.
We carry out experiments on synthetic traffic grid and real-world traffic network of Monaco city to compare with the existing A2C and Q-learning algorithms.
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10.1109/ICASSP39728.2021.9414532
The experiment results suggest the proposed model can achieve 94% for F1 measure in the macro average of five labels on real-world traffic data.
The experiment results suggest the proposed model can achieve 94% for F1 measure in the macro average of five labels on real-world traffic data.
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10.1016/J.TRB.2021.03.007
Numerous continuum models have been proposed for freeway traffic, but their performance for real-world traffic flows has not been rigorously evaluated and compared in the literature.
Numerous continuum models have been proposed for freeway traffic, but their performance for real-world traffic flows has not been rigorously evaluated and compared in the literature.
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10.1109/ICASSP39728.2021.9414134
Extensive evaluations on real-world traffic flow data demonstrate the superiority of the proposed method.
Extensive evaluations on real-world traffic flow data demonstrate the superiority of the proposed method.
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10.1109/TIFS.2020.3046876
We collect two real-world traffic datasets and construct closed- and open-world evaluations to verify the effectiveness of FineWP.
We collect two real-world traffic datasets and construct closed- and open-world evaluations to verify the effectiveness of FineWP.
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10.1109/ICASSP39728.2021.9414596
Extensive experiments on two real-world traffic datasets demonstrate the superiority of our proposed approach.
Extensive experiments on two real-world traffic datasets demonstrate the superiority of our proposed approach.
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10.1109/SECON52354.2021.9491587
We use a real-world traffic dataset from the United States Department of Transportation Federal Highway Administration to evaluate optimal control decision determination performance of ReDS in comparison with the state-of-the-art methods.
We use a real-world traffic dataset from the United States Department of Transportation Federal Highway Administration to evaluate optimal control decision determination performance of ReDS in comparison with the state-of-the-art methods.
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10.1109/TIFS.2021.3050608
We collect real-world traffic datasets from 1,300 DApps with more than 169,000 flows.
We collect real-world traffic datasets from 1,300 DApps with more than 169,000 flows.
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10.1007/s10586-021-03393-2
We demonstrate how our classification scheme and all its configurations perform well on real-world traffic from a high performance computing network environment.
We demonstrate how our classification scheme and all its configurations perform well on real-world traffic from a high performance computing network environment.
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10.1016/J.TRC.2021.103188
We develop a microscopic simulation model of evacuation traffic in SUMO and calibrate it using real-world traffic data collected during the evacuation period of hurricane Irma for a segment in the Interstate highway in Florida.
We develop a microscopic simulation model of evacuation traffic in SUMO and calibrate it using real-world traffic data collected during the evacuation period of hurricane Irma for a segment in the Interstate highway in Florida.
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10.1109/ICDCS51616.2021.00073
Experimental results show the effectiveness of the proposed framework compared to state-of-the-art methods, and indicate the potential to be deployed into real-world traffic prediction systems.
Experimental results show the effectiveness of the proposed framework compared to state-of-the-art methods, and indicate the potential to be deployed into real-world traffic prediction systems.
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10.1109/TVCG.2021.3071387
We demonstrate the capability and effectiveness of VisCas with two case studies conducted on real-world traffic congestion and air pollution datasets with domain experts.
We demonstrate the capability and effectiveness of VisCas with two case studies conducted on real-world traffic congestion and air pollution datasets with domain experts.
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10.1109/IJCNN52387.2021.9533821
The uneven distribution hidden in the real-world traffic will cause performance degradation of the existing schemes.
The uneven distribution hidden in the real-world traffic will cause performance degradation of the existing schemes.
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10.1109/itsc48978.2021.9565011
Experiments on real-world traffic datasets demonstrate that the proposed model outperforms other baselines and has interpretability in real scenarios.
Experiments on real-world traffic datasets demonstrate that the proposed model outperforms other baselines and has interpretability in real scenarios.
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10.1109/INFOCOMWKSHPS51825.2021.9484477
We evaluate the effectiveness of the model on a real-world traffic dataset that we collected by using a tcpdump utility of Linux.
We evaluate the effectiveness of the model on a real-world traffic dataset that we collected by using a tcpdump utility of Linux.
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10.1016/J.ESWA.2021.115093
Large scale evaluation experiments were conducted using two real-world traffic datasets, and the experimental results indicate that the proposed model can achieve better balance between forecasting accuracy and computational efficiency compared to benchmark models.
Large scale evaluation experiments were conducted using two real-world traffic datasets, and the experimental results indicate that the proposed model can achieve better balance between forecasting accuracy and computational efficiency compared to benchmark models.
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10.1109/itsc48978.2021.9564771
A catalog with scenarios recorded in real-world traffic for resimulation must be assembled, defining a set of requirements the driving function must pass before release.
A catalog with scenarios recorded in real-world traffic for resimulation must be assembled, defining a set of requirements the driving function must pass before release.
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10.3390/JMSE9020149
For this purpose, vessel traffic data obtained in the western Baltic Sea based on the automatic identification system (AIS) is analysed to extract all close encounters between ships considered as real-world traffic situations with a potential risk of collision.
For this purpose, vessel traffic data obtained in the western Baltic Sea based on the automatic identification system (AIS) is analysed to extract all close encounters between ships considered as real-world traffic situations with a potential risk of collision.
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10.1007/S11042-020-10486-4
8% more accurate than the DHSTNet technique, for two different real-world traffic datasets.
8% more accurate than the DHSTNet technique, for two different real-world traffic datasets.
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10.1016/j.trb.2021.06.021
The proposed stochastic link-based FD was calibrated and validated using real-world traffic data obtained from two selected road segments in Hong Kong.
The proposed stochastic link-based FD was calibrated and validated using real-world traffic data obtained from two selected road segments in Hong Kong.
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10.1016/j.aap.2021.106322
By experiments with a real-world traffic accident dataset, we demonstrated the effectiveness and applicability of the framework.
By experiments with a real-world traffic accident dataset, we demonstrated the effectiveness and applicability of the framework.
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10.1109/TKDE.2021.3112977
Extensive experiments on real-world traffic flows demonstrate that DeFlow-Net outperforms existing solutions using standard convolutions, and spatial partition by pre-conceived regions further enhances the performance.
Extensive experiments on real-world traffic flows demonstrate that DeFlow-Net outperforms existing solutions using standard convolutions, and spatial partition by pre-conceived regions further enhances the performance.
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10.1007/s40825-021-00191-5
ΙΜΤ links a real-world traffic model, a dynamic emissions model and a Lagrangian dispersion model coupled with a boundary layer flow module.
ΙΜΤ links a real-world traffic model, a dynamic emissions model and a Lagrangian dispersion model coupled with a boundary layer flow module.
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10.3390/rs13040573
4% faster than the state-of-the-art model and while being able to generalize to different real-world traffic scenes.
4% faster than the state-of-the-art model and while being able to generalize to different real-world traffic scenes.
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10.1109/JIOT.2021.3064342
We implement a highly efficient prototype and conduct extensive experiments on two large-scale real-world traffic data sets collected by a modern ride-hailing platform.
We implement a highly efficient prototype and conduct extensive experiments on two large-scale real-world traffic data sets collected by a modern ride-hailing platform.
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10.1016/j.trc.2021.103372
Experiments are carried out on two real-world traffic networks, including traffic speed and flow datasets.
Experiments are carried out on two real-world traffic networks, including traffic speed and flow datasets.
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10.1016/J.EGYAI.2021.100051
The traditional fixed-profile test methods only indicate the effect of powertrain efficiency on fuel economy and cannot reflect the influences of control algorithms or driving behaviors on fuel consumption under real-world traffic conditions.
The traditional fixed-profile test methods only indicate the effect of powertrain efficiency on fuel economy and cannot reflect the influences of control algorithms or driving behaviors on fuel consumption under real-world traffic conditions.
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10.1016/J.RESS.2021.107800
The proposed methodology is demonstrated using a real-world traffic network in Southern California under earthquake considering deterministic and stochastic repair durations.
The proposed methodology is demonstrated using a real-world traffic network in Southern California under earthquake considering deterministic and stochastic repair durations.
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10.1109/MET52542.2021.00012
Thus, it does not provide sufficient expressiveness for users to define custom metamorphic relations nor means to automatically generate meaningful inputs based on such expressive metamorphic relations that reflect real-world traffic behaviors.
Thus, it does not provide sufficient expressiveness for users to define custom metamorphic relations nor means to automatically generate meaningful inputs based on such expressive metamorphic relations that reflect real-world traffic behaviors.
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10.1109/LRA.2021.3059628
The proposed method is qualitatively and quantitatively evaluated in real-world traffic scenarios with various baselines.
The proposed method is qualitatively and quantitatively evaluated in real-world traffic scenarios with various baselines.
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10.1109/tits.2021.3099031
The proposed solution surpasses state-of-art baselines based on real-world traffic datasets, which treat various real-time delays differently.
The proposed solution surpasses state-of-art baselines based on real-world traffic datasets, which treat various real-time delays differently.
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10.1145/3449639.3459272
We test ZTT in a diversity of real-world traffic scenarios and show that it is able to obtain a significant performance boost over static configurations suggested by experts.
We test ZTT in a diversity of real-world traffic scenarios and show that it is able to obtain a significant performance boost over static configurations suggested by experts.
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10.1109/TII.2020.3009280
Extensive experiments conducted on two real-world traffic datasets demonstrate that the proposed VGRAN model outperforms state-of-the-art approaches while capturing innate ambiguity of the predicted results.
Extensive experiments conducted on two real-world traffic datasets demonstrate that the proposed VGRAN model outperforms state-of-the-art approaches while capturing innate ambiguity of the predicted results.
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10.1016/J.ESWA.2021.115489
The proposal is validated through a simulation study based on real-world traffic data collected in Santiago, Chile.
The proposal is validated through a simulation study based on real-world traffic data collected in Santiago, Chile.
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10.1145/3466772.3467049
By conducting simulations on real-world traffic datasets, we demonstrate that our proposed weak signal detection scheme can achieve throughput gain of up to 3.
By conducting simulations on real-world traffic datasets, we demonstrate that our proposed weak signal detection scheme can achieve throughput gain of up to 3.
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10.1155/2021/6616800
Experimental results based on real-world traffic sensor data indicate that the structures of traffic causality graphs are time-varying; the traffic cause-effect interaction among different road segments during the peak time is more significant than that during the nonpeak time; and the critical road segments can be identified, which are mainly located at the intersections of arterial roads, undertaking the convergence and dispersion of large traffic flows.
Experimental results based on real-world traffic sensor data indicate that the structures of traffic causality graphs are time-varying; the traffic cause-effect interaction among different road segments during the peak time is more significant than that during the nonpeak time; and the critical road segments can be identified, which are mainly located at the intersections of arterial roads, undertaking the convergence and dispersion of large traffic flows.
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10.1109/TKDE.2021.3056502
Experiments on five real-world traffic flow datasets demonstrate that ASTGNN outperforms the state-of-the-art baselines.
Experiments on five real-world traffic flow datasets demonstrate that ASTGNN outperforms the state-of-the-art baselines.
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10.1016/j.neucom.2020.10.091
Experimental results on real-world traffic data show that the proposed method outperforms coupled Bayesian robust principal component analysis (coupled BRPCA), the rank sparsity tensor decomposition (RSTD), and standard normal deviates (SND) in detecting NRTC.
Experimental results on real-world traffic data show that the proposed method outperforms coupled Bayesian robust principal component analysis (coupled BRPCA), the rank sparsity tensor decomposition (RSTD), and standard normal deviates (SND) in detecting NRTC.
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10.1155/2021/6393951
This approach is implemented on real-world traffic flow data and demonstrates the prominent superiority.
This approach is implemented on real-world traffic flow data and demonstrates the prominent superiority.
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10.3233/sw-200408
An experimental evaluation of queries that reflect the requirements has been conducted using the real-world traffic simulation tool PTV Vissim.
An experimental evaluation of queries that reflect the requirements has been conducted using the real-world traffic simulation tool PTV Vissim.
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10.1109/tits.2021.3102983
Experimental results on the public traffic network datasets and real-world traffic network datasets generated by ourselves demonstrate our proposed model achieves better performance than the state-of-the-art ones.
Experimental results on the public traffic network datasets and real-world traffic network datasets generated by ourselves demonstrate our proposed model achieves better performance than the state-of-the-art ones.
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10.1109/OJITS.2021.3093712
While the use of real-world data for model parameter identification is a well-known method, NDS are commonly used to explore the behavior of drivers or to analyze real-world traffic situations.
While the use of real-world data for model parameter identification is a well-known method, NDS are commonly used to explore the behavior of drivers or to analyze real-world traffic situations.
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10.1109/TITS.2020.2997832
Experimental results based on real-world traffic data demonstrate that our proposed method outperforms other methods from various aspects.
Experimental results based on real-world traffic data demonstrate that our proposed method outperforms other methods from various aspects.
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10.1109/JIOT.2020.3034899
Real-world traffic sign recognition is an important step toward building autonomous vehicles, most of which highly dependent on deep neural networks (DNNs).
Real-world traffic sign recognition is an important step toward building autonomous vehicles, most of which highly dependent on deep neural networks (DNNs).
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10.1109/EuRAD48048.2021.00078
It is necessary to validate their functional performance in the installed state thoroughly, reliably, and efficiently under realistic conditions before deploying them in real-world traffic.
It is necessary to validate their functional performance in the installed state thoroughly, reliably, and efficiently under realistic conditions before deploying them in real-world traffic.
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10.1109/itsc48978.2021.9564544
Then the SGDE-S2S model and some other baseline models are tested on real-world traffic speed data of Chengdu, China.
Then the SGDE-S2S model and some other baseline models are tested on real-world traffic speed data of Chengdu, China.
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10.23919/Eusipco47968.2020.9287226
We validate it against two real-world traffic datasets and provide discussion why the entropy of codes is a reliable performance indicator.
We validate it against two real-world traffic datasets and provide discussion why the entropy of codes is a reliable performance indicator.
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10.1109/itsc48978.2021.9565117
The utility and efficiency of the recommendation framework are demonstrated using real-world traffic data.
The utility and efficiency of the recommendation framework are demonstrated using real-world traffic data.
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10.7717/peerj-cs.470
To evaluate the proposed model, four months of real-world traffic data are collected in Xiaoshan District, Hangzhou, China.
To evaluate the proposed model, four months of real-world traffic data are collected in Xiaoshan District, Hangzhou, China.
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10.1109/TVT.2020.3046501
We validate the accuracy of the analytical model by comparing it with simulations using real-world traffic data and vehicle distributions.
We validate the accuracy of the analytical model by comparing it with simulations using real-world traffic data and vehicle distributions.
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10.1016/J.JNCA.2021.103083
The key problem in Fog-RAN optimization is how to cluster complementary RRHs into communities and allocate adequate numbers of BBUs for the fog servers, since real-world traffic and mobility patterns are highly dynamic to model, and it is not trivial to find an optimal RRH clustering and BBU allocation scheme from potentially enormous numbers of candidates.
The key problem in Fog-RAN optimization is how to cluster complementary RRHs into communities and allocate adequate numbers of BBUs for the fog servers, since real-world traffic and mobility patterns are highly dynamic to model, and it is not trivial to find an optimal RRH clustering and BBU allocation scheme from potentially enormous numbers of candidates.
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10.1007/978-3-030-75768-7_8
With extensive experimental analysis, we have shown that our model has significantly outperformed the state-of-the-art models on three real-world traffic datasets from the Performance Measurement System (PeMS).
With extensive experimental analysis, we have shown that our model has significantly outperformed the state-of-the-art models on three real-world traffic datasets from the Performance Measurement System (PeMS).
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10.1049/IET-ITS.2018.5381
The proposed MCS was tested on real-world traffic via simulations to assess its performance compared to existing fixed-time system.
The proposed MCS was tested on real-world traffic via simulations to assess its performance compared to existing fixed-time system.
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10.1109/APPEEC45492.2019.8994675
In this work, we focus on the study on electric taxis (ETs) dispatching, with consideration of picking up customers and recharging, based on real-world traffic data of a large number of taxis in Beijing.
In this work, we focus on the study on electric taxis (ETs) dispatching, with consideration of picking up customers and recharging, based on real-world traffic data of a large number of taxis in Beijing.
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10.1109/ACCESS.2018.2888561
Finally, we conduct extensive experiments to evaluate STANN on three real-world traffic datasets.
Finally, we conduct extensive experiments to evaluate STANN on three real-world traffic datasets.
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10.24963/ijcai.2019/234
Extensive experiments on two real-world traffic datasets from Didi Chuxing have demonstrated our effectiveness.
Extensive experiments on two real-world traffic datasets from Didi Chuxing have demonstrated our effectiveness.
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10.1109/access.2019.2919103
The experimental results on the KITTI dataset and the UA-DETRAC dataset demonstrate that the CMNet can achieve efficient detection performance in terms of accuracy and speed for the real-world traffic surveillance data.
The experimental results on the KITTI dataset and the UA-DETRAC dataset demonstrate that the CMNet can achieve efficient detection performance in terms of accuracy and speed for the real-world traffic surveillance data.
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10.1109/MDM.2019.00-53
Finally, we conduct extensive experiments to evaluate STCNN on two real-world traffic datasets.
Finally, we conduct extensive experiments to evaluate STCNN on two real-world traffic datasets.
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