Estimation of travel time reliability in large-scale networks

Babaei, Mohsen; Rajabi-Bahaabadi, Mojtaba; Mohaymany, Afshin Shariat

doi:10.1080/19427867.2015.1122141

Cited by 12 publications

(2 citation statements)

References 15 publications

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“…Airports B and C can be directly connected by route BC or indirectly connected by BE and EC. There are no direct routes between A and D. Currently, there is no general definition of air traffic reliability [35][36][37][38]. Based on the characteristic analysis of air traffic, we propose a definition of air traffic reliability, that is, the ability of the air traffic network to continuously satisfy the air traffic demand under the influence of random factors on air traffic operation within a certain period of time [37].…”

Section: Modeling Of the Air Traffic Networkmentioning

confidence: 99%

Reliability Analysis of an Air Traffic Network: From Network Structure to Transport Function

Zhang

Cheng

2020

Applied Sciences

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To scientifically evaluate the reliability of air traffic networks, a definition of air traffic network reliability is proposed in this paper. Calculation models of the connectivity reliability, travel-time reliability, and capacity reliability of the air traffic network are constructed based on collected historical data, considering the current status and the predicted future evolution trends. Considering the randomness and fuzziness of factors affecting reliability, a comprehensive evaluation model of air traffic networks based on the uncertainty transformation model is established. Finally, the reliability of the US air traffic network is analyzed based on data published by the Transportation Statistics Bureau of the US Department of Transportation. The results show that the connectivity reliability is 0.4073, the capacity reliability is 0.8300, the travel-time reliability is 0.9180, and the overall reliability evaluated is “relatively reliable”. This indicates that although the US structural reliability is relatively low, the US air traffic management is very efficient, and the overall reliability is strong. The reliability in nonpeak hours is much higher than that in peak hours. The method can identify air traffic network reliability efficiently. The main factors affecting reliability can be found in the calculation process, and are beneficial for air traffic planning and management. The empirical analysis also reflects that the evaluation model based on the uncertainty transformation model can transform the quantitative data of network structure and traffic function into the qualitative language of reliability.

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Section: Modeling Of the Air Traffic Networkmentioning

confidence: 99%

Reliability Analysis of an Air Traffic Network: From Network Structure to Transport Function

Zhang

Cheng

2020

Applied Sciences

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“…In addition, while serving passengers at a bus stop, the interaction among buses and passengers may constraint the discharge flows of buses and degrade the bus systems' service quality overall [11,12]. Consequently, the bus dwell time estimation is essential for improving the service quality as well as reliability of the public transit system [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Impact of Carriage Crowding Level on Bus Dwell Time: Modelling and Analysis

Bie

Wang

Zhang

2020

Journal of Advanced Transportation

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This paper develops two types of estimation models to quantify the impacts of carriage crowding level on bus dwell time. The first model (model I) takes the crowding level and the number of alighting and boarding passengers into consideration and estimates the alighting time and boarding time, respectively. The second model (model II) adopts almost the same regression method, except that the impact of crowding on dwell time is neglected. The analysis was conducted along two major bus routes in Harbin, China, by collecting 640 groups of dwell times under crowded condition manually. Compared with model II, the mean absolute error (MAE) of model I is reduced by 137.51%, which indicates that the accuracy of bus dwell time estimation could be highly improved by introducing carriage crowding level into the model. Meanwhile, the MAE of model I is about 3.9 seconds, which is acceptable in travel time estimation and bus schedule.

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Finding the $$\mathrm{K}$$ Mean-Standard Deviation Shortest Paths Under Travel Time Uncertainty

Song,

Cheng,

et al. 2024

Netw Spat Econ

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Estimation of travel time reliability in large-scale networks

Cited by 12 publications

References 15 publications

Reliability Analysis of an Air Traffic Network: From Network Structure to Transport Function

Reliability Analysis of an Air Traffic Network: From Network Structure to Transport Function

Impact of Carriage Crowding Level on Bus Dwell Time: Modelling and Analysis

Finding the $$\mathrm{K}$$ Mean-Standard Deviation Shortest Paths Under Travel Time Uncertainty

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