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Travel Time Distribution under Interrupted Flow and Application to Travel Time Reliability
Transportation Research Record: Journal of the Transportation Research Board, 2014The travel time distribution under interrupted flow based on radio frequency identification–detected data is analyzed. The urban road network studied is in downtown Nanjing, Jiangsu Province, in China, where video cameras and radio frequency equipment are installed at some arterial links to acquire traffic flow data including vehicle type, passing ...
Fan Yang, Mei-Ping Yun, Xiao-Guang Yang
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Critical capacity, travel time delays and travel time distribution of rapid mass transit systems
Physica A: Statistical Mechanics and its Applications, 2014Abstract We set up a mechanistic agent-based model of a rapid mass transit system. Using empirical data from Singapore’s unidentifiable smart fare card, we validate our model by reconstructing actual travel demand and duration of travel statistics. We subsequently use this model to investigate two phenomena that are known to significantly affect the ...
Erika Fille Legara +3 more
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Trip travel time distribution prediction for urban signalized arterials
16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013), 2013Travel time prediction is a challenge, especially if we consider urban trips. For freeways well-known models for traffic flow and speeds are applicable, e.g., based on physical models inspired by hydrodynamic or statistical models ranging from more conventional to more advanced AI approaches.
Fangfang Zheng, Henk J. van Zuylen
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Travel Time Distribution Estimation by Learning Representations Over Temporal Attributed Graphs
IEEE transactions on intelligent transportation systems (Print), 2023Travel time estimation is a crucial task in practical transportation applications, while providing the reliability of estimation is important in many working scenarios.
Wanyi Zhou +10 more
semanticscholar +1 more source
Learn Travel Time Distribution with Graph Deep Learning and Generative Adversarial Network
International Conference on Intelligent Transportation Systems, 2021How to obtain accurate travel time predictions is among the most critical problems in Intelligent Transportation Systems (ITS). Recent literature has shown the effectiveness of machine learning models on travel time forecasting problems. However, most of
Xiaozhuang Song +2 more
semanticscholar +1 more source
A novel approach for vehicle travel time distribution: copula-based dependent discrete convolution
Transportation letters, 2021Travel time reliability is considered as one of the key indicators for the performance of transportation systems. The majority of studies concerning estimating arterial travel time distribution commonly assume that the path travel time follows a certain ...
Adam Samara +2 more
semanticscholar +1 more source
Transportmetrica A: Transport Science, 2021
This paper proposes a dynamic vehicle count estimation method for signalized links using license plate recognition (LPR) data considering the recognition errors. The framework contains three sub-components. First, travel time probability density function
Chunguang He +4 more
semanticscholar +1 more source
This paper proposes a dynamic vehicle count estimation method for signalized links using license plate recognition (LPR) data considering the recognition errors. The framework contains three sub-components. First, travel time probability density function
Chunguang He +4 more
semanticscholar +1 more source
Transportation Research Record: Journal of the Transportation Research Board, 2021
Travel time reliability quantifies variability in travel times and has become a critical aspect for evaluating transportation network performance. The empirical travel time cumulative distribution function (CDF) has been used as a tool to preserve inherent information on the variability and distribution of travel times.
Xiaoxiao Zhang +3 more
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Travel time reliability quantifies variability in travel times and has become a critical aspect for evaluating transportation network performance. The empirical travel time cumulative distribution function (CDF) has been used as a tool to preserve inherent information on the variability and distribution of travel times.
Xiaoxiao Zhang +3 more
openaire +1 more source
Estimation of Link Travel Time Distribution With Limited Traffic Detectors
IEEE transactions on intelligent transportation systems (Print), 2020Motivated by the network tomography, in this paper, we present a novel methodology to estimate link travel time distributions (TTDs) using end-to-end (E2E) measurements detected by the limited traffic detectors at or near the road intersections. As it is
Peibo Duan +3 more
semanticscholar +1 more source
Estimation of urban arterial travel time distribution considering link correlations
Transportmetrica A: Transport Science, 2020This study proposes a pair-copula construction approach to estimate the probability distribution of urban arterial travel times from link travel time distributions (TTDs).
Wenwen Qin, Xiaofeng Ji, Feiwen Liang
semanticscholar +1 more source