A novel approach for vehicle travel time distribution: copula-based dependent discrete convolution

Despite the wide application of floating car data (FCD) in urban link travel time estimation, limited efforts have been made to determine the minimum sample size of floating cars appropriate to the requirements for travel time distribution (TTD) estimation. This study develops a framework for seeking the required minimum number of travel time observations generated from FCD for urban link TTD estimation. The basic idea is to test how, with a decreasing the number of observations, the similarities between the distribution of estimated travel time from observations and those from the ground-truth vary. These are measured by employing the Hellinger Distance (HD) and Kolmogorov-Smirnov (KS) tests. Finally, the minimum sample size is determined by the HD value, ensuring that corresponding distribution passes the KS test. The proposed method is validated with the sources of FCD and Radio Frequency Identification Data (RFID) collected from an urban arterial in Nanjing, China. The results indicate that: (1) the average travel times derived from FCD give good estimation accuracy for real-time application; (2) the minimum required sample size range changes with the extent of time-varying fluctuations in traffic flows; (3) the minimum sample size determination is sensitive to whether observations are aggregated near each peak in the multistate distribution; (4) sparse and incomplete observations from FCD in most time periods cannot be used to achieve the minimum sample size. Moreover, this would produce a significant deviation from the ground-truth distributions. Finally, FCD is strongly recommended for better TTD estimation incorporating both historical trends and real-time observations.

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Estimation of urban route travel time distribution using Markov chains and pair-copula construction

Transportmetrica B Transport Dynamics ◽

10.1080/21680566.2019.1637798 ◽

2019 ◽

Vol 7 (1) ◽

pp. 1521-1552 ◽

Cited By ~ 3

Author(s):

Meiping Yun ◽

Wenwen Qin ◽

Xiaoguang Yang ◽

Feiwen Liang

Keyword(s):

Markov Chains ◽

Travel Time ◽

Time Distribution ◽

Travel Time Distribution

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Evaluating Travel Time Reliability Based on Fuzzy Logic

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.97-98.952 ◽

2011 ◽

Vol 97-98 ◽

pp. 952-955

Author(s):

Xiong Fei Zhang ◽

Rui Min Li ◽

Min Liu ◽

Qi Xin Shi

Keyword(s):

Fuzzy Logic ◽

Travel Time ◽

Time Distribution ◽

Travel Time Reliability ◽

Statistical Measures ◽

Travel Time Distribution ◽

Network Operations ◽

Deviation Coefficient ◽

Measure Of Performance ◽

Stochastic Properties

Travel time reliability, as a measure of performance, is attracting more and more attention because unreliable transportation information hinders travelers’ decision making and creates difficulties for authorities to manage network operations. Since travel time reliability is closely related to the stochastic properties of the day-to-day travel time distribution, several statistical measures have been proposed, including standard deviation, coefficient of variation, buffer index, misery index and so on. Each of these measures is derived from travel time distribution but captures only one or two characteristics of travel time. In this paper, an effort is made to evaluate travel time reliability incorporating as many characteristics of travel time as possible based on fuzzy logic. The basic rules are: (1) the larger the variance is, the more unreliable the travel time is; (2) the larger the travel times of unlucky travelers are, the more unreliable the travel time is; (3) the larger the distribution skews to the left, the more unreliable the travel time is. The proposed methodology has been tested and analyzed with field data.

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Travel Time Reliability Measures Accommodating Scheduling Preferences of Travelers

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198119836980 ◽

2019 ◽

Vol 2673 (4) ◽

pp. 708-721 ◽

Cited By ~ 1

Author(s):

Mojtaba Rajabi-Bahaabadi ◽

Afshin Shariat-Mohaymany ◽

Shu Yang

Keyword(s):

Travel Time ◽

Time Distribution ◽

Travel Time Reliability ◽

Time Data ◽

Reliability Measures ◽

Time Performance ◽

Early Arrival ◽

Travel Time Distribution ◽

Travel Time Data ◽

Schedule Adherence

Existing travel time reliability measures fail to accommodate scheduling preferences of travelers and cannot distinguish between the variability associated with early and late arrivals. This study introduces two new travel time reliability measures based on concepts from behavioral economics. The first proposed measure is an indicator of the width of travel time distribution. It considers scheduling preferences of travelers and can distinguish between early arrival and late arrival. The second measure determines the skewness of travel time distribution. To estimate the proposed measures, travel time is modeled by mixture models and closed-form expressions are derived for the expected values of early and late arrivals. In addition, real travel time data from a freeway segment is used to compare the proposed measures with the existing travel time reliability measures. The results suggest that, although there exist significant correlations between travel time reliability measures, travelers’ preferences have considerable effects on the travel time reliability as perceived by them. Furthermore, four measures are developed based on the notions of early and late arrivals to assess the on-time performance (schedule adherence) of transit vehicles at stop level. The results of this study show that the four measures can serve as complementary to the existing on-time performance indices.

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