Performance Evaluation of Travel-Time Estimation Methods for Real-Time Traffic Applications

2010 ◽  
Vol 14 (2) ◽  
pp. 54-67 ◽  
Author(s):  
Xuegang Jeff Ban ◽  
Yuwei Li ◽  
Alexander Skabardonis ◽  
J. D. Margulici
Keyword(s):  
Performance Evaluation ◽  
Travel Time ◽  
Real Time ◽  
Time Estimation ◽  
Estimation Methods ◽  
Travel Time Estimation ◽  
Real Time Traffic

Dynamic Travel Time Estimation Techniques for Urban Freight Transportation Networks Using Historical and Real-Time Data

2011 ◽  
pp. 252-273
Author(s):  
Vasileios Zeimpekis
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Real Life ◽  
Time Estimation ◽  
Travel Time Estimation ◽  
Travel Time Prediction ◽  
Time Data ◽  
Urban Freight ◽  
Real Time Traffic ◽  
Real Time Data

Effective travel time prediction is of great importance for efficient real-time management of freight deliveries, especially in urban networks. This is due to the need for dynamic handling of unexpected events, which is an important factor for successful completion of a delivery schedule in a predefined time period. This chapter discusses the prediction results generated by two travel time estimation methods that use historical and real-time data respectively. The first method follows the k-nn model, which relies on the non-parametric regression method, whereas the second one relies on an interpolation scheme which is employed during the transmission of real-time traffic data in fixed intervals. The study focuses on exploring the interaction of factors that affect prediction accuracy by modelling both prediction methods. The data employed are provided by real-life scenarios of a freight carrier and the experiments follow a 2-level full factorial design approach.

Real-time Travel Time Estimation with Sparse Reliable Surveillance Information

2020 ◽  
Vol 4 (1) ◽  
pp. 1-23
Author(s):  
Wen Zhang ◽  
Yang Wang ◽  
Xike Xie ◽  
Chuancai Ge ◽  
Hengchang Liu
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Time Estimation ◽  
Time Travel ◽  
Travel Time Estimation

scholarly journals An Optimization Method of Time Window Based on Travel Time and Reliability

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Fengjie Fu ◽  
Dongfang Ma ◽  
Dianhai Wang ◽  
Wei Qian
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Time Window ◽  
Time Windows ◽  
Time Estimation ◽  
Optimization Method ◽  
Time Change ◽  
Basic Unit ◽  
Optimal Time ◽  
Travel Time Estimation

The dynamic change of urban road travel time was analyzed using video image detector data, and it showed cyclic variation, so the signal cycle length at the upstream intersection was conducted as the basic unit of time window; there was some evidence of bimodality in the actual travel time distributions; therefore, the fitting parameters of the travel time bimodal distribution were estimated using the EM algorithm. Then the weighted average value of the two means was indicated as the travel time estimation value, and the Modified Buffer Time Index (MBIT) was expressed as travel time variability; based on the characteristics of travel time change and MBIT along with different time windows, the time window was optimized dynamically for minimum MBIT, requiring that the travel time change be lower than the threshold value and traffic incidents can be detected real time; finally, travel times on Shandong Road in Qingdao were estimated every 10 s, 120 s, optimal time windows, and 480 s and the comparisons demonstrated that travel time estimation in optimal time windows can exactly and steadily reflect the real-time traffic. It verifies the effectiveness of the optimization method.

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