Dynamically Predicting Corridor Travel Time Under Incident Conditions Using A Neural Network Approach
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Author |
: Xiaosi Zeng |
Publisher |
: |
Total Pages |
: |
Release |
: 2011 |
ISBN-10 |
: OCLC:706505463 |
ISBN-13 |
: |
Rating |
: 4/5 (63 Downloads) |
Synopsis Dynamically Predicting Corridor Travel Time Under Incident Conditions Using a Neural Network Approach by : Xiaosi Zeng
The artificial neural network (ANN) approach has been recognized as a capable technique to model the highly complex and nonlinear problem of travel time prediction. In addition to the nonlinearity, a traffic system is also temporally and spatially dynamic. Addressing the temporal-spatial relationships of a traffic system in the context of neural networks, however, has not received much attention. Furthermore, many of the past studies have not fully explored the inclusion of incident information into the ANN model development, despite that incident might be a major source of prediction degradations. Additionally, directly deriving corridor travel times in a one-step manner raises some intractable problems, such as pairing input-target data, which have not yet been adequately discussed. In this study, the corridor travel time prediction problem has been divided into two stages with the first stage on prediction of the segment travel time and the second stage on corridor travel time aggregation methodologies of the predicted segmental results. To address the dynamic nature of traffic system that are often under the influence of incidents, time delay neural network (TDNN), state-space neural network (SSNN), and an extended state-space neural network (ExtSSNN) that incorporates incident inputs are evaluated for travel time prediction along with a traditional back propagation neural network (BP) and compared with baseline methods based on historical data. In the first stage, the empirical results show that the SSNN and ExtSSNN, which are both trained with Bayesian regulated Levenberg Marquardt algorithm, outperform other models. It is also concluded that the incident information is redundant to the travel time prediction problem with speed and volume data as inputs. In the second stage, the evaluations on the applications of the SSNN model to predict snapshot travel times and experienced travel times are made. The outcomes of these evaluations are satisfactory and the method is found to be practically significant in that it (1) explicitly reconstructs the temporalspatial traffic dynamics in the model, (2) is extendable to arbitrary O-D pairs without complete retraining of the model, and (3) can be used to predict both traveler experiences and system overall conditions.
Author |
: Yang Tao |
Publisher |
: |
Total Pages |
: 208 |
Release |
: 2005 |
ISBN-10 |
: WISC:89091720243 |
ISBN-13 |
: |
Rating |
: 4/5 (43 Downloads) |
Synopsis Travel Time Prediction in the Prescence of Traffic Incidents by : Yang Tao
Author |
: J. W. C. van Lint |
Publisher |
: |
Total Pages |
: 332 |
Release |
: 2004 |
ISBN-10 |
: NWU:35556035570134 |
ISBN-13 |
: |
Rating |
: 4/5 (34 Downloads) |
Synopsis Reliable Travel Time Prediction for Freeways by : J. W. C. van Lint
Author |
: Charles D. Mark |
Publisher |
: |
Total Pages |
: 390 |
Release |
: 2005 |
ISBN-10 |
: OCLC:60358825 |
ISBN-13 |
: |
Rating |
: 4/5 (25 Downloads) |
Synopsis Predicting Experienced Travel Time for Freeway and Arterial Systems by : Charles D. Mark
Author |
: Chronis Stamatiadis |
Publisher |
: |
Total Pages |
: 464 |
Release |
: 1992 |
ISBN-10 |
: MSU:31293008990198 |
ISBN-13 |
: |
Rating |
: 4/5 (98 Downloads) |
Synopsis Travel Time Predictions Under Dynamic Route Guidance with a Recursive Adaptive Algorithm by : Chronis Stamatiadis
Author |
: Mohamed Zaki |
Publisher |
: Infinite Study |
Total Pages |
: 16 |
Release |
: |
ISBN-10 |
: |
ISBN-13 |
: |
Rating |
: 4/5 ( Downloads) |
Synopsis Travel Time Prediction under Egypt Heterogeneous Traffic Conditions using Neural Network and Data Fusion by : Mohamed Zaki
Cairo is experiencing traffic congestion that places it among the worst in the world. Obviously, it is difficult if not impossible to solve the transportation problem because it is multi-dimensional problem but it's good to reduce this waste of money and the associated waste of time resulting from congestion.
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: |
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: |
Total Pages |
: 564 |
Release |
: 1999 |
ISBN-10 |
: UCBK:C100827439 |
ISBN-13 |
: |
Rating |
: 4/5 (39 Downloads) |
Synopsis Geomaterials by :
Author |
: Rossitza Setchi |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 719 |
Release |
: 2010-08-30 |
ISBN-10 |
: 9783642153860 |
ISBN-13 |
: 3642153860 |
Rating |
: 4/5 (60 Downloads) |
Synopsis Knowledge-Based and Intelligent Information and Engineering Systems by : Rossitza Setchi
The four-volume set LNAI 6276--6279 constitutes the refereed proceedings of the 14th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2010, held in Cardiff, UK, in September 2010. The 272 revised papers presented were carefully reviewed and selected from 360 submissions. They present the results of high-quality research on a broad range of intelligent systems topics.
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: |
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: |
Total Pages |
: 700 |
Release |
: 1999 |
ISBN-10 |
: UOM:39015048116944 |
ISBN-13 |
: |
Rating |
: 4/5 (44 Downloads) |
Synopsis Transportation Research Record by :
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: |
Publisher |
: |
Total Pages |
: 82 |
Release |
: 1997 |
ISBN-10 |
: UCBK:C101102615 |
ISBN-13 |
: |
Rating |
: 4/5 (15 Downloads) |
Synopsis Prediction of Traffic Conditions Along the I-4 Central Corridor by :