Travel Time Prediction Models for Urban Corridor: A Case Study of Delhi
This study attempts to make use of traffic behaviour on the aggregate level to estimate congestion on urban arterial and sub-arterial roads of a city exhibiting heterogeneous traffic conditions by breaking the route into independent segments and approximating the origin-destination based traffic flow behaviour of the segments. The expected travel time in making a trip is modelled against sectional traffic characteristics (flow and speed) at origin and destination points of road segments, and roadway and segment traffic characteristics such as diversion routes are also tried in accounting for travel time. Predicted travel time is then used along with free flow time to determine the state of congestion on the segments using a congestion index (CI). Travel time is calculated using regression and ANN techniques and comparison has been made. A development of this kind may help in understanding traffic and congestion behaviour practically using easily accessible inputs, limited only to the nodes, and help in improving road network planning and management.
 Chang, H., Park, D., Lee, S., Lee, H. and Baek, S. 2010. Dynamic Multi-Interval Bus Travel Time prediction Using Bus Transit Data, Transportmetrica, Vol. 6, No.1, pp. 19-38.
 Gurmu, Z. K. and Fan, W. D. 2014. Artificial Neural Network Travel Time Prediction Model for Buses using only GPS Data, Journal of Public Transportation, Vol. 17, No. 2, pp. 45-65.
 Johar, A., Jain, S. S. and Garg, P.K. (2015), “Prediction of Bus Travel Time using Artificial Neural Network”, International Journal for Traffic and Transport Engineering (IJTTE), Vol. 5, No. 4, pp. 410-424.
 Li, C. S. and Chen, M. C. 2013. Identifying Important Variables for Predicting Travel Time of Freeway with Non-recurrent Congestion with Neural Networks, Neural Computing and Applications, Vol. 23, No. 6, pp. 1611-1629.
 Mahmoudabadi, A. 2010. Using Artificial Neural Network to Estimate Average Speed of Vehicles in Rural Roads, International Conference on Intelligent Networking and Computing, Nov. 26, pp. VI-25-VI-30.
 Mazloumi, E., Moridpour, S., Currie, G. and Rose, G. 2012. Exploring the Value of Traffic Flow Data in Bus Travel Time Prediction, Journal of Transportation Engineering, Vol. 138, No. 4, pp. 436-446.
 Ramakrishna, Y., Ramakrishna, P., Lakshmanan, V. and Sivanandan, R. 2006. Bus Travel Time Prediction using GPS Data, Proceedings, Map India. Avaliable on: http://www.gisdevelopment.net/proceedings/mapindia/2006/, Accessed on 26-05-2015.
 Rice, J. and Van Zwet, E. 2004. A Simple and Effective Method for Predicting Travel Times on Freeways, IEEE Transactions on Intelligent Transportation Systems, Vol. 5, No. 3, pp. 200-207.
 TRB. 2003a. TCRP Synthesis 48: Real-Time Bus Arrival Information Systems: A Synthesis of Transit Practice, Transit Cooperative Research Program, Federal Transit Administration, Transportation Research Board (TRB), Washington D. C.
 Vanajakshi, L., Subramanian, S.C. and Sivanandan, R. 2009. Travel Time Prediction under Heterogeneous Traffic condition using Global Positioning System Data from Buses, IET Intelligent Transport System, Vol. 3, No.1, pp.1-9.
 Williams, B. and Hoel, L. 2003. Modeling and Forecasting Vehicle Traffic Flow as a Seasonal Arima Process: Theoretical Basis and Empirical Results, Journal of Transportation Engineering, Vol. 129, No. 6, pp. 664–672.
 You, J. and Kim, T. J. 2000. Development and Evaluation of a Hybrid Travel Time Forecasting Model, Transportation Research Part C: Emerging Technologies, Vol. 8, No. 1-6, pp. 231-256.
 Yu, B., Lam, W. H. K., and Tam, M. L. 2011. Bus Arrival Time Prediction at Bus Stop with Multiple Routes, Transportation Research Part C: Emerging Technologies, Vol. 19, No. 6, pp. 1157-1170.
 Yu, B., Ye, T., Tian, X. M., Ning, G. B., and Zhong, S.Q. 2014. Bus Travel Time Prediction with Forgetting Factor, Journal of Computing in Civil Engineering, ASCE, Vol. 28, No. 3, p. 06014002.
 Zhangc, X. and Rice, J. A. 2003. Short-Term Travel Time Prediction using A Time-Varying Coefficient Linear Model, Transportation Research Part C: Emerging Technologies, Vol. 11, pp 187-210.
 Zheng, F. and Van Zuylen, H. 2013, “Urban Link Travel Time Estimation Based on Sparse Probe Vehicle Data”, Transportation Research Part C: Emerging Technologies, Vol. 31, pp. 145-157.
To ensure uniformity of treatment among all contributors, other forms may not be substituted for this form, nor may any wording of the form be changed. This form is intended for original material submitted to AJCT and must accompany any such material in order to be published by AJCT. Please read the form carefully.
The undersigned hereby assigns to the Asian Journal of Convergence in Technology Issues ("AJCT") all rights under copyright that may exist in and to the above Work, any revised or expanded derivative works submitted to AJCT by the undersigned based on the Work, and any associated written, audio and/or visual presentations or other enhancements accompanying the Work. The undersigned hereby warrants that the Work is original and that he/she is the author of the Work; to the extent the Work incorporates text passages, figures, data or other material from the works of others, the undersigned has obtained any necessary permission. See Retained Rights, below.
AJCT distributes its technical publications throughout the world and wants to ensure that the material submitted to its publications is properly available to the readership of those publications. Authors must ensure that The Work is their own and is original. It is the responsibility of the authors, not AJCT, to determine whether disclosure of their material requires the prior consent of other parties and, if so, to obtain it.
RETAINED RIGHTS/TERMS AND CONDITIONS
1. Authors/employers retain all proprietary rights in any process, procedure, or article of manufacture described in the Work.
2. Authors/employers may reproduce or authorize others to reproduce The Work and for the author's personal use or for company or organizational use, provided that the source and any AJCT copyright notice are indicated, the copies are not used in any way that implies AJCT endorsement of a product or service of any employer, and the copies themselves are not offered for sale.
3. Authors/employers may make limited distribution of all or portions of the Work prior to publication if they inform AJCT in advance of the nature and extent of such limited distribution.
4. For all uses not covered by items 2 and 3, authors/employers must request permission from AJCT.
5. Although authors are permitted to re-use all or portions of the Work in other works, this does not include granting third-party requests for reprinting, republishing, or other types of re-use.
INFORMATION FOR AUTHORS
AJCT Copyright Ownership
It is the formal policy of AJCT to own the copyrights to all copyrightable material in its technical publications and to the individual contributions contained therein, in order to protect the interests of AJCT, its authors and their employers, and, at the same time, to facilitate the appropriate re-use of this material by others.
If you are employed and prepared the Work on a subject within the scope of your employment, the copyright in the Work belongs to your employer as a work-for-hire. In that case, AJCT assumes that when you sign this Form, you are authorized to do so by your employer and that your employer has consented to the transfer of copyright, to the representation and warranty of publication rights, and to all other terms and conditions of this Form. If such authorization and consent has not been given to you, an authorized representative of your employer should sign this Form as the Author.
AJCT requires that the consent of the first-named author and employer be sought as a condition to granting reprint or republication rights to others or for permitting use of a Work for promotion or marketing purposes.
1. The undersigned represents that he/she has the power and authority to make and execute this assignment.
2. The undersigned agrees to indemnify and hold harmless AJCT from any damage or expense that may arise in the event of a breach of any of the warranties set forth above.
3. In the event the above work is accepted and published by AJCT and consequently withdrawn by the author(s), the foregoing copyright transfer shall become null and void and all materials embodying the Work submitted to AJCT will be destroyed.
4. For jointly authored Works, all joint authors should sign, or one of the authors should sign as authorized agent
for the others.
Licenced by :