A Dynamic Road Incident Information Delivery Strategy to Reduce Urban Traffic Congestion

Liang Qi; Mengchu Zhou; Wenjing Luan

doi:10.1109/JAS.2018.7511165

Volume 5 Issue 5

Aug. 2018

IEEE/CAA Journal of Automatica Sinica

JCR Impact Factor: 15.3, Top 1 (SCI Q1)

CiteScore: 23.5, Top 2% (Q1)
Google Scholar h5-index: 77， TOP 5

Turn off MathJax

Article Contents

Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2018 > 5(5): 934-945

Liang Qi, Mengchu Zhou and Wenjing Luan, "A Dynamic Road Incident Information Delivery Strategy to Reduce Urban Traffic Congestion," IEEE/CAA J. Autom. Sinica, vol. 5, no. 5, pp. 934-945, Sept. 2018. doi: 10.1109/JAS.2018.7511165

Citation:

Liang Qi, Mengchu Zhou and Wenjing Luan, "A Dynamic Road Incident Information Delivery Strategy to Reduce Urban Traffic Congestion," IEEE/CAA J. Autom. Sinica, vol. 5, no. 5, pp. 934-945, Sept. 2018. doi: 10.1109/JAS.2018.7511165

Citation:

PDF( 10907 KB)

A Dynamic Road Incident Information Delivery Strategy to Reduce Urban Traffic Congestion

doi: 10.1109/JAS.2018.7511165

Liang Qi^{1, 2, 3
,},
Mengchu Zhou^{3
,
,},
Wenjing Luan^4
,

1.
Department of Computer Science and Technology, Shandong University of Science and Technology, Qingdao 266590, China
2.
Department of Computer Science, Tongji University, Shanghai 201804, China
3.
Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark NJ 07102, USA
4.
Key Laboratory of Embedded System and Service Computing, Ministry of Education, Shanghai Electronic Transactions and Information Service Collaborative Innovation Center, Department of Computer Science, Tongji University, Shanghai 201804, China

Funds:

the National Natural Science Foundation of China 61374148

More Information

Author Bio:
Liang Qi (S'16-M'18) received the B. S. degree in information and computing science and M. S. degree in computer software and theory from Shandong University of Science and Technology, Qingdao, China, in 2009 and 2012, respectively. He received the Ph. D. degree in computer software and theory from Tongji University, Shanghai, China in 2017. He is currently a Lecturer of computer science and technology at Shandong University of Science and Technology, Qingdao, China. From 2015 to 2017, he was a visiting student in the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA. He has authored over 20 technical papers in journals and conference proceedings, including IEEE/CAA Journal of Automatica Sinica, IEEE Transactions on System, Man, and Cybernetics:Systems, and IEEE Transactions on Intelligent Transportation Systems. He received the Best Student Paper Award-Finalist in the 15th IEEE International Conference on Networking, Sensing and Control (ICNSC'2018). His current research interests include Petri nets, discrete event systems, intelligent transportation systems, and optimization algorithms. (e-mail: qiliangsdkd@163.com)

Mengchu Zhou (S'88-M'90-SM'93-F'03) received the B. S. degree in control engineering from Nanjing University of Science and Technology, Nanjing, China in 1983, the M. S. degree in automatic control from Beijing Institute of Technology, Beijing, China in 1986, and the Ph. D. degree in computer and systems engineering from Rensselaer Polytechnic Institute, Troy, NY in 1990. He joined New Jersey Institute of Technology (NJIT), Newark, NJ in 1990, and is now a Distinguished Professor of Electrical and Computer Engineering. His research interests include Petri nets, intelligent automation, Internet of Things, big data, web services, and intelligent transportation. He has over 700 publications including 12 books, 400+ journal papers (300+ in IEEE transactions), 11 patents and 28 book-chapters. He is the founding Editor of IEEE Press Book Series on Systems Science and Engineering and Editor-in-Chief of IEEE/CAA Journal of Automatica Sinica. He is a recipient of Humboldt Research Award for US Senior Scientists from Alexander von Humboldt Foundation, Franklin V. Taylor Memorial Award and the Norbert Wiener Award from IEEE Systems, Man and Cybernetics Society for which he serves as VP for Conferences and Meetings. He is a life member of Chinese Association for Science and Technology-USA and served as its President in 1999. He is a Fellow of International Federation of Automatic Control (IFAC), American Association for the Advancement of Science (AAAS) and Chinese Association of Automation (CAA)

Wenjing Luan (S'16) received the B. S. and M. S. degrees from Shandong University of Science and Technology, Qingdao, China, in 2009 and 2012, respectively. She is currently pursuing Ph. D. degree with the Department of Computer Science and Technology, Tongji University, Shanghai, China. Her current research interests include location-based social networks, recommender systems, and intelligent transportation systems. She received the Best Student Paper Award-Finalist in the 13th IEEE International Conference on Networking, Sensing and Control (ICNSC'2016) Conference. (e-mail: wenjingmengjing@163.com)
Corresponding author: Mengchu Zhou, e-mail: zhou@njit.edu
Received Date: 2017-11-13
Accepted Date: 2018-03-07

Abstract

Abstract

Advanced information and communication technologies can be used to facilitate traffic incident management. If an incident is detected and blocks a road link, in order to reduce the incident-induced traffic congestion, a dynamic strategy to deliver incident information to selected drivers and help them make detours in urban areas is proposed by this work. Time-dependent shortest path algorithms are used to generate a subnetwork where vehicles should receive such information. A simulation approach based on an extended cell transmission model is used to describe traffic flow in urban networks where path information and traffic flow at downstream road links are well modeled. Simulation results reveal the influences of some major parameters of an incident-induced congestion dissipation process such as the ratio of route-changing vehicles to the total vehicles, operation time interval of the proposed strategy, traffic density in the traffic network, and the scope of the area where traffic incident information is delivered. The results can be used to improve the state of the art in preventing urban road traffic congestion caused by incidents.
- Cell transmission model (CTM),
- intelligent transportation systems (ITS),
- traffic incident management (TIM),
- urban traffic congestion

FullText(HTML)

References(48)

References

[1]	P. B. Farradyne, Traffic Incident Management Handbook. Washington, DC: Office of Travel Management, Federal Highway Administration, 2000.
[2]	K. Ozbay and P. Kachroo, Incident Management in Intelligent Transportation Systems. Norwood, MA: Artech House Publishers, 1999.
[3]	M. Jha, D. Cuneo, and M. Ben-Akiva, "Evaluation of freeway lane control for incident management, " J. Transp. Eng., vol. 125, no. 6, pp. 495-501, Nov. -Dec. 1999.
[4]	P. W. Lin, K. P. Kang, and G. L. Chang, "Exploring the effectiveness of variable speed limit controls on highway work-zone operations, " J. Intell. Transp. Syst., vol. 8, no. 3, pp. 155-168, 2004. doi: 10.1080/15472450490492851
[5]	J. B. Sheu and M. S. Chang, "Stochastic optimal-control approach to automatic incident-responsive coordinated ramp control, " IEEE Trans. Intell. Transp. Syst., vol. 8, no. 2, pp. 359-367, Jun. 2007. http://ieeexplore.ieee.org/document/4220665/
[6]	F. -Y. Wang, N. -N. Zheng, D. P. Cao, C. M. Martinez, L. Li, and T. Liu, "Parallel driving in CPSS: a unified approach for transport automation and vehicle intelligence, " IEEE/CAA J. of Autom. Sinica, vol. 4, no. 4, pp. 577-587, Oct. 2017. http://ieeexplore.ieee.org/document/8039015/
[7]	G. Xiong, F. H. Zhu, X. W. Liu, X. S. Dong, W. L. Huang, S. H. Chen, and K. Zhao, "Cyber-physical-social system in intelligent transportation, " IEEE/CAA J. of Autom. Sinica, vol. 2, no. 3, pp. 320- 333, Jul. 2015. http://ieeexplore.ieee.org/document/7152667/
[8]	F. -Y. Wang, "Parallel control and management for intelligent transportation systems: concepts, architectures, and applications, " IEEE Trans. Intell. Transp. Syst., vol. 11, no. 3, pp. 630-638, Sep. 2010. http://ieeexplore.ieee.org/document/5549912/
[9]	M. Papageorgiou, C. Diakaki, V. Dinopoulou, A. Kotsialos, and Y. B. Wang, "Review of road traffic control strategies, " Proc. IEEE, vol. 91, no. 12, pp. 2043-2067, Dec. 2003.
[10]	S. Zhao, Y. M. Chen, and J. A. Farrell, "High-precision vehicle navigation in urban environments using an MEM's IMU and single-frequency GPS receiver, " IEEE Trans. Intell. Transp. Syst. , vol. 17, no. 10, pp. 2854-2867, Apr. 2016. http://ieeexplore.ieee.org/document/7447761/
[11]	Y. C. Chiua and N. Huynhb, "Location configuration design for dynamic message signs under stochastic incident and ATIS scenarios, " Transp. Res. C: Emerg. Technol. , vol. 15, no. 1, pp. 33-50, Feb. 2007. https://www.sciencedirect.com/science/article/pii/S0968090X0600101X
[12]	C. A. Williams, "A data mining approach to rapidly learning traveler activity patterns for mobile applications, " Ph. D. dissertation, Dept. Comp. Sci., Univ. Illinois at Chicago, Chicago, USA, 2010.
[13]	C. Wright and P. Roberg, "The conceptual structure of traffic jams, " Transp. Policy, vol. 5, no. 1, pp. 23-35, Jan. 1998.
[14]	P. O. Roberg, C. Abbess, and C. Wright, "Traffic jam simulation, " J. Maps, vol. 3, no. 1, pp. 107-121, 2007. doi: 10.1080/jom.2007.9710832
[15]	J. C. Long, Z. Y. Gao, P. Orenstein, and H. L. Ren, "Control strategies for dispersing incident-based traffic jams in two-way grid networks, " IEEE Trans. Intell. Transp. Syst. , vol. 13, no. 2, pp. 469-481, Oct. 2012. http://ieeexplore.ieee.org/document/6064894/
[16]	J. C. Long, Z. Y. Gao, X. M. Zhao, A. P. Lian, and P. Orenstein, "Urban traffic jam simulation based on the cell transmission model, " Netw. Spat. Econ. , vol. 11, no. 1, pp. 43-64, Mar. 2011.
[17]	L. Qi, M. C. Zhou, and W. J. Luan, "Emergency traffic-light control system design for intersections subject to accidents, " IEEE Trans. Intell. Transp. Syst. , vol. 17, no. 1, pp. 170-183, Jan. 2016. http://ieeexplore.ieee.org/document/7268911/
[18]	L. Qi, M. C. Zhou, and W. J. Luan, "A two-level traffic light control strategy for preventing incident-based urban traffic congestion, " IEEE Trans. Intell. Transp. Syst., vol. 19, no. 1, pp. 13-24, Jan. 2018. http://ieeexplore.ieee.org/document/7802596/
[19]	P. Roberg, "A distributed strategy for eliminating incident-based traffic jams from urban networks, " Traffic Eng. Control, vol. 36, no. 6, pp. 348-354, Jun. 1995.
[20]	Y. S. Huang, Y. S. Wen, W. M. Wu, and B. Y. Chen, "Control strategies for solving the problem of traffic congestion, " IET Intell. Transp. Syst., vol. 10, no. 10, pp. 642-648, 2016. doi: 10.1049/iet-its.2016.0003
[21]	Y. S. Huang, W. P. Huang, and W. P. Wu, "Analysis of urban traffic jam control strategies using simulation technology, " in Proc. 13th IEEE Int. Conf. Networking, Sensing, Control, Mexico City, Mexico, 2016, pp. 1-6.
[22]	W. Y. Szeto and S. C. Wong, "Dynamic traffic assignment: model classifications and recent advances in travel choice principles, " Central Eur. J. Eng. , vol. 2, no. 1. pp. 1-18, Mar. 2012. doi: 10.2478%2Fs13531-011-0057-y
[23]	W. Y. Szeto, "Dynamic traffic assignment: formulations, properties, and extensions, " Ph. D. dissertation, The Hong Kong Univ. Sci. Technol., China, 2003.
[24]	C. G. Chorus, E. J. E. Molin, and B. van Wee, "Use and effects of advanced traveller information services (ATIS): a review of the literature, " Transp. Rev., vol. 26, no. 2, pp. 127-149, 2006. doi: 10.1080/01441640500333677
[25]	H. S. Mahmassani, "Dynamic network traffic assignment and simulation methodology for advanced system management applications, " Netw. Spat. Econ., vol. 1, no. 3-4, pp. 267-292, Sep. 2001.
[26]	Y. Tian and Y. C. Chiu, "A variable time-discretization strategies-based, time-dependent shortest path algorithm for dynamic traffic assignment, " J. Intell.Transp. Syst., vol. 18, no. 4, pp. 339-351, 2014. doi: 10.1080/15472450.2013.806753
[27]	Y. Q. Jiang, S. C. Wong, H. W. Ho, P. Zhang, R. X. Liu, and A. Sumalee, "A dynamic traffic assignment model for a continuum transportation system, " Transp. Res. B: Methodol. , vol. 45, no. 2, pp. 343-363, Feb. 2011.
[28]	W. Y. Szeto and H. K. Lo, "Dynamic traffic assignment: properties and extensions, " Transportmetrica, vol. 2, no. 1, pp. 31-52, 2006. doi: 10.1080/18128600608685654
[29]	S. T. Waller, D. Fajardo, M. Duell, and V. Dixit, "Linear programming formulation for strategic dynamic traffic assignment, " Netw. Spat. Econ. , vol. 13, no. 4, pp. 427-443, Dec. 2013. https://utexas.influuent.utsystem.edu/en/publications/linear-programming-formulation-for-strategic-dynamic-traffic-assi
[30]	B. Ran, D. E. Boyce, and L. J. Leblanc, "A new class of instantaneous dynamic user-optimal traffic assignment models, " Oper. Res. , vol. 41, no. 1, pp. 192-202, Feb. 1993. https://dl.acm.org/citation.cfm?id=154555.152083
[31]	B. Ran and D. Boyce, Modeling Dynamic Transportation Networks: An Intelligent Transportation System Oriented Approach. Heidelberg, Germany: Springer, 1996.
[32]	X. G. Ban, H. X. Liu, M. C. Ferris, and B. Ran, "A link-node complementarity model and solution algorithm for dynamic user equilibria with exact flow propagations, " Transp. Res. B: Methodol. , vol. 42, no. 9, pp. 823-842, Nov. 2008.
[33]	G. N. Bifulco, G. E. Cantarella, F. Simonelli, and P. Veloná, "Advanced traveller information systems under recurrent traffic conditions: network equilibrium and stability, " Transp. Res. B: Methodol. , vol. 92, pp. 73- 87, Oct. 2016.
[34]	R. H. M. Emmerink, K. W. Axhausen, P. Nijkamp, and P. Rietveld, "The potential of information provision in a simulated road transport network with non-recurrent congestion, " Transp. Res. C: Emerg. Technol. , vol. 3, no. 5, pp. 293-309, Oct. 1995. https://www.sciencedirect.com/science/article/pii/0968090X95000128
[35]	C. F. Daganzo, "The cell transmission model, part Ⅱ: network traffic, " Transp. Res. B: Methodol., vol. 29, no. 2, pp. 79-93, Apr. 1995.
[36]	M. J. Lighthill and G. B. Whitman, "On kinematic waves Ⅱ: a theory of traffic flow on long crowded roads, " Proc. Roy. Soc. London Series A: Math. Phys. Eng. Sci., vol. 229, no. 1178, 1955, pp. 317-345. http://amath.colorado.edu/sites/default/files/2013/09/81806977/PRSA_Lighthill_1955.pdf
[37]	P. I. Richards, "Shock waves on the highway, " Oper. Res., vol. 4, no. 1, pp. 42-51, Feb. 1956.
[38]	S. V. Ukkusuri, L. S. Han, and K. Doan, "Dynamic user equilibrium with a path based cell transmission model for general traffic networks, " Transp. Res. B: Methodol., vol. 46, no. 10, pp. 1657-1684, Dec. 2012. https://trid.trb.org/view/1237995
[39]	H. K. Lo, "A cell-based traffic control formulation: strategies and benefits of dynamic timing plans, " Transp. Sci., vol. 35, no. 2, pp. 148- 164, May 2001.
[40]	E. Almasri and B. Friedrich, "Online offset optimisation in urban networks based on cell transmission model, " in Proc. 2005 European Congress and Exhibition on Intelligent Transport Systems and Services, Hannover, Gernamy, 2005, pp. 1-12.
[41]	Y. Pavlis and W. Recker, "A mathematical logic approach for the transformation of the linear conditional piecewise functions of dispersionand-store and cell transmission traffic flow models into linear mixedinteger form, " Transp. Sci. , vol. 43, no. 1, pp. 98-116, Feb. 2009. doi: 10.1287/trsc.1080.0254
[42]	X. T. Sun, L. Munoz, and R. Horowitz, "Highway traffic state estimation using improved mixture Kalman filters for effective ramp metering control, " in Proc. 42nd IEEE Int. Conf. Decision and Control, Maui, HI, USA, 2003, pp. 6333-6338.
[43]	G. Gomes, R. Horowitz, A. A. Kurzhanskiy, P. Varaiya, and J. Kwon, "Behavior of the cell transmission model and effectiveness of ramp metering, " Transp. Res. C: Emerg. Technol. , vol. 16, no. 4, pp. 485-513, Aug. 2008.
[44]	L. Munoz, X. T. Sun, R. Horowitz, and L. Alvarez, "Traffic density estimation with the cell transmission model, " in Proc. 2003 IEEE American Control Conf. , Denver, CO, USA, pp. 3750-3755.
[45]	K. Staňková and B. De Schutter, "On freeway traffic density estimation for a jump Markov linear model based on Daganzo's cell transmission model, " in Proc. 13th Int. IEEE Conf. Intelligent Transportation Systems, Funchal, Portugal, 2010, pp. 13-18.
[46]	S. Timotheou, C. Panayiotou, and M. Polycarpou, "Fault-adaptive traffic density estimation for the asymmetric cell transmission model, " in Proc. 18th IEEE Int. Conf. Intelligent Transportation Systems, Las Palmas, Spain, 2015, pp. 2855-2860. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7313551
[47]	H. B. Celikoglu, "Dynamic classification of traffic flow patterns simulated by a switching multimode discrete cell transmission model, " IEEE Trans. Intell. Transp. Syst. , vol. 15, no. 6, pp. 2539-2550, Dec. 2014. http://ieeexplore.ieee.org/document/6814951/
[48]	D. B. West, Introduction to Graph Theory. Upper Saddle River, NJ, USA: Prentice Hall, 1996.

Supplements(0)

Cited By

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Figures(12) / Tables(3)

Get Citation

PDF

XML

Article Metrics

Article views (1276) PDF downloads(23)

A Dynamic Road Incident Information Delivery Strategy to Reduce Urban Traffic Congestion

doi: 10.1109/JAS.2018.7511165

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Export File

Citation

Format

Content