Skip to main content
SpringerLink
Log in

Intelligent transportation systems for smart cities: a progress review

  • Progress
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

Abstract

To better meet the challenge of providing effective, low-cost, energy efficient transport services, the concept of intelligent transport systems (ITS) has been proposed and lauded as an innovative and promising solution for next generation transport networks. In this paper, the progress of ITS research around the world is briefly reviewed and current challenges are outlined, thereby offering further insight into ITS development for all researchers in this area.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. The Ministry of Transport of the People’s Republic of China. 2010 Annual Report of City Transportation Development in China. Beijing: China Communications Press, 2011

    Google Scholar 

  2. Chen Z Y, Fan W, Xiong Z, et al. Visual data security and management for smart cities. Front Comput Sci China, 2010, 4: 386–393

    Article  Google Scholar 

  3. RITA Intelligent Transportation Systems Joint Program Office. Transit Connected Vehicle Research Program. Washington, DC, 2011

  4. Carrotta A (ERTICO). Report on the Progress of the 28 eSafety Recommendations. Brussels, 2008

  5. ITS Japan. The 6th Japan ITS Promotion Forum Report. Tokyo, 2011

  6. Rosen D A, Mammano F J, Favout R. An electronic route-guidance system for highway vehicles. IEEE Trans Veh Technol, 1970, 19: 143–152

    Article  Google Scholar 

  7. Demo’ 97: proving AHS works. Public Roads, 1997, 61. http://www.fhwa.dot.gov/publications/publicroads/97july/demo97.cfm

  8. Little C. The intelligent vehicle initiative: advancing “human-centered” smart vehicles. Public Roads, 1997, 61. http://www.fhwa.dot.gov/publications/publicroads/97septoct/p97sept18.cfm

  9. Kandarpa R, Chenzaie M, Anderson J, et al. Final Report: Vehicle Infrastructure Integration Proof-of-Concept Results and Findings-C Infrastructure. Technical Report FHWA-JPO-09-057. 2009

  10. Yin Y F, Miller M A, Shladover S E. Assessment of the applicability of cooperative vehicle-highway automation systems to freight movement in Chicago. In: The 83rd TRB Annual Meeting, Washington, DC, 2004

  11. Catling I, McQueen B. Road transport informatics in Europe-major programs and demonstrations. IEEE Trans Veh Technol, 1991, 40: 132–140

    Article  Google Scholar 

  12. Oxley P R, Mitchell C G B. Final report on elderly and disabled drivers information telematics. R & D Programme Telematics System in the Area of Transport (DRIVE II), Commission of the European Communities CEC, Brussels, 1995

    Google Scholar 

  13. Tanaka T, Yamamoto T, Fukuda S. Onboard system devices for a vehicle information and communication system. FUJITSU TEN Tech J, 1995, 7: 26–34

    Google Scholar 

  14. Bar T, Nienhuser D, Kohlhaas R, et al. Probabilistic driving style determination by means of a situation based analysis of the vehicle data. In: The 14th International IEEE Conference on Intelligent Transportation Systems, Washington, DC, 2011. 1698–1703

  15. Wei L, Cappelle C, Ruichek Y, et al. GPS and stereovision based visual odometry: application to urban scene mapping and intelligent vehicle localization. Int J Veh Technol, 2011, 1–17

  16. Bailey T, Durrant-Whyte H. Simultaneous localization and mapping (SLAM)-part II. IEEE Robot Autom Mag, 2006, 13: 108–117

    Article  Google Scholar 

  17. Parra I, Sotelo M A, Llorca D F, et al. Robust visual odometry for vehicle localization in urban environments. Robotica, 2010, 28: 441–452

    Article  Google Scholar 

  18. Miller I, Campbell M. Sensitivity analysis of a tightly-coupled GPS/INS system for autonomous navigation. IEEE Trans Aerosp Electron Syst, 2012, 48: 1115–1135

    Article  Google Scholar 

  19. Cappelle C, Najjar M, Pomorski D, et al. Intelligent geolocalization in urban areas using global positioning systems, three-dimensional geographic information systems, and vision. J Intell Transport Syst, 2010, 14: 3–12

    Article  MATH  Google Scholar 

  20. Zhang Z X, Wang Y H. Automatic object classification using motion blob based local feature fusion for traffic scene surveillance. Front Comput Sci China, 2012, 6: 537–546

    Google Scholar 

  21. Fortin B, Lherbier R, Noyer J C. Feature extraction in scanning laser range data using invariant parameters: application to vehicle detection. IEEE Trans Veh Technol, 2012, 99: 1–12

    Google Scholar 

  22. Chavez-Aragon A, Laganiere R, Payeur P. Vision-based detection and labeling of multiple vehicle parts. In: The 14th International IEEE Conference on Intelligent Transportation Systems, Washington, DC, 2011. 1273–1278

  23. Lin M C, Manocha D. Virtual cityscapes: recent advances in crowd modeling and traffic simulation. Front Comput Sci China, 2010, 4: 405–416

    Article  Google Scholar 

  24. Miyajima C, Takeda K, Suzuki T, et al. A driving diagnosis and feedback system for next-generation drive recorders. In: The First International Symposium on Future Active Safety Technology Toward Zero-Traffic-Accident (FAST-zero’ 11), Tokyo, 2011

  25. Enzweiler M, Gavrila D M. Monocular pedestrian detection: survey and experiments. IEEE Trans Pattern Anal Mach Intell, 2009, 31: 2179–2195

    Article  Google Scholar 

  26. Feng X, Zhang J, Fujiwara A, et al. Improved feedback modeling of transport in enlarging urban areas of developing countries. Front Comput Sci China, 2010, 4: 112–122

    Article  Google Scholar 

  27. Li X L, Pan G, Wu Z H, et al. Prediction of urban human mobility using large-scale taxi traces and its applications. Front Comput Sci China, 2012, 6: 111–121

    MathSciNet  Google Scholar 

  28. Dalal N, Triggs B. Histograms of oriented gradients for human detection. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2005), San Diego, 2005. 886–893

  29. Gavrila D M, Munder S. Multi-cue pedestrian detection and tracking from a moving vehicle. Int J Comput Vis, 2007, 73: 41–59

    Article  Google Scholar 

  30. Saleet H, Basir O, Langar R, et al. Region-based location-service-management protocol for VANETs. IEEE Trans Veh Technol, 2010, 59: 917–931

    Article  Google Scholar 

  31. Sommer C, Schmidt A, Chen Y, et al. On the feasibility of UMTS-based traffic information systems. Ad Hoc Netw, 2010, 8: 506–517

    Article  Google Scholar 

  32. Li F, Wang Y. Routing in vehicular ad hoc networks: a survey. IEEE Veh Technol Mag, 2007, 2: 12–22

    Article  Google Scholar 

  33. Lequerica I, Ruiz P M, Cabrera V. Improvement of vehicular communications by using 3G capabilities to disseminate control information. IEEE Netw, 2010, 24: 32–38

    Article  Google Scholar 

  34. Xu Y, Wang W. Topology stability analysis and its application in hierarchical mobile ad hoc networks. IEEE Trans Veh Technol, 2009, 58: 1546–1560

    Article  Google Scholar 

  35. Fang M K, Li L, Huang W. Research of hybrid positioning based vehicle interactive navigation system. In: 2010 International Conference on Multimedia Information Networking and Security (MINES), Nanjing, 2010. 974–978

  36. Mai Y T, Chen J Y, Liu Y K, et al. Intelligent vehicular warning system for VANET. Appl Mech Mater, 2012, 145: 164–168

    Article  Google Scholar 

  37. Mamdouhi H, Khatun S, Zarrin J. Bluetooth wireless monitoring, managing and control for inter vehicle in vehicular ad-hoc networks. J Comput Sci, 2009, 5: 922–929

    Article  Google Scholar 

  38. Robertson N, Reid I. A general method for human activity recognition in video. Comput Vis Image Underst, 2006, 104: 232–248

    Article  Google Scholar 

  39. Sheng H, Zhao H, Huang J, et al. A spatio-velocity model based semantic event detection algorithm for traffic surveillance video. Sci China Tech Sci, 2010, 53: 120–125

    Article  Google Scholar 

  40. Sheng H, Xiong Z, Weng J N, et al. An approach to detecting abnormal vehicle events in complex factors over highway surveillance video. Sci China Ser E-Tech Sci, 2008, 51: 199–208

    Article  Google Scholar 

  41. Hao J Y, Xiong Z, Sheng H, et al. A primitive-based traffic scene semantic description model. J Internet Technol, 2010, 11: 787–800

    Google Scholar 

  42. Xue G, Zhang K, He Q, et al. Real-time traffic information estimation with limited surveillance cameras in the city. Front Comput Sci China, 2012. To appear

  43. Shlayan N, Kachroo P, Wadoo S. Bayesian safety analyzer using multiple data sources of accidents. In: The 14th International IEEE Conference on Intelligent Transportation Systems, Washington, DC, 2011. 151–156

  44. Carlson R C, Papamichail I, Papageorgiou M, et al. Optimal motorway traffic flow control involving variable speed limits and ramp metering. Transp Sci, 2010, 44: 238–253

    Article  Google Scholar 

  45. Carlson R C, Papamichail I, Papageorgiou M, et al. Optimal mainstream traffic flow control of large-scale motorway networks. Transp Res Pt C-Emerg Technol, 2010, 18: 193–212

    Article  Google Scholar 

  46. Esawey M E, Sayed T. Travel time estimation in urban networks using neighbor links travel time data. In: The 89th Annual Meeting of Transportation Research Board, Washington, DC, 2010. 394–410

  47. Chan K S, William H, Tam M L. Real-time estimation of arterial travel times with spatial travel time covariance relationships. Transp Res Record, 2009, 2121: 102–109

    Article  Google Scholar 

  48. Nie Y, Wu X. Reliable a priori shortest path problem with limited spatial and temporal dependencies. In: Lam W H K, Wong S C, Lo H K, eds. Transportation and Traffic Theory 2009: Golden Jubilee. New York: Springer, 2009. 169–C 195

    Chapter  Google Scholar 

  49. Danescu R, Nedevschi S. New results in stereovision based lane tracking. In: IEEE Intelligent Vehicles Symposium (IV), Baden-Baden, 2011, 230 C-235

  50. Maldonado-Bascon S, Lafuente-Arroyo S, Siegmann P, et al. Traffic sign recognition system for inventory purposes. In: IEEE Intelligent Vehicles Symposium, Eindhoven, 2008. 590–595

  51. Gillula J H, Haomiao H, Vitus M P, et al. Design of guaranteed safe maneuvers using reachable sets: Autonomous quadrotor aerobatics in theory and practice. In: IEEE International Conference on Robotics and Automation, Anchorage, 2010, 1649–1654

  52. Shladover S. Cooperative (rather than autonomous) vehicle-highway automation systems. IEEE Intell Transport Syst Mag, 2009, 1: 10–19

    Article  Google Scholar 

  53. Milanes V, Alonso J, Bouraoui L, et al. Cooperative maneuvering in close environments among cybercars and dualmode cars. IEEE Trans Intell Transp Syst, 2011, 12: 15–24

    Article  Google Scholar 

  54. Milanes V, Onieva E, Perez J, et al. An approach to driverless vehicles in highways. In: The 14th International IEEE Conference on Intelligent Transportation Systems (ITSC), Washington, DC, 2011. 668–673

Download references

Author information

Authors and Affiliations

  1. State Key Laboratory of Software Development Environment, School of Computer Science and Engineering, Beihang University, Beijing, 100191, China

    Zhang Xiong, Hao Sheng, WenGe Rong & Dave E. Cooper

  2. Shenzhen Key Laboratory of Data Vitalization, Research Institute in Shenzhen, Beihang University, Shenzhen, 518057, China

    Zhang Xiong & Hao Sheng

  3. Beijing Engneering Laboratory of IOT Content Security, School of Computer Science and Engineering, Beihang University, Beijing, 100191, China

    WenGe Rong

Authors
  1. Zhang Xiong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hao Sheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. WenGe Rong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Dave E. Cooper
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hao Sheng.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Xiong, Z., Sheng, H., Rong, W. et al. Intelligent transportation systems for smart cities: a progress review. Sci. China Inf. Sci. 55, 2908–2914 (2012). https://doi.org/10.1007/s11432-012-4725-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11432-012-4725-1

Keywords

Search

Navigation