Positioning improvements for Intelligent Transportation Systems (ITS)
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Transcript of Positioning improvements for Intelligent Transportation Systems (ITS)
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Bastien [email protected]
Presentation« Positioning Improvements for Intelligent Transportation Systems »
6/18/2015
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2
Introduction
6/18/2015 Bastien Terret – RWTH Aachen
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Bastien Terret – RWTH Aachen 3
Outline• Introduction
• Intelligent Transportation Systems
• Global Navigation Satellite Systems
• How to improve the localization ?
• Conclusion6/18/2015
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Bastien Terret – RWTH Aachen 46/18/2015
Intelligent Transportation Systems
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Bastien Terret – RWTH Aachen 5
Intelligent Transportation Systems
“Intelligent Transportation Systems (ITS) can be defined as the application of advanced information and communications technology to surface transportation in order to achieve enhanced safety and mobility while reducing the environmental impact of transportation”. - [1]
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Bastien Terret – RWTH Aachen 6
Intelligent Transportation Systems
• Helping to relieve congestion
• Safety and environmental benefits
• Making public transport more attractive
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Global Navigation Satellite SystemsGNSS : Global Navigation Satellite System“System of satellites that provide autonomous geo-spatial positioning with global coverage.” – [2]
Examples: • GPS• GLONASS• BDS• Galileo• IRNSS
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How does GPS work ?
You need :- Measure travel time with accurate timing- Know the exact position of satellites- Have sufficient number of satellites
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GPS constellation - [2]
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How does GPS work ?GPS Frequencies
Band Frequency(MHz)
L1 1575.42
L2 1227.60
L3 1381.05
L4 1379.913
L5 1176.45
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L1 & L2 -- Navigation signalL3 & L4 -- Nuclear Detection System /
Ionospheric correctionsL5 -- Safety of LifeL2C -- Accuracy
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How does GPS work ?
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GPS Navigation Message – [3]
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How does GPS work ?
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Ambiguity resulting from measurements to two sources – [4]
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How does GPS work ?
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Position ambiguity removal by additional measurement– [4]
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How does GPS work ?
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Effect of measurement errors– [4]
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Advantages & DrawbacksSTRENGTHS • Self-calibrating• Size of devices• Works anywhere on earth• Cost• Updated systemWEAKNESSES • Drain power• Signal drawbacks : multipath, signal reception, can’t pass through solid objects
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Requirements
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Position accuracy classification – [6]
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How to locate something ?• V2I, V2V & V2P• Cellular systems• Unlicensed-band• Dead-reckoning• Map-matching• RFID
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V2I, V2V & V2P
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• V2I – Vehicle-to-Infrastructure• V2V – Vehicle-to-Vehicle• V2P – Vehicle-to-Pedestrian
“Linking road vehicles to their […] surroundings” – [3]
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V2I, V2V & V2P• How ?
DSRC – Dedicated Short-Range Communication75 MHz spectrum band around 5.9 GHz - ISM band
Content : ID, position, motion, control, basic
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V2I : Vehicle-to-Infrastructure
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V2I Illustration – [7]
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V2I : Vehicle-to-Infrastructure
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Map setup – [8] Results of the simulation – [8]
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Vehicle-to-Vehicle and Vehicle-to-Pedestrian (V2V & V2P)
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V2V illustration – [9]
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Vehicle-to-Vehicle (V2V)• equipped & non-equipped vehicles
Ranging sensors & GPS receivers
• DSRC communication devices
Goals :- recognize presence of non-equipped vehicles- estimate positions of vehicles
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Vehicle-to-Vehicle (V2V)
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[10][10]
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V2x – x : Infrastructure, Vehicle or PedestrianLimitations :
PrivacyCoordinationMaintenanceSecurity
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Dead-Reckoning (DR)
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Overcome limitations of GNSS technology
Calculate a current position using a previously determined position
How ? With sensors
But … Cumulative errors -> Cannot replace GNSS alone
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Integrated Algorithm
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Plot of the proposed transportation network – [11]
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Integrated Algorithm
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Plot of the proposed transportation network – [11]
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Integrated Algorithm
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Plot of the proposed transportation network – [11]
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Integrated Algorithm
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Plot of the proposed transportation network – [11]
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Integrated Algorithm
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Plot of the proposed transportation network – [11]
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Integrated Algorithm
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Plot of the proposed transportation network – [11]
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Integrated Algorithm
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Plot of the proposed transportation network – [11]
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Integrated Algorithm
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Plot of the proposed transportation network – [11]
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Integrated Algorithm
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Plot of the proposed transportation network – [11]
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Integrated Algorithm
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Plot of the proposed transportation network – [11]
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Integrated Algorithm
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Plot of the proposed transportation network – [11]
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Integrated Algorithm
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Plot of the proposed transportation network – [11]
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Integrated AlgorithmCombination of V2I, V2V, V2P, RFID, and DR resources
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Cramer Rao Lower Bound (CRLB)
δ – current accuracyε – required accuracy
if δ < −0.15ε thenremove the worst connectionelseif δ > 0.15ε thenadd the best connectionelsedo not change the setendif
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Integrated Algorithm
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Localization error as function of time-step – [11]
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Integrated Algorithm
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Localization error as function of time-step – [11]
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Integrated Algorithm
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Localization error as function of time-step – [11]
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Integrated Algorithm
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Localization error as function of time-step – [11]
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Integrated Algorithm
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Localization error as function of time-step – [11]
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Integrated Algorithm
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Localization error as function of time-step – [11]
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Integrated Algorithm
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Localization error as function of time-step – [11]
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Integrated Algorithm
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Localization error as function of time-step – [11]
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Integrated Algorithm
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[11][11]
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Integrated Algorithm
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[11][11]
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Bibliography[1] - its.dot.gov
[2] - Dr. Sergio Camacho-Lara, Handbook of Satellite Applications, “Current and Future GNSS and Their Augmentation Systems”, 2013, pp 617-654
[3] – Wikipedia.com
[4] - Elliott Kaplan, Christopher Hegarty , “Understanding GPS: Principles and Applications”, Second Edition, Artech House, 2005
[5] - wirelessdictionary.com
[6] - S. Stephenson, X. Meng, T. Moore, A. Baxendale, and T. Ford, “Accuracy requirements and benchmarking position solutions for intelligent transportation location based services,” in Proceedings of the 8th International Symposium on Location-Based Services, Vienna, Austria, 2011.
[7] - johndayautomotivelectronics.com
[8] - O. Hassan, I. Adly, and K. Shehata, “Vehicle localization n system based on ir-uwb for v2i applications,” in Computer Engineering Systems (ICCES), 2013 8th International Conference on , Nov 2013, pp. 133–137
[9] – gizmondo.com
[10] - S. Fujii, A. Fujita, T. Umedu, S. Kaneda, H. Yamaguchi, T. Higashino, and M. Takai, “Cooperative Vehicle Positioning via V2V Communications and Onboard Sensors,” 2011 IEEE Vehicular Technology Conference (VTC Fall), pp. 1–5, Sep. 2011
[11] - Amini, A., Vaghefi, R.M., De La Garza, J.M., Buehrer, R.M.: Improving GPS-based vehicle positioning for intelligent transportation systems. In: Proceedings of IEEE Intelligent Vehicles Symposium, (2014), pp. 1023–1029
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Conclusion
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• GNSS : good but not sufficient• Improvement with many different techniques• Hope (self-driving vehicles ..)