A proactive route search method for an efficient city surveillance
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A city surveillance system based on floating car system is a promising technique for resilient city management. A floating car system can compose a volatile and efficient fabric for a sustainable city. We examine two kinds of extension on a normal floating car system. The one is a radar-assisted floating. The other is a proactive route search in which each floating car proactively inform their route to the center. We confirmed how these extensions contribute to both sensing coverage and traffic efficiency. The result encourages a floating car center operator can harvest higher coverage sensing data without extending contributor’s travel time
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A proactive route search method for an efficient city surveillance
- 1. ITS World Congress 2014 A proactive route search method for an efficient city surveillance Osamu Masutani Denso IT Laboratory, Inc. 1 Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 2. Summary Background : City surveillance and FCD Sensing coverage for city surveillance Method 1 : Radar-assisted FCD Method 2 : Proactive route guidance Conclusion & future work 2 Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 3. Background : ITS for Smart City ITS has potential to be an important fabric for sustainable smart city Power train with less environmental impact Efficient traffic management Alternative way to monitor urban environment City surveillance by vehicle Key feature for smart city management Crowd sourcing is promising = FCD Denso Technical Review https://www.denso.co.jp/ja/aboutdenso/technology/dtr/v16/files/14.pdf 3 Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 4. Key performance indices for city surveillance KPI for city surveillance by FCD : Sensing quality (Accuracy) Quality sensors Sensing quantity (Coverage) Number of sensors Trajectory of sensors = routing 4 Number of satellites Trajectory (orbit) of satellites Coverage Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 5. Enhancement of coverage by environment sensor Utilize environment sensor in vehicle In some scenario, detection of surrounding vehicle virtually be able to increase data points of sensing Camera, Radar, Lidar, etc.. Radar-assisted FCD 5 Denso Technical Review https://www.denso.co.jp/ja/aboutdenso/technology/dtr/v17/files/10.pdf http://www.embedded.com/print/4011081 Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 6. Enhancement of coverage by proactive routing Route control can dispatch each floating car efficiently By dispersing their routes in the city Can floating car be controlled by center ? – Yes ! In-direct traffic control (Signs, navigation) Fleet management Automated car Proactive route search Probing Route control 6 Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 7. Core simulation function is available as Metro traffic simulator Evaluation environment Traffic simulation with a simple setting Simple micro simulation Grid map, One way traffic City surveillance target : Traffic (Volume, Speed) 7 Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 8. Evaluation 1 : Rader Assisted FCD (R-FCD) Adaptive cruise control system can measure surrounding vehicles Traffic volume and relative speed can be estimated Evaluation How radar leverage data points compared to conventional FCD ? 8 Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 9. Evaluation 1 : Result - observation coverage R-FCD produce much higher coverage than conventional FCD 9 Link ID time Traffic Volume Full observation FCD (10%) R-FCD (10%) Example Link time Volume Observed traffic volume ratio Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 10. Evaluation 1 : Result - Link travel time estimation Higher link coverage yields higher accuracy of link travel time estimation 10 Link ID time Link Travel Time Full observation FCD (10%) R-FCD (10%) Example Link time Travel TIme Estimation error Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 11. Evaluation 2 : Proactive route search Each FC reserves route before it arrives Find optimal route according to number of reservations Reserve each link on the route Implementation Telematics-based navigation Path prediction Connected - automated driving 11 Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 12. Evaluation 2 : Evaluation spec Indices Coverage Travel time Compared with conventional route search methods Static (distance cost) Reactive (current traffic) Proactive (reservation) 12 20 15 10 5 0 Static Reactive Proactive 1000 2000 3000 4000 5000 # of congested links Simulation Steps Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 13. Evaluation 2 : Result - both indices are improved Coverage is increased Travel time is reduced 13 Traffic Volume Link ID Distance Reactive Proactive Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 14. Evaluation 2 : Result - Trade-off Trade-off between coverage and travel time In this case, traffic dispersion also carries reduction of traffic congestion The effect of reduction of traffic congestion compensate extension of travel distance. Relation between coverage and average travel time 14 0.49 0.48 0.47 0.46 0.45 0.44 0.43 0.42 0.41 0.4 Better Distance Reactive Worse 300 400 500 600 Coverage Average Travel Time [sec] Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 15. Conclusion and Future work Both of two active sensing methods can enhance FCD Radar assisted FCD can dramatically increase data amount Proactive route search can also increase sensing area coverage without extending travel time of each car Future work More realistic evaluation (real city, real traffic) More dynamic situation (dynamic sensing target) 15 Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 16. Appendix 16 Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 17. Appendix – Scalability : traffic demand Proactive route search enhance more in congested time 17 Coverage Traffic demand [volume/hour] Traffic demand [volume/hour] Travel time [sec] Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
- 18. Appendix – Scalability : trip length Proactive route search can be applicable for short trip 18 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 3 4 5 6 7 8 9 1011121314151617181920 Distance RealTimeTravelTime RealTimeVolume Predicted Map length [blocks] Coverage Copyright (C) 2014 DENSO IT LABORATORY,INC. All Rights Reserved.
Editor's Notes
- Hello everyone I am Osamu Masutani from Dnso IT Laboratory, Inc. in Japan. Our company is a subsidiary company of Denso whose mission is developing and evaluating advanced software tehcnologies. Today I’ll present you about a proactive route search method for an efficient city surveillance.
- Here is a summary of today’s presentation. First of all I’ll show you the background of this project. And I’ll briefly explain about sensing coverage for city surveillance And then I’ll show you two kind of methods to enhance sensing coverage. First one is radar-assited FCD and second one is a proactive route guidance. Finally I’ll conclude these work and show future work
- Let me introduce background of this project. These technologies helps not only traffic system but also whole city. ITS has potential to be an important fabric for sustainable smart city. For example power train with less einvironmental impact , efficient traffic management or alternative way to monitor urban environment can be important role of sustainable smart city. We focused on third element or city surveillance by vehicle. This is a key feature for smart city management and in this field crowd sourcing is promising technique.
- Key performance index for city surveillance consists of two aspects. Sensing quality and sensing quantity. Sensing quality is mainly affected by quality of sensors. Sensing quantity is mainly affected by both number of sensors and trafectory of sensors.
- To enhance coverage we first utilize environment sensor in vehicle. In some scenario, detection of surrounding vehicle can to virtually increase data points of sensing. We introduce radar-assisted FCD in this work.
- And secondly we introduce proactive routing to enhance coverage. Route control can dispatch each floating car efficiently by dispersing their routes in the city. Fleet management system, traffic signs and car navigation can provide controllability to floating car. Upon these assumption we introduce proactive route search method.
- Let me introduce our evaluation environment. We examine traffic simulation with simple setting micro simulation. We employ grid map and one way traffic. And our city surveillance target is traffic itself in this work.
- We evaluate radar assisted FCD. In adaptive cruise control system already have enough specification for this. Traffic volume and relative speed can be estimated. We confirm how radar leverage data points compared to conventional FCD.
- Here is first result. We calculate observation coverage of r-FCD and conventional FCD. R=FCD produce much higher coverage than FCD. This is observed traffic volume ratio on full traffic.
- This is the other result. We evaluate link travel time of each link from each traffic data. R-FCD has much less error than conventional one.
- Next we introduce second technique. In proactive route search each floating car reserves route before it arrives there. At first the vehicle query route to traffic center, then traffic enter answer optimal route according to reservations, and vehicle reserve the each links on the route. We can implement this on telematics service or path prediction system on ADAS or connected automated driving system.
- Here is evaluation specification of proactive route search. There are two indices coverage and travel time here. And we compared these three route search static means distance based search reactive means current traffic based search and proactive means reservation based search. Instant result shows proactive route search has effect of reduction of congestion.
- This result shows time-space traffic volume plot. With distance based search traffic concentrate to some main arterial links then heavily congested. With reactive search traffic congestion seems to be moved but is not avoided. With proactive search congestion seems to be eliminated. So average travel time is lowest with proactive route search. Proactive route also provide high coverage.
- Naturally said trade-off exist between coverage and travel time. Traffic dispersion which is conducted by de-touring brings extension of travel time. However in this simulation setting, traffic dispersion also carries reduction of traffic congestion. The effect of reduction of traffic congestion compensate extension of travel distance.
- Let me conclude my presentation. I introduced two active sensing methods and confirm their effect of enhance FCD coverage. Radar assisted FCD can dramatically increase net amount of floating car data. Proactive route search can also increase sensing area coverage without extending total travel time. For future work we will try more realistic simulation using real city , traffic data . And try to extend our method more dynamic situation.