1. Designing an Inter-Vehicular Network Stack for Car-to-Car Communication Pravin Shankar spravin@rutgers.edu Department of Computer Science Rutgers University

2. Outline Motivation – Traffic Safety TrafficView  Overview of System  Data Aggregation/Validation layer  On-demand Traffic Query Future work Conclusion

3. Some facts on Traffic safety * Since 1975, vehicle safety technology has focused on passive devices:  Seat belts  Air bags  Antilock Brake System However, the number of reported traffic accidents in US has remained relatively constant * based on U.S. Traffic Safety Facts Report

4. Passive Approach is not Enough What’s in front of that bus ? What’s behind the bend ? On rainy days On foggy days

5. TrafficView Uses vehicle-to-vehicle ad hoc network Enables active accident-prevention using dissemination of safety messages

6. TrafficView Overview Infrastructure-free approach based on car- to-car communication Each vehicle has an embedded system  short-range wireless communication  location information from GPS receiver  vehicle’s data from sensors through on-board diagnostic system (OBD-II)

7. How TrafficView works? Receive data from remote vehicle Non-validated dataset Validate Validated dataset Local data Display Broadcast data

8. TrafficView Prototype Developed in Java, ported to both Windows and Linux User Interface developed using OpenGL 802.11b network card  augmented with 5dBi omni-directional antenna Garmin eTrex GPS receiver TIGER ® road maps from U.S. Census Bureau (publicly available) Tested using 3 cars in real traffic conditions

9. TrafficView Outdoors

10. Too much traffic! Vehicles transfer records:  Vehicle ID (ID), position (POS), speed (SPD), broadcast time (BT) Consider a very high-density 5-lane road  Distance between consecutive cars – 5m  Average size of data records – 50 bytes  Wireless transmission range of 250 m 250 vehicles compete for the same wireless medium Total data transmitted every broadcast period = 250 MB Beyond the capabilities of current wireless technology!

11. Data Aggregation Aggregate data to see vehicles as far as possible with “acceptable” accuracy loss  Combine data for vehicles that are close to each other  Perform more aggregation as distance increases

12. Data Aggregation Having n records Calculate the aggregated record’s fields: POS and SPD are weighted averages.

13. Need for Data Validation Out-of-date information  Vehicles move and change speed  Packets may get lost in transit  Information received from OBD* might be invalid  Solution: Data aging Malicious nodes can corrupt data  Inject incorrect data  Refuse to forward data  Modify data  Solution: Probabilistic validation * On-Board Diagnostic Interface

14. Push v/s Pull Most cars are interested in information about immediate neighboring road segment  “Push” mechanism is sufficient How to get information about other roads? Broadcast is not scalable  Road segments are extensive in size  Traffic information is dynamic in nature There is a need for “pull” i.e. On-Demand traffic query

15. On-demand Traffic Query Protocol VITP – Vehicular Information Transfer Protocol  Location-sensitive queries and replies between nodes of a VANET  VITP Peers – nodes that operate as Clients Intermediates Servers  Agnostic of network communication layer

16. Location-sensitive queries Gas Station Coffee place GSM Link Traffic Server

17. Virtual Ad-Hoc Servers (VAHS) The server that computes the reply is a dynamic collection of VITP peers that:  Run on vehicles moving inside the target-location area of Q.  Are willing and able to participate in Q’s resolution. Gas Station Q

18. VAHS (continued) Established on the fly in an ad-hoc manner Identified with a query and its target-location area. Maintains no explicit knowledge (state) about its constituent VITP peers Follows a best-effort approach in serving queries VAHS members maintain no information about other members of the VAHS.

19. VITP transactions VITP Peer VANET node VAHS Q Q Intermediary nodes Q1 Q2 Q3 Q4 Q5 Q6 Q7 R R R Dispatch-query phaseVAHS-computation phase Dispatch-Reply phase Reply-delivery phase

20. Return Conditions (RC) Determine at which point in time the resolution of a VITP request can be considered done (VAHS computation completes). RC decision depends upon:  Query semantics: RC must be defined explicitly in the query specification.  Timeout condition: either pre-set by higher-level application semantics or default.

21. Other protocol features Support for caching. Message identifiers. Privacy protection. Dissemination vs. pull-based retrieval.

22. VITP – Message Format METHOD VITP/ Target: [rd_id_dest,seg_id_dest] From: [rd_id_src,seg_id_src] with Time: Expires: Cache-Control: TTL: msgID: Content-Length: CRLF

23. VITP URI Format / / ?[ &…]& &… type: classes of physical-world entities involved in the request (vehicle,service). tag: actual information sought (traffic, alert, gas, index). Example VITP requests: GET /vehicle/traffic?[cnt=10&tout=2000ms]&tframe=3min GET /service/gas?[cnt=4&tout=1800ms]&price<2USD POST /vehicle/alert?[cnt=*&tout=*]&type=slippery-road

24. Future work Reliable multicast – content delivery on VANETs  Provide support for rich multimedia on cars Outdoor Experiments  Perform experiments in real traffic conditions in order to better understand VANET characteristics Mobility emulation Traffic modelling Privacy Issues Deployment on real systems

25. Related Work Car Manufacturers  GM-CMU - http://gm.web.cmu.edu/http://gm.web.cmu.edu/  Daimler-Chrysler - http://www.rtna.daimlerchrysler.com/http://www.rtna.daimlerchrysler.com/  MIT CarTel, Berkeley PATH, PSU CITrans, etc. Europe  Fleetnet  Network-On-Wheels  Car 2 Car Communication Consortium - http://www.car-2-car.org/http://www.car-2-car.org/ Japan  Toyota InfoTechnology Center - http://www.toyota-itc.com/http://www.toyota-itc.com/  Tokyo University, Keio University And many more…

26. Thank you! http://discolab.rutgers.edu/traffic/ Work supported in part by NSF Collaborative Research: NeTS-NBD: (ANI 0520123) grant and NSF Information Technology Research (ANI 0121416) grant.. Faculty Liviu Iftode Graduate Students Pravin ShankarPravin Shankar, Stephen Smaldone, Nishkam RaviStephen SmaldoneNishkam Ravi Collaborators Cristian Borcea, Marios Dikaiakos, Tamer Nadeem, Yanzhi Bai, Josiane Nzouonta

27. E-Road Vision To use ad-hoc vehicular networking to improve the way we drive by supporting  Collaborative traffic information exchange  Emergency/safety message dissemination  On-demand traffic conditions monitoring  Dynamic route planning  Rich multimedia distribution