1. Realistic Mobility Models for Vehicular Ad hoc Network (VANET) Simulations ITST 2008 69821507 高弘毅 69821514 洪佳瑜 69821516 蔣克欽

2. Outline  Motive  Introduction  Architecture  Evaluation  Conclusion & Future work

3. Motive  The goal of VANET research is to develop a vehicular communication system to enable quick and cost-efficient distribution of data for the benefit of passengers’ safety and comfort.  ns-2, OPNET and Qualnet  PARAMICS, CORSIM, VISSIM etc.  We previously developed a tool MOVE to facilitate users to rapidly generate realistic mobility models for VANET simulations.

4. Introduction  To describe the architecture and implementation of MOVE  Three case studies The existence of traffic Driver route choice at the intersection Car overtaking behavior  We discuss how these details affect the network topology and resultingly the performance of VANET in the simulation.

5. Architecture (1/4)  MOVE consists of two main components: Map Editor Vehicle Movement Editor

6. Architecture (2/4)  Map Editor: to create the road topology~ To be manually created by the user To be generated automatically To be imported from existing real world maps (Ex: TIGER)

7. Architecture (3/4)  Vehicle Movement Editor: to specify the trips of vehicles and the route that each vehicle will take for one particular trip~ To be manually created by the user To be generated automatically To be specified based on a bus time table to simulate the movements of public transport

8. Architecture (4/4)

9. Evalution  A “ truely realistic ” simulation is very challenging since human behavior (e.g. mood, sex, age, etc.) and unexpected road accidents are difficult to model while all of them have strong effects on vehicle movement patterns.  We set out to understand how the existence of Traffic lights Driver route choice Car overtaking behavior affect the VANET simulation results.

10. Evalution  The impact of mobility models generated by MOVE on the performance of ad-hoc routing protocols.  The road topology generated by MOVE is based on the TIGER database data.  The propagation model employed in our simulation is the TwoRayGround model.  All nodes use 802.11 MAC operating at 2Mbps.  The transmission range is 250m.  The routing protocol is AODV.

11. A. Existence of traffic lights (1/4)  A high node density To improve the network connectivity. To suggest a higher chance for packet collision since more nodes might be transmitting at the same time.

12. A. Existence of traffic lights (2/4)  As a result, the packet delivery ratio decrease when there are more traffic sources.  The packet delivery ratio is improved when the traffic lights are simulated.

13. A. Existence of traffic lights (3/4)  Frequent link breakage between two adjacent clusters which significant degrades the network performance.

14. A. Existence of traffic lights (4/4)  The increased traffic light cycle increases the cluster size, it also introduce more link breakage between clusters and results in more packet losses.

15. B. Driver route choice  Different choices of route directions can significantly change the simulation results(the x-y-z notation in Figure 7 means that the car has x% of chance to turn left, y% to go straight and z% to turn right)

16. C. Overtaking behavior  The effect of overtaking behavior is less significant when the network density is higher.  The packet delivery ratios in overtaking-allowed scenario is close to results of no-overtaking scenario when we increase the number of nodes from 250 to 350.

17. Conclusion & Future work  We show that the details of a mobility model such as the existence of traffic lights, driver route choice and car overtaking behavior can have a significant impact on the simulation results.  In the next version of our software, we plan to build an interface to tightly integrate SUMO and ns-2. The vehicles can dynamically adjust their routes based on different traffic scenarios and communication techniques employed.

18. THANK YOU