Simulative Identification of Possibilities

Transcription

1 Simulative Identification of Possibilities and Impacts of V2X-Communication Silja Assenmacher, Axel Leonhardt, Florian Schimandl, Fritz Busch Traffic Simulation Workshop Graz, June 30 July 02, 2008

2 Motivation Vehicle-Center- Communication WLAN, DSRC GPRS, UMTS DAB, FM Vehicle-Vehicle- Communication Vehicle-Infrastructure- Communication! 60! Center-Infrastructure- Communication 2

3 Motivation What kinds of applications are thinkable? What are the most efficient algorithms - thresholds? Simulation as a development assistance Required penetration rates? What are the impacts? on traffic flow traffic safety environment, fuel consumption data quality large-scale scenarios Simulation as an analysis assistance Cost-Benefit-Analysis to assist investment decision 3

4 Simulative Approach - Architecture t V2X-Application get_position() get_speed() set_speed() speed() setdesiredspeed() get_lane() setdesiredlane() Send (vehicle, message) Receive (vehicles, messages) VISSIM Traffic Vehicles within transmission range of sending vehicles Communication VCom.dll 4

5 Simulative Approach - Communication Main Requirement: Scalability: scenarios that are interesting easily comprise a few ten thousands of vehicles over tens of hundreds of kilometers. Beaconing Number of scheduled events in NS-2 in dependency of the number of vehicles and of fthe traffic density. All scenarios ran 100s and each node broadcasted a single 500-byte packet each second. Modeling the communication instead of simulating 5

6 Simulative Approach - Communication Probabilities of packet receptions Comparison of probabilities of packet receptions depending on the distance between sender and receiver and varying traffic densities Stochastic modeling of packet receptions with VCOM.dll 6

7 Simulative Approach - Interaction ti 7

8 Simulative Approach Application Example per time step send current speed limit to all veh. per second data collection by vehicle data (v, q per lane) per 30 seconds data aggregation lane (v, q), cross section (V, Q), section (D) congestion-check per RSU cross section: Checking On-Condition value on off Checking Off-Condition time t If congestion is detected: virtual speed funnel: V_zul [RSU] = 60 km/h V_zul [RSU - 1] = 70 km/h V_zul [RSU - 2] = 80 km/h V_zul [RSU - 3] = 90 km/h V_zul [RSU - 4] = 100 km/h 8

9 Simulative Approach Application Example Congestion/Hazard detection: Everywhere Faster Congestion/Hazard Warning: Everywhere Faster More Adaptive 9

10 Simulative Approach Application Example km/h 80 km/h 70 km/h 60 km/h 10

11 km/h Technische Universität München Simulative Approach Application Example Conventional Dynamic Traffic Control Delay times: 80 km/h - 5 % veh*hours 70 km/h 20 % C2X Penetration Rate - 10 % veh*hours 60 km/h 50 % C2X Penetration Rate - 10 % veh*hours 100 % C2X Penetration Rate - 26 % veh*hours compared to reference szenario without any traffic control 11

12 km/h Technische Universität München Simulative Approach Application Example Conventional Dynamic Traffic Control Delay times: 80 km/h - 5 % veh*hours 70 km/h 20 % V2X Penetration Rate - 10 % veh*hours 60 km/h 50 % V2X Penetration Rate - 10 % veh*hours 100 % V2X Penetration Rate - 26 % veh*hours compared to reference szenario without any traffic control 12

13 Processes driving i a vehicle How can V2X help? Road other road users Road environment Driving strategy Situation objective terms of reference Perception subjective terms of reference Driving of a vehicle Ati Actions vehicle Psychological and physical state of the driver Dynamic of the vehicle What are the impacts of driver warning? driver information? depending on the current v2x penetration rate [based on Todoskoff et al.,1996] How do drivers react on advanced In-Vehicle Information Systems? 13

14 Conclusions & future prospects Large-scale v2x-scenarios can be tested and analyzed using this approach to assist investment decisions Potentials concerning the simulation of traffic safety aspects we need to learn more about tactical driving and driver reactions on information and warning Extrapolation simulation lab calibration driver behavior penetration rate impacts field test Assistance for test site and test planning regional, real-life conditions, detailed 14

15 Questions? 15

16 Citationti ASSENMACHER, S.; LEONHARDT, A.; SCHIMANDL, F.; BUSCH, F. Simulative Identification of Possibilities and Impacts of V2X-Communication Communication, In Proceedings of Workshop on Traffic Modeling: Traffic Behavior and Simulation, Graz, June 30 - July 02,