Distributed EmbeddedSystems Group – CCS
Towards the Tactile Internet: Low Latency Communication for Connected Cars1
Falko Dressler
Towards the Tactile Internet: Low Latency Communication for Connected Cars
Towards the Tactile Internet: Low Latency Communication for Connected Cars2
n Coordinated Automated Driving
n Towards the Tactile Internet
n Vehicular Networking
n Beaconing and Vehicular Ad Hoc Networks
n Case Study: Platooning
n Performance Evaluation
Outline
Towards the Tactile Internet: Low Latency Communication for Connected Cars3
Coordinated Automated Driving
Towards Autonomous Driving
Towards the Tactile Internet: Low Latency Communication for Connected Cars4
Inter-Vehicle Networking for Situation Awareness
Illustrations: C2C-CC
Towards the Tactile Internet: Low Latency Communication for Connected Cars5
Towards the Tactile Internet: Low Latency Communication for Connected Cars6
n Many communication channels availablen Which to pick when?
Towards Heterogeneous Vehicular Networks
Wi-Fi
DSRC
cellular
?“Technology2020”
mmWAVE
SoftwareDefinedRadio
VLC
Towards the Tactile Internet: Low Latency Communication for Connected Cars7
n Dedicated spectrum for inter-vehicle communicationin Europe (5.9 GHz), the US (5.9 GHz), and Japan (700 MHz)
n IEEE DSRC/WAVE, ETSI ITS G5, ARIB T109n Both build upon IEEE 802.11p
n Situation awareness as major year-one-applicationn ETSI DCC (Decentralized Congestion Control)
n But many fundamental research questions still unansweredn Scalability, real-time capabilities, use of heterogeneous networks
n Dagstuhl seminar series identified key challengesn Falko Dressler, Hannes Hartenstein, Onur Altintas and Ozan K. Tonguz, "Inter-Vehicle
Communication - Quo Vadis," IEEE Communications Magazine, vol. 52 (6), pp. 170-177, June 2014.
Standardization and Open Research
Towards the Tactile Internet: Low Latency Communication for Connected Cars8
Towards the Tactile Internet
Towards the Tactile Internet: Low Latency Communication for Connected Cars9
n Via Della Conciliazione
Towards 5GHuge Data Rates
Source: http://www.spiegel.de/panorama/bild-889031-473266.html and http://www.spiegel.de/panorama/bild-889031-473242.html
2005/4/4 2013/3/12
Towards the Tactile Internet: Low Latency Communication for Connected Cars10
Towards 5GThe evolution…
Source: http://de.slideshare.net/qualcommwirelessevolution/qualcomm-5g-vision-presentation
Towards the Tactile Internet: Low Latency Communication for Connected Cars11
n 7 billion devices in 2014 à 500 billion devices in 2022
Towards 5GHuge Data Rates
G. Fettweis, “5G: And Its Impact on Electronics”, 5G Lab Germany
Towards the Tactile Internet: Low Latency Communication for Connected Cars12
Towards 5GThe Internet of everything
Towards the Tactile Internet: Low Latency Communication for Connected Cars13
Towards 5GThe evolution…
Source: http://de.slideshare.net/qualcommwirelessevolution/qualcomm-5g-vision-presentation
Towards the Tactile Internet: Low Latency Communication for Connected Cars14
The New Challenge:Delays in the Order of a Millisecond
Towards the Tactile Internet: Low Latency Communication for Connected Cars15
Towards 5G and the Tactile InternetHaptics and remote control as a game changer
Source: http://ostsee-spezial.de/?p=148
Towards the Tactile Internet: Low Latency Communication for Connected Cars16
n 10 cameras @ 100Hz frame rate à 100Gb/s Latency @ <10ms
Towards 5G and the Tactile InternetLatencies in the low milliseconds
Source: http://baumgartnerfl.lima-city.de/stadion.html
Towards the Tactile Internet: Low Latency Communication for Connected Cars17
Towards 5G and the Tactile InternetDistributed Real-Time Control Systems
Towards the Tactile Internet: Low Latency Communication for Connected Cars18
Towards 5G and the Tactile InternetNetworked Control
4G:Content and
communications5G:
Networked Control
Towards the Tactile Internet: Low Latency Communication for Connected Cars19
Towards 5G and the Tactile InternetNew Challenges
The Tactile Internet
Towards the Tactile Internet: Low Latency Communication for Connected Cars20
n IEEE COMSOC Subcommittee “Tactile Internet”n Involved in a new standards family P1918.X
Towards 5G and the Tactile InternetStandardization
Architecture, Terminology and
Assumptions(IEEE P1918.X)
Codecs for Tactile Internet
(IEEE P1918.X.1)
AI for Tactile Internet(IEEE P1918.X.2)
MAC(P1918.X.3)
Vehicular Networking
Towards the Tactile Internet: Low Latency Communication for Connected Cars21
n WAVEn IEEE 1609.1: “Core System”
n IEEE 1609.2: Security
IVC Specific Protocols: DSRC/WAVE
[1] Jiang, D. and Delgrossi, L., "IEEE 802.11p: Towards an international standard for wireless access in vehicular environments," Proceedings of 67th IEEE Vehicular Technology Conference (VTC2008-Spring), Marina Bay, Singapore, May 2008
[2] Uzcátegui, Roberto A. and Acosta-Marum, Guillermo, "WAVE: A Tutorial," IEEE Communications Magazine, vol. 47 (5), pp. 126-133, May 2009
TCP / UDP
WAVE PHY
WAVE MAC and Channel Coordination
IPv6WSMP
Man
agem
ent
Secu
rity LLC
802.
11p 16
09.4
1609
.3
1609
.2
WAVE PHY
n IEEE 1609.3: Network Services
n IEEE 1609.4: Channel Management
Towards the Tactile Internet: Low Latency Communication for Connected Cars22
n PHY layer almost identical to IEEE 802.11an OFDM using 16 QAMn Reduced inter symbol interference
(multipath effects and Doppler shift)n Doubled timing parametersn Channel bandwidth (10 MHz instead of 20 MHz)n Reduced throughput (3 ... 27 Mbit/s instead of 6 ... 54 Mbit/s)n Communication range of up to 1000 mn Vehicles’ velocity up to 200 km/h
n MAC layer with extensions to IEEE 802.11an Randomized MAC addressn QoS (Priorities, see IEEE 802.11e, ...)n Support for multi channel and multi radion New ad hoc mode
IEEE 802.11p
Towards the Tactile Internet: Low Latency Communication for Connected Cars23
n New: 802.11 WAVE mode, now called OCB moden Main mode for all WAVE nodes
n Suggests the use of “Wildcard-BSS” in transmitted packets
n Every node is required to receive all packets using a wildcard BSS
n Inherently allows simultaneous transmission from and to a BSS
n Membership management just by using a BSS
IEEE 802.11 Basic Service Set (BSS)
BSSSSID “A”
BSSSSID “B”
Towards the Tactile Internet: Low Latency Communication for Connected Cars24
n Use of EDCA equivalent to IEEE 802.11e EDCA n DCF -> EDCA (Enhanced Distributed Channel Access)n Definition of four Access Categories (AC)
n AC0 (lowest) to AC3 (highest priority)n Introduction of AIFS (Arbitration Inter-Frame Space)
n ACs define...n CWmin, CWmax, AIFS, TXOP-Limit (max. continuous channel use)
n Management data are transmitted using DIFS instead of an AIFS
Access Control and QoS in WAVE
Medium busy Data
Data
Data
Towards the Tactile Internet: Low Latency Communication for Connected Cars25
n WAVE uses a dedicated frequency range in the 5.9 GHz bandn Exclusive for V2V and V2I communication
n Strictly regulated but no license costs
n In the US, FCC reserved 7 channels a 10 MHz (“U.S. DSRC”)
n 1 control and 4 service channels to be used by applications
n In Europa, ETSI reserved 5 channels a 10 MHz
Channel Management
[1] ETSI ES 202 663 V1.1.0 (2010-01) : Intelligent Transport Systems (ITS); European profile standard for the physical and medium access control layer of Intelligent Transport Systems operating in the 5 GHz frequency band
…
CriticalSafety of
Life
ch 1725.860GHz
SCH
ch 1745.870GHz
SCH
ch 1765.880GHz
ControlChannel(CCH)
ch 1785.890GHz
SCH
ch 1805.900GHz
SCH
ch 1825.910GHz
Hi-PowerPublicSafety
ch 184 5.920GHz
…
SCH
ch 1725.860GHz
SCH
ch 1745.870GHz
SCH
ch 1765.880GHz
SCH
ch 1785.890GHz
CCH
ch 1805.900GHz
Towards the Tactile Internet: Low Latency Communication for Connected Cars26
n Channel Managementn Management and safety information on the Control Channel (CCH)
à single radios have to switch to the CCH at known times
n Two-way communication on the Service Channel (SCH)
n Slot managementn Synchronization using GPS
n Standard: 100ms sync interval including 50ms on the CCH
n Slots start with a guard interval
Channel Management
[1] IEEE Vehicular Technology Society, "IEEE 1609.4 (Multi-channel Operation)," IEEE Std, November, 2006
CCHinterval
CCHinterval
“SCH”interval
“SCH”interval
t = n × 1s
Towards the Tactile Internet: Low Latency Communication for Connected Cars27
Beaconing and Vehicular Ad Hoc Networks
Towards the Tactile Internet: Low Latency Communication for Connected Cars28
n Fully distributed approach
n No communication infrastructure needed
n No data loss in fragmented networks
n No unique node identifiers mandated
n No network topology assumed, created, or maintained
n SOTIS: local knowledge bases + beaconing
n Aggregate all sensed data + received data
n Periodic broadcast of entries (beaconing)
n Ex.: one beacon every five seconds
n No congestion control in the wireless network
The SOTIS Approach
<!><!>
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SOTIS
Towards the Tactile Internet: Low Latency Communication for Connected Cars30
<!><!>
<!>
<!>
<!>
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idle send
rcvdup
n Flooding (Multi-Hop Broadcast)n Simplest protocol: „Smart Flooding“:
n Problem: Broadcast Storm
n Superfluous re-broadcasts overload channel
Broadcast Storm Problem
Towards the Tactile Internet: Low Latency Communication for Connected Cars31
n Estimate distance to sender as 0 ≤ ρij ≤ 1
n GPS based
n RSS based
Broadcast Suppression
[1] Wisitpongphan, Nawaporn and Tonguz, Ozan K. and Parikh, J. S. and Mudalige, Priyantha and Bai, Fan and Sadekar, Varsha, "Broadcast Storm Mitigation Techniques in Vehicular Ad Hoc Networks," IEEE Wireless Communications, vol. 14 (6), pp. 84-94, December 2007
Towards the Tactile Internet: Low Latency Communication for Connected Cars32
n Beacon interval: measure of channel quality and message prioritiesn Infrastructure elements: RSUs of different capabilities can be included
n Lightweight SSUs (service support unit)
n Interconnected RSUs
Fully Distributed: Adaptive Traffic Beacon (ATB)
[1] Christoph Sommer, Ozan K. Tonguz and Falko Dressler, "Traffic Information Systems: Efficient Message Dissemination via Adaptive Beaconing," IEEE Communications Magazine, vol. 49 (5), pp. 173-179, May 2011
[2] Christoph Sommer, Ozan K. Tonguz and Falko Dressler, "Adaptive Beaconing for Delay-Sensitive and Congestion-Aware Traffic Information Systems," Proceedings of 2nd IEEE Vehicular Networking Conference (VNC 2010), Jersey City, NJ, December 2010, pp. 1-8
Challenging questions• How frequently can the beacons be sent?• How frequently should the beacons be sent?• Which information should be included into the beacon?
Towards the Tactile Internet: Low Latency Communication for Connected Cars33
n Adaptive selection of beacon interval ΔI
n Consider message utility P
n Consider channel quality C
n Choose interval from range Imin to Imax
n Use factor wI to increase weight of C (ex. wI=0.75)
n ΔI = ((1 – wI) × P2 + (wI × C 2)) × (Imax – Imin) + Imin
Adaptive Traffic Beacon (ATB)
00.20.40.60.81
00.250.5
0.751
0 0.2 0.
4 0.6 0.8 1
P
I
C
Towards the Tactile Internet: Low Latency Communication for Connected Cars34
n Adaptive selection of beacon interval ΔI
n Calculation of message utility P based on metrics of (ex.)
n A: age of information
n De: distance to source of information
n Dr: distance to closest Road Side Unit (RSU)
n B: ratio of beacon contents received from Road Side Unit (RSU)
n Calculation of channel quality C based on metrics of (ex.)
n N: (estimated) number of neighbors (à future)
n S: (observed) signal-to-noise ratio (à present )
n K: (measured) collisions on channel (à past )
Adaptive Traffic Beacon (ATB)
P = A+De +Dr
3×B C = N +wC (S +K ) / 2
1+wC
Towards the Tactile Internet: Low Latency Communication for Connected Cars35
State of the Art: Adaptive Beaconing
n First proposed in Adaptive Traffic Beacon (ATB) protocol
[1] Christoph Sommer, Ozan K. Tonguz and Falko Dressler, "Traffic Information Systems: Efficient Message Dissemination via Adaptive Beaconing," IEEE Communications Magazine, vol. 49 (5), pp. 173-179, May 2011
10s 3s 1s 300ms 100ms 30ms ATB
1020
3040
5060
Beacon interval
Em
erge
ncy
msg
del
ay in
s
State of the Art: Adaptive Beaconing
n Later introduced in standardizationn ETSI ITS-G5 developed DCC (Decentralized Congestion Control) with TRC
(Transmit Rate Control)
n bt is the “busy ratio” of the channel
n Rather coarse grained measurement intervals
[1] Werner, Marc and Lupoaie, Radu and Subramanian, Sundar and Jose, Jubin, "MAC Layer Performance of ITS G5 - Optimized DCC and Advanced Transmitter Coordination," Proceedings of 4th ETSI TC ITS Workshop, Doha, Qatar, February 2012
1 . . .
. . . n
active
relaxed restrictive
bmin,1 s ≥ 15 % bmin,1 s ≥ 40 %
bmax,5 s < 15 % bmax,5 s < 40 %
n Maybe we all overlooked some issues!
n Antenna characteristicsn Radio signal shadowing
Problem Solved?
Towards the Tactile Internet: Low Latency Communication for Connected Cars38
Experimental Validation
[1] Christoph Sommer, David Eckhoff, Reinhard German and Falko Dressler, "A Computationally Inexpensive Empirical Model of IEEE 802.11p Radio Shadowing in Urban Environments," Proceedings of 8th IEEE/IFIP Conference on Wireless On demand Network Systems and Services (WONS 2011), Bardonecchia, Italy, January 2011, pp. 84-90
[2] David Eckhoff, Christoph Sommer, Reinhard German and Falko Dressler, "Cooperative Awareness At Low Vehicle Densities: How Parked Cars Can Help See Through Buildings," Proceedings of IEEE Global Telecommunications Conference (GLOBECOM 2011), Houston, TX, December 2011
Towards the Tactile Internet: Low Latency Communication for Connected Cars39
n Models allow taking into consideration(a) static and(b) moving obstacles
n Research question: What is their impact on beaconing?
Establishment of New Models
Towards the Tactile Internet: Low Latency Communication for Connected Cars40
n DynB – Dynamic Beaconing
n Considering all the radio shadowing effects to adapt very quickly to the current channel quality
n Main idea: continuously observe the load of the wireless channel to calculate the current beacon interval
n I = Imin + r (Imax – Imin)
with Imax = (N+1) Imin (N is the number of neighbors)and r = (bt / bdes) - 1 clipped in [0, 1]
Towards new Beaconing Concepts
[1] Christoph Sommer, Stefan Joerer, Michele Segata, Ozan K. Tonguz, Renato Lo Cigno and Falko Dressler, "How Shadowing Hurts Vehicular Communications and How Dynamic Beaconing Can Help," Proceedings of 32nd IEEE Conference on Computer Communications (INFOCOM 2013), Mini-Conference, Turin, Italy, April 2013
Towards the Tactile Internet: Low Latency Communication for Connected Cars41
n Assuming a payload of l = 512 bit (at 18 Mbit/s),we obtain
tbusy = Tpreamble + Tsignal + Tsym [(16 + l + 6) / NDBPS] = 104 µs
n Using a minimum AIFS and an average initial backoff counter, we get a maximum bt
bt = tbusy / (tbusy + taifs + tidle) = 0.64
n With some maximum collision probability of 0.05, we get a maximum bt
bt = 0.25
How Busy Can/Should the Channel Be?
Towards the Tactile Internet: Low Latency Communication for Connected Cars42
n Assuming two larger clusters of vehicles meeting spontaneously (e.g., at intersections in suburban or when two big trucks leave the freeway)
Handling Dynamics in the Environment
Towards the Tactile Internet: Low Latency Communication for Connected Cars43
n Temporary network fragmentation
Remaining Problems
Towards the Tactile Internet: Low Latency Communication for Connected Cars44
n Idea: detect current scenario, switch between protocols
n Check for fragmented networkn Network connected à perform broadcast suppression
n Network fragmented à perform Store-Carry-Forward
DV-CAST
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Towards the Tactile Internet: Low Latency Communication for Connected Cars45
n Mechanismn Nodes periodically send Hello beacons containing position, speedn Nodes maintain 3 neighbor tables
n Same direction, aheadn Same direction, driving behindn Opposite direction
n Messages contain source position and Region of Interest (ROI)
n For each message received, evaluate 3 Flags:n Destination Flag (DFlg):
Vehicle in ROI, approaching sourcen Message Direction Connectivity (MDC):
neighbor driving in same direction, further away from sourcen Opposite Direction Connectivity (ODC):
neighbor driving in opposite direction
DV-CAST
[1] Tonguz, Ozan K. and Wisitpongphan, N. and Bai, F., "DV-CAST: A distributed vehicular broadcast protocol for vehicular ad hoc networks," IEEE Wireless Communications, vol. 17 (2), pp. 47-57, April 2010
Towards the Tactile Internet: Low Latency Communication for Connected Cars46
n Algorithm
DV-CAST
Towards the Tactile Internet: Low Latency Communication for Connected Cars47
n Simulation results
DV-CAST
Towards the Tactile Internet: Low Latency Communication for Connected Cars48
n Temporary network fragmentation
n Undirected message dissemination
Remaining Problems
Towards the Tactile Internet: Low Latency Communication for Connected Cars49
✓
n TO-GOn “Topology-Assisted Geo-Opportunistic Routing”
n Nodes periodically send Hello beacons; Contents:
n Number of neighbors
n Bloom filter of neighbor IDs
n IDs of neighbors furthest down the road/roads
n Thus, nodes know about all 2-hop neighbors
Geocast
[1] Lee, K.C. and Lee, U. and Gerla, M., "Geo-Opportunistic Routing for Vehicular Networks," IEEE Communications Magazine, vol. 48 (5), pp. 164-170, May 2010
Towards the Tactile Internet: Low Latency Communication for Connected Cars50
n Bloom Filtern Idea:
n Bloom filter is a bit field X
n Hash functions h1 to hk map input data x à one bit (each) in X
n Insertion of x: Set X[hi(x)] ← 1 i [1..k]
n Test for x X: Check X[hi(x)] 1 i [1..k]
n Probabilistic test for “x X”
n Possible results: no / maybe (à chance of false positives)
n Allows for very compact representation of X
Geocast
[1] Bloom, Burton H., "Space/time trade-offs in hash coding with allowable errors," Communications of the ACM, vol. 13 (7), pp. 422-426, 1970
0 1 0 0 0 1 0 1
“foo”
h1 h2 h3
Towards the Tactile Internet: Low Latency Communication for Connected Cars51
n TO-GOn Find best next hop (Target Node, T)
n Find N: Furthest neighbor towards destination
n Find J: Furthest neighbor towards destination, currently on junction
n Find NJ: Furthest neighbor towards destination, as seen by J
n if N, NJ are on the same road (and running in greedy mode),pick Nelse, pick J
Geocast
N
NJ
J
Towards the Tactile Internet: Low Latency Communication for Connected Cars52
Case Study: Platooning
Towards the Tactile Internet: Low Latency Communication for Connected Cars53
Towards the Tactile Internet: Low Latency Communication for Connected Cars54
n A specific application: platooningn solve traffic congestion problems
n decrease pollution
n increase safety
n decrease severe injuries/deaths
n Avoid wasting driving time
n Research questionsn Impact of platooning on network (and vice versa)
n Develop protocols to better support platooning
Distributed ControlPlatooning as one of the most challenging applications
Towards the Tactile Internet: Low Latency Communication for Connected Cars55
n Manual driving (Dist: 2s ~ 50m @ 100km/h)
n ACC – Radar based (Dist: 1s ~ 28m @ 100km/h)
n Simple CACC – Radar + IVC (Dist: 0.6s ~ 16m @ 100km/h)
Automated Car Following
BrakeReactionPerception
BrakeRadar
BrakeComm
Towards the Tactile Internet: Low Latency Communication for Connected Cars56
n Cooperative CACC (Dist: 0.2s ~ 5m @ 100km/h)
CACC / Platooning Controller
Michele Segata, Bastian Bloessl, Stefan Joerer, Christoph Sommer, Mario Gerla, Renato Lo Cigno and Falko Dressler, "Towards Communication Strategies for Platooning: Simulative and Experimental Evaluation," IEEE Transactions on Vehicular Technology, vol. 64 (12), pp. 5411-5423, December 2015.
BrakeComm BrakeComm
57
n Permit detailed simulation ofn Communications
n Road traffic
Simulation Framework
Michele Segata, Stefan Joerer, Bastian Bloessl, Christoph Sommer, Falko Dressler and Renato Lo Cigno, "PLEXE: A Platooning Extension for Veins," Proceedings of 6th IEEE Vehicular Networking Conference (VNC 2014), Paderborn, Germany, December 2014, pp. 53-60.
Towards the Tactile Internet: Low Latency Communication for Connected Cars
Platooning Braking – Minimum Distance
1 2 3 4 5 10 20
01
23
45
1 .33 .2 .1 .05.5 .25
minim
um
distance
(m)
beacon frequency (Hz)
inter-message delay (s)
2 m/s2
4 m/s2
6 m/s2
8 m/s2
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59
n Develop and test 4 different protocolsn Random transmission (static beaconing)
n Synchronized transmission (slotted beaconing)
n Both w/ and w/o transmission power control
Communication Protocols
Towards the Tactile Internet: Low Latency Communication for Connected Cars
Protocol Performance for 640 Cars
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0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
00.2
0.4
0.6
0.8
1safe
timeratio
delay requirement (s)
StbPSlbPStbSlbDynBDCC
Emergency Braking Requirements
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WE CAN USE ADYNAMIC APPROACH!
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n Main idea:n the more constant the system, the lower the requirement
n send updates only when needed, use prediction otherwise
n Problems:n awareness: we can’t simply stop beaconing
n what does it mean “constant”?
Jerk: The Concept
Michele Segata, Falko Dressler and Renato Lo Cigno, "Jerk Beaconing: A Dynamic Approach to Platooning," Proceedings of 7th IEEE Vehicular Networking Conference (VNC 2015), Kyoto,Japan, December 2015, pp. 135-142.
Towards the Tactile Internet: Low Latency Communication for Connected Cars63
n Jerk:n physical quantity measuring variation of acceleration over time
n using an estimation of jerk we compute the beacon interval
n tunable parameters:
n minimum beacon interval
n maximum beacon interval
n sensitivity
Jerk Beaconing
Jerk Beaconing
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n Problem:n (dynamically) undersampling a system à risk in case of losses
n Solution: couple with a reliable delivery mechanismn send packets in a chained fashion
n use transmit power control to increase spatial re-use
n static assignment
n piggyback acknowledgements
n ensure delivery OR
n try again OR
n notify application about failure (stop simulation and log outcome)
n re-propagate leader information (most important)
Jerk Beaconing: Reliability
Protocol Performance for 640 Cars – Harsh scenario
Towards the Tactile Internet: Low Latency Communication for Connected Cars66
3 m
45 %
4 m
17 %
Towards the Tactile Internet: Low Latency Communication for Connected Cars67
n There’s life after static beaconing even for platooning, butn jerk beaconing still a heuristic proof of conceptn can we theoretically link control requirements, beacon interval, and inter-
vehicle gap? à optimal beacon rate for target requirementn how can we handle network failures?
n More Options: Getting Heterogeneousn Communication between platoon lead and all followers: radio broadcastn Communication between succeeding cars: visual light communication
(VLC)
n Simple VLC model:n Constant (processing) delayn 20% packet loss
Next Steps
Michele Segata, Renato Lo Cigno, Hsin-Mu Tsai and Falko Dressler, "On Platooning Control using IEEE 802.11p in Conjunction with Visible Light Communications," Proceedings of 12th IEEE/IFIP Conference on Wireless On demand Network Systems and Services (WONS 2016), Cortina d'Ampezzo, Italy, January 2016, pp. 124-127.
n LED transmitter, CCD receiver
Impact of Using VLC
8 - 11p 8 - vlc 160 - vlc 320 - vlc 640 - vlc
0
1
2
3
4
5
6
distance
(m)
scenario
bad
great
Towards the Tactile Internet: Low Latency Communication for Connected Cars68
Protocol Performance with VLC
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
00.2
0.4
0.6
0.8
1safe
timeratio
delay requirement (s)
802.11p only, 8 vehicles802.11p/VLC (leader/front), 8 vehicles802.11p/VLC (leader/front), 160 vehicles802.11p/VLC (leader/front), 320 vehicles802.11p/VLC (leader/front), 640 vehicles
Towards the Tactile Internet: Low Latency Communication for Connected Cars69
Performance Evaluation
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n Real-world experimentsn Outline only limited information about the feasibility and the performance
à experiments with roughly 400 cars are planned in a German project
n Performance evaluation for 2%, 10%, 50%,… penetration?
n Simulationn Usually using standard network simulation methods
n ns2/ns3, OMNeT++, GloMoSim, OPNET, …
n Detailed network layers, simple “support” modules
n Appropriate for VANETs?
n Research challenge: appropriate mobility modeling
Evaluation
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n Early approachesn Random Waypoint
n Manhattan Grid
n Traces
n Road traffic microsimulationn Simulation of individual cars
n Exact modeling of streets, speed limits, etc.
n Coupling with network simulationn Pre-computation (or on-demand simulation) of road traffic
n Incorporation of computed traces into network simulators(can be used for real-world traces as well)
Mobility Modeling
[1] C. Sommer and F. Dressler, "Progressing Towards Realistic Mobility Models in VANET Simulations," IEEE Communications Magazine, vol. 46 (11), pp. 132-137, November 2008
[2] J. Yoon, M. Liu, and B. Noble, "Random waypoint considered harmful," Proceedings of 22nd IEEE Conference on Computer Communications (IEEE INFOCOM 2003), vol. 2, San Francisco, CA, March 2003, pp. 1312-1321
[3] V. Naumov, R. Baumann, and T. Gross, "An evaluation of inter-vehicle ad hoc networks based on realistic vehicular traces," Proceedings of 7th ACM International Symposium on Mobile Ad Hoc Networking and Computing (ACM Mobihoc 2006), Florence, Italy, March 2006, pp. 108-119
Towards the Tactile Internet: Low Latency Communication for Connected Cars72
n Unidirectional coupling: models road traffic without any optimization through TIS information
n Bidirectional coupling is important to analyze effects of IVC on road traffic and vice versa
Coupling Approaches
[1] Christoph Sommer, Reinhard German and Falko Dressler, "Bidirectionally Coupled Network and Road Traffic Simulation for Improved IVC Analysis," IEEE Transactions on Mobile Computing, vol. 10 (1), pp. 3-15, January 2011
[2] M. Treiber, A. Hennecke, and D. Helbing, "Congested Traffic States in Empirical Observations and Microscopic Simulations," Physical Review E, vol. 62, pp. 1805, 2000
Network Simulation Road Traffic Simulation
B. Real-world traces
A. Random node movement C. Micro-
simulation
D. Bidirect. coupling
Towards the Tactile Internet: Low Latency Communication for Connected Cars73
n Veins – Vehicles in Network Simulationn http://veins.car2x.org/
n Based on tools that are well-acceptedin their respective communitiesn OMNeT++ for network simulation
n SUMO for road traffic microsimulation
n Objectivesn Bidirectionally coupled simulation of VANETs
n Incorporation of real-world street maps
n Flexible and fast(!) simulation
Veins
[1] Christoph Sommer, Reinhard German and Falko Dressler, "Bidirectionally Coupled Network and Road Traffic Simulation for Improved IVC Analysis," IEEE Transactions on Mobile Computing, vol. 10 (1), pp. 3-15, January 2011
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Veins System Architecture
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[1] Christoph Sommer, Reinhard German and Falko Dressler, "Bidirectionally Coupled Network and Road Traffic Simulation for Improved IVC Analysis," IEEE Transactions on Mobile Computing, vol. 10 (1), pp. 3-15, January 2011
http://veins.car2x.org
n Evaluation metrics: traveling time vs. CO2 emissionn Quite accurate gas consumption / emission models available
n E.g., EMIT
Further Challenges
[1] A. Cappiello, I. Chabini, E. Nam, A. Lue, and M. Abou Zeid, “A statistical model of vehicle emissions and fuel consumption,” 5th IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC), pp. 801–809, 2002
[2] C. Sommer, R. Krul, R. German, and F. Dressler, "Emissions vs. Travel Time: Simulative Evaluation of the Environmental Impact of ITS," Proceedings of 71st IEEE Vehicular Technology Conference (VTC2010-Spring), Taipei, Taiwan, May 2010
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Traveling Time vs. CO2 Emission
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n Accuracy of technically optimal solutions and imperfect driver behavior
Further Challenges
[1] R. König, A. Saffran, and H. Breckle, “Modelling of drivers’ behaviour,” in Vehicle Navigation and Information Systems Conference, Yokohamashi, Japan, August/September 1994, pp. 371–376.
[2] W. Barfield, M. Haselkorn, J. Spyridakis, and L. Conquest, “Commuter Behavior and Decision-Making: Designing Motorist. Information Systems,” in 33rd Human Factors and Ergonomics Society Annual Meeting, Santa Monica, CA, 1989, pp. 611–614.
[3] P. C. Cacciabue, Ed., Modelling Driver Behaviour in Automotive Environments: Critical Issues in Driver Interactions with Intelligent Transport Systems. Springer, 2007.
[4] F. Dressler and C. Sommer, "On the Impact of Human Driver Behavior on Intelligent Transportation Systems," Proceedings of 71st IEEE Vehicular Technology Conference (VTC2010-Spring), Taipei, Taiwan, May 2010
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Driver Behavior – Results
[1] F. Dressler and C. Sommer, "On the Impact of Human Driver Behavior on Intelligent Transportation Systems," Proceedings of 71st IEEE Vehicular Technology Conference (VTC2010-Spring), Taipei, Taiwan, May 2010
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Conclusions
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Today, we studied
n Challenges and opportunities of using connected cars conceptsn Capability to connect everyone and everything
n Can be seen as a big data storage
n Help improving our daily road traffic experience and safety
n Not discussedn Security issues: Strong debate about privacy vs. security
… as can be seen, there are many open challenges and questions for another decade of interesting research JJ
Conclusions
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n Vehicular Networking (Cambridge University Press)
More Information?
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