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Enhance mobility and driver experience with multihop data exchange
between UAVs and vehicles
Yaroslav Domaratsky, PhD​1*
1. CTO, Head of Engineering at Sreda Software Solutions, email: ​yaroslav@sredasolutions.com
Abstract
Unmanned Aerial Vehicles (UAVs) have growing potential in the Public Safety (PS), commercial,
government, and consumer domains. Over six million UAVs will be sold in the US in 2016, and the
total available UAV market is estimated to reach 100 million UAVs sold worldwide by 2020. We
believe that flying Wireless Mesh Network (WMN) would be the most suitable technology to organize
communication between UAVs, between UAVs and ground infrastructure and between UAVs and
ground vehicles. In the paper we propose technical approach to implement the above listed use cases
using low cost communication technologies within ITS architecture. In the paper we define use cases,
discuss potentially applicable communication technologies, overview WMN data routing protocols,
list UAV specific requirements and discuss product differentiation.
Keywords:
UAV, WMN, C-ITS, 802.11p, DSRC, LTE Proximity Services, LTE ProSe, LTE Advanced Pro,
Cellular-V2x, Public Safety, ADAS
1. Threats And Opportunities
Given the rapid growth of UAVs, new threats have emerged and include:
● New safety risks for private and commercial aviation
● UAV to UAV traffic management and collision avoidance
● UAV to ground vehicle collaboration
● Collision avoidance with ground structures and terrain
● Secure command and control, video and data links.
The existent ADS-B aviation safety and control systems are very expensive so this is desirable to use
low communication technologies to implement small civil UAV safety and control features.
The below figure shows target markets for the system we propose in the paper.
Figure 1 - Target market
Targeting the small civil UAVs market segment, the opportunities for operating UAVs utilizing WMN
include:
● Low cost safety messaging, collision avoidance, communication and data routing solution
● Simple integration, operation and extended user interface capabilities
● New PS, commercial, government, and consumer applications
● oOerating UAVs beyond line of sight safely and securely.

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Enhance mobility and driver experience with multihop data exchange between UAVs and vehicles
The main challenges related to UAVs communication networks include ad-hoc data routing,
intermittent connectivity, changing link quality, Disruption Tolerant Networking (DTN), seamless
handovers and application level software aspects. We propose to utilize IEEE 802.11p [1] or / and
LTE communication technology (LTE Proximity Services, Cellular-V2x) to address the above
challenges. We believe the proposed approach enables reliable data exchange in UAVs
communication networks to support collision avoidance, Сommand and Сontrol (С&С) and media
streaming between UAVs and between UAVs and ground vehicles.
2. Wireless Mesh Networking
2.1. WMN overview
WMN is a communications network made up of radio nodes communicating with each other in ad-hoc
(peer-to-peer) mode. This is in contrast to a star topology network, in which each node communicates
only with a hub. In WMN links are typically self-forming, and topology is based on the wireless
environment, rather than configuration parameters. WMN often consist of mesh clients, Mesh Points
(MP) and Mesh Point Roots (MPR). The mesh clients are often laptops, cell phones and other wireless
devices while the MP’s forward traffic to and from the MPR’s which may, but need not, connect to the
Internet. When one MP can no longer operate, the rest of the MP’s can still communicate with each
other, directly or through one or more intermediate MP’s.
2.2. Wireless communication between UAVs
There are wireless communication technologies potentially suitable for mass deployment UAV
communication:
● IEEE 802.11p, [1] (originally developed for V2x applications)
● LTE Proximity Services (defined starting 3GPP release 12).
Both technologies allow a sub 10ms latency and a mobility range of few kilometers at delta speed up
to 1000 km/h. Both technologies use the same signal modulation. IEEE 802.11p technology is already
proven. LTE Proximity Services (Cellular-V2x) technology is in validation stage. Vehicle crash
prevention systems utilize IEEE 802.11p technology to constantly broadcast vehicle positioning and
status information.
Similar approach can be used for small civil UAVs safety systems to:
● Protect critical infrastructure objects (e.g. airports, tall buildings, bridges, etc.)
● Prevent collisions between UAVs
● Exchange data between UAVs, between UAVs and ground infrastructure, between UAVs and
vehicles (e.g. broadcast 3D “ Travelways” information, implement media streaming)
● Broadcast messages between UAVs (e.g. alarm, environmental and context messages).
Field tests show we could reach 2-4 kilometers communication range with IEEE 802.11p technology
and high power antennas.
3. UAV Communication Within C-ITS Telecom vision
Figure 2 shows how UAV communication could be organized within C-ITS Telecom vision.
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Enhance mobility and driver experience with multihop data exchange between UAVs and vehicles
Figure 2 - UAV communication within C-ITS Telecom vision
Table 1 shows how interfaces highlighted in Figure 2 could be used to exchange information between
UAVs and C-ITS infrastructure.
Table 1 - How to utilise UAV2x wireless communication interfaces
Interface number How the interface could be used
1 To get UAV location information
2 To get environmental (e.g. flight control) information
3, 5 To get environmental information
To shave UAV context (e.g. coordinates, flight direction) information
4 To shave UAV context and other (e.g. video stream) information
6 To store-carry-and-forward environmental information
To shave UAV context and other information
4. Main Use Cases
4.1. Customers
There are users interested in the features discussed in the paper:
● Early adopters
✓ Automotive OEMs, UAV makers, PS system providers
● Majority customers
✓ Transportation and logistics, agriculture, gas and oil, utilities, construction, smart
cities, etc.
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Enhance mobility and driver experience with multihop data exchange between UAVs and vehicles
4.2. Use case - protect critical infrastructure elements
Ground infrastructructure devices could broadcast the information about critical infrastructure
elements (such as airports, bridges, tall buildings, etc.) as well as flights regulation rules associated
with the above elements (e.g. UAV shall keep X meters away from the element, UAV shall not enter
specific geographic area, etc.).
Each UAVs which gets the above information will do the following:
● Will use the received information to determine the geographic location, overall dimensions,
flight regulation rules and other parameters of the critical infrastructure elements
● Will trigger actions to ensure compliance with the flights regulation rules associated with the
critical infrastructure elements
● Will forward the received information about the critical infrastructure elements to another
UAVs in proximity using Disruption Tolerant Networking (DTN) message
store-carry-and-forward mechanism.
The above use case illustrated in Figure 3.
Figure 3 - Protect critical infrastructure elements
The above use case assume ad-hoc communication between UAVs and ground infrastructure
devices and does not need complete citywide ground infrastructure deployment. Ground
infrastructure devices may be installed close to critical infrastructure elements only.
4.3. Use case - broadcast 3D travelways information
Ground infrastructructure elements could broadcast the information about 3D travelways and flights
regulation rules associated with them to UAVs.
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Enhance mobility and driver experience with multihop data exchange between UAVs and vehicles
Each UAVs which gets the above information will do the following:
● Will use the received information to determine 3D travelways
● Will trigger actions to ensure compliance with the flights regulation rules associated with the
3D travelways
● Will forward the received information about 3D travelways to another UAVs in using DTN
message store-carry-and-forward mechanism.
Note:
● We think this is useful to forward the information about 3D travelways from one UAV to
another because this may help us to minimize the number of ground infrastructure devices
needed, because this information could be used for the flight trajectory optimization and to
avoid traffic congestion near entries to 3D travelway (early warning)
● The DTN message store-carry-and-forward algorithm should be defined to minimize network
flooding and to ensure up to date information delivered.
The above use case illustrated in the Figure 4.
Figure 4 - Broadcast 3D travelways information
The above use case assume ad-hoc communication between UAV’s and ground infrastructure devices
and needs ground infrastructure deployment along 3D travelways. The use case does not need
complete citywide ground infrastructure deployment.
4.4. Use case - command and control
Ground infrastructructure devices could be used to support real-time bidirectional information
information exchange between UAV and UAV control point to implement C&C features.
The below information should be exchanged between UAV and UAV control point:
● Control commands coming from UAV control point to UAV
● UAV status / context information coming from UAV to UAV control point.
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Enhance mobility and driver experience with multihop data exchange between UAVs and vehicles
We think this is useful to tunned the above information through WMN consisting of UAVs and ground
infrastructure devices because this extends communication range, increases reliability the information
successfully transmitted and enables incremental ground infrastructure deployment.
The above use case illustrated in Figure 4.
Figure 4 - Command and control
The above use case assume multi hop communication between UAVs and ground infrastructure
devices and needs ground infrastructure deployment.
4.5. Use case - media streaming
Multi hop streaming does not need ground infrastructure deployment and works as illustrated in
Figure 5 e.g. to manage PS incidents.
Figure 5 - Multi hop media streaming
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Enhance mobility and driver experience with multihop data exchange between UAVs and vehicles
4.6. Additional automotive use cases
We also could use UAV as the additional information source for vehicle ADAS and to setup audio
communication between public safety vehicles at the incident scene w/o the mobile network coverage.
Additional use case for the multi hop video streaming is the trucks platooning / convoy where the lead
vehicle may stream what they see to the trucks following behind driving autonomously. The above use
cases are illustrated in the Figures 6 and 7 below.
Figure 6 - Trucks platooning / convoy
We enable multi hop (1-2 hops) real-time data streaming between trucks in platooning / convoy:
● Leading truck could broadcast video and ADAS sensors information to other trucks going
behind the leader.
● All trucks could share data at real time e.g. we could setup group voice call between truck
drivers.
Two hops provide at least 1.2 kilometers communication range with standard IEEE 802.11p on board
unit.
Figure 7 - Pictures related to UAV / vehicle communication from Ford and NXP
Additional automotive PS multi hop data streaming use cases illustrated in the Figure 8.
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Enhance mobility and driver experience with multihop data exchange between UAVs and vehicles
Figure 8 - Automotive PS data streaming use cases
We organise back-up data channel between PS vehicles at the incident scene (left part of the picture)
and enable real-time data exchange between specialized vehicles along the road (right part of the
picture).
5. Multi Hop Data Routing Protocols
5.1. General overview
The performance of WMN is highly dependent upon the characteristics of the routing algorithm
implemented in the DRE. Routing algorithms are typically classified as either proactive or reactive.
Proactive algorithms (e.g. OLSR, [2]) maintain a current list of routes to each node in the network,
while completely reactive algorithms (e.g. AODV, [3]) maintain no route information, but discover or
create the most efficient route when a data packet is to be transmitted. Hybrid routing algorithms (e.g.
HWMP, [4]) use elements of both proactive and reactive routing, providing fast route acquisition and
route optimization. Hybrid routing algorithms have proven to provide higher scalability than pure
proactive or reactive protocols. Hybrid routing algorithms are suitable for broadband, low-latency
applications such as video and IP telephony. The hybrid algorithm also guarantees loop free routing,
which means that packets will never get lost.
Based on the team experience and based on the recent research (e.g. IEEE paper “Survey of Important
Issues in UAV Communication Networks”, [5]) we conclude the hybrid data routing algorithm using
AODV core logic and UAV domain specific optimizations should work well for the UAV related use
cases discussed above. UAV domain specific optimizations include data routing core logic fine tuning
for typical WMN topologies, faster route construction, alternative route search, link quality prediction,
soft handoffs and smart WMN clusterization. Additional data routing efficiency could be achieved
using Geographic 3D modelling based on real-time positioning data (longitude, latitude, elevation)
coming from individual UAVs and UAVs context / tasks state sharing.
5.2. UAV specific optimizations
The below table provides information on UAV specific optimizations we might want to implement in
the data routing protocol.
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Enhance mobility and driver experience with multihop data exchange between UAVs and vehicles
Table 2 - UAV specific optimizations
# Use case / application UAV specific optimizations
1 C&C and video streaming for PS
applications (incident management)
AODV extensions for faster route construction and
background alternative route search for slow changing WMN
topologies consisting of UAVs and vehicles
2 C&C and video streaming for
corporate applications (e.g. objects
monitoring)
Additional optimisation for intermittent connectivity and fast
changes in the link quality based on link quality prediction
and Geographic 3D modelling
3 Protect critical infrastructure objects Optimization is not needed
4 Prevent collisions between UAVs Optimization is not needed
5 Broadcast and handle messages (e.g.
alarm, environmental, context)
between UAVs
Need to implement DTN data routing, minimize data
replication and support Quality of Service (QoS) control for
DTN data
6 Further solution improvement: soft
handoffs
Support soft handoffs between UAVs and between UAVs and
ground infrastructure (vehicles)
7 Further solution improvement: smart
WMN clusterization
Support smart WMN clusterization based on Geographic 3D
modelling and UAV context / tasks state sharing
6. Product differentiation
The proposed software solution includes the following unique features:
● First UAV safety solution in the world using IEEE 802.11p or / and LTE Proximity Services
● Advanced UAV and vehicle cooperation capabilities including video streaming
● Multi hop data streaming capabilities for trucks platooning / convoy and PS applications
● UAV specific optimizations for multi hop data routing, link quality metrics, data path metrics
● WMN clusterization, DTN data routing
● Automatic congestion management, QoS control and load balancing.
The proposed software solution could be also used for vehicle (e.g. specialized PS vehicles) and smart
city applications. Vehicle OEMs also interested in UAV and vehicle collaboration.
Sreda Software Solutions already developed multi hop data streaming solution which is ideally suited
for multi hop communication between UAs and vehicles. We intend to engage with Tier 1 partner to
integrate our technology into IEEE 802.11p (Cellular-V2x) on board units.
References
1. 802.11p-2010 - IEEE Standard -- Part 11: Wireless LAN Medium Access Control (MAC) and
Physical Layer (PHY) Amendment 6: Wireless Access in Vehicular Environments.
2. RFC3626: Optimized Link State Routing Protocol (OLSR).
3. RFC 3561: Ad hoc On-Demand Distance Vector (AODV) Routing.
4. IEEE P802.11. Wireless LANs. HWMP Specification.
5. Survey of Important Issues in UAV Communication Networks. IEEE Communications Surveys and
Tutorials, Volume PP, Issue 99, November 2015.
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