# Controlling Communications Quality in V2V Platooning: a TSN-like Slot-Based
Scheduler Approach

Angelo Feraudo, Andrea Garbugli, Paolo Bellavista  Department of Computer
Science and Engineering
University of Bologna
Bologna, Italy
<EMAIL_ADDRESS>
###### Abstract

Connected vehicles, facilitated by Vehicle-to-Vehicle (V2V) communications,
play a key role in enhancing road safety and traffic efficiency. However, V2V
communications primarily rely on wireless protocols, such as Wi-Fi, that
require additional collision avoidance mechanisms to better ensure bounded
latency and reliability in critical scenarios. In this paper, we introduce a
novel approach to address the challenge of message collision in V2V platooning
through a slotted-based solution inspired by Time-Sensitive Networking (TSN),
which is gaining momentum for in-vehicle networks. To this end, we present a
controller, named TSNCtl, operating at the application level of the vehicular
communications stack. TSNCtl employs a finite state machine (FSM) to manage
platoon formation and slot-based scheduling for message dissemination. The
reported evaluation results, based on the OMNeT++ simulation framework and
INET library, demonstrate the effectiveness of TSNCtl in reducing packet
collisions across various scenarios. Specifically, our experiments reveal a
significant reduction in packet collisions compared to the CSMA-CA baseline
used in traditional Wi-Fi-based protocols (e.g., IEEE 802.11p): for instance,
with slot lengths of 2 ms, our solution achieves an average collision rate
under 1%, compared to up to 50% for the baseline case.

###### Index Terms:

V2X, V2V, Car Platooning, Time Sensitive Networking, Collision Avoidance,
Intelligent Transportation Systems

##  I Introduction

In the current landscape of transportation, vehicles have experienced a
significant transformation, evolving into interconnected entities equipped
with a range of sensors, driver assistance, and safety-related systems. This
evolution has driven car manufacturers, standard institutes, academia, and
government agencies to enable vehicles and network infrastructure with new
communications modes, e.g., Vehicle-to-Vehicle (V2V), Vehicle-to-
Infrastructure (V2I), and Vehicle-to-Pedestrian (V2P). The necessity for
vehicles to communicate arises from the need to facilitate numerous advanced
applications leveraging vehicular technologies to enhance road safety, to
provide advanced infotainment opportunities, to optimize traffic, to enable
autonomous driving, and to support advanced manufacturer services [1, 2, 3].
For instance, vehicles can leverage V2V communications to form dynamic
platoons, i.e., a cooperative group of vehicles united in a common purpose,
such as traffic flow optimization and infotainment services [4, 5].

Central to enabling these networks are the underlying communication protocols,
typically based nowadays on Wi-Fi and cellular technologies. The initial
effort toward enabling connectivity between vehicles was the development of
the IEEE 802.11p [6] protocol, standardized in the EU with the Intelligent
Transport Systems (ITS) G5 (ITS-G5) framework [7] and in the U.S. with
Wireless Access in Vehicular Environment (WAVE) framework [8]. In addition,
the 3rd Generation Partnership Project (3GPP) leverages the existing cellular
network infrastructure to offer a unified solution for V2X communications [9,
10]. These protocols play a central role in enabling seamless data exchange,
by enabling vehicles to transmit also safety-critical information, such as
position, speed, and trajectory, to nearby vehicles on time.

Despite the advancements in V2V communication protocols, future applications
like remote and autonomous driving demand meticulous resource coordination and
control among vehicles [11, 12, 13]. These scenarios heavily rely on messages
for cooperative awareness and safety applications, which are broadcast without
acknowledgments [14, 15]. The loss of such messages could disrupt the
correctness of some critical functionality, such as for autonomous driving, by
non-negligibly increasing the risk of accidents. Moreover, the transmission of
cooperative awareness messages occurs at a given frequency, thus exacerbating
the probability of data loss and leading to repeated interference between
nodes [12]. Consequently, mitigating interference and data loss calls for the
development of effective and efficient collision avoidance solutions,
specifically tailored to vehicular communication scenarios.

We claim that the next generation of solutions for V2V communications hinges
on the integration of Time-Sensitive Networking (TSN), a technology that
offers precise timing synchronization and deterministic communication
capabilities [16]. This integration extends beyond V2V communication,
encompassing inner-vehicle communication networks as well as broader V2X
communication frameworks [17]. By leveraging TSN-based slotted protocols and
exploiting time synchronization mechanisms, it becomes possible to orchestrate
coordinated message transmission schedules, thereby mitigating the risk of
message collisions and enhancing the overall communication reliability.

In this paper, we propose an original TSN-like controller, named TSNCtl, that
aims at facilitating data delivery within car platooning based on V2V
communications. For enhanced flexibility and dynamic deployment, it operates
at the application layer and employs a finite state machine (FSM) to help in
platoon formation and message dissemination for intra-platoon communications.
The platoon creation/joining procedure starts upon receiving ITS service-
related messages or detecting to be in the neighborhood of an existing
platoon. Once a vehicle becomes part of a platoon, TSNCtl intercepts each
message generated by the ITS service running on the vehicle, determining the
priority queue for its storage. Next, it disseminates the messages based on
its allocated time slots and the priority of each message.

To validate the effectiveness of our proposed approach, we have implemented
our TSNCtl solution on the OMNeT++ simulation library and employed INET 4.5 to
replicate V2V scenarios in accordance with the IEEE 802.11p standard. Next, we
conducted a series of experiments aimed at evaluating performance metrics, by
particularly focusing on packet collisions resulting from vehicle
communications within a platoon. Our experiments clearly indicate that our
solution outperforms traditional collision avoidance methods utilized in IEEE
802.11 protocols, such as CSMA-CA. Specifically, when considering slot lengths
exceeding 1 ms, our proposal exhibits an average collision rate of less than
1%, in contrast to up to 50% collision rate observed with more traditional
approaches.

The remainder of the paper is organized as follows. In Section II, we present
the needed background about TSN-based in-vehicle communications, vehicular
networks, and related simulation tools. Section III analyses the existing
solutions for collision avoidance in V2V communications. Next, Section IV
presents the details of our original TSNCtl controller. We then evaluate our
proposal in section V, by focusing on packet collisions in intra-platoon
communications. Finally, we conclude with a discussion on the current
limitations of our approach and on the main extensions that are the subject of
our ongoing research work.

Figure 1: State Diagram Message Controller

##  II Background

This section provides a brief overview of the protocols used in V2X
communications, with a specific emphasis on the Wi-Fi technologies that
underlie V2V communications. It also introduces the suite of TSN protocols
used for in-vehicle communications, along with an exploration of the
simulation tools used to model complex vehicular networks, i.e. the OMNeT++
framework, which allows for simulation of both in-vehicle and V2V
communication protocols.

###  II-A TSN for in-vehicle communication

Time-Sensitive Networking (TSN) comprises a suite of standards designed to
make Ethernet networks deterministic, particularly to accommodate real-time
traffic flows. In the field of automotive Ethernet communications, TSN
outlines a specialized profile known as IEEE 802.1DG, tailored to meet the
rigorous requirements of in-vehicle networks (IVNs) in terms of high
reliability and low latency [18].

The 802.1DG profile was developed to provide a set of mechanisms that ensure
the timely delivery of crucial traffic, particularly control and security
messages while supporting best-effort traffic.

In applications using TSN protocols, a crucial component is to establish a
reliable time synchronization mechanism that ensures that all communication
entities operate based on a unified time reference. This synchronization is
facilitated within TSNs by the IEEE 802.1AS protocol, an extension of the IEEE
1588 Precision Time Protocol (PTP) known as generic PTP (gPTP) [19]. Central
to the PTP specification is the concept of a grandmaster clock, typically a
highly accurate and stable source such as a Global Positioning System (GPS)
receiver. This grandmaster clock serves as the central provider of reference
time for all devices in the network. In the context of gPTP, devices in the
network are designated as Clock Master (CM) and Clock Slave (CS), each of
which participates in the exchange of synchronization messages. The CM
disseminates time information to the connected CSs via multicast
communication. Then, each CS, known as a gPTP instance, adjusts its
synchronized time taking into account the message propagation delay along the
gPTP communication path from the master to the instance. Once synchronization
is achieved among all devices, a cohesive and time-aware network emerges,
forming the so-called gPTP domain.

For Quality of Service (QoS), the TSN working group defines several traffic
shaping techniques [16]. In particular, IEEE 802.1Qbv introduces a time shaper
known as the Time-Aware Shaper (TAS). The TAS orchestrates the scheduling of
network frames belonging to different types of time-critical flows [20]. The
standard outlines time-aware communication windows, each associated with a
specific transmission queue. These windows are further segregated into
cyclically repeating time slots, allowing frames to be buffered until the next
associated time slot is opened. This segregation ensures that assured traffic
maintains low latency and minimal jitter while avoiding interference from
other traffic streams. The definition of windows and slots is facilitated by a
Gate Control List (GCL), which identifies the time instants at which queues
are open for frame transmission. As a result, TAS can meet the requirements of
ultra-low latency and reliability, provided that all time windows are
synchronized, which makes its combination with PTP necessary.

###  II-B V2X Communications and Protocols

In Vehicular Ad-Hoc Networks (VANET) vehicles exploit On Board Unit (OBU)
network interface to propagate messages with other vehicles within their
proximity. These networks define various communication modes aimed at
automating message dissemination [5]: Vehicle-to-Vehicle (V2V), Vehicle-to-
Infrastructure (V2I), Vehicle-to-Pedestrian (V2P), and Vehicle-to-Everything
(V2X). Communications modes are enabled by both WiFi-based technologies, such
as IEEE 802.11p/bd [6], and Cellular-based technologies like LTE and NR C-V2X
[9, 10].

This proposal primarily focuses on WiFi-based technologies and V2V mode,
considering the exchange of messages for cooperative awareness [14] and
safety-related applications [15]. Thus, Cellular-based standards and other
communication modes pertaining to the vehicular environment are beyond the
scope of this paper.

IEEE 802.11p is specifically tailored to support vehicular communication
requirements. It introduces enhancements to accommodate features such as
vehicle velocities up to 200 km/h and communication ranges up to 100m.
Operating at the physical and Medium Access Control (MAC) layers, IEEE 802.11p
enables connectivity between vehicles and infrastructure. At the physical
layer, it employs Orthogonal Frequency Division Multiplexing (OFDM), while at
the MAC layer, it utilizes the Enhanced Distributed Channel Access (EDCA)
method, incorporating carrier sense multiple access with collision avoidance
(CSMA/CA), without exponential back-off and message acknowledgment.

In 2019, the Internet Task Force embarked on the development of a new standard
for V2X communication, known as IEEE 802.11bd. This standard aims to supersede
IEEE 802.11p by offering twice the performance in terms of throughput,
latency, reliability, and communication range [21]. IEEE 802.11bd also
introduces support for message retransmissions and ensures backward
compatibility with its predecessor.

###  II-C OMNeT++ and INET

OMNeT++ [22] is a well known discrete-event simulation framework capable of
modeling various network types and communications. It relies on the concept of
modules, fundamental elements that facilitate message exchange through
connections and gates. Their behavior is defined in C++, while descriptions,
including gates, connections, and parameters, are expressed in Network
Description language (NED). Initialization files (INI) are used to specify
parameter values for model initialization, allowing for multiple values or
intervals to be defined for parameters. With its provision of basic simulation
functionalities, OMNeT++ allows users to concentrate on creating their
simulation models.

The INET [23] framework is a library built on top of OMNeT++. It furnishes
models for a myriad of network components, including communication protocols,
network nodes, and connections. Furthermore, it features Internet stack models
and wired and wireless link layer protocols. This enables users to instantiate
and interconnect protocol layers, facilitating the creation of custom hosts
tailored to their specific requirements. This modular framework enables rapid
configuration of complex models, thereby enhancing efficiency in simulation
setup.

##  III Related Work

Platooning plays a crucial role in advanced vehicular applications, enabling
vehicles to cooperate towards a common goal. However, vehicular networking
performance, such as packet loss and transmission delay, can significantly
affect platoon dynamics [4].

Addressing these challenges, Shao et al. [24] introduced a MAC-layer protocol
able to deal with the intermittent connectivity of VANETs. This protocol
relies on multichannel reservation and priority schemes that enhance
throughput and packet delivery ratio. Similarly, in [25] the authors proposed
a polling-based MAC-layer protocol coupled with a customized transport layer
retransmission scheme that reduces message error rates within intra-platoon
communications.

Other existing proposals operate under the assumption that a designated
platoon leader is tasked with allocating time slots, similar to Time Division
Multiple Access (TDMA), to other platoon members, thus defining specific time
windows for their communication activities [26, 27, 28]. For instance, in [26]
Fernandes et al. provided a system that divides the control channel of the
IEEE 802.11p into slots to ensure stable intra-platoon communications. In the
same directions, Segata et al. proposed a beacon dissemination strategy based
on TDMA in [27], where the platoon leader takes the lead in beacon
transmission, followed by other platoon members.

From a collision avoidance perspective, Zang et al. [11] proposed a collision
detection approach, where transmitting nodes employ full-duplex channel
sensing to detect simultaneous transmissions. In cellular-based environments
(C-V2X), researchers are exploring methods to enhance scheduling algorithms,
aiming to reduce or detect packet collisions in scenarios where vehicles are
out of base stations coverage (V2V) [13, 12, 29].

Despite the research efforts to enhance the reliability of vehicular network
communications, there remains a need for more building solutions that are
technology-agnostic, regardless of whether they are based on Wi-Fior cellular
technology. Moreover, it is crucial to consider larger-scale scenarios without
solely relying on mathematical models.

In our proposal, we have developed a TSN-like controller at the application
layer, which operates independently of the specific wireless technology
utilized in the vehicle. This controller is designed to enhance the packet
delivery ratio in intra-platoon V2V communications by establishing platoons,
wherein each vehicle has a dedicated slot for message dissemination. The
adoption of a TSN-based scheme aligns with the emerging trend in both car
manufacturing and academia, where there is a growing interest in utilizing
this technology in in-vehicle communications systems.

Figure 2: Integration of Message and Platoon Controller in V2X Stack

##  IV System Architecture

###  IV-A General Overview

As mentioned in Section II-A, the future of in-vehicle communications is
increasingly focused on exploiting TSN to ensure low-latency, reliability, and
determinism for critical vehicular services [18]. Our proposal relies on the
concept that TSN-enabled vehicles could leverage Radio and GPS technologies
[30, 31, 32, 33] to synchronize themselves, facilitating synchronized and
time-sensitive communications over wireless connectivity. Thus, in our
proposal, each vehicle is equipped with a TSN-like controller responsible for
orchestrating the dissemination of messages in V2V communications (in this
work we do not address at all vehicle clock synchronization).

In Figure 2, we observe the integration of the proposed controller, TSNCtl, at
the application layer of the V2X stack. TSNCtl operates an FSM that helps
vehicles in platoon formation and engages in V2V communications through slot-
based scheduling. The platoon formation process regards determining which
vehicles partake in the communications network. In our scenario, this relies
on TSNCtl FSM, which initiates platoon creation or joining procedures upon
receiving ITS service-related messages or upon detecting proximity to an
existing platoon. During this procedure, a platoon master is elected among the
vehicles, and tasked with allocating slots to each member of the platoon.
These slots are utilized by vehicles to communicate at designated times,
minimizing the risk of collisions during communications with other vehicles
within the platoon. It should be noted that a vehicle may request multiple
slot allocations if it hosts multiple ITS or safety-related services.

Once the platoon has been established, TSNCtl intercepts messages generated by
the ITS Service running on the vehicle and, based on the slot allocated for
that vehicle, determines the optimal timing for their dissemination across the
network. To manage this process effectively, TSNCtl maintains a series of
queues, each assigned with a distinct priority level, wherein these messages
are stored before transmission. Depending on the nature of the message, such
as safety or non-safety related, TSNCtl determines the appropriate queue for
its placement and subsequent dispatching.

Figure 3: Slot-based Scheduling

51015202530Number of Generated
Vehicles$\displaystyle{0}$$\displaystyle{10}$$\displaystyle{20}$$\displaystyle{30}$$\displaystyle{40}$$\displaystyle{50}$$\displaystyle{60}$Percentage
of Packet CollisionsBaseline1ms2ms3ms

(a) Packet Collisions with a $100\mu s$ Vehicle Spawning Frequency

51015202530Number of Generated
Vehicles$\displaystyle{0}$$\displaystyle{10}$$\displaystyle{20}$$\displaystyle{30}$$\displaystyle{40}$Percentage
of Packet CollisionsBaseline1ms2ms3ms

(b) Packet Collisions with a $1ms$ Vehicle Spawning Frequency

Figure 4: Collisions in Packet Transmission with Different Platoon Size

###  IV-B TSNCtl: Platoon Formation and Slot Assignment

The TSNCtl FSM is used to model the behaviors that vehicles exhibit during
platoon formation. Figure 1 illustrates the states that the FSM can assume.
Each state is defined by a combination of node status, including init,
joining_platoon and in_platoon, and a node role,slave and master, defining
vehicle responsibilities within the platoon.

During the initialization phase, the vehicle is in the init state, wherein
parameters such as communication window duration and slot length are
established. The communication window duration sets the interval for vehicle
coordination within the platoon. Meanwhile, the slot length determines the
slot duration, which is used to select when a vehicle can transmit its
messages regulating the timing of data dissemination.

In the init state, the internal TSNCtl component remains idle until the
specified window duration elapses. Referring to Figure 3, if the communication
window duration is set to 100 ms, controller-based messages can only be
exchanged at intervals that are multiples of this time interval (window). The
number of available slots within a window is determined by the slot length;
for example, with a 100 ms window and a 10 ms slot length, the total available
slots amount to 10.

After the window elapses, the first two slots are designated for controlling
operations, specifically aimed at forming or joining a platoon (red slots in
Fig. 3). In the initial time slot, controller messages are transmitted,
conveying node-related information alongside the timestamp of message
generation. It is worth noting that, in this phase, nodes compete to become
masters of the platoon. Thus, controller messages are randomly generated
within the interval defined by the slot length, to prevent collisions during
this slot.

During the second time slot, TSNCtl examines the content of the messages
received in the previous time slot and changes its status in joining_platoon.
As illustrated in Figure 1, in steps \raisebox{-.9pt} {1}⃝ and
\raisebox{-.9pt} {2}⃝ the node’s role in this state depends on the timestamps
gathered thus far: the node with the earliest timestamp, representing the
first generation of the controller message, assumes the role of master, while
the others become slaves. Within this slot, the master node dispatches a
message containing details about slot allocations. These allocations can be
determined using various policies, potentially influenced by factors such as
the number of slots requested by a node and the type of node (e.g., car,
ambulance, etc.).

However, the master node requires at least one neighboring node to establish a
platoon. Thus, if no node is detected nearby, the master node maintains the
current status and restarts the procedure to form the platoon (step
\raisebox{-.9pt} {4}⃝). A master node persisting in this state, may become
slave at the next iteration of the controller-related messages (step
\raisebox{-.9pt} {5}⃝). Conversely, in the presence of other nodes, its state
transits in in_platoon (step \raisebox{-.9pt} {7}⃝).

On the other side, slave nodes await the slot allocation defined by the master
and prepare to transmit their data during their allocated time slot. Upon
receiving the internal trigger corresponding to their slot, slave nodes
confirm their role and transition to the in_platoon state (step
\raisebox{-.9pt} {6}⃝). However, those slave nodes that fail to receive a
message from the master remain in this state, step ③ in Figure 1, and restart
the platoon joining procedure during the next TSNCtl slots.

In the in_platoon state, TSNCtls with a slave role transmit messages solely
during their designated slots, while master nodes also utilize the second slot
reserved for controller communication. The latter allows the integration of
new nodes into the platoon.

Following platoon formation, each message generated by the ITS service is
categorized based on its priority and inserted into one of the available
queues within the controller. The TSNCtl then disseminates these messages
according to the allocated slots and message priorities.

##  V Evaluation Results

To demonstrate the usefulness and efficiency of our proposal, we developed the
TSNCtl component outlined in Section IV within the OMNeT++ simulation library.
We utilized INET 4.5 to simulate ad-hoc communications and specifically V2V
scenarios, adhering to the IEEE-802.11p standard. We implemented two OMNeT++
simple modules: a mock service, sending messages to the controller (Fig. 2),
and a mock application, sending messages directly on the socket. Both modules
generate UDP packets with a regular interval of 100 ms, by following the ETSI
standard for Cooperative Awareness[14]. Packet sizes relies on the analysis
conducted by the CAR2CAR Communication Consortium [34] in real-world
scenarios. Furthermore, we introduced a spawner module that generates vehicles
within a specified area and frequency. For our testing, we considered an area
for platoon formation that corresponds to the V2V communication coverage range
(between 100 to 300 meters) and different frequencies for vehicle spawning (1
ms and 100 $\mu s$).

We have conducted several experiments to assess the viability of our proposal.
Initially, we explored the behavior of our model by varying the number of
vehicles within a platoon and their entry frequency. Secondly, we have tested
the resilience of our solution when changing packet size. These experiments
were performed on a Linux VM running OMNeT++ having 16 CPUs and 32 GB of RAM.
Each experiment was repeated five times to ensure statistical reliability. It
should be noted that, at this stage, the experiments do not take into account
signal attenuation due to obstacles like objects and foliage on the road. This
approach also allowed us to correctly identify those packets that collided
within the simulated scenario.

###  V-A Assessing Packet Collisions by Varying Platoon Sizes

The first set of experiments involves the investigation of the performance of
our proposed solution (Section IV) when varying the dimension of the platoon
size. These experiments consider 800 bytes as max packet size [34, 35].
Furthermore, the window duration is set to 100 $ms$ and three slot lengths are
analyzed: namely 1, 2, and 3 $ms$. The graphs showed in Figure 4 compare the
percentage of packet collisions in intra-platoon communications between
scenarios without TSNCtl (Baseline) and those using it.

Figure 4(a) shows the percentage of packet collisions obtained when vehicles
join the platoon with a frequency of $100\mu s$, while Figure 4(b) with
$100ms$ generation frequency. The spawner module generates vehicles within the
simulation area of 100 meters at the specified frequency. Upon generation,
each vehicle starts broadcasting messages every 100$ms$. In both scenarios, it
is evident that the proposed TSNCtl correctly avoids packet collisions and
helps in platoon formation. However, when the slot length is below 2$ms$, the
controller performance is significantly reduced, from an average of 0.40% and
0.23% packet collisions for the 2$ms$ and 3$ms$ cases, to an average of 13.8%
with slot length of 1$ms$ (Figure 4(a)). The indicator reaches around 20% of
collisions when the platoon size is above 20 vehicles. Similarly, widening the
gap between vehicle generation (Figure 4(b)) results in collision rates
approaching 25% for platoon size over 20 vehicles.

Hence, slot lengths shorter than 2$ms$ fail to allow messages to propagate in
time from the source to all destinations within the platoon, leading to packet
interference. Furthermore, we have experiences that this issue gets worse when
considering signal attenuation caused by obstacles and foliage, although this
aspect is not specifically addressed yet in this paper. Despite the poor
performance with small slot length, anyway our controller is still able to
synchronize platoon vehicles, by outperforming more traditional scenarios. As
illustrated in both Figure 4(a) and 4(b), the Baseline performance yields a
minimum of 10% of collisions during platoon formation, while our solution does
not exceed 1% when choosing the appropriate slot length.

###  V-B Assessing Packet Collisions by Varying Packet Sizes

In these experiments, we examine a platoon consisting of 20 vehicles generated
within a 100-meter area at intervals of 1$ms$. Window duration is fixed to 100
$ms$, while different slots lengths are analyzed. Figure 5 illustrates the
percentage of collisions observed while varying packet dimensions in this
scenario. The chosen packet dimensions for this analysis are derived from the
data provided [34].

The overall trend depicted the Baseline bar, is an increase in collisions as
packet dimensions grow. It shows an approximate 12% increase in collisions
with each incremental change in packet dimension. Conversely, the controller
shows a consistent collisions rate below 1% when using slot length above
1$ms$. However, as also occurred in the previous analysis (Section V-A), using
short slots fail to adequately avoid collisions. As the picture demonstrates,
for the largest packet size considered (650 bytes) the packet collisions
exceed the 10% of the total message sent.

190360650Packet Size in
Bytes$\displaystyle{0}$$\displaystyle{5}$$\displaystyle{10}$$\displaystyle{15}$$\displaystyle{20}$$\displaystyle{25}$$\displaystyle{30}$$\displaystyle{35}$Percentage
of Packet CollisionsBaseline1ms2ms3ms

Figure 5: Collisions in Packet Transmission with Different Packet Size

##  VI Discussion and Future works

Efficiently achieving intra-platoon message dissemination continues to be a
challenging issue. To this purpose, we propose a TSN-like controller that
leverages the capabilities of in-vehicle networks based on the TSN [18]
approach. This direction is motivated by the growing enthusiasm of academia
and industry for the use of TSN in wireless environments for message
propagation [36], in particular thanks to the introduction of the latest IEEE
802.11 standard, i.e. IEEE 802.11be, also called Wi-Fi 7 [37], which aims to
fully integrate TSN functionality to support low-latency and ultra-reliable
communications.

5G Integration. Our approach not only opens up new challenges and directions
for research but also holds the potential to profoundly change the landscape
of message dissemination within VANETs. A TSN-enabled V2V environment can
boost both packet delivery ratios, as demonstrated in this paper, and network
performance in large-scale VANET deployments. Furthermore, the integration of
the cellular and TSN domains is considered a promising solution for supporting
time-sensitive applications and low-latency communications, especially in the
case of 5G infrastructures [17]. This will bring several benefits also in V2V
communications based on cellular technologies.

Platoon Formation. Looking ahead, our future research will involve extending
our solution to realistic scenarios that consider signal attenuation generated
by obstacles and vehicle trajectories, while also creating effective and smart
strategies to handle errors in platoon formation. Moreover, vehicles that
reside at the border of two different platoons must be handled accordingly,
and can also be exploited as relays to forward messages between platoons, thus
extending the communication range and facilitating seamless integration
between adjacent platoons.

Synchronization. Our current implementation of the proposed solution is based
on a common GPS-based time reference, i.e., all vehicles participating in the
platoon are already synchronized before the platoon is formed. In a more
complex scenario where not all participants are constrained to host GPS
equipment, time synchronization opens up additional technical challenges.
Related to that, the evolution of our solution will include a first phase in
which the vehicles try to synchronize their clocks through the use of a
wireless implementation of the PTP protocol; only once a synchronized time
domain has been built, the actual communication can start.

Messages Prioritization. In complex communication scenarios, vehicles may want
to exchange messages with different priorities. In this case, the design and
implementation of different queues for differentiated message priority,
especially in delay-sensitive scenarios, could take advantage of the TSN-based
approach adopted by our solution. Distinguishing between safety-critical and
non-safety-related messages allows for more efficient resource allocation and
ensures timely delivery of critical information, thus improving the overall
system reliability. In addition, we envision integrating our proposal within a
cellular-based domain, particularly in out-of-coverage scenarios where
vehicles may exploit the new V2X Mode 2 [38] radio. The integration of
distinct priority-based queues will also facilitate the reliable and rapid
dissemination of safety-critical messages between different platoons.

##  VII Conclusions

This study introduces an innovative approach to improve V2V communications
through a TSN-like slot-based scheduling solution, as a first step towards
deterministic communication within vehicular networks. Our TSNCtl effectively
orchestrates message dissemination, by mitigating packet collisions and by
ensuring reliable data exchange between vehicles. The reported performance
results, measured on top of the OMNeT++ simulation environment, highlight the
effectiveness of our approach, in particular in scenarios with different
platoon sizes and packet sizes. Going forward, our focus will shift to
refining the TSNCtl component to adapt it to different traffic conditions and
to incorporate priority-based message queuing; in addition, we will better
explore the implications of different network performance parameters and will
evaluate the feasibility of operating the controller without prior
synchronization.

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