Strategic Coordination of Cooperative Truck Overtaking Maneuvers

Jan Cedric Mertens

, Jürgen Hauenstein

, Frank Diermeyer

and Andreas Zimmermann

Institute of Automotive Technology, Technical University of Munich, Garching b., München, Germany

Corporate Research, MAN Truck & Bus SE, München, Germany

Keywords: V2X, Cooperation, Truck Overtaking, Message Specification, Distributed State Machine, Connected Vehicles.

Abstract: This paper demonstrates how a cooperative truck overtaking maneuver can be coordinated and synchronized

via V2X. This is relevant because the classical truck overtaking maneuver imposes high stress on truck drivers,

which can lead to work absences or accidents. We define which abstract/atomic tasks are involved in the truck

overtaking maneuver and assign them to a distributed state machine. With the help of a V2X message we then

synchronize this state machine and exchange all information relevant for the overtaking maneuver. The

simulation of 600 overtaking scenarios demonstrates that the developed concept is adequate and that a

transmission frequency of 5 Hz offers the best trade-off between channel load and maneuver quality.

1 INTRODUCTION

In Germany, the volume of freight transport has

increased since 2015 from 4,470,468 kt annually by

1.5-2 % to 4,726,810 kt in 2018. In the same period,

the share of the total volume transported by road

transport increased from 78.1 % to 79.2 %

(Statistisches Bundesamt, 2020). Of this again, about

90 % is transported by truck (Statista, 2020). Thus, a

trend toward an increasing need for transportation by

truck becomes obvious. The Covid-19 pandemic has

also highlighted the need for and our dependence on

truck transportation. In March 2020, shortly before

the first lockdown in Germany, fears of supply chains

breaking down due to the effects of the pandemic

were already being fanned and an extreme strain on

truck drivers was predicted (Hecking, 2020). Shortly

afterwards, the MAN Truck & Bus SE for instance,

had to stop production, partly due to supply chains

breaking down (MAN Truck & Bus SE, 2020).

However, for the fact that despite the extreme

conditions the basic supply of goods in Germany

could be secured, Federal Minister Scheuer expressed

a big gratitude to all truck drivers and emphasized

their importance (Bundesministerium für Verkehr

und digitale Infrastruktur, 2020).

While the need for truck drivers is undisputed for

a sustainable supply and economy, Germany is also

https://orcid.org/0000-0002-4079-2730

https://orcid.org/0000-0003-1441-5226

faced with a severe driver shortage (Schlamp, 2020).

In addition, existing truck drivers are under extreme

stress during their working day, often caused by time

pressure and conflicts with other road users (Evers,

2010). The consequences of these strains are illnesses

(Bergrath, 2011) and accidents (Evers, 2010) For

example, the recent health reports of the insurance

companies show a peak of days-off-work per year in

transport and logistics occupations (approx. 30 %

above the average) and especially for vehicle drivers:

25 days per year, 70 % above the average (Bessel,

2020). Among the transportation professions, 27 % of

the days off work were caused by back pain, while

13 % were caused by mental illnesses categorized

according to ICD-10.

However, stress not only leads to illness, but also

to risky and error-prone driving (Evers, 2010). In

2018, 61 % of accidents with personal injuries

involving trucks on highways were caused by driver

error (Statistisches Bundesamt, 2018).

Our short-term goal is therefore to relieve truck

drivers through a cooperative truck overtaking

assistant in order to reduce lost working days and

accidents and to promote sustainable truck traffic.

The long-term goal is to prepare trucks for

cooperative autonomous driving functions. For these

goals, we have already published the concept of the

cooperative truck overtaking with optimized starting

points, velocity profiles (Mertens, Hauenstein,

Mertens, J., Hauenstein, J., Diermeyer, F. and Zimmermann, A.

Strategic Coordination of Cooperative Truck Overtaking Maneuvers.

DOI: 10.5220/0010447805130520

In Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS 2021), pages 513-520

ISBN: 978-989-758-513-5

513

Diermeyer, Jahn, & Kraus, 2020) and reduced safety

distance (Mertens, Hauenstein, Diermeyer, & Kraus,

2020).

This paper starts in Section 2 with an overview of

V2X, Cooperative Truck Overtaking, and the

Collaborative Maneuver Protocol. In Section 3, it

continues to introduce the distributed state machine

for the strategic planning level and specify the

message for coordination. The following Section 4

describes our simulation setup and present the results

and discussions in before ending with a conclusion in

Section 5.

2 STATE OF THE ART

This section, gives a briefly review of V2X and

analysis of trends in this field over the last 20 years.

Afterwards it states approaches for cooperative truck

overtaking before presenting the Collaborative

Maneuver Protocol as a possibility for strategic

coordination. Afterwards a brief introduction to the

project IMAGinE with the participating partners and

goals is given.

2.1 V2X

An important step toward autonomous road traffic is

connectivity and cooperation between vehicles

(Mertens, Knies, et al., 2020). While it is still unclear

which technology will prevail for data exchange in

the future (WLAN or cellular based (Vukadinovic et

al., 2018)), the standardization of the messages to be

transmitted is progressing successfully. In Europe,

the Cooperative Awareness Message (CAM) (ETSI -

ITS, 2014a) and Decentralized Environmental

Notification Message (DENM) (ETSI - ITS, 2014b)

have already been specified by ETSI and the first

vehicles such as the VW Golf 8 or the VW ID.3 are

sending them as part of their standard equipment via

ITS-G5 (ADAC, 2020).

In addition to these so-called Day 1 messages, the

development of the Day 2 message Collective

Perception Message (CPM) (ETSI, 2020) is already

well advanced and will enable the exchange of sensor

information in the future. Following on from this, the

Maneuver Coordination Message (MCM) is being

developed for coordination and maneuver planning

via trajectories (CAR 2 CAR Communication

Consortium, 2019).

2.2 Cooperative Truck Overtaking

During truck overtaking maneuver, the safety

distances between the trucks before and after the lane

change are often greatly undercut and conflicts arise

with the car drivers because the truck blocks the

overtaking lane. As already mentioned in the

introduction, this can lead to high stress for the truck

drivers and to accidents. V2X may be used also

between trucks to optimize the truck overtaking

maneuver and there are four steps (Mertens,

Hauenstein, Diermeyer, Jahn, & Kraus, 2020):

 Find an optimized overtaking position

 Secure the reduced safety gap

 Perform a cooperative lane change

 Adjust the velocities during overtaking

While maneuver planning on a trajectory level

could e.g. coordinate the cooperative lane change

with MCM, agreeing on a certain overtaking point is

a strategic decision that requires a much longer

planning horizon than MCM allows. Therefore, a

different message type is needed which is discussed

in this paper.

2.3 Collaborative Maneuver Protocol

Oliver Sawade et al. have developed the

Collaborative Maneuver Protocol (CMP) with the

corresponding Collaborative Maneuver Message

(CMM) for the negotiation of cooperative maneuver

in ad-hoc networks between vehicles in 2018. The

objective of the CMP is to enable robust coordination

under byzantine network conditions. For this purpose,

function-specific distributed state machines are

designed in which each state assigns tasks for

different roles. For example, in a platooning scenario

the roles "leader" and "follower" could be

implemented, where the follower in one of the states

has the task to "follow with a small distance". To

synchronize the vehicles in a distributed state

machine, a session with all involved vehicles is

started and the roles are assigned. Within the session

each participant can start a vote for a state transition.

In case of a uniform decision, the chosen state is

transitioned and each participant takes over the task

assigned to its role there. To detect a

desynchronization or the failure of a session

participant, each vehicle sends a heartbeat message

with the hash of the current state (Sawade et al.,

2018).

The advantage of the CMP is that no specific

maneuver has to be planned in detail, but the

coordination takes place on a higher strategic and

VEHITS 2021 - 7th International Conference on Vehicle Technology and Intelligent Transport Systems

514

abstract level. This increases robustness, since, for

example, deviations from specific trajectories can

occur more quickly and then lead to an abort of the

maneuver. In addition, the vehicles can be kept in a

synchronized state over a long period of time, which

makes it possible to make long-term strategic

decisions together. The individual function

implementation of the corresponding vehicle is then

responsible for the implementation of the role-

specific tasks. Thus, the CMP can be set on top of an

existing trajectory planning, which may differ from

vehicle to vehicle. The disadvantage is that the

specific trajectories are not coordinated between the

vehicles, so especially in highly dynamic scenarios,

maneuver can be planned better on trajectory level

than on a strategic level. Furthermore, although the

coordination and synchronization concepts are

generic, the distributed state machine must be

developed specifically for each function and initially

distributed to all vehicles.

2.4 IMAGinE

The IMAGinE project (Intelligent Maneuver

Automation - Cooperative Hazard Avoidance in

Real-Time) addresses cooperative driving maneuver

in 6 different scenarios, including turning on rural

roads, merging onto highways, and truck overtaking

(IMAGinE, 2016). The 12 consortium partners (Opel

Automobile GmbH, BMW AG, Mercedes-Benz AG,

MAN Truck & Bus SE, Volkswagen AG, Continental

Teves AG & Co. ohG, Robert Bosch GmbH, IPG

Automotive GmbH, Nordsys GmbH, WIVW GmbH,

Hessen Mobil - Straßen und Verkehrsmanagement,

Technische Universität München) are funded by the

German Federal Ministry for Economic Affairs and

Energy and aim to implement a collective perception

with subsequent cooperative maneuver planning in

simulation and real vehicles. Central to this is the

agreement on common and uniform message

specifications, in particular the CPM and MCM, with

which important experience is being gained in the

project for further specification and applications of

the messages.

In IMAGinE, the MAN Truck & Bus SE is

focusing in particular on the cooperative truck

overtaking maneuver. For this purpose, two test

vehicles were equipped with advanced sensors,

actuators, computing units and a communication

module for WLAN 802.11p.

3 METHODS

This section describes how the strategic planning

layer for the cooperative truck overtaking maneuver

is implemented and how the distributed state machine

is designed. It is also determined what information

needs to be exchanged and how it can be specified in

a message. At the end, our simulation setup as well as

the experiments are described. The main purpose of

the experiments is to demonstrate that the cooperative

maneuver coordination works and to investigate what

transmission frequency of the described message is

needed.

3.1 Strategic Planning

The truck overtaking maneuver requires a long

planning horizon, since the low differential speeds of

the trucks mean that long distances are covered from

the first contact via V2X to the completion of the

overtaking maneuver. A truck with a constant speed

of 80 km/h overtaking a 70 km/h truck travels from

the first contact via V2X at a communication range of

400 m about 3 km to the lane change into the

overtaking lane and further 1.1 km to the second lane

change. Such a long cooperative maneuver needs to

be coordinated at a strategic planning level (also

called behaviour or tactical level) (Gu et al., 2016),

since the planning horizon of an MCM at a trajectory

level is around 20 s, i.e. 440 m. Even though longer

MCMs can be constructed, it is impossible to predict

the position and velocity at 4 km distance accurately

enough for a trajectory planning level. On a strategic

level, it is enough to coordinate:

 About where lane changes are to be made

 How long the overtaking maneuver will take

 What safety distances are necessary

 Which type of cooperation is chosen

With this compact information, an unambiguous

overtaking maneuver can essentially be described. It

is not yet important, for example, to calculate the

exact trajectory for the lane change, but to formulate

abstract tasks that enable the execution of the

overtaking maneuver. The following distributed state

machine summarizes these tasks.

3.2 Distributed State Machine

As described by Sawade et al., a cooperative

maneuver can be broken down at the strategic level

into abstract tasks, which are then executed in a

coordinated manner by the participating vehicles

(Sawade et al., 2018). Execution in this context can

Strategic Coordination of Cooperative Truck Overtaking Maneuvers

515

mean, for example, that the underlying trajectory

maneuver planning is parameterized accordingly. For

the truck overtaking maneuver two roles are defined,

whose tasks differ per state: the overtaker and the

overtaken. Passenger cars, which of course also have

to be considered in the truck overtaking maneuver,

are not considered on the strategic level, since the

cooperation between passenger cars and trucks is

limited to the trajectory level during the first lane

change. In the following, the ten states with the

corresponding tasks are described:

1. Solo (not synchronized) - No truck in the

surrounding area or for all trucks determined

that overtaking is not practical.

2. Initialization - Information is exchanged and an

attempt is made to establish the roles for

Overtaker and Overtaken. If the assignment is

successful switch to 3.

3. Planning - Both: The overtaking maneuver is

planned and described by lane change, duration,

safety distances and cooperation mode. If both

trucks agree on the same overtaking maneuver,

switch to 4.

4. Approach - Overtaken: Follow your originally

planned Velocity-Profile. Overtaker: Adjust

speed continuously so that the overtaker reaches

the overtaken approximately at the time of the

planned lane change. If the safety distance to the

overtaken is ≤ 60 m change to 5.

5. Secure Gap (pre) - Overtaken: Transmit during

emergency braking, brake signals via V2X.

Overtaker: Reduce the safety distance secured

by the V2X messages and react to possible

emergency braking of the overtaken. Plan the

cooperative lane change with the vehicles in the

overtaking lane. When safety distance is

reached, change to 6.

6. Lane Change (to 2) - Overtaken: Send braking

signals via V2X in case of emergency braking.

Overtaker: Perform lane change to overtaking

lane and react to possible emergency braking.

When lane change is finished change to 7.

7. Pass - Overtaken: Reduce your speed within the

hysteresis. Overtaker: Increase your speed

within the hysteresis. When safety distance is

reached after overtaking maneuver change to 8.

8. Lane Change (to 1) - Overtaken: React to

possible emergency braking from the overtaker.

Overtaker: Execute the lane change to the first

lane and send brake signals via V2X in case of

emergency braking. When lane change is

finished switch to 9.

9. Secure Gap (post) - Overtaken: React to

possible emergency braking from the overtaker

and accelerate again to the desired speed.

Overtaker: Slow down again to desired speed

and send brake signals via V2X in case of

emergency braking. If the safety distance to the

overtaker is ≥ 50 m change to 10.

10. End - Overtaking maneuver is completed, both

continue at desired speed and reset all states.

In each state there are abort conditions, so that if

an overtaking maneuver is no longer useful or a

participant ends the cooperation prematurely, the

system returns to state 1. It should be noted that the

state changes do not depend on an absolute condition

specified in state 3. For example, the transition to the

lane change state does not depend on an absolute

position on the road, but on the relative position to the

overtaken. This allows that the overtaking maneuver

can be adapted dynamically even after the initial

planning and does not have to be aborted if minor

deviations occur.

3.3 Required Information

As already mentioned, it is not useful to use an MCM

over such a long planning horizon, since for example

the lateral location component can be reduced to the

two lane changes. However, for example, it is

indispensable to determine when the first possible

overtaking time point is, i.e. when the distance

between the overtaker and the overtaken has reached

the safety distance. To predict this point, the current

positions and the upcoming velocity profiles of both

trucks must be known. In “Cooperative Truck

Overtaking on Freeways” (Mertens, Hauenstein,

Diermeyer, Jahn, & Kraus, 2020) we investigated

how velocity profiles can be exchanged over V2X

and designed an ASN.1 specification that allows 7 km

long velocity profiles to be transmitted in a 33 Byte

message. The compression used resulted in an

average deviation of 0.1 m/s between the original and

the received velocity profile.

Now we want to go a step further and consider

how the velocity profiles were determined in the first

place. Most trucks today are equipped with a GPS

cruise control system that calculates an energy-

efficient velocity profile depending on the topology.

The main factors that go into this calculation are

(Passenberg et al., 2009):

 Road topology

 Position of the truck

 Desired speed: V

set

 Hysteresis with speed variation: H

min

max

 Weight of the truck: W

 Engine model: E

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516

Figure 1: IMAGinE Driving Strategy Message

specification.

Under the assumption that both trucks have a GPS

cruise control that deliver approximately the same

results with the same input, it is sufficient to transmit

only the initial parameters for its calculation instead

of the complete velocity profile. Since the road

topology is already available in both trucks and the

position is sent via the CAM, only V

set

, H

min

, H

max

, W

and E remain, which can be transmitted more

compactly than a velocity profile. This information

also allows us to determine the reduced safety

distance, which depends mainly on the weight and the

velocity. In the next step, we will embed this required

information into a message to synchronously run

through the distributed state machine and plan the

overtaking maneuver.

3.4 IDSM Message

In order to synchronize the vehicles in the distributed

state machine and exchange the required information

for planning the overtaking maneuver, a message

needs to be specified. Building on the CMP and the

CMM of Sawade et al., the IMAGinE project

designed the IMAGinE Driving Strategy Message

(IDSM). Figure 1 shows the main elements of the

IDSM. Beside the header it contains the IDS which

indicates via Nature which function and thus which

state machine is active. Furthermore, the current

session and an optional desired session are included.

These contain in each case a state with the ID and

Payload of the current and the desire state. In the

desired state there is also a timeout, for how long can

be voted for it. The last elements of the sessions are

the

participant

lists

with

the

corresponding

IDs

and

Figure 2: Payload for Cooperative Truck Overtaking.

their roles. In the current state, each vehicle can add a

payload to its participant entry to share details about

itself. This message is thus generic in the sense that

arbitrary state machines can be traversed

synchronously. Once a session is initiated, each

participant in the session can send a desired state in

addition to the current state. As soon as all

participants send the same desired state, the system

switches synchronously to this state.

The payloads in the IDSM are defined as a byte

array so that specific content can be appended

depending on the function activated. Figure 2 shows

the payload for the Cooperative Truck Overtaking

Maneuver and contains the information derived in

Section 3.1 and Section 3.3.

3.5 Simulation

To test the coordination of the cooperative overtaking

maneuver between two trucks with the IDSM, we

implemented a simulation environment and a

dashboard for visualization. The simulation of the

two trucks is implemented in ROS-Kinetic (ROS,

2018) and ego data as well as simulated CAMs are

provided as ROS-topic. For each truck one instance

of the Cooperative Truck Overtaking Assistant is

running which receives the data and provides IDSMs

as ROS-topic for the other truck. Except for the lane

changes, the trucks always drive on lane center and

the speed of the trucks is directly controlled by the

Cooperative Truck Overtaking Assistant. The

calculation of the speed profiles is based on the

already published tool "Truck Overtaking Analyser"

which has now been extended by the coordination

with the Distributed State Machine and the IDSM.

3.6 Experimental Setup

With the described simulation a series of tests with

two objectives has been performed. Firstly, we

wanted to see whether the strategic coordination

concept works and whether the overtaking maneuvers

Strategic Coordination of Cooperative Truck Overtaking Maneuvers

517

as planned by the "Truck Overtaking Analyzer" are

actually realized. On the other hand, we wanted to

investigate which transmission frequency is

necessary to achieve this. For this purpose, 100

scenarios for cooperative truck overtaking maneuvers

with 1, 2, 3, 5, 7 and 10 Hz each were simulated while

logging details like lane change positions, duration,

number of messages sent and time in each state. The

100 scenarios were set up so that all were performed

in Active Cooperative mode, both trucks had a total

mass of 25 t, and the overtaken started 200 m ahead

of the overtaker. The starting position of the overtaker

went in 1 km steps from 3 km to 102 km on a 116 km

long section of the A8 from Ulm to Munich with

original elevation profile. 50 % of the scenarios were

to be performed with reduced safety distance and the

speeds were set at 20 % each as follows (Overtaker

[km/h] / Overtaken [km/h] / Hysteresis [±km/h]):

80/70/5, 85/75/5, 75/70/7, 80/77/7, 85/80/7. The

order of all overtaking maneuvers remained the same,

so that they differed in the six runs only by the

transmission frequency of the IDSM.

4 RESULTS AND DISCUSSON

The described tests were carried out at real speed and

no problems or failures occurred. In total, about

30 hours of truck driving were simulated and 600

overtaking maneuvers were successfully coordinated

and executed. Now we need to determine which

IDSM frequency provides the best trade-off between

message count, i.e. channel load, and coordination

quality. For this, it is assumed in the following that

the overtaking maneuver can be coordinated best with

a high frequency, since queries can be exchanged

more frequently and the delay is low. Therefore, for

our experiments, 10 Hz is selected as reference.

Figure 3: Mean±Sigma for overtaking duration and

message count at different IDSM Frequencies.

Figure 3 shows the influence of the IDSM frequency

on the average overtaking time and the average

number of messages transmitted. As the frequency

increases, the number of messages increases and so

does the channel load. Further, it is noticeable that the

average overtaking time differs from the reference by

only 0.08 s even at 1 Hz. It is obvious, however,

that the standard deviation of the average overtaking

Figure 4: The correlation of overtaking duration and lane change position between lower IDSM Frequencies and 10 Hz.

VEHITS 2021 - 7th International Conference on Vehicle Technology and Intelligent Transport Systems

518

duration increases with falling frequency. Thus,

deviations from the optimal overtaking maneuver

occur more frequently

Since this can have an effect on more than just the

overtaking duration, we also considered the position

of the first lane change in the next step. Figure 4

shows the correlation of the overtaking time and lane

change position at 1, 2, 4, 5 and 7 Hz to our 10 Hz

reference. While there is a strong correlation of

= 0.98 for duration and R

= 0.99 for position for

5 Hz and 7 Hz, the correlation drops steadily to

= 0.92 and R

= 0.91 at 1 Hz.

We conclude that the best trade-off between

tuning and channel load is established at an IDSM

frequency of 5 Hz. However, as a kind of dynamic

congestion control, the frequency can be reduced to

3 Hz or 2 Hz if the current channel load requires it.

While the coordination with 1 Hz still worked

successfully, more frequent overtaking maneuvers

were performed which deviated from the optimal

overtaking maneuver. The coordination of the

cooperative truck overtaking maneuver with 1 Hz

should therefore be avoided. This is also confirmed

by our last investigation. Figure 5 shows how the

average time spent in each state differs from the

references. In particular, at 1 Hz there are large

deviations that clearly stand out from those of the

other frequencies.

Figure 5: Average time spent in each state at different

IDSM frequencies compared to 10 Hz.

5 CONCLUSIONS

It was demonstrated that the truck overtaking

maneuver can be coordinated and executed

cooperatively at a strategic level using a distributed

state machine. To synchronize the vehicles in the

distributed state machine, a message is required that

groups the participants in a session and enables

coordination for a transition to a new desired state.

For this, the IMAGinE project specified a generic

message on which we built and added a truck

overtaking specific payload. Using this message, 600

overtaking maneuvers at different transmission

frequencies were simulated, and all overtaking

maneuvers were successfully planned and completed.

Our subsequent investigation showed that a

transmission frequency of 5 Hz provided the best

trade-off between channel load and overtaking

maneuver quality.

Having demonstrated in “Cooperative Truck

Overtaking on Freeways” how a cooperative truck

overtaking maneuver can be optimally planned, we

now have the capability to coordinate this planning

between two vehicles via V2X. The next step will be

the integration of our system into two trucks to

investigate the cooperative truck overtaking

maneuver not only in simulation but in real field tests.

A resulting assistance system would have the

potential to relieve the truck driver and lead to a more

sustainable working environment and is a step

towards autonomous truck traffic in the long term.

ACKNOWLEDGEMENTS

Research supported by MAN Truck & Bus SE and the

IMAGinE project (Intelligent Maneuver Automation

- cooperative hazard avoidance in real-time).

IMAGinE is founded by the German Federal Ministry

for Economic Affairs and Energy (BMWi).

CONTRIBUTIONS

J.C.M. (first and corresponding author) initiated the

idea of the paper and contributed to the

conceptualization, methodology, software,

investigation and writing of the original draft. J.H.

supported the methodology and investigation with

insights and discussions. F.D. and A.Z. made an

essential contribution to the conception of the

research project and revised the paper critically for

intellectual content. F.D. and A.Z. give final approval

for the version to be published and agree to all aspects

of the work. As a guarantor, F.D. accepts

responsibility for the overall integrity of the paper.

Strategic Coordination of Cooperative Truck Overtaking Maneuvers

519

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