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Cooperative Driving and the Tactile InternetFalko Dressler Fellow, IEEE, Florian Klingler Student Member, IEEE,

Michele Segata Member, IEEE and Renato Lo Cigno Senior Member, IEEE

Abstract—The trend towards autonomous driving and therecent advances in vehicular networking led to a number of verysuccessful proposals towards cooperative driving. Maneuvers canbe coordinated among participating vehicles and controlled bymeans of wireless communications. One of the most challengingscenario or application in this context is Cooperative AdaptiveCruise Control (CACC) or platooning. When it comes to realizingsafety gaps between the cars of less than 5 m, very strongrequirements on the communication system need to be satisfied.The underlying distributed control system needs regular updatesof sensor information from the other cars in the order of about10 Hz. This leads to message rates in the order of up to 10 kHzfor large networks, which, given the possibly unreliable wirelesscommunication and the critical network congestion, is beyondthe capabilities of current vehicular networking concepts. In thisarticle, we summarize the concepts of networked control systemsand revisit the capabilities of current vehicular networkingapproaches. We then present opportunities of Tactile Internetconcepts that integrate interdisciplinary approaches from bothcontrol theory, mechanical engineering, and communication pro-tocol design. This way, it becomes possible to solve the highreliability and latency issues in this context.

Index Terms—Cooperative Driving, Real-Time Guarantees,Cooperative Adaptive Cruise Control (CACC), Tactile Internet

I. INTRODUCTION

We are currently experiencing astonishing developments inthe field of wireless communications. Since the early days ofWi-Fi and 2G/3G networks, data rates went up two to fourorders of magnitude from a few kilobit per second (2G) or afew megabit per second (Wi-Fi, 3G) to now more than a gigabitper second. This trend still continues and we see novel wirelesscommunication technologies at the horizon mainly focused onproviding big data pipes. In the field of short range wireless,Wi-Fi includes now IEEE 802.11ac [1] and in the cellularworld, we see first (trial) deployments of 5G networks [2]. Weanticipate that these advances will continue to speed up ourwireless networks in the coming years; yet, data rates aloneare not sufficient.

Orthogonal to these huge data pipes, there is the needfor improvements in other directions. Given the widespreadavailability of wireless communication technology, interesthas grown to apply this to either previously wire dominatedfields (e.g., industry automation) as well as to completelynew application domains (e.g., connected cars). The mainemphasis in these areas is on ultra low latency and very highreliability. With these objectives in mind, the Tactile Internet

Falko Dressler and Florian Klingler are with the Distributed EmbeddedSystems Group, Heinz Nixdorf Institute and Dept. of Computer Science,Paderborn University, Germany ({dressler,klingler}@ccs-labs.org).

Michele Segata and Renato Lo Cigno are with the Dept. of Infor-mation Engineering and Computer Science, University of Trento, Italy({msegata,locigno}@disi.unitn.it).

initiative has been formed [3], [4]. The name Tactile has beencoined with applications on remote haptics in mind. Thisincludes distributed robot control, remote surgery, coordinatedautomated driving, and many other Cyber Physical Systems(CPS) solutions. In summary, we can describe most of theseapplications as networked control solutions, where local controlis influenced by remote sensors or actors and even humanplayers in the loop, the latter one introduced by the researcharea of Cyber Physical Social Systems (CPSS) [5].

We concentrate on one of the prime application domains ofthe Tactile Internet: cooperative automated driving. Researchin this field is driven by two main technologies: vehicularnetworking and automated driving. We concentrate on thecommunications part that is often also referred to as VehicularAd Hoc Network (VANET) or, more recently, car-to-carcommunication [6]. The fundamental basis of VANETs is theuse of IEEE 802.11p [7] based communication stacks, whichare fully relying on the CSMA/CA based medium access.In particular, we are talking about IEEE WAVE/1609 [8] inthe U.S., ETSI ITS-G5 [9] in Europe, and ARIB T109 [10]in Japan. Following results from early field trials, thesecommunication stacks have been extended to primarily supportvery large numbers of cars by introducing congestion controlmechanisms. The European Decentralized Congestion Control(DCC) solution [11] is now also incorporated into the U.S.IEEE WAVE stack. However, little priority has been put onguarantees for low latency communication or certain degreesof reliability. This is currently changing with the introductionof cooperative automated driving applications.

Bringing both research domains, i.e., cooperative drivingand the Tactile Internet, together, we see not only a perfect fitbut a strong need for introducing these concepts as enablers forfuture cooperative automated driving solutions. Looking froman automated driving perspective, we are essentially concernedabout vehicle dynamics and control [12]. Cooperative AdaptiveCruise Control (CACC) based platooning [13] is the primeexample for large scale distributed control applications in thisfield, where local dynamics and control influence an entireset of cars that need to be coordinated and controlled as awhole in order to avoid crashes [14]. Having said that, the twomain objectives of Tactile Internet research are also the mostimportant ones for platooning: high communication reliabilityand low latency. These two objectives are essential to guaranteethe bounds that ensure safety, which are much more importantthan elegant optimal solutions that cannot incorporate systemsimpairments.

In this paper, we address the need for such bounds andguarantees taking cooperative driving as an example application.We investigate how such time critical communication can berealized in this field and also derive open research challenges

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that need to be addressed by our entire research community.The remainder of this paper is structured as follows. InSection II, we briefly revisit current vehicular networkingsolutions that build the basis for cooperative driving maneuvers.In Section III, we discuss CACC based platooning concepts, theunderlying control problem, and its current not yet satisfyingimplementations using IEEE 802.11p based protocols. InSection IV, we introduce two possible ways out of thisdilemma, looking at Tactile Internet based solutions usingeither integrated network-control concepts or heterogeneousnetworking technologies, which are eventually complementaryto each other. We conclude the paper highlighting relevantopen research challenges in Section V.

II. VEHICULAR NETWORKING: A RETROSPECTIVE VIEW

After more than 15 years of research in vehicular networking,research evolved from pure theoretical studies up to largescale field tests, and nowadays to the first deployed systemsin newly sold vehicles. A first and still very importantapplication domain for vehicular networks has been cooperativeawareness: cooperative awareness messages are broadcast toinform neighboring nodes about a vehicle’s current status,i.e., position, speed, acceleration, heading, etc.; this processis also called beaconing. These small 1-hop broadcasts helpimproving road traffic safety and efficiency [6], [15]. In thepast, several protocols have been proposed starting with fixedperiod beaconing [16], adaptive beacon interval selection [17]–[21], and to coordinated use of multiple channels [22], [23]for improved performance in highly congested road trafficscenarios.

SOTIS [16] proposes the usage of a knowledge base for aself-organizing traffic information system. Selected knowledgebase items are periodically transmitted to local neighbors ata fixed time interval. Evaluations showed that such staticperiod beaconing is not suitable for every traffic scenario (tooslow for spare traffic, too fast for dense traffic). Protocolssuch as REACT [17] and ATB [18] investigated adaptivebeaconing approaches, in which the interval between twoconsecutive beacons is adapted according to the traffic density.The primary goal is to send information as often as possible,but avoid overloading the wireless channel at any time. Thishas further been extended to include receiver centric metricsin FairDD [24], as in realistic road traffic networks, a potentialreceiver could be interested in different information items thana sender. The concept therefore aims at maximizing the overalltransmitted message utility. For congestion control, FairDD hasbeen integrated with ATB. The resulting FairAD [25] conceptthus provides a resilient communication protocol for vehicularnetworks.

Standardization bodies picked these research findings onbeaconing protocols up and developed communication stacksfor vehicular communications. In Europe this is the ETSI ITS-G5 protocol suite, which also introduces DCC to not overloadthe wireless channel. In particular, the channel load is constantlymonitored and the standard defines a dedicated state machine tocontrol beacon interval, transmit power, transmit data rate andsensitivity according to the currently perceived load. In U.S.,

the IEEE 1609 protocol suite also offers multi channel operation(IEEE 1609.4), security services (IEEE 1609.2), routing andmessage dissemination (IEEE 1609.3), as well as resourcemanagement (IEEE 1609.1). Congestion control is currentlybeing added based on the LIMERIC approach [19]. The basisfor both standards is the IEEE 802.11p protocol which is basedon WLAN and defines both PHY and MAC using a dedicatedspectrum in the 5.9 GHz band.

On the other hand, cellular communication based on 4G in-corporating LTE and LTE D2D (infrastructure supported ad-hoccommunication) is getting keen attention to be used as anothervehicular communication technology [26]. In particular, therecent development of LTE V2X focuses on the requirements ofvehicular communications and their challenges concerning thehigh mobility of nodes in the network [27]. LTE V2X is basedon LTE D2D, which allows nodes to communicate directlywithout relaying data over the base station (eNodeB) having thebenefit of lowering the channel load and the ability for spatialreuse of the frequency spectrum. LTE D2D specifies two modesfor channel allocation, one requiring central infrastructure, andone fully distributed channel resource allocation without theneed of any infrastructure.

Recent research investigations also consider other technolo-gies than IEEE 802.11p as a feasible medium for communi-cation between Vehicles, and between Vehicles and RoadsideUnits (RSUs). One prominent candidate is Visible LightCommunication (VLC), for which the existing head and taillights of vehicles can be used to transmit information [28]–[30].The receiving part in VLC can either be a Photo Diode or aCamera Based system [31]. Another candidate is Millimeter-Wave (mmWAVE) which takes advantage of the spectrumbetween 30–300 GHz [32]. However both technologies, VLCand mmWAVE, depend on good channel characteristics due totheir high frequency and requiring Line of Sight (LOS) linksto reach good performance. First evaluations of VLC showthat it is feasible for outdoor communication in the vehicularcontext [33], [34].

Having all the mentioned communication technologies inmind, we believe that the real question is not which technologywill be used for future vehicular networks, but how all thesetechnologies should be combined and orchestrated to fullyoptimize the information flow through intelligent road trafficnetworks. These different communication techniques shouldbe combined to fully exploit their potential, and go onestep beyond 5G. This is in particular needed to support therequirements for future wireless networks incorporating theTactile Internet and Cooperate Driving, meaning low latency,high throughput, and high reliability and dependability byproviding full availability of the communication links whenthey are needed.

From the protocol design perspective, algorithms for messagedissemination need to move away from providing functionalityonly for a single application domain. Having realistic scenariosin mind, many different applications need to communicatewith neighboring vehicles at the same time. The dominatingcommunication primitive is broadcasting, even though thementioned application requirements still need to be considered.

In [35], a class based and context aware broadcasting scheme

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BroadcastClasses

Low-Priority GeocastClass D

reliable Broadcast withgeographical constraints

Class C

2-hop BroadcastClas

s B

Cooperative Awareness &Neighbor Management

Class A

Figure 1. Overview of the four different categories of context aware and classbased broadcasting to support a variety of different application domains invehicular networks.

is proposed to support past and future application domainsby abstracting application layer functionality from messageforwarding logics. We believe that this helps to further gainperformance in vehicular networks as it avoids disseminationof redundant information, and gives applications the possibilityto be operated concurrently on a wireless network avoidingnegative impacts of each other. The primary goal is to classifyapplications into four different categories as outlined in Figure 1.Here, Class A specifies simple 1-hop broadcasts for cooperativeawareness and building 2-hop neighbor information whichserves as a fundamental basis for Class B/C/D. Class B isusing this 2-hop neighbor information to disseminate importantinformation among all direct and indirect (2-hop) neighbors;possible applications for this type of broadcast class areintersection collision avoidance or pre-crash warning. Class Cperforms broadcasting with geographic constraints, e.g. along aroad segment to inform nodes about an approaching emergencyvehicle. Finally, Class D supports low priority geocasting ofinformation elements maintained in knowledge bases, similarto epidemic forwarding of information related to geographicregions and interest of receivers to disseminate informatione.g., about traffic conditions or warnings about a wrong waydriver. Each of these classes implements a set of protocolsto be used to perform the needed data dissemination schemesaccording to the actual traffic situation, node density, andapplication requirements. This fundamental paradigm change ofnetwork protocol design is an important step towards deployinga heterogeneous set of applications while maintaining all safetyrelated performance metrics.

PerceptionRadar Reaction Control Actuation Communication

(a) Manual driving (mainly depending on perception and response times):minimum headway time 2 s, i.e., 50 m at 100 km/h

(b) Radar based ACC: minimum headway time 1 s, i.e., 28 m at 100 km/h

(c) Simple CACC (radar plus IVC): minimum headway time 0.6 s, i.e., 16 mat 100 km/h

(d) Advanced CACC (multiple IVC links): speed-independent vehicle gap,e.g., 5 m

Figure 2. Comparison of vehicle following approaches with their typicalachievable performance.

III. PLATOONING OF CARS

Platooning, or cooperative automated driving, is an IntelligentTransportation Systems (ITS) application that groups vehiclestogether in road trains, or platoons [13], [36]. Vehicles in aplatoon autonomously follow each other at a close distance,all driven by a common shared leader. The leader can becontrolled by a professional driver, as envisioned by theSARTRE project [37], it can be a self-driving vehicle, orit can be remotely controlled (teleoperated [38]).

This application tackles multiple road transportation issuestogether. The first one is traffic congestion. The increasein the number of vehicles without the upgrade of the roadinfrastructure is leading to a complete congestion of urbanstreets and freeways. Increasing road capacity by building newstreets in cities or adding new lanes to freeways might eitherbe too expensive or simply unfeasible.

The solution thus lies behind a more efficient use of theexisting infrastructure, which, in turn, means reducing thewasted inter-vehicle spacing due to safety distances. Accordingto recommendations, the safety gap should be 2–4 s, whichtranslates into an actual distance around 55–110 m for a cruisingspeed of 100 km/h (Figure 2a). This gives an idea of the wastedcapacity on roads today.

Reducing inter-vehicle spacing can only be achieved withan automated driving system, as human drivers can not handleshort distances without compromising safety. One possible wayis through sensor-based systems, such as the ACC (Figure 2b),or brand-new self-driving cars. Although both seems to bepromising, they would not actually improve the situation much,as their perception is somewhat limited as for human beings.Sensor-based solutions work only in LOS conditions, i.e., theycan not see behind corners or past other vehicles. Moreover,and maybe more fundamentally, for system stability (and thussafety) reasons, these solutions must keep a safety distancewhich is comparable to the one kept by human drivers [12],

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resulting in no traffic improvement or, in some cases, evenreducing the traffic flow [39].

The solution is thus through connected and cooperativevehicles. Sharing information through a wireless link solvesthe LOS problem, increasing the perception that a vehicle hasof its surroundings. This permits to design CACC systems [12],[40]–[43], which are at the core of the platooning application.A CACC is an advanced version of a standard ACC thatexploits data received from other vehicles to improve thereactivity to any event, permitting to reduce inter-vehicledistance without compromising safety. As an example, theleader of a platoon can share its dynamics data so that allfollowers can replicate its actions in real time (Figure 2d). Thispermits to maintain speed-independent inter-vehicle gaps in theorder of a few meters, as witnessed by the pioneering CaliforniaPATH project [44] or in the European Project SARTRE [37].Other proposed implementations require communication onlybetween consecutive pairs of vehicles [40]. On one hand, thisavoids the necessity of a communication link to the leaderbut, on the other hand, the vehicles must use a time headway-based spacing, which is smaller than the ACC one, but resultsin a larger inter-vehicle spacing than leader-based solutions(Figure 2c). This is necessary because, if the control systemonly considers data received from the preceding vehicle, actionsperformed by the leader are only detected due to the physicalpropagation of vehicle dynamics, which is inherently slow.When the control system explicitly considers data sent by theleading vehicle, each platoon member can immediately exploitthis information almost simultaneously, making it feasible totighten the inter-vehicle spacing without reducing safety.

The second issue tackled by platooning is safety. Congestedfreeways cause the formation of traffic shock waves, whichare high-density waves of slowly moving vehicles that travelbackwards with respect to driving direction. Shock wavescan form spontaneously due to the amplification of smalltraffic perturbations that are normally absorbed in low-densityconditions [45]. They pose a high safety risk as they causeunexpected emergency braking maneuvers that can lead tochain collisions. Platooning can improve safety as the CACCtakes over control of the vehicle and, most importantly bymaking traffic flow smoother, thus reducing shock wavephenomena [39], [46].

Last but not least, by reducing traffic shock waves, platooningcan reduce CO2 emissions eliminating start-and-stop dynamicsthat consume more fuel than constant speed cruising. Inaddition, tailgating reduces aerodynamic drag, which canaccount for the 75 % of the tractive force during highwaycruising [47].

Platooning has clearly tight requirements on the wirelesscommunication network. In particular, an update frequencyin the order of 10 Hz is commonly assumed [40], althoughthis can be relaxed, if very high communication reliability canbe provided, to 5 Hz [48]. More recent work shows that thismight even change depending on vehicle dynamics [49]. It iswell-known, however, that WLAN-based technologies such asIEEE 802.11p [7] suffer high packet loss ratio due to channelcongestion, and in really dense scenarios they would simply beunable to meet CACC requirements. A detailed study in [48]

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Figure 3. Protocol delay performance (empirical cumulative density functionof packets meeting the delay requirement) studying ETSI ITS-G5 DCC, DynB,as well as an app-tuned approach using platooning optimized transmit powerand time slotting (figure inspired to [48], for detailed results see the originalpaper).

shows that the current standard for vehicular networking inEurope, ETSI ITS-G5 DCC, is not able to guarantee suchdelay requirements (see Figure 3). Other approaches such asDynamic Beaconing (DynB) fail as well, both only achievinga latency of 200 ms in less than 20 % of the cases. Whentrying all tricks known in the field of wireless communicationsincluding optimization of the transmit power and assigningtime slots for communications, the situation improves but stillthe delay requirement is not met in all cases as the App-tunedcurve in Figure 3 shows.

We find studies that address such limitations by exploitingthe natural structure of platoons. As an example, we canreduce intra-platoon channel contention by synchronizing com-munication between platoon members [50] and inter-platooninterference by adapting transmit power control [48]. In additionto such mechanisms, we can increase intra-platoon reliability byimplementing distributed reliable broadcast protocols throughre-transmission schemes [51].

Although promising, such approaches only focus on thenetwork without looking at the actual requirements, whichmight be time-varying [49]. The solution, as well as thechallenge, can be found in the Tactile Internet concepts, wherethe design of the system by jointly considering the application,the control system, and the communication mean, represents anon-marginal step forward.

In addition, the Tactile Internet finds application in the remotecontrol of the leading vehicle. Such application requires real-time data transfer between the vehicle and the control center,but the nature of the link is different with respect to the CACCuse case. The CACC requires a localized broadcast link thatshould periodically transfer small amounts of data, such asacceleration, speed, and position. However, the network is self-organizing, so there is the possibility of channel congestion. Theremote control link, instead, is a unicast connection through aninfrastructure-based network, which must continuously transfercontrol commands and visual feedback between the vehicleand the operator. The amount of data to be transferred is highercompared to what is required by a CACC, especially for thevisual feedback. On the other hand, in an infrastructure-basednetwork we have the possibility of pre-allocating the resources.Still, this is not something that can be achieved with a standard

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telecommunication network, so Tactile Internet concepts aredefinitely needed in this context.

IV. TACTILE INTERNET BASED SOLUTION SPACE

In the following, we investigate two possible approaches toaddress the lack of communication guarantees in CACC basedplatooning solutions. A first approach is to rely on an integrateddesign paradigm for network protocols and the underlyingvehicle control loop. A second approach is to use multipleheterogeneous communication technologies complementingeach other. These approaches are orthogonal to one another,i.e., can be used in combination for future robust and safeplatooning solutions.

A. Joint Network-Control Design

A promising method to realize cooperative driving is througha multi-disciplinary approach. Early studies both in the controltheory and in the networking areas did not consider limitationsand problems outside their scopes. As an example, the CACCdeveloped in the PATH project, does not even considercommunication impairments [44]. The CACC developed byPloeg et al., instead, models the wireless network with a delay,which does not capture all problems a wireless network canexperience [40]. On the other hand, we find communicationstudies that try to maximize packet delivery without consideringthe real requirements of the control system [48].

Recently, we are witnessing a change in perspective, with thetwo communities joining forces to design the control systemand the communication protocol together. One example is thework in [14], where the authors analyze the stability of aCACC in a control-theoretical framework, but considering amore realistic modeling of the network behavior with respectto the one assumed in [40]. In particular, the authors modelnetwork impairments as a constant delay together with a ZeroOrder Hold (ZOH) that emulates the sampling effect. The workderives stability conditions of the system depending on timeheadway, transmission delay, and sampling time.

The work in [49] proposes an adaptive protocol named “JerkBeaconing”. The authors observe that the data requirementsof the CACC depend on the dynamics of the vehicles. Ifthe dynamics of a vehicle are constant, periodic broadcastingsimply wastes resources, as other vehicles can predict thestate by knowing the initial one and the amount of timeelapsed since the generation of the initial state. Under thisassumption, the work proposes an empirical function thatcomputes the next packet sending time depending on how muchthe acceleration changed since the last sent update. The largerthe difference, the shorter the sending interval. In addition, theadaptive beaconing scheme is coupled with a reliable deliveryprotocol, which ensures the immediate re-transmission of thepacket in case of loss. The results shows that the approachnot only reduces network resource utilization, but that it iseven safer than standard periodic beaconing, because datais sent at the right time instant and due to the predictionmechanism. This approach, although empirical, is a proof ofconcept showing the importance of a joint design. A similardynamics-based approach is present in the DCC algorithm of

ETSI ITS-G5 [11] which, however, is not capable of meetinglow latency requirements as shown in [48] due to the congestioncaused by high-speed driving.

Dolk et al. [52] pursue a very similar concept, although in acontrol-theoretical framework. The authors oppose the idea ofevent-driven control to standard time-driven control, i.e., controlinformation is sent in the network only when required to ensuresystem’s stability. The idea is first mathematically formalizedand then verified with a benchmark composed by three carsand an IEEE 802.11p radio. In their experiments, the adaptivescheme is compared to a static, 25 Hz beaconing, showing thatthe system achieves exactly the same performance but withless resource utilization. Differently from [49], however, nopacket loss recovery is implemented.

We then find another joint network/control design which,differently from [49], [52], does not adapt the messagedissemination rate, but instead derives distance error boundssubject to packet losses and vehicle performance. Given acertain number of possible consecutive packet losses and themaximum vehicle dynamics in terms of jerk, the frameworkderives an upper bound on the distance error, which can thenbe applied as the actual inter-vehicle spacing. The simulativeanalysis shows that such bounds are always respected. In fact,as the experiments employ a prediction mechanism as in [49],the bounds are respected by a large margin.

These works clearly highlight the potential behind jointnetwork-control design approaches. Expert domain knowledgeis needed from both fields to eventually construct high qualityTactile Internet solutions. We can conclude that it is of utmostimportance to work in a multidisciplinary manner for the designof cooperative driving systems.

B. Heterogeneous Communication Technologies

An orthogonal approach is to improve communicationbehavior by relying on multiple communication technologies atthe same time. This idea has become popular under the nameheterogeneous networking with applications in 5G networks forfurther improving data rates but also in the Tactile Internet erato reduce latencies and to improve communication reliabilityin general [53], [54].

In the field of vehicular networking, this concept has beenidentified as one of the most important research questions [55],[56]. Many approaches concentrate now on the complementarityof IEEE 802.11p and LTE [57]–[59]. Most cases actually lookinto clustering cars to reduce the overhead on the control planeand, therefore, improving data plane communication [60], [61].

In this section, we concentrate on yet another set ofcommunication protocols, namely LOS techniques, that areof particular interest in the domain of cooperative drivingand platooning to complement some of the already discusseddeficiencies of IEEE 802.11p. The best known examples areMillimeter-Wave communication in the upper GHz band [62]–[64] as well as Visible Light Communication (VLC) usingthe frequency bands beyond radio frequency technologies [30],[65], [66]. Without loss of generality, we concentrate on VLCin the following but the concepts and ideas are applicable tommWAVE communication and vehicular radar as well.

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A first study on using an heterogeneous approach based onthe combination of IEEE 802.11p and VLC has been presentedin [67]. The paper addresses the main two problems of IEEE802.11p based platooning solutions: First, congestion on thewireless channel may lead to packet loss and, therefore, mayrequire a substantial increase of the desired distance betweenfollowing vehicles to ensure safety. Secondly, security concernsneed to be considered, from jamming of the channel (whichtranslates to packet loss) to malicious attacks. Both problemsare addressed by integrating VLC as a second communicationchannel. In fact, the following communication pattern wasconsidered: Only the platoon leader uses IEEE 802.11pand communication between consecutive vehicles is realizedthrough VLC. By using an 802.11p link, the leader reachesall platoon members simultaneously, which is fundamental forCACC systems that rely on a leader- and predecessor-followingcontrol topology [42], [44], [68]. The VLC link, in addition,can be used as a re-propagation mean in case 802.11p leaderbeacons are lost. The impact of the delay introduced by the re-propagation mechanism is still an open question. Each platoonleader is controlled by an ACC, while all the followers use theCACC controller described in [48]. This way, even multipleplatoons on the same lane can be supported in realistic freewayenvironments.

For this initial analysis, a simplified, purely stochastic, VLCchannel and physical layer model was used. In particular,assumea maximum reception range of 25 m was considered as wellas a decoding delay (i.e., processing time) to be distributedaccording to a truncated normal distribution (strictly positive)with a mean of 20 ms and a standard deviation of 1 ms. Thesevalues were tuned for a CCD camera based receiver with arather fixed processing delay, which becomes negligible whenswitching to a photodiode-based receiver [29]. At this shortdistance, also the light radiation pattern has almost no impact,which must be considered for larger distances [34].

In order to test the combined IEEE 802.11p/VLC approach,a freeway scenario was used in a traffic jam situation as in [48].In particular, a 4-lane freeway was simulated with 160, 320and 640 cars divided in platoons of 20 cars. As shown inSection III, particularly the dense scenario has been shown tofail (i.e., to miss the 200 ms delay requirements) using IEEE802.11p only. The key reason was the high load on the networkleading to congestion and eventually packet loss.

Figure 4 shows the figure we discussed already in Section III.This time, a curve for the heterogeneous approach usingIEEE 802.11p in combination with VLC has been added (cf.[67] for more details). As can be seen, the heterogeneouscommunication solution not only substantially outperforms allIEEE 802.11p based solutions but even guarantees to meet thedelay requirements in all cases.

Similar results can be achieved by combining IEEE 802.11pwith other LOS technologies such as mmWAVE using auto-motive radar [64], [69].

C. Research Roadmap

In summary, Tactile Internet solutions can help makingcooperative driving a reality from a technical point of view.

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Figure 4. Protocol delay performance as shown in Figure 3 now adding acurve for the heterogeneous networking approach using IEEE 802.11p andVLC (for detailed results see [67]).

From a research roadmap perspective, the following challengesneed to be addressed on a fundamental level:

• Ultra low latency and ultra high reliability – to allowremote control of cooperative driving maneuvers; this canbe achieved by

• design of integrated network protocols – to enable closedloop control algorithms in networked systems; and

• combination of complementary communication technolo-gies such as short range RF (e.g., IEEE 802.11p) andLOS solutions such as mmWAVE or VLC.

V. FURTHER RESEARCH CHALLENGES

Based on our investigation of communication conceptsfor supporting ultra low latency and very high reliabilityapplications in the automotive environment using platooningas an example, we discuss selected open research challenges inthe following. We aim at guiding researchers that are new inthe field or who are thinking about different angles to approachthe problem. This list can by no measure be complete. Instead,we focus on three important aspects that also have been debatedstrongly in recent conferences.

A. Scalability and Dependability

From the communications perspective, cooperative drivingwill pose big challenges in the dependability and scalability ofthe networking system. The two topics are different, but inter-twined, and neither of them received sufficient attention so far.The question of scalability has been raised already, but mainlyin the form of channel congestion control, which is definitelya wrong perspective. Any safety-related communication, beit for cooperative driving or for any other application of theTactile Internet, cannot wait for the congestion on the channelto subside before the information is sent. Indeed, the scalabilityissue must be tackled from the perspective of guaranteeingthat enough resources are available to always support safetyapplications, i.e., from a resource allocation perspective. Thisentails not only a proper policy to guarantee that enoughspectrum is allocated for cooperative driving, but also thatwithin that spectrum the communication devices can followthe technological trend to improve the spectrum efficiency, e.g.,with the adoption of Multi-Channel / Multi-Radio devicesas well as massive Multi User – Multiple Input Multiple

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Output (MU-MIMO) techniques. Needless to say that MU-MIMO technology has never been explored in conjunctionwith multicast/broadcast communications; and in the vehicularenvironment it has hardly even been mentioned. Moreover,scalability in cooperative driving means finding proper waysof ensuring the “graceful degradation” of the system towardautonomous and/or human driving (cf. Section V-C), when,whatever the reason, the communications system cannot sustainanymore the globally entangled cooperative driving maneuvers.

This is where scalability intertwines with dependability.Clearly nobody can even consider the idea that cooperative,autonomous vehicles fail when they are most needed, i.e.,when safety is at stake. This is why we refer to dependabilityand not reliability: A system that is reliable 99.999 % of thetime, but fails when human safety is at stake is not onlyuseless, but indeed dangerous. To guarantee full dependability,communications for the mobile Tactile Internet must be basedon properly coordinated and physically different communicationmeans. Several channels are needed, and they must be asuncorrelated to each other as possible, so that dependability isachieved. For instance, in the realm of cooperative driving, wecan imagine that not only local short range radio techniques areused in parallel with cellular networks, but also communicationchannels built on VLC as well as mmWAVE communicationstechniques. This is a sound assumption given the widespreaduse of LED lights as well as radar ranging devices measuringdistance of vehicles in front, behind, and around.

Besides posing interesting problems and questions on re-source organization and orchestration, the presence of severalcommunications channels for dependability, if properly man-aged, also support scalability. Once several communicationchannels are available, the congestion or unavailability of oneof them is just another event to be considered within the globalmanagement of safety and cooperation, for instance by relaxingthe performance requirements to improve the system resilience.

B. Security and Privacy

Security in cooperative driving is especially challenging as itis strictly related to safety. A system that is insecure leaves roomfor attacks, which could have serious consequences. Besidesthe public safety concerns, accidents during the initial roll-outphase might negatively influence the public opinion, whichalready shows concerns about riding in self-driving cars [70].

Security in this context embraces different aspects, includingsystem design and communication. All the devices involvedin cooperative driving, including the vehicle itself, must betamper-proof. From the vehicle perspective, cooperative carswill be equipped with actuators for electronic control purposes.Needless to say, gaining access to any of the in-car componentscan give an attacker the possibility of controlling the entire car.Here, however, we put our focus on security concerns regardingcommunication as a key feature of the Tactile Internet.

Tampering of the On Board Unit (OBU) can lead to differentpossible attacks. First, it could be possible to attack the vehicleon which the tampered OBU is installed. The attacker couldfeed malicious data to the CACC, causing the vehicle toaccelerate or decelerate at his/her own will [71]. To protect

against such attacks, besides properly designing OBUs froma security perspective, a data-fusion layer should serve as anadditional barrier against malicious data. Ideally, data-fusionshould take data from multiple sources, detect erroneous data,and discard it, potentially warning the system about the problem.The second type of attack exploits the radio for sending fake butauthenticated messages. As CACC algorithms are not designedto cope with malicious network impairments, this may trickvehicles in the same platoon causing collisions [72], [73].

In both attack scenarios, it is data that should be made timelyand reliable, as data is the means to cooperation. For this reason,we believe the research direction must not be vertical, aimingat making one particular communication technology able tosupport cooperative driving, but rather horizontal. Multipletechnologies should be put together to realize parallel linksbetween the vehicles, providing redundant communication (cf.Section V-A). Data can (and must) be fused and checked forconsistency before being handed over to control algorithms.

In addition, we must change the way we design controlalgorithms to specifically take into account the effects ofcommunication failures, e.g., due to a jamming attack. Thisprovides safety margins that can be exploited for counter-actingdata losses. In particular, disaster recovery procedures needto be developed that are triggered by certain events. Whatshould clearly be defined are such triggering conditions andthe best actions to be taken to ensure passengers’ safety; bothof which are still open research problems. Again, relying on,for example, LOS communication technologies as discussedbefore, offers additional opportunities also for security – simplybecause it is very hard for an attacker to compromise VLC ormmWAVE links.

Strictly related to security is privacy. Some authors havediscussed that privacy and security conflicts in this context.However, works like [74] already question the strong clashbetween privacy and safety, if not for else because vehicles onthe road neither require, nor have today, strong anonymity. Thissaid, research on the proper means to protect users’ privacyin cooperative driving is far from concluded, and indeed theextremely low latency requirements of the Tactile Internet addchallenges to privacy protection methodologies like the use oftime varying pseudonyms, group authentication, and so forth.

Once more the platooning applications is clarifying: Howcan the identity of vehicles forming a platoon be reasonablyconcealed while the control information is distributed in theplatoon? Furthermore, should this information be cryptograph-ically protected so that only vehicles involved in the platooncan receive it or not? Indeed, privacy and anonymity protectionfor road users is a very broad issue that involved technicalissues, but also legal and societal questions and decisions: Farfetching, visionary, and interdisciplinary research is neededalong this path.

C. Public Acceptance

One of the most critical questions when it comes to deployingany new technology is public acceptance. Indeed, there is nofield where automation is as critically discussed and arguedabout as automotive and the ability to drive on your own

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account. Right now, we see many activities worldwide toenable automated driving not only from a technological pointof view but most importantly from both a social and a legalone. Regarding the social aspects, in-depth studies have beenconducted to analyze the socio-psychological impacts of publicacceptance [75]. Seemingly, there is a multitude of aspects thateven depends on the cultural and historical developments of aspecific country.

Furthermore, there is the very important problem of lack-ing correct self-assessment by many or even most people,particularly, when it comes to questions like who is a gooddriver. The well-known Dunning-Kruger effect [76] explainsthe cognitive bias, wherein persons of low ability suffer fromillusory superiority when they mistakenly assess their cognitiveability as greater than it is. This has been confirmed in manyempirical studies investigating public acceptance of automateddriving [77]. The outcome is that a substantial group of peoplesimply rejects the idea due to their (wrong) belief that theyare able to handle problems better. Legal issues, on the otherhand, have in part already been addressed successfully in manycountries. First fields trials are being conducted worldwide andautomated driving has been legalized in many places.

These observations go hand in hand with findings thatautomated decision making is moving more into the focus ofthe public. In automated driving, cars have to make decisionsthat possibly affect (and threat) human lives – including thecar owner’s one. The frequently cited example of, when beingin a very critical situation, whether the car should prefer thedriver against pedestrians has been modeled in-depth by theMIT moral machine [78]. In a huge variety of situations, onecan test his own decision preferences to see how complexautomated decision making can get.

Getting back to cooperative driving, the situation gets evenworse. Here, only automated cars can successfully interact to,e.g., form a platoon and drive safely with a gap of just a fewmeters between each car. Human drivers will never be ableto handle the required short reaction (and perception) times.On the other hand, there will be legacy cars driven by humandrivers. Together with semi-automated and fully automated cars,they form what is now called a Cyber Physical Social Systems(CPSS) [5]. The impact of communication technologies onsuch CPSS is not understood completely and there is a strongneed to re-iterate on accepted solutions and their applicationon such complex systems where human drivers interact withautomated cars in a closed loop fashion.

D. Research Roadmap

In summary, Tactile Internet solutions need to be enhancedto also cover non-functional aspects substantially affectingcooperative driving maneuvers. From a research roadmapperspective, the following challenges need to be addressedon a fundamental level:

• Scalability is at the core of many of the research questionsdiscussed and often solutions work pretty well as longas only a limited number of systems participate in thenetwork;

• security solutions have been defined in standardizedprotocol stacks but often either limit scalability or theyintroduce privacy concerns; and

• human interaction affects technical solutions either due toacceptance problems or, if the human is part of the system,due to limited reaction times or misleading self-assessmentof own capabilities.

VI. CONCLUSIONS

We studied the need of novel communication paradigmssupporting the emerging field of cooperative driving. Partic-ularly, when it comes to safety critical applications such asCooperative Adaptive Cruise Control (CACC) and platooning,where safety gaps of less than 5 m need to be controlled not onlyusing local sensors but most importantly input obtained fromneighboring cars via wireless communications, state of the artsolutions do not provide the required degree of reliability andthe necessary guarantees on low latencies. The Tactile Internetinitiative has been formed having exactly these objectivesin mind. We have shown how such concepts, in particularthe use of integrated network-control design as well as theuse of orthogonal heterogeneous communication technologieshelps overcoming some of these challenges. In conclusion, itcan be said that some first steps have been done successfullyin applying Tactile Internet solutions to cooperative drivingbut there is still a long way to go for enabling large scaledeployment while meeting all the safety requirements.

ACKNOWLEDGEMENTS

This work has been supported in part by the GermanResearch Foundation (DFG), grant no. DR 639/18-1.

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Falko Dressler (dressler@ccs-labs.org) is full pro-fessor of computer science and chair for DistributedEmbedded Systems at the Heinz Nixdorf Institute andthe Dept. of Computer Science, Paderborn University.Before moving to Paderborn, he was a full professorat the Institute of Computer Science, University ofInnsbruck and an assistant professor at the Dept.of Computer Science, University of Erlangen. Hereceived his M.Sc. and Ph.D. degrees from the Dept.of Computer Science, University of Erlangen in1998 and 2003, respectively. Dr. Dressler is associate

editor-in-chief for Elsevier Computer Communications as well as an editorfor journals such as IEEE Trans. on Mobile Computing, IEEE Trans. onNetwork Science and Engineering, Elsevier Ad Hoc Networks, and ElsevierNano Communication Networks. He has been guest editor of special issues inIEEE Journal on Selected Areas in Communications, IEEE CommunicationsMagazine, Elsevier Ad Hoc Networks, and many others. He has been chairingconferences such as IEEE INFOCOM, ACM MobiSys, ACM MobiHoc, IEEEVNC, IEEE GLOBECOM, and many others. He authored the textbooks Self-Organization in Sensor and Actor Networks published by Wiley & Sons andVehicular Networking published by Cambridge University Press. He has beenan IEEE Distinguished Lecturer as well as an ACM Distinguished Speaker. Dr.Dressler is a fellow of the IEEE as well as a senior member of the ACM, andmember of the german computer science society (GI). He also serves on theIEEE COMSOC Conference Council and the ACM SIGMOBILE ExecutiveCommittee. His research objectives include adaptive wireless networking, self-organization techniques, and embedded system design with applications in adhoc and sensor networks, vehicular networks, industrial wireless networks,and nano-networking.

Florian Klingler (klingler@ccs-labs.org) receivedhis BSc and MSc in Computer Science from theUniversity of Innsbruck, Austria, in 2010 and 2012,respectively. In 2012 he was a visiting ResearchAssistant with the group of Jiannong Cao at the De-partment of Computing at the Polytechnic University(PolyU) in Hong Kong. He is currently workingtowards his Ph.D. in the Distributed EmbeddedSystems Group of Falko Dressler at Paderborn Uni-versity, Germany. His research focuses on protocolsfor adaptive wireless networks in highly dynamic

scenarios, with applications in vehicular communications.

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Michele Segata (msegata@disi.unitn.it) is a PostDocresearch fellow at the University of Trento, Italy. Hereceived his B.Sc. and M.Sc. in Computer Sciencefrom the University of Trento in 2009 and 2011,respectively. In 2016 he received a double PhD inComputer Science from the Universities of Innsbruck(Austria) and Trento. His main research focus is onautomated car following (or platooning), analyzingthe impact of the wireless network on the dynamicsof the vehicles, and vice versa. He is also workingon the development of highly realistic simulation

models for platooning, vehicular networking-based safety applications, and asoftware defined radio implementation of the IEEE 802.11p physical layer. Hehas served in many TPCs of international conferences, including GLOBECOM,VNC, VTC, and Med-Hoc-Net.

Renato Lo Cigno (locigno@disi.unitn.it) is As-sociate Professor at the Department of ComputerScience and Telecommunications (DISI) of the Uni-versity of Trento, Italy, where he leads the AdvancedNetworks Systems research group in computer andcommunication networks. He received a degreein Electronic Engineering with a specialization inTelecommunications from Politecnico di Torino in1988, the same institution where he worked until2002. In 1998/9, he was with the CS Dep., UCLA, asa Visiting Scholar. Renato Lo Cigno has been General

Chair of IEEE Int. Conf. on Peer-to-Peer Computing, TPC Chair of IEEEVNC, and General Chair and TPC Chair of ACM WMASH and IEEE WONSin different years. He has served in many TPCs of IEEE and ACM conferences,including INFOCOM, GLOBECOM, ICC, MSWiM, VNC, and CoNext, andhas been Area Editor for Computer Networks and is currently Editor forIEEE/ACM Transactions on Networking. He has been guest editor for SpecialIssues of Elsevier Computer Networks and Computer Communications, andSpringer LNCS. His current research interests are in performance evaluation ofwired and wireless networks, modeling and simulation techniques, congestioncontrol, P2P networks and networked systems in general, with specific attentiontoward applications and sustainable solutions. Vehicular networks, with a hypeon safety and cooperative driving applications, are a special niche in hisinterests. Renato Lo Cigno is senior member of IEEE and ACM and hasco-authored around 200 papers in international, peer reviewed journals andconferences.