Position-Aware Ad Hoc Wireless Networks for Inter-Vehicle Communications: the Fleetnet Project Hannes Hartenstein

NEC Europe Ltd.

hartenst@ccrle.nec.de

Matthias Lott Siemens AG

matthias.lott@icn.siemens.de

Bernd Bochow GMD Fokus

bochow@fokus.gmd.de

Markus Radimirsch University of Hannover

radimirsch@ant.uni-hannover.de

André Ebner University of Hamburg-Harburg

ebner@tu-harburg.de

Dieter Vollmer DaimlerChrysler AG

dieter.vollmer@daimlerchrysler.com

ABSTRACT The Fleetnet project aims at the development of a wireless ad hoc network for inter-vehicle communications. We present the ratio-nale behind the choice of an appropriate radio hardware and the use of a position-based routing approach and outline applications to exploit the Fleetnet platform. In addition, we discuss simulation of vehicle movements as a basis for protocol evaluation as well as aspects of Internet integration of Fleetnet. We state the basic problems together with the intended approach of tackling these challenges, thereby providing an overview of the Fleetnet project.

Keywords Ad hoc networking, vehicle networks, position-based routing.

1. INTRODUCTION In this paper we present the project ‘Fleetnet – Internet on the Road’ that aims at the development and demonstration of a position-aware wireless ad hoc network for inter-vehicle communications. Fleetnet is an activity of a consortium consisting of DaimlerChrysler AG, GMD FOKUS, NEC Europe Ltd., Robert Bosch GmbH, Siemens AG, and TEMIC TELEFUNKEN micro-electronic GmbH, and the Universities of Mannheim, Hamburg-Harburg, and Hannover. The project has started in September 2000 with a planned duration of 40 months and is partly funded by the German Ministry of Education and Research (BMB+F). By enabling multi-hop vehicle-to-vehicle communication one can achieve i) improved safety through an extended range of awareness of a vehicle and its driver, and ii) a new low-cost communication option for a vehicle’s passengers and network components. The first aspect, safety, benefits from the fact that vehicles will be enabled to quickly distribute sensor data they

have collected to surrounding vehicles allowing them to take appropriate actions. The second aspect, low cost communication for the vehicle’s passengers and network components, will allow co-operations of car passengers driving the same route as well as Internet integration of the vehicles through gateways located along the routes. Fleetnet will realize single-/multihop transmissions and transmissions to/from stationary nodes. All communications will be decentrally organized, i.e., stationary nodes will not perform any centralized control, they will run the same protocols as mobile Fleetnet nodes. Fleetnet will provide the basis for a broad range of applications in the areas of cooperative driver assistance systems and mobile information systems. We see three significant advantages of ad hoc networks over cellular systems in this context: i) minimal delay for time-critical safety-related information, ii) low trans-mission costs, and iii) addressing of neigboring cars based on their (relative) position. The cost aspect is important for decentralized floating car data applications since sensor data has to be transmitted periodically from each vehicle to the vehicles in a ‘few hop’ neighborhood. With a cellular approach the costs for these periodic transmissions would be excessive. In contrast, with a decentralized wireless multihop ad hoc network, the ‘locality’ of the data and their importance is exploited. Since the data’s relevance to a specific geographic area is one of the key features of an inter-vehicle network, Fleetnet nodes will not only be addressable via IP addressing but also according to their current position. Such a position-based addressing scheme naturally supports geocasting [6] as well as location-based services, and it enables position-based routing. In this paper we present the current state and objectives of the project with respect to the various aspects of ad hoc networking: applications and their requirements (Section 2), models of vehicle traffic needed for protocol evaluation (Section 3), choice of radio hardware and DLC issues (Section 4), position-based routing (Section 5), and Internet integration (Section 6).

2. FLEETNET APPLICATIONS Fleetnet applications are in the areas of driver assistance, decentralized floating car data, and user communications. Cooperative driver assistance systems exploit the exchange of sensor data between cars. A first application to be implemented

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will be emergency braking: in case of accident or hard braking a notification will be send to following cars. Information of accidents can even be transported by cars driving in the opposite direction and, thereby, be conveyed to vehicles that might run into the accident [2]. One of the most sophisticated applications in the area of driver assistance is platooning of vehicles, i.e., the coupling of a group of vehicles for automatically coordinated manoevering. Other areas of driver assistance are: overtaking assistance, security distance warning, and support for optimal driving strategy. These applications require position awareness of the vehicles, addressing according to current positions, short transmission delay, and high reliability of data exchange. Cooperative driver assistance provides an excellent example for the need of exchange of data that is of local relevance. Current floating car data services are based on service centers which collect and combine data from cars and broadcast ‘drawn conclusions’ back to the service members. For example, from several ‘no movement’ messages of cars on a highway, a traffic jam can be recognized, and a traffic jam warning message can be sent to service subscribers. However, such a service can be realized without any centralized information processing in an inter-vehicle communication system which exploits position-awareness for data distribution. Thus, service centers and expensive transmissions via cellular radio systems are avoided. Assuming that cars are equipped with digital maps and, therefore, are aware of the route to go, messages can be sent along the route ahead to ask vehicles about traffic flow, weather conditions and other data. Alternative routes can be assessed very fast. Fleetnet applications do not only deal with the driver’s safety and with traffic flow but also with the aspect of ‘comfort’ of the vehicle’s passengers. For example, passengers in the backseats can play online games with passengers in other cars that are traveling on the same highway. Other applications include transmissions of data from commercial vehicles about their businesses. With its static Fleetnet gateways on the roadside, Fleetnet also provides a means for marketing along the road. The above collection of applications provides enough variety in order to define the types of service Fleetnet has to provide: i) emergency notifications, ii) periodic data (on traffic flow), and iii) passenger communication and information. Emergency notifications show high requirements with respect to end-to-end delay but have small bandwidth requirements. Periodic data, i.e., floating car data, also has small bandwidth requirements but need frequent access to the medium. ‘User communications’ shows bandwidth requirements ranging from small to very high.

3. MODELING OF NODE MOVEMENTS While most ad hoc networking research has assumed a ‘rectangular’ network area and a random waypoint mobility model, the specific patterns of vehicle movements and traffic give inter-vehicle networks their distinctive feature with respect to other ad hoc networks. In particular, the high speeds and ‘one-dimensionality’ of highway scenarios are different to other ad hoc communication scenarios. Traffic patterns depend on the traffic’s density, i.e., the number of vehicles per kilometer. For small densities one can assume that cars are moving independently of each other. At high densities, the complex interactions between neighboring vehicles make modeling of such a dynamical system a challenge.

For low density scenarios one usually builds basic traffic models by specifying probability distributions for vehicle speeds and for time headways (time between two following cars passing a reference point). These headways are typically measured in seconds and provide a safety-related measurement of distances. However, for Fleetnet purposes we are more interested in distances between vehicles measured in meters. We model the probability for a Fleetnet node to reach at least one other Fleetnet node within a distance d with an exponential distribution

dedFP λ−−=< 1)( where λ is derived as follows. We

assume an average velocity av , an average gross time headway ∆t, a given number of lanes N, and a Fleetnet penetration rate r (r gives the percentage of all vehicles equipped with the Fleetnet system). Then, the average effective distance ad between two

Fleetnet nodes is given via )/()( Nrtvd aa ⋅∆⋅= .

The mean value of the given exponential distribution is 1/λ. Therefore, ad/1=λ is the right parameter for our distribution. We give an example of the use of such an exponential distribution model in the following section where we derive probabilities for the distances of multi-hop connectivity. For more accurate modeling, in particular for high density scenarios, microscopic traffic simulation models have been proposed in the literature. The cellular automaton approach [5] has been selected as a promising candidate for Fleetnet simulations since it provides sufficient accuracy for low computational costs, i.e., it enables large-scale simulations. Furthermore, DaimlerChrysler is currently compiling a set of vehicle movement scenarios using their driver-based modeling approach. These scenarios show vehicle movements on German autobahns, country roads and streets of the inner city of Berlin. Highways with different number of lanes, highway crossings, different traffic situation such as night traffic, rush hour traffic or traffic jam will be taken into account. This database is used as input data for protocol evaluation by simulation means.

4. RADIO HARDWARE AND DLC In this section we focus on the required radio coverage area of a Fleetnet node, i.e., on the impact of the range of coverage with respect to multihop connectivity. After presenting a list of requirements for the radio system, the radio hardware chosen for Fleetnet will be introduced. Range of bandwidth needs. While emergency calls require only a few bytes for signalization, services like internet access may require high bitrates of more than 100 kbit/s. Hence, the Fleetnet radio systems has to support a high range of bandwidth needs. Radio Path characteristics. The integration of the wireless ad hoc system into the vehicle implies the operation of the radio system within a multipath propagation environment. In addition, the radio system has to cope with Doppler frequency shifts caused by the mobility of the radio system. Particularly, within highway environments high relative velocities of up to 400km/h may occur. Contact times. Due to the high relative velocities, the radio contact of two approaching vehicles or between a Fleetnet gateway and a passing vehicle can be very short. Calculations for the duration of the radio contact depending on the range of the radio system show that radio systems supporting a distance lower

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than 500m can only guarantee for a contact below 10s. Note that beyond the transmission and reception of data, the duration of the radio contact also comprises additional tasks like signal detection, adaptation of the amplifier gain and synchronization. Multihop connectivity. We have studied the impact of the range of a node’s radio coverage area on the feasible multihop communication distance of a node. Simulations based on the model outlined in Section 3 give results as presented in Figure 1 and 2. Two highway scenarios characterized by high and low traffic volume, respectively, are studied. An average velocity of 125km/h and a Fleetnet penetration of 10% is assumed. The highway has two lines per direction. Although the first case with a high traffic volume defines a ‘best case’ scenario for Fleetnet multihop communications, the radio system has to support a distance of at least 1km to guarantee 5 hop communication with a probability of more than 90% (i.e., allowing for the realization of a multihop distance of up to 5km). Note that for radio systems with a distance of less than 200m the probability for the realization of an additional hop is less than 20%. The situation gets even worse in scenarios with a low traffic volume (Figure 2). Even when a radio range of 1km is used, the probability for the realization of 5 hops falls significantly below 20%. Thus, for the realization of Fleetnet multihop communications it is desireable that the radio system at least provides a radio range of 1km. Regulatory issues. In order to find market acceptance perhaps the most important criterion is the availability of an unlicensed frequency band. Project constraints. Due to cost reasons it is not possible to define a Fleetnet specific air interface. Therefore, Fleetnet has to be based on an existing air interface, which has to be modified according to the Fleetnet requirements. Taking the above requirements into account, we have evaluated a number of wireless systems: UMTS Terrestrial Radio Access with Time Division Duplexing (UTRA-TDD) [1], IEEE 802.11, HiperLAN\2, a Bosch warning system, and a radar-based system of DaimlerChrysler. UTRA-TDD has been selected the most promising target system for reasons outlined below. The Bosch warning system and the radar technology will be further investigated for providing the safety-related aspects of an inter-vehicle communication system. UTRA TDD offers high flexibility with respect to asymmetric data flows, allows the communication over large distances and supports high velocities. Another important argument for the usage of UTRA TDD as a basis for Fleetnet is the availability of an exclusive unlicensed frequency band in Europe (2010 – 2020 MHz) that offers two completely separate operating channels. Furthermore, it allows a high granularity for data transmission owing to its CDMA component. However, due to the cellular architecture of UTRA TDD a new ad hoc mode for mobile nodes has to be developed within the Fleetnet project. Due to space limitations we refer the reader for DLC issues to the companion paper [3] in the same volume. Alternative air interfaces for ad hoc networking like IEEE 802.11 or HIPERLAN/2 do not support the required large communication distances and high velocities.

Figure 1. Probability of multi-hop range for high traffic

density highway scenario (2x2 lanes, penetration 10%, average velocity 125km/h, average distance between two vehicles 69m,

between two Fleetnet nodes 174m).

Figure 2. Probability of multi-hop range for low traffic density

highway scenario (2x2 lanes, penetration 10%, average velocity 125km/h, average distance between two vehicles

208m, between two Fleetnet nodes 521m). Furthermore, 802.11 does not yet support quality of service. Another drawback for IEEE 802.11 is the use of ISM bands that are shared, e.g., with Bluetooth devices also present in a vehicle. Nevertheless, we will use IEEE 802.11b for first trials, i.e., as long as the Fleetnet ad hoc version of UTRA-TDD is in implementation stage.

5. POSITION-BASED ROUTING Adaptivity w.r.t. network topology and scalability represent the competing aspects and key challenges for Fleetnet routing because of the high relative speeds and large number of nodes involved. Since future cars will be equipped with an on-board positioning system like a GPS receiver, routing in Fleetnet will be based on position-based routing that shows advantages over purely topology-based methods with respect to adaptivity and scalability. In position-based routing a node is addressed by a unique identifier (e.g. IP address) and its current position (e.g. GPS coordinate). In order to forward a packet that contains the destination position, a router only has to be aware of its own position as well as of the positions of its one-hop neighbors. The router simply forwards the packet to a node closer to the

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destination than itself. Several greedy strategies have been pro-posed in the literature, see, e.g., [7]. If there is no neighboring node closer to the destination, the router has to employ a recovery strategy to route around such a ‘gap’. The key feature of position-based routing is that neither route setup nor route maintenance as in the case of topology-based routing approaches are required. In contrast to topology-based routing, the decision for a route is done on-the-fly: no hop-by-hop chain of routers has to be fixed before the packet is sent. These benefits do not come for free: as a prerequisite for position-based routing, a system for dissemination/management of position information is needed. While the basic ideas of position-based routing have been known since the 1960’s and recent work has extended position-based forwarding strategies, there are several routing-related research efforts required to make a ‘Fleetnet’ operational. We have identified the following items: Location Service. Methods like GLS [4], which use each node as a location server for some nodes (load balancing) and spread the location servers for a node ‘logarithmically’ with the distance to the node, appear to be an interesting proposal. However, GLS shows a lack of adaptivity due to the fixed partitioning of the network’s area. In addition, it has to be shown whether GLS is actually able to support high dynamics. We decided to investigate also probabilistic approaches where each nodes selects its position servers following a ‘density constraint’ that assures that position requests for the nodes can be answered by a server ‘close’ to a requesting node with high probability. Recovery strategies. Several strategies have been proposed in the literature. However, it remains to be shown whether the costs involved with these strategies really justify the benefits or whether some simple timeout-based approaches without recovery strategies lead to results as achieved with recovery strategies. Vehicle movement patterns. Position-based routing approaches have to be checked for typical vehicle traffic scenarios. In highway scenarios the greedy forwarding options are essentially restricted to two directions. Nevertheless, oncoming traffic, junctions, and neighboring roads provide for some challenge. Digital maps and navigation systems. Digital maps and navigation systems can support routing decisions. Although digital maps are not considered as a mandatory system of a Fleetnet node, the routing protocols should include such data in the routing decisions if available.

6. INTERNET INTEGRATION Fleetnet as a network of vehicles should be integrated to the Internet in order to support applications that rely on information obtained from the Web. However, providing Internet access to a vehicle’s passengers is not the whole story. Within a network of cars where each node is generating information and is collecting information from its neighboring nodes and its geographical surroundings, each car becomes a server capable to provide up-to-date information, e.g., on traffic status, as a service to Fleetnet clients as well as to Internet clients. Internet integration of Fleetnet is based on a gateway architecture. We follow the approach not to use a managed infrastructure of some specific type of access points but to allow a gateway function to be provided by an arbitrary Fleetnet node as a service

to another Fleetnet node within reach. Assuming a sparse density of gateways in an early stage of Fleetnet deployment or in rural regions later on, connectivity to the Internet will be rather short living, i.e., it can not be assumed that a sufficient number of Fleetnet gateways will be in reach even when using multi-hop techniques in order to establish a connection to some distant gateway while on the move. Thus, Internet integration will rely basically on efficient caching, hot-spot communication techniques, protocols optimized for bulk data transfer, and agent-based approaches. An agent based approach allows for communications with Internet servers that do not tolerate a disruption of active connections or, to a limited degree, for interactive applications such as Web browsing despite the fact that a Fleetnet node might be without range of a gateway for quite a long time. In this case, a user or application agent is placed on a gateway when driving by. This agent acts as a user proxy until it is contacted again. When contacted, the agent transfers itself, including any collected data and state information, back to the requesting Fleetnet node.

7. SUMMARY We have presented a description of the Fleetnet project by reporting requirements, design decisions, and challenges of such an inter-vehicle ad hoc network. In particular, we have indicated the importance of a radio coverage area of at least 1km and motivated the choice of UTRA TDD as radio hardware. Futhermore, we outlined challenges involved with position-based routing and showed the relation to ‘infostation’ concepts for Internet integration. For more information see www.fleetnet.de.

8. ACKNOWLEDGMENTS We like to thank all our Fleetnet partners for their ideas and input, in particular Walter Franz, Rüdiger Halfmann, and Martin Mauve.

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[3] Lott, M., Halfmann, R., Schulz, E., Radimirsch, M., MAC and RRM for ad hoc networks based on UTRA TDD, Proc. MobiHoc 2001, Long Beach, Oct. 2001.

[4] Morris, R., et al., A scalable ad hoc wireless network system, Proc. 9th ACM SIGOPS, Kolding, Denmark, Sept. 2000.

[5] Nagel, K., Schreckenberg, M., A cellular automaton model for freeway traffic, J. Physique I2, 2221, 1992.

[6] Navas, J.C., Imielinski, T., Geographic addressing and routing, Proc. MobiCom’97, Sept. 1997.

[7] Takagi, H., Kleinrock, L., Optimal transmission ranges for randomly distributed packet radio terminals, IEEE Trans. on Comm., 32 (3):246-257, March 1984.

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