Scenario analysis for advanced speed support systems

Integrated full-Range Speed Assistance and the congestion assistant

Advanced driver assistance (ADA) systems have the potency to improve traffic safety, traffic flow and the environment. In the Netherlands, the main causes of accidents are speed, headway and direction. On highways, 30-40 percent of all accidents are head-tail collisions. Experts suggest that something revolutionary has to be done if further decrease of the number of casualties in traffic is wanted. According to accident statistics speed and headway are the two most important factors for traffic safety. During the last years, these figures initiated numerous research projects with a focus on ADA system that assist the driver in their longitudinal driving task, mostly involving the vehicle’s speed.

In the following sections the scope of the research will be explained on the basis of an explanation of Integrated full-Range Speed Assistance and the congestion assistant. The last sections discuss the position of the research and the research objective.

Integrated full-Range Speed Assistance (IRSA)

This research is part of the IRSA sub-project of the SUMMITS project of TNO. The aim of the IRSA subproject is to assist drivers in their longitudinal driving tasks by providing speed advice or speed warnings and cruise control-like functionalities (Versteegt, 2005). Headway advice is added to make sure the IRSA system will smooth traffic flow near merging and weaving locations.

IRSA can be used in different ways, either as a pure advisory system, as a system that partly intervenes in the vehicle controls, or as a controlling system that fully controls the longitudinal speed of the vehicle. The driver determines in which way he will use IRSA by selecting a mode of operation of the system. Basically, the only difference between the advisory and intervening mode and the controlling mode of IRSA is the presence of a driver which ‘distorts’ the optimal desired acceleration computed by the IRSA systems in the controlling mode.

The speed advice and/or warnings IRSA presents to the driver are based on object warning. The object warnings can be communicated via either infrastructure-vehicle (I-V) communication or vehicle-vehicle (V-V) communication. Three of these objects warnings and their aims are shortly summarized below. Other objects are curved road segments, leaving the traffic jam and cruise control-like functionalities.


(Reduced) speed limit zones (figure 1); the primary aim of these warnings is to calmly reduce the traffic speed to prevent the formation of shock waves due to abrupt braking manoeuvres.


Vehicle-based speed warning (figure 2); broadcast messages containing their location and speed when their speed drops below a certain threshold, or when they have to brake hard. The primary aim of this early breaking-like functionality is to increase traffic safety.


Headway advice (figure 3); a recent study showed that the platoon formation caused by introduction of Cooperative Adaptive CC might seriously hamper merging processes at merging or weaving sections. The time headway advice will aim at increasing the gaps between vehicles, to create a smooth merging flow.

Congestion assistant

Besides the IRSA functionalities that were described by TNO, this research also considers the congestion assistant. The congestion assistant is a system that supports the driver in different ways in driving in congested traffic conditions (Van Driel, 2005). Basically, the primary aim of the congestion assistant is similar to that of IRSA; calmly reduce the speed of the traffic flow to prevent the formations of shock waves due to abrupt braking manoeuvres and increase traffic safety. The congestion assistant consists of three functions which will be shortly summarised below.


Congestion warning (figure 4). The driver receives a congestion warning via the display of the congestion assistant. With the first congestion warning the driver will hear a sound signal. At the same time the accompanying icon on the display is lighted. Furthermore the display provides information about the distance (in kilometres) and time (in minutes) up to the tail of the congested part of the road. When the driver drives in the congested part of the road, the display provides information about the length of the congestion. All information is updated every half a kilometre.


Active pedal (figure 5). When the vehicle comes near the congested part of the road, the active pedal is activated. The driver will hear a sound signal and the accompanying icon on the display is lighted. From now on the driver can feel counterpressure on the pedal if, according to the congestion assistant, the vehicle approaches the congested part of the road to fast. However, the driver can ignore the counterpressure by pressing the pedal harder. When the vehicle drives at the right speed, the driver will not feel any counterpressure.


Stop & Go (figure 6). The Stop & Go takes over braking, accelerating and decelerating during driving in the congested part of the road. The systems can also stop automatically and after that accelerate again. The only task of the driver is steering. Before the Stop & Go is activated a voice will make notice of this event. The Stop & Go is activated when the driver hears a signal and the accompanying icon is lighted. At the same time the active accelerator is deactivated. From now on the vehicle will not react when the brake or accelerator are used. When the vehicle approaches the end of the congested part of the road the Stop & Go will be deactivated. Before this happens again a voice will make notice of this event. The Stop & Go is deactivated when the driver hears a sound signal and all icons on the display are doused. From now on the vehicle has to be controlled by the driver.

Market perspective and deployment

One of the work-packages of the SUMMITS-IRSA subproject is ‘market perspective and deployment’ which explorers how applications of IRSA can be implemented on the market. All the stakeholders involved, their positions and interests are identified, and it is examined to what extend the stakeholders’ positions and interests are of influence to the development of the IRSA systems. The final objective is to identify the decisive factors with respect to the implementation of IRSA systems. Although the advantages and disadvantages of ADA systems are mostly known, the systems are still not widely implemented. The main research question of this work-package is why ADA systems are not implemented within a certain time dimension.

Research objective and approach

In summary, this research is supportive for the market perspective and deployment work-package of the subproject Integrated full-Range Speed Assistance of the SUMMITS project of TNO. Therefore this research focuses only on one category of ADA systems, namely advanced speed support systems defined as IRSA and the Congestion assistant. The aim is to identify factors that influence the development and implementation of advanced speed support systems, formulate possible deployment scenarios and determine the costs and benefits for the stakeholders involved. The main objective of the research is to find relations between the factors of influence, the stakeholders’ positions and the system variants, and process this information in a ‘scenario model’.

The first part of the research involves interviews with stakeholders and experts in combination with a literature review in order to identify the most critical factors with respect to the implementation of advanced speed support systems. On the basis of these results in combination with results form previous scenario studies, variables for the scenario model will to be identified. First, the variables will be used for making causal relation diagrams or decision trees of the deployment process of advanced driver assistance system, after which the diagrams or trees will be converted into a scenario model. Eventually, it is expected that the scenario model will provide insights in the costs and benefits of possible deployment scenarios for stakeholders. Finally, the scenario model will be calibrated on the basis of predefined hypothesis and if time allows, the model will be validated by discussing the results with stakeholders and experts.


Driel, C.J.G. van (2005), Werking van de Fileassistent, TNO Rijsimulatorstudie mei 2005, Soesterberg

Versteegt, E. (2005), Specifications of IRSA (the meta-model), SUMMITS-IRSA WP1, TNO Report 2005-20, Delft