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( This is the English version of ' De resultaten' )

In February 2010 various experiments were performed on the A270 highway between Helmond and Eindhoven. The aim of the experiments was to demonstrate the potential of cooperative systems intended to improve the traffic flow on highways. These experiments show that cooperative systems can help reduce phantom traffic jams.


… which technology

The drivers of the cars in the right-hand lane are assisted by an advisory system. This system consists of a number of parts.
  1. A MobilEye camera from Clifford that determines the relative position and relative speed of the car immediately ahead.
  2. Wireless communication to receive the position, speed and acceleration of the five cars ahead. This enables a more rapid response to the braking actions of the cars ahead.
  3. A TomTom to determine the vehicle’s own position, speed and acceleration. The TomTom also serves as the human-machine interface that tells the driver the vehicle’s ideal acceleration.
  4. A computer with ‘smart’ TNO software that combines the information from the various systems and ultimately determines an ideal acceleration for the vehicle. This acceleration is communicated to the driver by means of the TomTom. The driver should adhere as closely as possible to this ideal acceleration.

… location

The experiments take place on the A270 highway between Helmond and Eindhoven. The decision to perform these experiments on the public highway was a deliberate one. It would show everyone that the use of techniques of this kind is not location-dependent. The highway is completely closed to other traffic on three Sundays. This is to prevent other drivers with non-equipped vehicles from joining in the experiments, which would reduce the safety of the participants.

Fig. 1: Test locatie A270 tussen Helmond en Eindhoven (bron: Google Maps).

Fig. 1: Test locatie A270 tussen Helmond en Eindhoven (bron: Google Maps).

… how we measure the effects

For the experiments on the A270 measuring systems are installed in the vehicles and set up along the route. This makes it possible to accurately measure and compare the effects of driving behaviour with and without the advisory system.

Along the A270 highway 20 video cameras are set up. They track the vehicles closely over a distance of two kilometres. During and directly after the experiments, the TNO Video-Based Monitoring systeem (VBM). This system is able to track vehicles and its various cameras measure continuously the speeds and distances between vehicles. In the film below, an overview is provided of the 20 consecutively placed cameras during an experiment.

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In addition, data is locally collected from the vehicles themselves. This data is used to validate the VBM data. This data also provides information about the position, speed and acceleration of the individual vehicles travelling outside the field of view of the cameras.

… how we create the shockwaves

Two equal lines of 47 vehicles are set up. They follow the car at the head of their line, the pace car, as closely as possible. The vehicles drive at a speed of 100 km/h and pass the serried cameras. After a certain time, the pace car brakes hard to reduce its speed to, say, 30 km/h. The vehicle behind responds as if an incident is occurring in front of it, necessitating its braking, see camera 10 in the film above. A number of seconds after the braking action, the pace car accelerates back to 100 km/h, see camera 12. The shock caused by this action is clearly evident among the braking cars following. Also clearly evident is that the effect of the shock lasts some time because the vehicles take longer to accelerate than they do to brake. This is consistent with the Japanese film in which a shockwave is shown
A range of braking actions is used to create an optimal shockwave.

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To determine the improvement in traffic flow, four aspects were analysed, namely:
  1. Traffic intensity;
  2. Finish line;
  3. Density;
  4. Time headway.
Below, the following film is used to explain each aspect in detail.

The film shows a scenario in which the group of vehicles fitted with the advisory system (grey) and the reference group (red) are visible. The pace car travelling upfront is emphasised by means of the colour blue and a circle. The pace car performs two braking actions, which result ultimately in a shockwave that travels through the following vehicles.

  1. Traffic intensity
    The traffic intensity is the number of vehicles that travels over a section of road per hour. An improvement in the traffic intensity means that in total more vehicles can travel over that section of highway, thereby increasing traffic flow. On average, the traffic intensity of the group of vehicles with communication is 12% higher than in the original situation. There are even spikes of up to 25%. Thus, sizeable differences are evident in the area of traffic intensity. At present, research is continuing into how we can further increase this traffic intensity.
  2. Finish line
    As well as the traffic intensity, a finish line scenario was also analysed. An imaginary finish line was positioned alongside the last camera. Level with this camera the advantage of the group of vehicles with advisory system was determined compared to the reference group (the group of vehicles without the system). Averaged out across all three trips, the equipped group achieved an advantage of more than three vehicles at the last camera. Once again, there were spikes of up to seven vehicles’ advantage among the vehicles equipped with communication.
  3. Density
    The traffic density is the number of vehicles per kilometre per lane. The density is determined by the distance between two vehicles, otherwise referred to as the distance headway, maintained by drivers. The closer vehicles drive to one another, the higher the traffic density.

    Density and traffic intensity depend greatly on the driving speed; at higher speeds drivers will be inclined to increase their distance headway. This has the effect of reducing the density of the group of vehicles. When the weight of traffic increases, drivers are inclined to drive closer together and their speed necessarily decreases. Figure 2 shows the average density compared to the average speed for all experiments.

  4. Fig. 2: Gemiddelde snelheid ten opzichte van gemiddelde dichtheid voor alle experimenten.

    The speeds in the experiments are determined largely by the organisation’s pace car that initiates the breaking actions. Accordingly, the average speeds of the two lanes are more or less the same in the same experiments. Figure 2 shows that at the same speeds, the group of vehicles equipped with instruments (black) has a higher average density on each occasion than the reference group (grey). This is not because the equipped vehicles are driving closer together since the initial distance headways are almost the same at the start of each experiment. This difference arises as the equipped vehicles create smaller gaps as they accelerate out of the shocks. In a number of scenarios the reference group is almost equally as good as the group of vehicles with communication, but this is the case only incidentally. The instrumentation helps the drivers to maintain the correct distance headway at all times.
  5. Time headway
    As the last parameter for mobility, the time headway was also analysed. The time headway is the time that elapses between the passages of two consecutive cars past a measurement point along the route. The time headway is determined by the distance maintained by a driver from the car in front, and the driving speed. In the histogram below, the time headway is defined for all experiments.

Fig. 3: Histogram van de volgtijd voor alle experimenten.

It is clearly evident in the above histogram that the time headway of the equipped group of vehicles (black) shows a much narrower distribution than that of the reference group (grey). The reference group shows time headways that are representative of the time headways achieved by these drivers in everyday traffic situations. Here, a wider distribution is evident. The average time headway of the reference group is greater than that of the group of vehicles with communication. Once again, the explanation for this lies in the fact that the cars drive up too closely to the car ahead as they approach the tail end of a traffic jam and they accelerate too slowly out of the traffic jam. This gives the reference group a lower average density, which in turn is consistent with the figure in which average speed is plotted against average density..

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It can be concluded from the analysis of the above aspects that the technology that was demonstrated can significantly improve traffic flow. A vehicle with an advisory system helps the driver to approach a traffic jam less fast, and to accelerate away from a traffic jam more quickly. In the experiments an improvement averaging 12% was realised in the traffic flow, rising to a maximum of 25%.

Potential improvement of Dutch traffic jams

The problem of traffic jams costs the Netherlands a total of some 4 billion euros each year. At present 80% of the traffic jam misery is attributable to a capacity shortage on the Dutch highways. Phantom traffic jams are a consequence of the capacity shortage. When capacity is low, vehicles are driving closer together than is actually safe. When a car driver decides to brake, the car behind brakes harder, creating a shockwave/phantom traffic jam. In the Netherlands 25% of the traffic jam misery is caused by phantom traffic jams. The solution offered here, in combination with the other solutions we are currently devising, has the potential to halve the traffic jam misery created by phantom traffic jams. This means that the total traffic jam misery can be reduced by 12.5%. This reduction is consistent with a saving of roughly 500 million euros per year.

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