Pedestrian Simulation for Urban Traffic Scenarios

Figure 2. Pedestrian road crossing behavior.
Figure 3. Pedestrian way: Measures and lanes.
without right of way χ in � m · s −1� :
α = N 1.75
0.5 (1.33, 0.25) (2)
β = N 1.5·α
α (1.5, 0.5) (3)
χ = N 2·α
α (1.8, 0.5) (4)
These values correspond to the literature review given in [11].
Assuming that smaller interactions between pedestrians on
sidewalks average in time and space, pedestrians move linearly
without interaction with other pedestrians. For determining
ECT , pedestrians are modeled with a base AF of
AF = N +3
−3 (−0.5, 1.0) (5)
In order to cross a road, pedestrian p calculates ECT and enters
the road, when no road user passes the current road position
of p, before p leaves the road adding a safety distance
of two seconds, as shown in Figure 2. In this example, the
pedestrian will not cross the road, because the car on the right
side will reach its position before the crossing is done with
the safety distance of 2s.
Crossing a road is done at right angle to the course of the
EI. This is also done in linear movement, because it is unlikely
that interaction with other pedestrians will occur in
these situations. When a pedestrian has started crossing the
road, he will not abort it. When ECT was too low (e.g., because
of a negative AF), road users need to brake in order to
avoid an accident. In these cases, cars are interfered by pedestrians.
4.3 Pedestrian Interaction at Crossings
Crossings are the places where pedestrians may interact
with each other, e.g., because several pedestrians may use a
traffic light at once. Thus, a microscopic model for pedestrian
movement is used to model pedestrian ways, which are placed
at NIs. Figure 3 shows the composition of pedestrian ways.
1 function update(iteration)
2 if iteration �= iterationOld then
3 iterationOld ← iteration;
4 checkQueue();
5 foreach Pedestrian p do
6 determineUsableLanes())
7 foreach Pedestrian p do
8 chooseLane()
9 foreach Pedestrian p do
10 provideLane()
11 foreach Pedestrian p do
12 calcV()
13 foreach Pedestrian p do
14 f .pos ← f .pos + v;
15 if f .pos ≥ l then
16 f .crossingNI←false;
17 remove(p);
Figure 4. update()-method of way-objects.
The pedestrian way is separated into w lanes (width of the
crossing) and has a length of l (width of the EI to cross).
The proposed model is a space continuous adaptation of the
cellular automaton based model, described in [1], permitting
individual pedestrian velocities, that are not covered by [1].
The model reproduces the interaction between pedestrians,
walking in both directions on the way object. The basic algorithm
is shown in Figure 4.
Whenever a pedestrian p is on a way object w, it forwards
the update call to w. Lines 2 and 3 assure that the way is only
updated once per iteration.
Each pedestrian starting a crossing action on a way chooses
its lane at first. If no free lane is available, one lane will be
chosen randomly and the pedestrian will be put into a queue
for waiting pedestrians. Line 4 checks for pedestrians, waiting
to enter the way and adds them when their lane provides a free
entry position.
Each pedestrian p calculates the magnitude of usable lanes
in the neighborhood N lane of its current lane as shown in
equation 6.
N lane = {p.lane − 1, p.lane, p.lane + 1} ∩ {1,··· ,w} (6)
If possible sidestep positions of different pedestrians interfere
with each other, only one of them may use the corresponding
lane. Due to the avoidance of asynchronisms, the lane choosing
process is divided into an update (line 8) and a provide
(line 10) step.
In line 8, each pedestrian p calculates the gaps g(l) to the
next pedestrian for each lane l ∈ N lane in the direction of