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Multi-Modal Simulation-Based Planning For Pedestrians


Abstract and Figures

In this contribution Strasbourg's plan piéton will briefly be summarized and as a part of it the traffic situation around the central bridge Pont Kuss will be introduced. At Pont Kuss a number of safety and convenience issues in pedestrian traffic are reported. This is the motivation for a multi-modal microscopic simulation project which assesses measures to improve the situation for pedestrians. The assessment includes both: benefits for pedestrian and potential drawbacks for vehicular traffic. It will be shown in detail that clear benefits for pedestrians and for public transport are opposed by only small – if at all – drawbacks for vehicular traffic. It is concluded that multi-modal micro-simulation is a powerful tool to handle all traffic modes with equal care and equal rights in the planning process and that it is at the same time a powerful tool to produce material for communication with the public.
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T.Kretz, F. Reutenauer, and F. Schubert 1
Author 1: Tobias Kretz
Author 2: Frédéric Reutenauer
Author 3: Florian Schubert
Affiliation: PTV Group
Email: {Firstname.Surname}
Address Author 1: Haid-und-Neu-Straße 15, D-76131 Karlsruhe, Germany
Address Authors 2 and 3: 14 rue du Général Gouraud, F-67000 Strasbourg, France
Phone Author 1: +49 721 96 51-7280
Phone Authors 2 and 3: +33 (0)3 9022 1261
Fax: +49 721 96 51-693
In this contribution Strasbourg’s plan piéton will briefly be summarized and as a part of it the
traffic situation around the central bridge Pont Kuss will be introduced. At Pont Kuss a number of safety
and convenience issues in pedestrian traffic are reported. This is the motivation for a multi-modal
microscopic simulation project which assesses measures to improve the situation for pedestrians. The
assessment includes both: benefits for pedestrian and potential drawbacks for vehicular traffic. It will be
shown in detail that clear benefits for pedestrians and for public transport are opposed by only small if
at all drawbacks for vehicular traffic. It is concluded that multi-modal micro-simulation is a powerful
tool to handle all traffic modes with equal care and equal rights in the planning process and that it is at the
same time a powerful tool to produce material for communication with the public.
Many Old Towns predominantly in, but not limited to Europe have two properties in
common: their narrow street network and attractiveness for local population and tourists alike. In the Old
Towns traffic and mobility infrastructure and popular living spaces are most closely intermingled and
therefore also in conflict.
Pedestrians should feel comfortable in these areas. To formulate it as a political position: the
desires, needs and rights of citizens in traffic must not depend on their travel mode choice. However,
there is also a more tangible reason: city centers and particularly Old Towns have a considerable
economic (touristic) potential which can only be fully realized, if vehicular traffic is not pre-dominant.
On the contrary and particularly in the face of an aging population motorized traffic has to be
granted a minimum access. Delivery services might come to mind first, but it is also important to consider
people with reduced mobility and especially with difficulties to walk and keep their balance. For them
being taken somewhere with a car can be the by far easiest way or even the only chance to go somewhere.
However, once motorized access to some location is granted, typically there are many good reasons to
extend the accessibility with motorized traffic further and further. As a consequence planners have to
Multi-Modal Simulation-Based Planning for Pedestrians 2
perform a balancing act between both contrary objectives to maintain the city’s character livable and as a
living space.
In this work it is argued that this can only or at least most easily be achieved when all modes
of traffic pedestrians, cyclists, motorized individual traffic, and public transport are planned at the
same level of detail, with the same visibility and in this way are granted the same level of awareness.
Doing on the contrary a micro-simulation with second-wise signal plan optimization for vehicular
traffic and plan for pedestrians with a simple spread sheet will often disadvantage pedestrians in aspects
which may seem minor at first. It may then, however, happen that pedestrian lights regulating a crossing
to a tram platform always show red when a tram stops. As a result pedestrians face the alternative to miss
the bus or cross at red. More examples of traffic organization which may result from the approach is
described below. Equal awareness for all modes of mobility is automatically guaranteed, when all modes
are integrated in the same planning tool. Such a planning approach is demonstrated here along a concrete
planning example.
Planning for pedestrians and cyclists in some aspects is simpler than planning for vehicular
traffic. For example usually all pedestrians and cyclists waiting at a traffic light can pass a junction within
one green signal phase, no matter how short the phase is. For vehicles this is not the case. Sometimes
drivers have to wait three, four or even more cycles before they can pass. For such reasons elaborate
methods for the planning of vehicular traffic in cities have been developed and are in perpetual use. With
these tools often the vast majority of awareness and working hours are invested in vehicular traffic with
the implicit assumption that cyclists and especially pedestrians always somehow will make their way.
As a consequence pedestrians do not receive proper attention during the planning process and
thus potential problems are more likely missed and pedestrians therefore are disadvantaged.
The Old Towns may most clearly show the necessity for integrated and balanced planning, but
considering the rapid urbanization process which is currently going on (United Nations 2012) it becomes
clear that integrated planning is desirable for larger if not the whole urban area for the sake of giving
equal rights to pedestrians and by that motivate and promote walking, the most space-efficient way of
movement. In this way the Old Towns become trendsetters and point to the future of city and traffic
planning to create safe and livable city streets.
Early in 2012 the city of Strasbourg has announced a ten years (2011 2020) plan which intends
to improve the situation of pedestrians (Communauté Urbaine de Strasbourg 2012) (Conseil Municipal de
Strasbourg 2012) (Chabrol und Rouiller 2012). As motivation for this Plan Piéton ecological reasons are
mentioned, economic interests (see above), freedom and autonomy, and public health (countering the ever
more prevailing obesity), but also and particularly emphasized a civic interest: counteracting “mutual
The plan piéton on a strategic level encompasses all city quarters (see FIGURE 1) and breaks
this down stepwise to smaller areas (see FIGURE 2) for a detailed analysis.
T.Kretz, F. Reutenauer, and F. Schubert 3
FIGURE 1: Major Pedestrian Network (Réseau Piéton Magistral) in Strasbourg with a three-level assessment of the
current suitability for pedestrian needs for each link. Source: (Communauté Urbaine de Strasbourg 2012, p. 47).
Translation of legend: Level of service along the links:
[red] INSUFFICIANT: less than 50% of space for pedestrians AND low quality atmosphere
[yellow] INTERMEDIATE: less than 50% of space for pedestrians OR low quality atmosphere
[green] SATISFYING: more than 50% of space for pedestrians AND high quality atmosphere.
Centers Passage to cross Traffic node to cross
Multi-Modal Simulation-Based Planning for Pedestrians 4
From the analysis ten fields of action are deduced:
1) Promote (the relevance) of walking.
2) Redistribute the street space in favor of pedestrians.
3) Reduce conflicts between pedestrian and bike traffic.
4) Apply instruments of city and regional planning to pedestrian traffic to enhance the
pedestrian network.
5) Assign at least 1% of the budget of any major project to pedestrian issues.
6) Improve ways to schools and promote walking to school (Pedibus).
7) Reduce separating impact of arterials.
8) Arrange road nodes pedestrian-friendly.
9) Create new pedestrian links along and across waters to close gaps in the pedestrian network.
10) Create a Major Pedestrian Network (Réseau Piéton Magistral, FIGURE 1)
FIGURE 2: Zoom to city center. Red dots mark areas of insufficient level of quality for pedestrian needs. The red square
marked with (1) is Pont Kuss. Source: (Communauté Urbaine de Strasbourg 2012, p. 48).
Translation of legend: Zoom of sector Station-Etoile-Neudorf
[blue dots] Arrangements of satisfactory quality
[red dots] Arrangements of insufficient quality have to be passed
T.Kretz, F. Reutenauer, and F. Schubert 5
It was decided to simulate the traffic (pedestrians, cyclists, motorized individual traffic, and
public transport) around Pont Kuss one of the hotspots microscopically applying PTV Vissim and
Viswalk (Fellendorf und Vortisch 2001) (Kretz, Hengst und Vortisch, Pedestrian Flow at Bottlenecks-
Validation and Calibration of Vissim's Social Force Model of Pedestrian Traffic and its Empirical
Foundations 2008) (Bönisch und Kretz 2009) (Fellendorf und Vortisch 2010) (PTV Group 2011). Micro-
simulation was used to be able to take into account uncertainties from adaptive or acyclic behavior, to
measure travel and waiting times on complete routes and at crossings, to reproduce the current situation,
and to use the 3D output as powerful element in the communication with the public (Laugel und
Reutenauer 2011).
Pont Kuss is a bridge over the Ill connecting Strasbourg’s main station and its Old Town, which
is entirely surrounded by the river Ill, see FIGURE 3. As such Pont Kuss is heavily frequented during
rush hour by pedestrians. A count which stood at the beginning of the project gave a number of 1,850
pedestrians per hour (see FIGURE 4) who share two sidewalks with each having a width of short to 2
meter while on the contrary for counted 250 vehicles per hour there is two lanes with a width of 3.5 m
each, which implies that even if all cars were fully occupied a citizen using a car would be granted more
public space than a walking citizen. This makes the location appear to be a potential case for number 2 of
the previously mentioned ten fields of action. However, does this unbalanced distribution of public space
really cause problems for pedestrians? And if so, can these be resolved by redistributing space and with
other measures? And if so how severe are the drawbacks for motorized individual traffic and what is the
impact for public transport?
The second and third question later will be answered using micro-simulation. The first question,
however, is a case for a field study which was done together with the aforementioned counts.
FIGURE 3: The location of the project with traffic modes (red: public transport, yellow: motorized individual, green:
pedestrians and cyclists). The main station is to the West (left), the Old Town to the East (right). See also .
Multi-Modal Simulation-Based Planning for Pedestrians 6
FIGURE 4: Volume counts of pedestrians (green) and motorized vehicles (red) during peak hour. The sum of 1849
pedestrians per hour who cross the bridge is not equally distributed but more use the northern side.
Two major issues were identified. The first is that pedestrians on the northern side of the bridge
often step on the adjacent road lane when evading opposing or overtaking slower pedestrians as the width
of the sidewalk on the northern side of the bridge is not sufficient for the demand, see FIGURE 5. The
asymmetric utilization of the bridge is a consequence of a tram stop (“Alt Winmärik”) which poses a
major origin and destination for pedestrians on the north-eastern side. Second the space on the sidewalk
on the southern side at the road to the main station in the west is occupied by cafes. This makes
pedestrians change to the northern side. See FIGURE 6.
The causes for the asymmetric usage cannot be eliminated, but it would be possible to increase
the width of the sidewalk on the northern side by assigning one of the road lanes to the pedestrians. The
benefit of that measure for pedestrians is obvious and the impact for vehicular traffic was investigated
with simulations (see below).
FIGURE 5: Pedestrians inundating the road, compare (Yuan, Giese und Lew 2009). This can even be observed off-peak,
see .
T.Kretz, F. Reutenauer, and F. Schubert 7
FIGURE 6: Asymmetric pedestrian usage of the bridge and its causes. The arrows in the left image indicate the position
of the photographer for the photos on the right side. With the color of arrows and image frames the photos can be
assigned to positions.
The second issue which was identified is that pedestrians on the large crossing on the western
side do not follow the intended path, see FIGURE 7. A major, albeit not necessarily the only, motivation
for this behavior was found in the simulations of the current state: the current traffic signalization is such
that if a pedestrian obeys the intended path and red light signals he or she will have to wait twice rather
long at both of the signals. The implicit assumption is that if a signalization was put in place that is more
in favor of pedestrians the level of obedience to the intended path would increase.
As a consequence of the identified issues three measures were considered and investigated and
assessed with micro-simulation: 1) reassigning the northern vehicle lane on the bridge to the northern
sidewalk, 2) extending pedestrian spaces on the western crossing into what so far is space for vehicles,
and 3) modifying the signal programs in favor of pedestrians.
FIGURE 7: Pedestrians short-cutting. This phenomenon also occurs off-peak: .
Multi-Modal Simulation-Based Planning for Pedestrians 8
Simulation models of the current situation and two alternative scenarios have been created, see
FIGURE 8. The simulation results showed that dwell times of pedestrians at all crossings would
significantly drop in both alternative scenarios, see FIGURE 9. At the same time no significant drawbacks
for vehicular traffic could be found as can be seen in FIGURE 10 or that drawbacks are balanced with
gains, see FIGURE 11. Finally it was found that the travel time of some PT lines reduces significantly in
the alternative scenarios, see FIGURE 12.
FIGURE 8: Current situation (left, “Voirie de’l etat actuel”) and two alternative scenarios (center and right). The two
alternatives differ in their signal programs (“”feu”) and in that in the second alternative scenario there is a right turning
lane for the vehicles leaving the bridge (“2 voies”). An animation of a simulation run of the current state can be seen here: . The 3D visualization of the buildings of the environment is one single 3D model which
has been loaded as background into the simulation software. This is not a requirement for the simulation.
As a side notice: initially it was also discussed if traffic could work out without traffic lights in a
kind of shared space configuration (see FIGURE 13), but this proposition did not make it to the point of
being modeled in the simulation software which would have been a challenge up to date.
FIGURE 9: Simulation results: pedestrian waiting times at signals in comparison for the three scenarios as shown in
T.Kretz, F. Reutenauer, and F. Schubert 9
FIGURE 10: Result from an assignment computation with PTV Visum: speed-based LOS for vehicular traffic for the
three scenarios as shown in FIGURE 8.
FIGURE 11: Simulation result: waiting times of motorized vehicles (private and PT) at red signals. Each of the two
diagrams shows a comparison for the three scenarios of FIGURE 8.
Multi-Modal Simulation-Based Planning for Pedestrians 10
FIGURE 12: Simulation result: comparison of travel times of the south-bound bus for all three scenarios of FIGURE 8.
FIGURE 13: Initially proposed shared space configuration without traffic lights. This was not followed further nor was it
simulated. Source: (Laugel und Reutenauer 2011).
T.Kretz, F. Reutenauer, and F. Schubert 11
This section provides a technical overview and therefore addresses mainly readers who have
already had contact with the software. A reader not interested in this can directly skip to the conclusions.
A micro-simulation planning tool is well suited to produce almost as a by-product 3D visual
output which allows to easily communicate with the entire interested public, even with people who are
nor engineering-affine. However, such (moving) pictures for a planner often blur what is going on inside.
Therefore let us “deconstruct” the realistic pictures from the animations to the point where the technical
character becomes visible. The first step is to remove the 3D model of the surrounding buildings which is
shown in FIGURE 14.
FIGURE 14: The model with and without 3D model of the surrounding buildings in the same 3D perspective. The 3D
model of the buildings is neither necessary for the simulation nor does it have an impact on the simulation at all.
The next step is to change to a 2D (birds’) perspective. This is done in FIGURE 15.
FIGURE 15: 2D perspective. The left image shows the network elements with the actual dimensions they have, the right
image displays the elements which functionally are essentially one-dimensional (road lanes) to one-dimensional
elements and displays those elements which are functionally two-dimensional (pedestrian areas) as polygons. In this way
from the left to the right image the information is further reduced to the essential one.
So far the reduction steps were generic. The next step is to have a look at tool specific modeling
elements like signals FIGURE 16 and other elements (conflict areas and priority rules) which control the
traffic flow FIGURE 17 as far as the right of way is concerned.
Conflict areas serve to model areas of clear priority. Therefore they are used here to model the
edge of the crossing area. They are quick to be put in place. Yielding drivers (or pedestrians) do not only
consider the next vehicle with priority, but plan for one of a number of gaps in the oncoming flow to pass
the conflict area. If a conflict area cannot be cleared in time by a pedestrian or a driver of the subordinate
direction this can happen for example to pedestrians when they are slowed down surprisingly by many
Multi-Modal Simulation-Based Planning for Pedestrians 12
pedestrians walking in opposite direction the driver or pedestrian with priority realizes this and does not
move inside.
FIGURE 16: Left: zoom of the network view on to the western crossing. Links are displayed blue, connectors (connecting
links) magenta, signal barriers red. Right: signal control programs which activate and deactivate the signal barriers
during a simulation.
FIGURE 17: Left: Conflict areas. Right: Priority rules.
Priority rules can be used to model crossing points with less strictly defined priority, so situations
which follow more a “first come first serve” rule. They require more effort to be modeled, but allow more
flexible calibration. Yielding drivers or pedestrians only consider the next upstream conflicting vehicle or
pedestrian and not subsequent gaps. Drivers or pedestrians with priority cannot realize if the exclusive
area is occupied by a vehicle or pedestrian of the subordinate direction. Thus priority rules model a
simpler behavior than conflict areas.
The model which computes the vehicle movement time step by time step is an extended version
of (Wiedemann 1974). The according pedestrian simulation model is a combination of variants of the
Social Force Model as discussed in (Johansson, Helbing und Shukla 2007) with extensions as for example
described in (Kretz, Große, et al. 2011).
In this contribution Strasbourg’s plan piéton was briefly summarized and as a part of it the traffic
situation around the central Pont Kuss was introduced. At Pont Kuss a number of safety and convenience
issues in pedestrian traffic have been found. This was the motivation for a multi-modal microscopic
simulation project which along the lines of the plan piéton assessed measures to improve the situation
for pedestrians. The assessment included both: benefits for pedestrian and potential drawbacks for
T.Kretz, F. Reutenauer, and F. Schubert 13
vehicular traffic. It could be shown in detail that clear benefits for pedestrians and for public transport are
opposed by only small if at all drawbacks for vehicular traffic. As a result in fall 2012 the
implementation of most of the suggested changes was commissioned.
The combination of detailed numerical and intuitive 3D output is helpful in a number of aspects:
first it makes for a precise planning base which at the same time has a high chance to not only analyze
known difficult issues, but also point to simpler issues which have simply been missed out at any
of the involved traffic modes. Second, the 3D output is a great resource for communication with the
public and especially those parts of the public whose expertise is far from engineering logic. Everyone
can be given an idea of what is intended. Third, the detailed numerical output is a heavy argument in
experts’ and even more so public discussion to meet objections derived from false believes ungrounded
fears or mere ideology. In this particular case one might think for example of a line of argumentation
coming from a fundamental pro-car lifestyle or even identity.
Bönisch, C., und T. Kretz. „Simulation of Pedestrians Crossing a Street.“ Traffic and Granular Flow '09.
Shanghai, 2009.
Chabrol, A., und A. Rouiller. Rue de l’Avenir. 2012.
Communauté Urbaine de Strasbourg. Plan Piéton - 2011>2020. Strasbourg: Communauté Urbaine de
Strasbourg, 2012.
Conseil Municipal de Strasbourg. - Délibération au Conseil Municipal - Strasbourg 'une
ville en marche' ou le plan piéton de la Ville de Strasbourg. 23. Jan 2012.
Fellendorf, M., und P. Vortisch. „Microscopic Traffic Flow Simulator VISSIM.“ In Fundamentals of
Traffic Simulation, von J Barceló, 63-93. Berlin Heidelberg New York: Springer, 2010.
—. „Validation of the microscopic traffic flow model VISSIM in different real-world situations.“ Annual
Meeting TRB . Washington DC: TRB, 2001. 1-9.
Johansson, A., D. Helbing, und P.K. Shukla. „Specification of the social force pedestrian model by
evolutionary adjustment to video tracking data.“ Advances in Complex Systems, 2007: 271-288.
Kretz, T., A. Große, S. Hengst, L. Kautzsch, A. Pohlmann, und P. Vortisch. „Quickest Paths in
Simulations of Pedestrians.“ Advances in Complex Systems, 2011: 733--759.
Kretz, T., S. Hengst, und P. Vortisch. „Pedestrian Flow at Bottlenecks-Validation and Calibration of
Vissim's Social Force Model of Pedestrian Traffic and its Empirical Foundations.“ 8th
International Symposium on Transport Simulation. Surfer's Paradise, Queensland, Australia:
Monash University, 2008. on CD.
Laugel, Y., und F. Reutenauer. „Pont Kuss (Strasbourg), choix de scénarios d'aménagement favorables
aux piétons.“ Simulation dynamique des déplacements - journée technique 2011. Paris, 2011.
PTV Group. PTV Vissim 5.40, user manual. 2011.
United Nations. World Urbanization Prospects, the 2011 Revision . United Nations, 2012.
Wiedemann, R. „Simulation des Straßenverkehrsflusses.“ Schriftenreihe des IfV, 1974.
Yuan, F., K. Giese, und K. Lew. „A Multiclass Dynamic Traffic Assignment Model for Special Events
Management.“ 12th TRB National Transportation Planning Applications Conference. Houston,
Texas: TRB, 2009.
... It is expressed in meters. It is minimum distance between vehicles when overtaking within the lane and keeping the distance to vehicles in the adjacent lanes [7]. ...
... This has encouraged the development of specific pedestrian modules and dedicated pedestrian simulation models (Kretz et al., 2013). Microsimulation modelling of cyclists is by contrast based on driver behaviour and vehicle characteristics, using different parameter distributions (e.g. ...
This paper contributes to debates around improving the modelling of cycles, through an exploratory case study of bus-cycle interactions in London. This case study examines undocumented delays to buses caused by high volumes of cyclists in bus lanes. It has generally been assumed that cyclists do not noticeably delay buses in shared lanes. However, in many contexts where cyclists routinely share bus lanes, cyclist numbers have historically been low. In some such places, bus lanes are now seeing very high volumes of cyclists, far above those previously studied. This may have implications for bus- A nd cycle-journey times, but traditionally traffic modelling has not represented the effects of such interactions well. With some manipulation of parameters taken from models of other cities, the model described here demonstrates that cycles can cause significant delays to buses in shared lanes, at high cycling volumes. These delays are likely to become substantially larger if London's cycling demographic becomes more diverse, because cyclist speeds will decline. Hence bus journey time benefits may derive from separating cycles from buses, where cycle flows are high. The project also suggests that microsimulation modelling software, as typically used, remains problematic for representing cyclists. © 2017 Published with permission by the ICE under the CC-BY license.
... Simulation of pedestrian movement becomes increasingly important to ensure safety for everybody wherever a crowd comes together. Large and dense crowds shape daily urban traffic, not only in areas assigned to walking but also at transfer locations such as train platforms or on shared spaces (Kretz et al., 2013). Thus, pedestrian movement is an integral part of the overall urban transportation problem and adequate modelling of human locomotion in a crowd has become essential to its solution. ...
Pedestrians adjust both speed and stride length when they navigate difficult situations such as tight corners or dense crowds. They try to avoid collisions and to preserve their personal space. State-of-the-art pedestrian motion models automatically reduce speed in dense crowds simply because there is no space where the pedestrians could go. The stride length and its correct adaptation, however, are rarely considered. This leads to artefacts that impact macroscopic observation parameters such as densities in front of bottlenecks and, through this, flow. Hence modelling stride adaptation is important to increase the predictive power of pedestrian models. To achieve this we reformulate the problem as an optimisation problem on a disk around the pedestrian. Each pedestrian seeks the position that is most attractive in a sense of balanced goals between the search for targets, the need for individual space and the need to keep a distance from obstacles. The need for space is modelled according to findings from psychology defining zones around a person that, when invaded, cause unease. The result is a fully automatic adjustment that allows calibration through meaningful social parameters and that gives visually natural results with an excellent fit to measured experimental data.
... It is a natural next question if the empirical results can be reproduced with a simulation model of pedestrian dynamics. We have tried to do so using PTV Viswalk [13][14][15][16] and in a first attempt achieved slightly too small densities and by far a too small flow. This is, however, not a surprise, as we could not expect to have the simulation reproduce results with this special population of participants applying nothing but the default parameters. ...
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Technical Report
Available online at:
PTV Vissim 5.40, user manual
  • Ptv Group
PTV Group. PTV Vissim 5.40, user manual. 2011.
A Multiclass Dynamic Traffic Assignment Model for Special Events Management
  • F Yuan
  • K Giese
  • Und K Lew
Yuan, F., K. Giese, und K. Lew. "A Multiclass Dynamic Traffic Assignment Model for Special Events Management." 12th TRB National Transportation Planning Applications Conference. Houston, Texas: TRB, 2009.