Microscopic modeling and simulation of vehicle parking (systematic review)

Microscopic Modeling & Simulation of Vehicle Parking
Systematic Review
Aboubakr MOUBARAK
High school of technology Fez – MIDLOG Laboratory
Sidi Mohamed ben Abdellah University Fez
Fez, Morocco
Aboubakr.moubarak@usmba.ac.ma
Fouad JAWAB
High school of technology Fez – MIDLOG Laboratory
Sidi Mohamed ben Abdellah University Fez
Fez, Morocco
Fouad.jawab@usmba.ac.ma
Abstract— This article achieves a comprehensive and
detailed presentation of various contributions made by the
scientific community in terms of analysis and understanding of
the negative externalities resulting from the vehicle parking
operation in the urban space such as congestion, accidents,
environmental nuisances, and many others, and this by relying on
microscopic modeling and simulation that analyze the behaviors
of each component of the transportation system individually.
These scientific articles were inventoried based on a
systematic approach in which a set of criteria and filtering steps
were considered during the search, in this paper, we have selected
only the scientific articles indexed in Scopus / Wos and which
have been published during the recent years (between 2010 and
2019) and focus mainly on parking as a subject of research, from
295 articles only 26 met the inclusion criteria and were
summarized in two tables, the first focus on the purpose of the
model and the tools that were used to achieve that goal and the
second table describes the steps of the simulation and where it
was performed. Also, the selected articles have been divided into
6 categories: Urban freight delivery and double parking; Impact
of parking on mobility and congestion, Impact of parking on the
urban pollution, Parking and Road safety, Study of parking
demand. Parking and decision-making,
As a result of this in-depth literature review, we could
understand how parking challenges have been addressed before
based on experiences worldwide and also create a modeling
toolbox that will help us get an idea on the approaches to follow
and the tools to use for each specific parking problematic,
furthermore we were able to situate our project as well as identify
the features that require more study and determine the future
needs in parking modeling.
Keywords — parking modelling, parking simulation, urban
logistics, Systematic literature, Microscopic.
I. INTRODUCTION
Parking management is a key lever for the modal
orientation of urban movement and presents itself as a major
tool for a more sustainable development of the city [1]
However, vehicle parking is sometimes a source of
environmental nuisance and degradation of the citizen's life
quality particularly in dense urban areas where the non-
availability of free parking places significantly affects the
fluidity and conditions of the transport network and increase
the possibility of traffic accidents, this dangerous effects it
causes and the complexity of its different components makes it
a challenging and a first-rank subject for multiple research
laboratories in universities worldwide, and as we also part of
these search laboratories, our contribution via this work is
offering a better understanding of how parking works within the
urban territory and provides a variety of models that study the
different spatial-temporal dimensions of parking on a microscopic
scale.
At present, the literature has several case studies and
experiences on parking modeling and simulation whether in the
macroscopic, mesoscopic or the microscopic level, however, there
is a vacuum in research that gathers and analyzes these studies,
for this reason, we tried to fill this void by providing a systematic
literature review that synthesizes and gives an overview that
focuses more specifically on Microscopic Vehicle Parking
Modeling and Simulation (MVPMS), a fertile field that keeps
growing every day
This paper will not only help researchers create a
comprehensive perception of tools, technologies, and approaches
recently established in the pitch of MVPMS to overcome parking
issues but also provide to the decision-makers, public powers and
different stakeholders a toolbox filled with methodologies to
follow in each specific situation and for each area characteristics.
II. BACKGROUND
An efficient transportation system is essential for the
smooth functioning and prosperity of modern society. it must
respond to four major challenges that are safety, reduction of
consumption, quality of life and reduction of greenhouse gas
emissions., The dilemma is that most of the problems that
cause the deterioration of these major points such as
congestion and priority management in the roadways, can not
be solved by traditional analytical tools because of their
complexity, here it became necessary to rely on advanced
means that allow the study of the entire road system and the
evaluation of different traffic management alternatives to
determine optimal solutions for different scenarios that may
occur in traffic.
Researchers found their stray in this field by relying on
traffic modeling, in fact, there are three key methodologies to
describe and test the occurrences of traffic, Macroscopic,
Mesoscopic and Microscopic simulation [Figure1]

In microscopic models, all the vehicles are individualized
and considered as a system of interacting particles, in fact,
microscopic models aim to simulate the manner a vehicle will
react in its environment and its response in some specific
situations, namely the infrastructure and the vehicles that
surround it in traffic.
Concerning parking, microscopic modeling aims to define
the behavior and decisions that will be made by vehicles during
the parking operation, for example, the moment when there are
no more empty parking spots in the parking lot, is the driver will
opt for the illegal parking? Or change the place? And if there is
a double-parking vehicle on the road, what will be the impact on
the movement of other vehicles? Also, the microscopic
modeling tests the effect of the availability of the parking spaces
on the use of the mean of transport and the planning of travel
activities.
III. THE RESEARCH METHODOLOGY
A. RESEARCH QUESTIONS
In order to identify all published papers and to have
an objective and transparent overview of our topic, we chose
that our article follows a systematic literature review, the latter
is considered as an advanced method that identifies,
selects, evaluates and summarizes primary studies, data and
research results on a specific issue, by applying a very rigorous,
reproducible, protocol-based method to reduce the possibility of
bias. [2] it is also effective for finding gaps in the existing
works, as well as preparing the way for the future researchers
interested by the subject to properly position their work and
contribute effectively to the scientific community.
In this document, we have sought to offer a detailed
systematic review of the various contributions made by the
scientific community in terms of analysis and understanding of
the negative externalities resulting from the vehicle parking
operation in the urban space such as congestion, accidents,
environmental nuisances, and many others by using microscopic
modeling and simulation, In the review, we focus on the
following research questions:
▪ 1st Research question: What are the solutions that have
been developed so far in parking modeling and
simulations?
▪ 2nd Research question: What are the tools, approach and
technologies used to overcome Parking challenges?
In the literature review, it was possible to answer many research
questions, but we chose the answer to these two questions because
of their major role in enabling a more accurate understanding
of the parking phenomenon and provide a road map for other
researchers to re-apply the findings of science in environments
and cities with the same or different characteristics, the purpose of
which is to minimize the consequences of parking and find
sustainable solutions for it.
B. RESEARCH PROCESS.
During the research inventory set of criteria and filtering steps
were considered, this document only includes the scientific
articles indexed in Scopus / Wos and which have been published
during the recent years (between 2010 and 2019) and focus
mainly on parking as a main subject of research, from 295 articles
only 26 met the inclusion criteria [Figure3]
After having identified the articles of the studies, we classified
them in 6 following categories on which our research laboratory
focuses the most:
Fig. 2. Categories of the models
Fig. 1. Traffic modeling scales

In each category there are two tables, the first is interested in
the model used and composed of 5 columns, the first concerns
the discipline in which the model enters, we have selected three
types of discipline, computer science, statistics and mathematics,
the second column contains the name of the article as published
in the scientific journals, the third column is for the year of
publication, the fourth dedicated to the purpose of the article ,
the fifth contains all the used tools either are technological tools
such as gadgets, software..., or statistical/mathematical formulas,
algorithms... and finally the sixth column is for the source of the
paper.
In the other hand, the second table is interested in the
simulation methodology and the steps that have been taken to
achieve the results, this table is composed of five columns, the
first is for the name of the article as published in the scientific
journals, the second presents in detail the simulation steps used in
the article, the third column is dedicated to the simulation
software used, the fourth concerns the simulation place and finally
the fifth is for the source of the paper.
At the end of the literature review, the article presents several
facts and data about the researches that have been inventoried
thing that will contribute to a better understanding, and will help
other researchers to make the right decisions about their future
research in the field.
IV. LITERATURE REVIEW
A. URBAN FREIGHT DELIVERY AND DOUBLE PARKING
The double parking of private or commercial vehicles is an
illegal parking type considered as a phenomenon in which most
urban cities suffer, several studies have shown the size of this
phenomenon in the city's transportation system, for example in
Paris, the half of the delivery/pickup movements of goods were
carried out with double-parking [3], another study in Parma
showed that 47% of heavyweight vehicles and 53% of light
vehicles were in illegal double-parking mode [4], also in Athens
Greece, the result of a study showed that from a total of 50000
vehicles, 8000 were in an illegal double-parking position which
represents 16% of vehicles in an area of 37 Km2 [5] This huge
number of vehicles in an illegal parking position is the main
responsible for the generation of multiple negative externalities,
especially that we are talking about a moving bottleneck and not a
stable one, the thing that can affect the whole traffic system to
create congestion, concentrate pollution in different areas,
increase the travel delays, create vehicle queues, increase the
probability of accidents between vehicles and also between a
vehicle and a pedestrian/jaywalker [Figure4], Increase the fuel
consumption and even the noise pollution is one of the resulting
issues of double parking [6],
Fig. 4. Demonstration of accidents resulting from double parking
All this has made the modeling of this nuisance in all its aspects
a very difficult thing to do, notwithstanding this, many researchers
have found in microscopic modeling the proper solution for
understanding this phenomenon by focusing their studies in the
subject taking into consideration different cases where the features
Fig. 3. The research process

of the roads are different [Figure5], and the area characteristics
are different, to provide all the information to the stakeholders and
the cities decision-makers to deal with this problem and its
consequences and create a better life for citizens of the city,
Below you will find a summary of the contributions of the
different researchers in the field.
TABLE I. URBAN FREIGHT DELIVERY AND DOUBLE PARKING — MODELING APPROACH
Scientific
discipline
Research title Year Objective Tools and approach used
Computer &
system software
Simulation of illegal double
parking: quantifying the traffic
and pollutant impacts
2010
The article presents a study on the effects of
illegal double-parking (congestion, environmental
impacts) in an urban area where this type of
parking is very frequent, this based on a
microscopic simulation model, calibrated and
validated depending on measured traffic
parameters and emission factors.
DRACULA Software
CMEM Software
GPS technologies
Manual and video surveys
[7]
Computer and
system software
Simulation-Based Assessment
of Double-Parking Impacts on
Traffic and Environmental
Conditions
2013
The purpose of this research is to estimate the
impact of double-parked vehicles on the average,
the speed, the delay, and the stopped time on the
traffic and the environment, also the article
evaluates the effects of improvement resulting
from the reduction or elimination of this
phenomenon from the network by using the
microscopic simulation.
TransModeler Software
Stochastic model
Normalized Root Mean Square
Error (NRMSE)
[8]
Computer and
system software
Truck parking in urban areas:
Application of choice
modelling within traffic
microsimulation
2014
This article proposes an innovative microscopic
simulation model capable of measuring the
different dimensions of the truck parking activity
by quantifying the impact of the latter on the road
traffic efficiency in terms of searching time for
parking, the walking time between the parking
spot and the destination and the total travel time.
Econometric discrete choice
model,
Binary logit model,
Google Maps,
Maximum likelihood
estimation,
Paramics traffic simulation
software
Monte Carlo simulation
The cumulative distribution
function
[9]
Computer and
system software
Assessing the impacts of goods
deliveries' double line parking
on the overall traffic under
realistic conditions
2016
The article comes up with a modeling framework
to measure the double-parking impact of delivery
vehicles during customer delivery on the traffic of
an urban artery using microscopic simulation. The
proposed approach is based on a combination of
stochastic traffic states and microscopic freight
demand generation model.
The Rayleigh probability
distribution
LWR (Lighthill-Whitham-
Richards) model
Macroscopic Fundamental
Diagram (MFD)
Stochastic model
[10]
Statistics
Modeling double parking
impacts on urban street
2016
This research aims to study the influence of
double parking and evaluate its negative impact on
the traffic by simulating multiple scenarios
Video recording
M/M/∞ queueing model
Stochastic approach
Google Geocoding API
The GEH Statistic
Root mean square error
[11]
Statistics
Using Structural Equations
Modeling to explore perceived
urban freight deliveries parking
issues
2017
This paper proposes a model that aims to identify
parking problems of urban freight transport and
the associated distribution channels, modes of
delivery, location of commercial establishments
and land use.
Structural Equation Modeling
(SEM)
AMOSTM software
The Bayes Theorem formula
Principal components factor
analysis
The Weighted Least Squares
estimation method
Markov chain Monte Carlo
(MCMC) simulation
Establishment-based freight
survey
[12]
Computer and
system software
Microsimulation Modelling of
the Impacts of Double-Parking
Along an Urban Axis
2018
The present work seeks to evaluate, using
microscopic modeling, the impacts of the double-
parking phenomenon on the fluidity of the traffic
in a passageway characterized by its strong
demand for transport.
AIMSUN software
DRACULA Software
[13]

Computer and
system software
Performance du transport de
marchandises en ville : Cas de
l'implantation des aires de
livraison
2018
The aim of this thesis is to propose a model for
improving the performance of goods transport in
the city by integrating delivery areas that allow a
temporary stop of commercial vehicles to carry
out delivery / removal operations.
Causal analysis
Influence diagram
GRAI grid
Structural Equation Modeling
LISREL method
Partial least squares method
Dynasim software
Exploratory and establishment
surveys
[14]
Computer and
system software
Microscopic Simulation of
Cruising for Parking of Trucks as
a Measure to Manage Freight
Loading Zone
2019
This research aims to enforce Freight Loading Zone
policies based on the parking behavior of commercial
vehicles in order to reduce the negative externalities
caused by the distribution and pick-up movements of
urban merchandise.
Dijkstra algorithm
the Bernoulli’s principle
stochastic approach
boxplot
SymuVia software
Lagrangian coordinates
Wardrop principle
Voronoï diagrams
[15]
TABLE II. URBAN FREIGHT DELIVERY AND DOUBLE PARKING — SIMULATION APPROACH
Research title The simulation approach
Simulation
software
The Area
Simulation of illegal
double parking:
quantifying the traffic
and pollutant impacts
1) Conduct several months of observations and characterize the double illegal parking
by making distributions according to time, location and duration
2) Preparation of the microscopic simulation model (physical geometry, node
location, link width, number of lanes, bus stop locations, parking, the timing of traffic
lights, origin/destination matrix, rotational movements, travel time between nodes,
delays, queue length, saturation rates
3) calibrate the model parameters to reflect the behavior of the Italians drivers;
4) characterize double parking in the DRACULA model based on video surveys
5) create and formulate the illegal dual parking scenarios and simulate the observed
situations;
6) perform an analysis of the results and determine for each scenario a comparison
with the basic scenario the one without the illegal parking. The effects were quantified
in terms of congestion (length of line and capacity) and pollutant emissions.
DRACULA
Notarbartolo
Street,
Palermo,
Italy
[7]
Simulation-Based
Assessment of Double-
Parking Impacts on
Traffic and
Environmental
Conditions
1) Gather data on the traffic volumes, parking maneuvers, double-parking
characteristics (Average, duration, the position in the road, and the intention to double
park) and finally the public transport system characteristics.
2) Estimate the origin-destination matrix for the studied area.
3) Apply the model on the microscopic simulation software TransModeler
4) Create an auxiliary lane for the vehicle that tries to avoid double-parked vehicles
5) Establish the relationship between intention and probability of double-parking,
using a list of tests.
6) Analyze the result and estimate the effects of double-parking on the average speed,
the delay, and the stopped time.
TransModeler
The
municipality
of Athens,
Greece
[8]
Truck parking in urban
areas: Application of
choice modelling within
traffic microsimulation
1) Data gathering: network characteristics (passageways, passageway loading zones,
and loadings bays), parking facility locations and capacities, and truck/private vehicle
demand matrices.
2) Determine the truck trip generation and attraction based on the parking survey.
3) Distribute the IN and OUT points of incoming and outgoing trucks and private
vehicles among the roads
4) Start the simulation on Paramics at time T = 0.
5) Locate vehicles within 250 M of their target destination.
6)Vehicles tracked test each parking lot they get close to until one is selected
7)When a parking lot is selected, its capacity is reduced by 1 place was taken by the
vehicle. Similarly, the capacity of the facility increases by 1 when the vehicles reach
their downtime and leave the facility.
8) The model stops searching for vehicles when they reach their downtime and they
are sent from the parking lot to leave the network.
Paramics
Toronto,
Canada
[9]

Assessing the impacts of
goods deliveries' double
line parking on the
overall traffic under
realistic conditions"
1) Define the time window for the simulation study.
2) Define the characteristics of the simulation model
• Customer = the shop who receives the delivery or picks up the goods and defined by
a movement.
• Demand = Sum of the movement
3) Gather data on the average freight movement for each town, the daily demand, the
goods movements in for all the shops in the study area, the morning deliveries.
4) Generate individual private vehicle trajectories in the traffic system using SymuVia
taking into consideration all the possible condition of the traffic including the period
(day and time) and the change of traffic conditions on the passageway.
5) Two traffic scenarios have been separated
• Free movement of all the vehicles in the passageway, without queues at traffic
lights;
• Limited outgoing flow that generates queues in the passageway.
6) For the double-parking context, 4 parameters are taken into account:
• The delivery time: set at 10, 20 and 30 minutes
• The place of delivery: the vehicles are parked in double position in front of the
customer's shop.
• The level of massification of the handling of goods: each delivery is made by a
single truck.
• The time window: period of 5 hours in the morning from 7AM to 12AM.
SymuVia
Lafayette
avenue,
Lyon, France
[10]
Microsimulation
Modelling of the Impacts
of Double-Parking
Along an Urban Axis
1) Statistics collection on the illegal parking cases along the axis concerning the
period of day, position, duration.
2) Set-up the information of the road (number/size of lanes, bus lanes, bus stop
locations, circulation control, turning movements, traffic demand and traffic structure)
in AIMSUN software
3) Modeling on AIMSUN using dedicated lanes and incidents, the consequents that
occur every time parking maneuvers take place because of the double-parking
phenomenon by making calibration of the model's parameters to reflect the actual
behavior of the vehicle. driver and evaluating the results of the scenarios and their
impact through 4 traffic indicators and 5 energy / environmental indicators (average
speed, travel time, delay time, Stop time, fuel consumption, CO2, NOx, VOC
emission)
AIMSUN
DRACULA
Thessaloniki,
Greece
[13]
Performance du transport
de marchandises en ville
: Cas de l'implantation
des aires de livraison
1) Delimitation of the spatio-temporal framework of the study perimeter,
2) Determination and formatting of data according to the simulator insertion
parameters: Networks, flows and demand, traffic lights and public transport,
3) Definition of the background (the geometric structure of the place of study), slaps
(objects of the network, objects of the parking and result),
4) Definition of a network scenario that includes the three slaps,
5) Elaboration of the theoretical network components (supports, trajectories, parking
areas, generators, outputs, links),
6) Definition of a flow scenario (simulation hours, category of vehicle and quantity of
traffic),
7) Definition of a parking scenario (downtime, location, schedule),
8) Definition of a simulation scenario that contains the flow scenario, the network
scenario and the parking scenario,
9) Launch of the simulation engine and analysis of the results based on the simulator
output tools
Dynasim
Fez,
Morocco
[14]
Microscopic Simulation
of the Cruising-for-
Trucks-Parking as a
measure to Manage
Freight Loading Zone
1) Define the simulation rules:
• Commercial vehicles can only park in an FLZ
• Demand is equal to the probability of finding a vacant FLZ
• Offer is equal to the number of FLZs per zone
• The search time is not influenced by the delivery route properties
• The origin, destination, and stop points are stochastically defined
2) Identify the characteristics of the delivery route
• The OD matrix
• Sequencing of customer stops
• Customer demand
• The route between the delivery points
•Break time
3) Measure the search time needed to find the first free FLZ using SymuVia software
SymuVia Lyon, France [15]
B. ILLEGAL PARKING & DRIVER BEHAVIOR
In the urban environment, a bad urban planning policy, a lack
of sufficient parking spaces and poor drivers' behavior can lead
to increase significantly the illegal parking phenomenon, the
latter take several forms as parking in a prohibited space, on the
sidewalk, parking in a place that limits the visibility of other
vehicles and pedestrians, parking during times when the latter is
not allowed like the peak times, parking in the area dedicated to
cyclists..etc. all these forms of parking cause many problems and

nuisances and have a great impact on the citizen's quality of life,
illegal parking can be one of the biggest causes of congestion,
traffic accidents and concentrations of air pollution in specific
areas, it also leads indirectly to generate other
externalities like increasing the travel time, increase the
consumption of fuel, slowing the movement of goods and trade
in the urban space, even the attractiveness of the city and tourism
can be affected since the visitors must deal with unwanted traffic
congestion resulting from illegal parking on the roadways, this
impact inspire many researchers to deal with this subject and
there is a significant number of scientific papers who investigate
illegal parking from its different angles like land use, congestion,
Driver behavior, and environmental degradation, we present their
entirety in the tables [3 - 8],
C. SEARCH TIME FOR FREE PARKING SPOT
In places characterized by an imbalance between load and
capacity to park, It can be seen that the proportion of vehicles that
search for a parking spot is important, a thing that increases the
strangulation of traffic and therefore leads to the generation of a
significant amount of negative externalities such as noise,
insecurity, air pollution, greenhouse effect pollution, congestion…
to understand the behavior of the driver during the search we can
find that, the more difficult it is to find an empty parking space,
the more the driver gradually widens his search circle, so in the
first 15 minutes, the distance to the destination is on average less
than 200 meters, when the search time exceeds 15 minutes, the
distance explodes and can sometimes exceed 500 meters
[Figure5], [16]
When looking for a parking space, the driver enters a space in
which he builds relationships. The strategy he will adopt during
his research depends both on the urban context in which the
research is carried out and on the individual characteristics of the
driver, whether it is the trip reason or other more personal factors
such as the subjective perception of different types of parking(
allowed or prohibited, free or paid…)
D. THE NEGATIVE EXTERNALITIES OF PARKING
TABLE. III. IMPACT OF PARKING ON MOBILITY AND URBAN CONGESTION — MODELING APPROACH
Scientific
Discipline
Research Title Year Objective Tools and approach used
Computer and
system
software
Evaluation of Real-Time Parking
Information Case Study of
Isolated University Campus
2010
The purpose of the article is to indicate the role of
roadside parking information systems to optimize
delay, reduce travel time, and manage volume
change of cars by guiding vehicles based on the
information of available parking spaces in
multiple parking lots.
VISSIM Software
Google earth
AutoCAD Software
Hi-Star traffic counters,
Dynamic routing decision
Stochastic model
ITS dloyment analysis system
(IDAS)
[17]
Mathematics
A multilayer model to simulate
cruising for parking in urban area
2011
The purpose of this research is to provide a model
for simulating the impact of parking research on
traffic congestion.
Like-BPR cost function
Multi-slice approach
Stochastic user equilibrium model
Method of successive averages
algorithm
[18]
Computer and
system
software
Applying dynamic traffic
assignment in modeling permit-
restricted parking utilizing
microscopic traffic simulation
2012
This research proposes a modeling method that
combines Dynamic traffic assignment with
microscopic simulation in the objective of
measuring the impact that relocation of a parking
lot can have on the mobility and the transportation
system.
VISSIM software
AutoCAD software
Dynamic traffic assignment
(DTA)
Google Maps
[19]
Fig. 5. Parking search time spiral.

Computer and
system
software
Intelligent Parking Management
System by Multi-Agent
Approach:
The case of Urban Area of Tunis
2014
This research proposes a multi-agent-based
approach that aims to decrease the searching time
for a vacant parking place by using multiple
information and communication technologies to
create Intelligent parking management, as a result,
the proposed model will help reducing vehicle
crowding and improve traffic flow in an urban
area.
Multi-Agents SYSTEM
cellular automata
Traffic sensors
GPS and GIS
OpenStreetMap
MATSim software
[20]
Mathematics
A downtown on-street parking
model with urban truck delivery
behavior
2017
The purpose of this article is examining the
relationship between the parking of passenger
vehicles and delivery trucks' behaviors to provide
a tool to aid decision in terms of parking
allocation, pricing and reducing network
congestion.
Commercial solver (fmincon) in
MATLAB
Pay-and-display devices
Interior-point algorithm
Discrete methods
AI06’s downtown parking and
traffic congestion model
Macroscopic fundamental
diagram (MFD)
MATLAB Software
[21]
Computer and
system
software
Integrating explicit parking
search into a transport simulation
2017
This paper demonstrates a methodology to
integrate parking search behavior in a
microsimulation modeling framework using a
within-day re-planning approach in order to
quantify the impact of parking search behavior on
the overall travel times by the vehicle.
MATSim
Agent-based simulation
framework
[22]
TABLE. IV. IMPACT OF PARKING ON MOBILITY AND URBAN CONGESTION — SIMULATION APPROACH
Simulation
software
The Area
Evaluation of Real-Time
Parking Information Case
Study of Isolated
University Campus
1) Build the model by collecting scaled, high-quality aerial pictures
2) Save the pictures as one image and import it in VISSIM.
3) Insert the links, connectors, and nodes.
4) Create in VISSIM one parking lot for each set of attached parking spaces of the
same restriction. (700 lots & 1200 Parking spaces)
5) Create the origin-destination (O-D) matrix for each class of vehicle-based on-
campus parking restrictions, (faculty staff, student, services vehicle, handicapped
vehicle, bus, trucks, and noncampus vehicle.
6) Determine the traffic control for all links and nodes in VISSIM including routing
decisions, speed changes, priority instructions, stop signs, signals, and traffic
detectors.
7) Calibrate an validate the model
VISSIM
The Clemson
University, South
Carolina, united
states
[17]
Applying dynamic traffic
assignment in modeling
permit-restricted parking
utilizing microscopic traffic
simulation
1)Choose the adequate simulation software (VISSIM) based on several criteria
defined by the researchers
2) build the Road Network based on Aerial Photos, Parking Maps and field Counts.
3) Install Traffic Control based on Parking Restrictions, Signal Timing, Sign
Placement
4) Create the original - destination Matrix
5) Distribute zonal trips based on parking restrictions
6) Run the volumes in DTA simulation model if the volumes are not converged,
repeat the process, if they are converged compare Travel Times, Signal Operations
and Volumes, if it’s not a match repeat the process, if it's a match compare
Volumes, Speeds, and Visual Display if it's not a match repeat the process, if it's a
match Run the model.
VISSIM
Clemson
University, South
Carolina, United
States
[19]
Intelligent Parking
Management System by
Multi-Agent Approach:
The case of Urban Area of
Tunis
1) Create the study network with only the roads using OpenStreetMap tool,
2) Collect network characteristics information (N of parking spaces, parking time &
price, traffic volume,
3) Develop a simulation environment on MATSim Software by:
• Identifying each node with a unique ID and attribute unique geographical
attributes
• Define each link with a unique ID and Strat/End Node, and identify the link
characteristics (capacity, speed, N of lane…)
• Define citizens as Agent person
• Determine for each itinerary the trip and the activities done by agents during a
period,
• Define for each trip the nodes, its distances, and the start/end time attributes
• Define for the activity, the type (shopping, education…), location, start/end time
attributes.
MATSim
Tunis city center,
Tunisia
[20]

4) Use MATSim to simile 2 types of cases the First one: the random movement of
people in the area to find an empty parking spot for their vehicles and the second
the guided movement of people to parking space
5) Establish a comparison between 2 scenarios
Integrating explicit parking
search into a transport
simulation
1) Gather the data requirement (number of parking spots on each link in the study
area, define the links with a direct on-street parking spot, Create the study
population from census data)
2) Define the daily activities plan carried out by the agents (the activity start
directly after the arriving of the agent by car since the parking location and the
activity location are in the same place)
3) Once the agent arrives at the destination, the agent browses a sequence of nearby
links selected randomly to search for a parking spot (this research depends on
several factors such as location, price, personal experiences, willingness for illegal
parking and more)
4) After parking removes the vehicle from the traffic and starts the next activity of
the agent.
5) Reschedule the plans (departure time, travel mode, travel road) of a share of
agents after each simulation repetition.
6) Assign a score to each iteration, if the change marks better than the previous one,
save it. If not, delete it.
7) Repeat the process multiple times until reaching the equilibrium form.
MATSim
Charlottenburg
district, Berlin,
Germany
[22]
TABLE. V. IMPACT OF PARKING ON URBAN POLLUTION — MODELING APPROACH
Scientific
Discipline
Computer and
system
software
A microsimulation of traffic,
parking, and emissions at
California polytechnic state
university- san Luis obispo
2011
The purpose of this thesis measures the negative
externalities in terms of environmental pollution
generated due to traffic and parking congestion
during an ordinary morning peak hour in a
university area, using the microsimulation
software VISSIM and CMEM.
VISSIM,
CMEM
Dynamic assignment module
The Gravity Model
Darcy friction factor formulae
Kirchhoff Distribution Formula
for Utility of Routes
Stochastic model
[23]
Computer and
system
software
Characterization of University
Parking System
2018
This research develops a model that helps
understanding parking demand and finds the right
solutions to manage it effectively; furthermore, the
proposed model comes up with a framework for
estimating the parking behavior impact on the air
quality based on the evaluation of the
environmental footprint.
VISSIM software
CMEM software
[24]
TABLE. VI. IMPACT OF PARKING ON URBAN POLLUTION — SIMULATION APPROACH
Simulation
software
The Area
A microsimulation of
traffic, parking, and
emissions at California
polytechnic state
university- san Luis obispo
1) Creating a road network, the links (streets) and connectors (intersection
movements) using numerous screenshots of satellite imagery tanked using
Google Earth
2) Create speed distributions of the vehicles in the network based on
information from the Police Department.
3) Insert traffic control devices and their rules of operation into the network
model
4) Insert signal heads and plan the signal timing
5) Determine the conflict areas (branch, cross or merge paths) and define the
priority rules of the vehicles
6) Place the parking lots, nodes and Transit Stops on the network
7) Forecast the traffic volume, (the number of people making trips, purposes,
Start /end of trips, attraction locations, transportation means used,
origin/destination matrix)
8) Insert data concerning the vehicle categorized based on type,
acceleration/deceleration, occupancies, and widths
9) measure emissions for different operating states of the vehicle on a second
by second-time scale based on VISSIM output
VISSIM
CMEM
California Polytechnic
State University- San
Luis Obispo, United
states
[23]

Characterization of
University Parking System
1) Integrate the geometry and traffic schematic of the street network in
VISSIM based on information obtained via satellite images and verified by
field observations.
2) Search the Traffic signal timing plans and intersection volume count
3) Define the links and connectors, intersection controls, decision points and
vehicle paths, vehicle compositions, Origin-Destination (O-D) matrices
4) define the parking lots as exit links in VISSIM and affect the number, the
number of vehicles to the parking lot equally to the number of stalls in the lot.
5) Built the vehicle paths by identifying the shortest routes between the
parking lots to the nearest points close to the campus entrances.
6) Simulate traffic operations in the campus network to measures the network
transportation performance and obtain the following traffic indicators: total
network travel time, total network delay, vehicle-miles traveled
7) Estimate total walking distance in the links
8) Make second-by-second CO2 and other pollution compounds estimation
by using CMEM emission software based on vehicle trajectory data
generated by VISSIM.
VISSIM
CMEM
Cornell University, The
University of Texas at
El Paso, University of
California at Davis and
University of South
Florida, United states
[24]
TABLE. VII. IMPACT OF PARKING ON ROAD SAFETY — MODELING APPROACH
Scientific
Discipline
Computer and
system software
A framework for risk reduction
for indoor parking facilities under
constraints using positioning
technologies
2018
This research proposes an innovative solution for
managing large parking lots with the aim of
reducing risks and improving traffic safety using a
combination of technologies and considering
serval constraints like: the maximum capacity in
terms of vehicle that require parking, departure or
arrival of several vehicles at the same time and the
need of having evacuation exit in the place.
Smart-phone,
Accelerometers,
Ultrawideband transceiver.
MATLAB
Python
AIMSUN software
Transmodeler software
RFID,
3G Femto Cells
Wi-Fi and Bluetooth meshlium
scanners
GNSS/MEMS IMU receivers,
Terrain-aiding methodology
Receiver clock biases
Cell-of-Origin technique
Kalman filter algorithms
[25]
TABLE. VIII. IMPACT OF PARKING ON ROAD SAFETY — SIMULATION APPROACH
Simulation
software
The Area
A framework for risk reduction
for indoor parking facilities
under constraints using
positioning technologies
1) Data collection using radio frequency, identification technology, high-
sensitivity GNSS receivers Ultra-wideband technology, smart-phone and
accelerometers.
2) Carry out multilevel parking modeling using the two traffic simulators,
Transmodeler which makes an explicit characterization of zones as parking
spaces, and the second AIMSUN which allows to model parking spaces in
the form of short links.
3) Perform scenario analysis using AIMSUN software.
Transmodeler
AIMSUN
Athens, Greece. [25]
E. STUDY OF PARKING DEMAND
With the population growth in several cities around the world,
the improvement of the purchasing power, and the relatively low
cost of cars, as well as several other reasons, all of this has led to a
significant increase in the number of vehicles on the streets which
makes the city parking demand also experienced rapid growth, the
problem that arises at this level is that if this increase is followed
by a poor planning and demand forecasting, these cities will have
a serious lack in parking facilities and an alarming traffic situation
that could impact the entire economic system of the city, here
shows the important role of studying parking demand, in fact
there are several researchers who have focused their studies on
this subject by proposing different models, each model possesses
its strengths and weaknesses, we did not have the opportunity to
present them all since only one article that met the inclusion
criteria under this category; the latter proposes a hybrid model that
improves precision of traffic prediction and reduce the variation in
the long-term.

TABLE. IX. STUDY OF PARKING DEMAND — MODELING APPROACH
Scientific
Discipline
Statistics
A hybrid modeling approach for
parking and traffic prediction in
urban simulations
2015
The purpose of this research is to improve
precision of traffic prediction and reduce the
variation in the long-term in urban simulations.
The article developed a new hybrid architecture
that can provide different information, which
allows decision-makers to select the best
forecasting model.
Agent-based models
Markov chain Monte Carlo
simulations
Metropolis–Hastings algorithm
Matlab Software
The MCmultinomdirichlet
function
[26]
F. PARKING AND DECISION-MAKING
Several factors such as the price, the type and the parking
place, can influence drivers choices in terms of parking decisions,
these factors have a direct effect on drivers behavior, for example
during the search for a parking spot, the question that arises is that
if there is no more free space or the parking price is too high in a
specific area, what will the driver decision? is he going to
continue searching search until he finds a suitable place or he will
resort to illegal parking or he will return without accomplishing
the purpose of travel, the second example of decisions that may be
conditioned by parking is the choice of the mean of transport to
use during a trip (car, public transport, combined transport ...)
based on the availability of parking space, this influence can go
as far as planning the travel activities, the literature on this subject
is very rich, in the table below we present a set of scientific
articles that have developed this relationship of influence.
TABLE. X. PARKING AND DECISION-MAKING — MODELING APPROACH
Scientific
Discipline
Statistics
Integrating parking behavior in
activity-based travel demand
modelling
2012
The purpose of this research was to identify the
nature of the relationship between the choice of
parking and the planning of a trip's activities and
also examine its impact on the travel demand
generation.
Generalized Extreme Value
model
Log-normal regression model
Gradient search algorithm
Broyden–Fletcher–Goldfarb–
Shanno algorithm
The inverse of the Hessian
procedure
[27]
Computer and
system
software
GPS Data and Car Drivers’
Parking Search Behavior in the
City of Turnhout, Belgium
2014
Based on the GPS tracking technologies, this
research aims to investigate the spatiotemporal
characteristics (Time and location) of the drivers
searching behavior for parking spots in the central
business districts and shopping areas
GPS logger
I-Blue 747A+GPS recorder
DataLog software
TransCAD
Empirical survey
Google Maps
Adjusted R-square value & F-
value
[28]
Mathematics
Parking search equilibrium on a
network
2015
This article presents an equilibrium modeling
approach that integrates parking search behavior
into traffic affectation models.
The Iverson notation
The bracket notation
Sioux Falls network
Stirling’s approximation
The asymptotic expressions
Stochastic approach
Flow-pushing algorithm
Network loading algorithm
Convex combination algorithm
[29]
Computer and
system
software
Modeling the impact of parking
price policy on free-floating
carsharing: Case study for
Zurich, Switzerland
2017
This research proposes a microscopic model to
study the relationship between carsharing and
parking using an agent-based simulation model
that determine the level of impact of the parking
price on the demand of free-floating carsharing
MATSim software
framework
The utility functions
Multinomial logit model
Qsim software
Empirical survey
[30]

Statistics
Modelling parking choices
considering user heterogeneity
2017
This paper seeks to understand drivers' parking
behavior when looking for parking (free / paid
parking on the street, multi-storey underground
parking) to define an effective parking policy that
regulates the use of parking spaces with limited
parking places.
Mixed logit model
Probability density function
LIMDEP Software
The Multinomial Logit Model
SP survey
The D-efficient design
Ngene software
[31]
Mathematics
Modelling the Effects of
Parking Charge and Supply
Policy Using System Dynamics
Method
2017
This paper proposes a model that examines the
effects of parking cost and supply policy on the
choice of parking type and speed of traffic.
System dynamics
The logit model
Random utility theory and
discrete choice models
Practical Road-Resistance
Function
Combination of RP survey and
SP survey
Matlab software
[32]
Computer and
system
software
Autonomous vehicles and
their impact on parking search
2018
This research proposes a microscopic simulation
model that analyzes the different phases of the
search behavior for a vacant parking spot using
autonomous vehicle, including walking into and
from the vehicle.
MATSim
framework
[33]
TABLE. XI. PARKING AND DECISION-MAKING — SIMULATION APPROACH
Simulation
software
The Area
GPS Data and Car
Drivers’ Parking Search
Behavior in the City of
Turnhout, Belgium
1) Select the study area based on the conditions defined by Kaplan and Bekhor [3]
2) Make trips to the center of the city using a car equipped with GPS logger and ‘i-
Blue 747A+GPS recorder’ to collect every 3 seconds, information on the vertical and
horizontal position, the time, and the number of satellites involved in the registration.
3) Save, analyze and present the collected data using the GIS system TransCAD
4) Based on serval empirical studies gather information about gender, age, familiarity
with the city, possession of parking cards, type of car, objective, road network, links
and intersections, parking prices, departure and arrival time, average speed and
acceleration or deceleration of the cars.
5) Search the optimal average travel speed using ‘trial and error’, and define the
starting point of parking search based on the average speed
6) Analyze the data focusing first on parking search time and second on parking
search routes including street segments using TransCAD and DataLog
TransCAD
The city center
of Turnhout,
Belgium
[28]
Modeling the impact of
parking price policy on
free-floating carsharing:
Case study for Zurich,
Switzerland
1) Determine The daily trips plans (work, school, shopping…) for each agent in
MATSim, the supply models, the road network and the building facilities.
2) Execute agents' plans using a microscopic simulation, which results in traffic flows
in the system and which can lead to the congestion of the traffic.
3) Pair the supply and demand in an iterative process to enable agents to learn.
4) Define the list of activities and connecting trips through the course of the day for
each agent that contains the type, location, duration, transportation modes, roads,
departure and the travel time. The maximum number of plans (the choice set) that
each agent can keep in his memory during the simulation
5) Repeats the simulation between plan generation and the traffic simulation, in each
repetition allow to a portion of agents to improve their plans by modifying one of
their trip choices (Road choice, Time allocation, Mode) taking into consideration a
limited number of choices,
6) Evaluate how a plan performs and compare different plans by assigning a
quantitative score to each plan scenario.
7) Simulate the traffic with waiting queues using QSim software
8) Develop a carsharing framework and plug it into MATSim, containing different
carsharing modules, each offers different carsharing options and take different cost
structures.
9) Calibrate the simulation scenario by fitting the simulation output to the empirical
information related to the modal split and distance distributions and validate it using
traffic counts data
MATSim
Qsim
Zurich,
Switzerland.
[30]

Autonomous vehicles and
their impact on parking
search
1) Choice of simulation software based on the obligation of the study
2) Collect the data: Physical characteristics, the number of parking places on each
link, vehicle and walking location ….
3)use simple random parking search logic & a dynamic dispatch of vehicles during
the simulation runtime
4)The study presents two simulation scenarios:
•Common autonomous vehicle: a vehicle is allocated for picking-up and transporting
an agent to its purpose, empty vehicles are re-allocated or placed at ranks.
•Private owned autonomous vehicle: always assigns each agent to its private AV.
5)In the arrival, the autonomous vehicle is inactive and will proceed according to the
following options:
•Free spot: the autonomous vehicle will not move from the arrival place
•Garage: Continue to the nearest not- fully occupied parking or garage
•Cruise: the autonomous vehicle will cruise in circles around the last arrival point
until it is commanded again.
MATSim
Berlin
Charlottenburg
Germany
[31]
V. LITERATURE REVIEW: FACTS AND ANALYSIS
A. GEOGRAPHICAL DISTRIBUTION OF THE STUDIED
AREAS.
In this section we present some facts about the scientific
articles that were extracted during the research, The first thing that
caught our attention is that the study of the negative effects of
parking from a microscopic perspective took the attention of
researchers from around the globe, although there is a greater
concentration in the European continent and North America that
can be explained by the progress of scientific research in its
member countries, however, we find that there is also an interest
from North Africa and West Asia on the subject despite the low
number of articles published, this indicates that all countries,
whatever their level of progress are interested in this problem and
seek the reduction of the negative externalities resulting from
parking.
B. LITERATURE REVIEW TIMELINE
During the years that were taken into account in this study,
we find that except 2017 and 2018, which have seen a significant
increase in the number of scientific papers on the subject, we
find that the rest of the years did not exceed a ratio of 2 research
each year, which is a bit far from what should be, because of to
the subject importance, this can be an incentive for future
researchers to find other solutions that have not been studied and
suggested yet. [Figure 6]
C. NUMBER OF USES PER SIMULATION SOFTWARE
The third fact concerns the software used for the microscopic
simulation, we find that there is a great diversity in the programs
used, that reached nine software, this is because of several
factors such as the nature of the problem to be studied and what
tools the software provides, sometimes the price can be a
decisive element in the choice, and many other factors that have
been mentioned and taken into account in the selection, some
software has not exceeded the number of 1 publication. When
others have been used many times, such as
VISSIM & MATSim that has been used in over 40% of the total
literature. [Figure 7]
Fig. 5. Geographical distribution of the studied areas

VI. FUTURE RESEARCH AGENDA
Based on the literature review, we could define a topic we
believe requires more study and understanding, given its critical
importance and the serious consequences that may result from it if
not studied in-depth, and find solutions for it, which is the
problem of parking and delivery of freight transport in urban
areas.
Currently, the supply of goods is at the heart of the functioning
of cities, but the arbitration between the different functions and
uses of the road network is particularly complex. Organize
everyone's movements safely, ensure the comfort of pedestrian
and cyclist movements, allow a certain fluidity of motorized
traffic, especially that deliveries usually take place in double-
parking, they clog and pose a problem for both delivery vehicles
and other road users: dangers for pedestrians and cyclists, delays
of buses and trams, congestion for motorists, ...
Today, there is a real need, and fortunately, real opportunities,
to better manage these essential stops to the smooth running of
urban activities, because they facilitate access to goods in the
heart of cities. Deliveries carry real issues sustaining the
commercial dynamism of city centers in the face of the growth of
commercial areas. Enabling deliveries is also essential to maintain
livability and business operations.
For this purpose, we intend to limit research on using
microscopic simulation for implementing delivery areas for
commercial transport, Currently, there is no one
universal method for exactly defining the distribution of delivery
areas. It makes sense that there are no rules, nor an ideal number
of delivery locations per number of businesses, as this depends on
the trade, its size, the goods transported, but also its environment.
Through our future research, we hope to answer the following
questions:
What are the criteria to consider for a quick and effective
diagnosis?
Where and how to build a delivery area?
What time management?
VII. CONCLUSIONS
In the absence of current research, that gather all scientific
achievements during the last years in the field of MVPMS, we
presented Through this paper a comprehensive and detailed
literature review in which we studied and analyzed over 290
research papers in the years between 2010 and 2019, the thing that
allowed us to come up with several conclusions and findings in
addition of providing a roadmap not only for us and the rest of the
research laboratories but also for the different stakeholders in the
urban cities.
All the articles studied in this research were intended to measure
and limit the negative externalities resulting from the parking
process and increase the competitiveness and attractiveness of the
city, based on an in-depth microscopic study of all the actors,
whether the one who operates the parking or the one affected by
the operation. The results and statistical surveys of these
researches were presented systematically thing that allowed us to
summarize the various finding, identify the gaps and give a
background for the positioning of future research in this area.
VII. REFERENCES
[1] : BOUJNAH, Houda. Modélisation et simulation du système
de stationnement pour la planification de la mobilité
urbaine : application au territoire de la cité Descartes. 2017.
Thèse de doctorat.
[2] : KITCHENHAM, Barbara. Procedures for performing
4
4
2
2
2
2
1
1
1
0 1 2 3 4 5
VISSIM
MATSim
SymuVia
AIMSUN
DRACULA
TransModeler
TransCAD
Dynasim
Paramics
Number of uses per simulation software
Fig. 7. Number of uses per simulation software
Fig. 6. Literature review timeline

systematic reviews. Keele, UK, Keele University, 2004,
vol. 33, no 2004, p. 1-26
[3] : DABLANC, Laetitia et BEZIAT, Adrien. Parking for
freight vehicles in dense urban centers-The issue of
delivery areas in Paris. Marne la Vallee, France, 2015.
[4] : MAJOCCHI, Alberto, ZATTI, Andrea, et al. Land use,
congestion and urban management. Societa Italiana di
Economia Pubblica (609), 2008.
[5] : KLADEFTIRAS, Markos et ANTONIOU, Constantinos.
Simulation-based assessment of double-parking impacts on
traffic and environmental conditions. Transportation
research record, 2013, vol. 2390, no 1, p. 121-130.
[6] : FIGLIOZZI, Miguel et TIPAGORNWONG, Chawalit.
Impact of last mile parking availability on commercial
vehicle costs and operations. In : Supply Chain Forum: An
International Journal. Taylor & Francis, 2017. p. 60-68.
[7] : GALATIOTO, F. et BELL, M. C. Simulation of illegal
double parking: quantifying the traffic and pollutant
impacts. In : 4th International SIIV Congress, Palermo,
Italy. 2007.
[8] : KLADEFTIRAS, Markos et ANTONIOU, Constantinos.
Simulation-based assessment of double-parking impacts on
traffic and environmental conditions. Transportation
[9] : NOURINEJAD, Mehdi, WENNEMAN, Adam, HABIB,
Khandker Nurul, et al. Truck parking in urban areas:
Application of choice modelling within traffic
microsimulation. Transportation Research Part A: Policy
and Practice, 2014, vol. 64, p. 54-64.
[10] : LOPEZ, Clélia, GONZALEZ-FELIU, Jesus,
CHIABAUT, Nicolas, et al. Assessing the impacts of goods
deliveries’ double line parking on the overall traffic under
realistic conditions. In : Proceedings of the 6th International
Conference Information Systems, Logistics, and Supply
Chain, Bordeaux, France. 2016. p. 1-4.
[11] : GAO, Jingqin et OZBAY, Kaan. Modeling double
parking impacts on urban street. Transportation Research
Board’s 95th, 2016.
[12] : E SILVA, João de Abreu et ALHO, André Romano.
Using Structural Equations Modeling to explore perceived
urban freight deliveries parking issues. Transportation
Research Part A: Policy and Practice, 2017, vol. 102, p. 18-
32.
[13] : MORFOULAKI, Maria. Microsimulation Modelling of
the Impacts of Double-Parking Along an Urban Axis. In :
Data Analytics: Paving the Way to Sustainable Urban
Mobility: Proceedings of 4th Conference on Sustainable
Urban Mobility (CSUM2018), 24-25 May, Skiathos Island,
Greece. Springer, 2018. p. 164.
[14] : MOUFAD, Imane et JAWAB, Fouad. Performance du
transport de marchandises en ville : Cas de l'implantation
des aires de livraison, 2017,
[15] : LOPEZ, Clélia, ZHAO, Chuan-Lin, MAGNIOL,
Stéphane, et al. Microscopic Simulation of Cruising for
Parking of Trucks as a Measure to Manage Freight Loading
Zone. Sustainability, 2019, vol. 11, no 5, p. 1276.
[16] : LEFAUCONNIER, Amélie et GANTELET, Eric. La
recherche d'une place de stationnement: Stratégies,
Nuisances associées, Enjeux pour la gestion du
stationnement en France. TEC (TRANSPORT,
ENVIRONNEMENT, CIRCULATION), 2005, no 187.
[17] : FRIES, Ryan, CHOWDHURY, Mashrur, DUNNING,
Anne, et al. Evaluation of Real-Time Parking Information:
Case Study of Isolated University Campus. Transportation
[18] : GALLO, Mariano, D'ACIERNO, Luca, et MONTELLA,
Bruno. A multilayer model to simulate cruising for parking
in urban areas. Transport policy, 2011, vol. 18, no 5, p.
735-744.
[19] : FRIES, Ryan, CHOWDHURY, Mashrur, et DUNNING,
Anne. Applying dynamic traffic assignment in modeling
permit-restricted parking utilizing microscopic traffic
simulation. Simulation, 2012, vol. 88, no 8, p. 936-947.
[20] : SANA, Benhassine, RIADH, Harizi, et RAFAA, Mraïhi.
Intelligent parking management system by multi-agent
approach: the case of urban area of Tunis. In : 2014
International Conference on Advanced Logistics and
Transport (ICALT). IEEE, 2014. p. 65-71.
[21] : AMER, Ahmed et CHOW, Joseph YJ. A downtown on-
street parking model with urban truck delivery behavior.
Transportation Research Part A: Policy and Practice, 2017,
vol. 102, p. 51-67.
[22] : BISCHOFF, Joschka et NAGEL, Kai. Integrating explicit
parking search into a transport simulation. Procedia
computer science, 2017, vol. 109, p. 881-886.
[23] : KILBERT, Steven Michael. A Microsimulation of Traffic,
Parking, and Emissions at California Polytechnic State
University-San Luis Obispo. 2011.
[24] : CHEU, Ruey L., GURBUZ, Okan, BALAL, Esmaeil, et
al. Characterization of University Parking System. 2018.
[25] : ANTONIOU, Constantinos, GIKAS, Vassilis,
PAPATHANASOPOULOU, Vasileia, et al. A framework
for risk reduction for indoor parking facilities under
constraints using positioning technologies. International
journal of disaster risk reduction, 2018, vol. 31, p. 1166-
1176.
[26] : BEHESHTI, Rahmatollah et SUKTHANKAR, Gita. A
hybrid modeling approach for parking and traffic prediction
in urban simulations. AI & society, 2015, vol. 30, no 3, p.
333-344.
[27] : HABIB, Khandker M. Nurul, MORENCY, Catherine, et
TRÉPANIER, Martin. Integrating parking behaviour in
activity-based travel demand modelling: Investigation of
the relationship between parking type choice and activity
scheduling process. Transportation Research Part A: Policy
and Practice, 2012, vol. 46, no 1, p. 154-166
[28] : VAN DER WAERDEN, Peter, TIMMERMANS, Harry,
et VAN HOVE, Lies. GPS Data and car drivers’ parking

search behavior in the city of Turnhout, Belgium. In :
Geoinformatics for Intelligent Transportation. Springer,
Cham, 2015. p. 247-256.
[29] : BOYLES, Stephen D., TANG, Shoupeng, et
UNNIKRISHNAN, Avinash. Parking search equilibrium
on a network. Transportation Research Part B:
Methodological, 2015, vol. 81, p. 390-409.
[30] : BALAC, Milos, CIARI, Francesco, et AXHAUSEN, Kay
W. Modeling the impact of parking price policy on free-
floating carsharing: Case study for Zurich, Switzerland.
Transportation Research Part C: Emerging Technologies,
2017, vol. 77, p. 207-225.
[31] : IBEAS, Angel, DELL’OLIO, Luigi, BORDAGARAY,
María, et al. Modelling parking choices considering user
heterogeneity. Transportation Research Part A: Policy and
Practice, 2014, vol. 70, p. 41-49.
[32] : MEI, Zhenyu, LOU, Qifeng, ZHANG, Wei, et al.
Modelling the Effects of Parking Charge and Supply Policy
Using System Dynamics Method. Journal of Advanced
Transportation, 2017, vol. 2017
[33] : BISCHOFF, Joschka, MACIEJEWSKI, Michał,
SCHLENTHER, Tilmann, et al. Autonomous vehicles and
their impact on parking search. 2018.
.

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