Combining Ridesharing& Social Networks

Combining Ridesharing
& Social Networks
By Roel Wessels s0023310

1

Table of Contents

Overview of Pooll ....................................................................... 3 Settings page................................................................... 13
The problem ........................................................................... 4 Choice modelling ................................................................ 14
The solution ............................................................................ 4 Experiment design ............................................................... 14
The innovation ........................................................................ 4 Experiment testing ............................................................... 16
The customers ....................................................................... 5 Questionnaire distribution.................................................... 16
Business model...................................................................... 5 Experiment results ............................................................... 17
Ridesharing ................................................................................ 6 CONVERGE assessment ........................................................ 19
Definition of terms .................................................................. 6 Application description ........................................................ 19
Traditional reasons for ridesharing ......................................... 6 Assessment objectives, assessment category and user
Present reasons for ridesharing ............................................. 9 groups ................................................................................. 20

System ..................................................................................... 11 Decision makers, user groups involved and assessment
objectives (two descision makers) ...................................... 21
System ................................................................................. 11
Expected impacts ................................................................ 22
Versioning schedule ............................................................. 11
Assessment method............................................................ 22
Workflow............................................................................... 12
Conclusion and Recommendations ........................................ 23
Trips pages....................................................................... 12
Literature ................................................................................. 24
Profile page ...................................................................... 13

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Appendix .................................................................................. 25

3

Overview of Pooll
transport as an alternative. Additionally, social aspects are
mentioned as primary reasons for carpooling.

The problem
Modern day car traffic in the Western world is inefficient in terms of The solution
occupancy, which leads to relative high travel costs. These costs Pooll provides a ridesharing service which ensures flexibility, trust,
are already rising due to the continually increasing oil prices. safety, reliability and fun. The solution is based on a system which
Moreover, there is a potential reduction of pollution by increasing enables travellers to announce their trips to other travellers.
the number of occupants per vehicle; fewer vehicles fulfil the same Whenever a part of a trip coincides with trips of other users, both
travel demand. travellers receive a notification and can invite each other for
travelling together. Once both travellers have agreed by accepting
Although in North America carpooling and ridesharing is gaining the invitations the trip is confirmed and both travellers will receive a
more and more popularity due to the construction of so-called High message with the details of their appointment. Future versions also
Occupancy Vehicle (HOV) lanes, Europe is still lacking any include a mobile client for on-trip access and a payment system so
advances of getting more persons into a single vehicle. that transfer of cash from the passenger to the driver is done
automatically.
It could be argued that traditionally, car travel is about freedom of
movement and that carpooling reduces freedom both in terms of The innovation
space and time. Also, in urban areas the quality of public transport
Pooll is innovative because it combines the strengths of social
can be considered very high. In that case using public transport is
networks to solve the current problems of ridesharing.
usually quicker, more flexible in terms of schedule and the privacy
or at least the anonymity is higher.
A social network is a web-based service that provides its users with
the ability to map their relations with other individuals and has
However, research in primarily, the US, has shown that carpooling
gained a lot of popularity in the last few years. Most social network
propensity increases if there are cost savings or low quality public
websites share the functionality of having a user profile with
personal information of the user and ability to connect to other
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users by inviting them to one’s own social network. The largest It can also show the location and progress of other users you have
social network in The Netherlands called Hyves has a user base of a matched trip with. In case of unforeseen circumstances such as
around 52% of the total Dutch population. traffic jams, the user can then adapt to this changed pickup time or
opt out of the trip completely.
Lack of trust and safety seem to be the main problems for
ridesharing. Pooll aims to solve this by integrating the social The customers
network of the user to his or her profile. Users can get information
The users are all travellers that want to make trips together with
about other users by simply checking the profile on their social
other users. While the focus of the system is on car drivers because
network. They can evaluate the profile and decide if the other
increased vehicle occupancy offers higher efficiency, there is also
traveller seems trustworthy and friendly. Furthermore, Pooll has an
the possibility to plan trips using other modes. Travelling with
own rating system which keeps scores of persons, just like the
friends, for example by train, also seems a nice experience to the
rating systems commonly seen on auctioning sites. Amongst the
user.
criteria are factors like reliability, safety and friendliness.

Another innovative feature of the system is the mobile client. The
Business model
mobile client consists of software that is run on a mobile device The basic service is free to all individual users. This is to make sure
such as a smart phone or PDA. It requires a wireless internet that the initial required user base will be large enough to generate a
connection and a built-in GPS sensor. This mobile client works as probability of a match for a certain trip.
an enhancement to the non-mobile pre-trip system.
There is also a premium service which only companies can
The mobile software can be used to replicates the functionality of subscribe to. By paying a setup fee and a small monthly fee, they
the browser based version, but it adds localisation capability. It can receive a portal to Pooll for use exclusively by employees of the
be used to find trips that pass your current location and create a company. This also adds another filter option, namely to filter trips
match on the fly. by users of a certain company.

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Finally, once a payment service is implemented, users can load between a driver and a passenger. This differs from hitchhiking in
cash to a balance attached to their user account. A passenger that ride-sharing is usually arranged pre-trip. Slugging is a form of
needs to have a prepaid balance which is high enough for the trip hitchhiking used to gain access to HOV lanes where both driver
that he or she wants to be a passenger on. Pooll will act as an and passenger have a mutual benefit. Finally, car sharing is model
escrow service, generating revenue from the combined value of all where multiple individuals rent or lease cars together in order to
the prepaid balances. share costs which is attractive when it only used occasionally.

Whenever in this paper ridesharing is mentioned, it is meant to
Ridesharing indicate this ad-hoc type of arrangement.

Over the years a lot of terms for travelling together by car have
evolved. It seems that in the present literature no clear distinction is
made between the different forms, instead a lot of terms are used
Traditional reasons for ridesharing
interchangeably. It seems wise to try to define different forms Most research on the topic of carpooling is has been conducted in
travelling together by car. North America. In the article by R.F. Teal “Carpooling: who, how and
why”, it is commented that carpooling can be considered as an old
phenomenon. It originates as a social gesture from the time when
Definition of terms car ownership was still very low. Car owners were usually happy to
The most well-known term is carpooling, which is the shared use of provide a ride to others if there was still space left in the car. Of
a car by the driver and one or more passengers usually for course, first in line were the household members that had to be
commuting purposes. Carpooling arrangements can vary in dropped off at a certain location.
regularity and formality. Ridesharing is sometimes said to be a
synonym for carpooling, but it is increasingly used to indicate a As car ownership increased, ridesharing became less common.
form of ad-hoc carpooling, thus with less regularity and formality. Generally, only if no car and no public transport are available,
Where carpooling is usually performed by a distinct group (pool) of tendency to carpool will be present, except for some urban areas,
individuals alternating driving responsibilities, ride-sharing is less where traffic became clogged and special treatment is now given to
regular in the sense that it usually is a onetime arrangement vehicles with a high occupancy.

6

Three main characteristics are traditionally present amongst the
drivers and trips where carpooling is being performed, these are: Socio-
Transportation Spatial Temporal
demographic
• Low income
• High trip distance Schedule
• Low trip average speed Transit flexibility per trip
Urban
Age Availability/ (usually
It seems that the cost savings that can be incurred due to population
Quality depends on
carpooling are an important aspect of the decision to carpool. motive)
Furthermore, a high trip distance increases carpooling propensity
because a comparatively small portion of the trip is spent on pickup
Residential
and drop off, increasing efficiency. Finally, a low trip average speed Regularity (every
location
is another aspect, because it has the side effect of the pickup and Sex Car availability weekday, every
(metropolitan vs
drop off influencing the total trip time only by small amount. Monday)
nonmetropolitan)

Other socio-demographic, spatial and temporal factors that are
Employment
traditionally mentioned as being important in several studies of
Travel Location
carpooling behaviour are listed in the table.. Income
distance/time (suburb, city,
CBD)

Household size
/ household car Travel speed
ownership

Trip Cost

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Present reasons for ridesharing attributes such as age, gender and vehicle ownership are modelled
but some other underlying factors a left out.
More recent studies (such as Morency, 2006) confirm the above
mentioned factors, but notice a shift from determining behavioural
factors such as income to for example car availability and
It is likely that especially in non-household ridesharing, which would
household composition. In this study in the Greater Montreal Area
be the focus of Pooll, the psychological elements of trust, safety
(Canada) it revealed that ridesharing increased during the study
and reliability are likely to be other important factors which the
period (1987-2003) but that this does not automatically mean more
determine if ridesharing with another individual is undertaken.
desirable end results.

These can be improved by the addition of information from social
The study shows that the increasing number of trips made by car
networks. Just like auctioning sites feature rating systems to
passengers does not necessarily result in a reduction in the total
indicate the business credibility and reliability of a vendor, a
number of kilometers traveled. While ridesharing can yield an
personal profile provides some indication of the trustworthiness of
effective matching of trips, it can result in the multiplication of trips
an individual, enhancing trust and safety.
by drivers who act as taxi drivers. This occurs frequently in
household-based ridesharing, where the mother drives a car to
accompany their children to school, suffering a large detour on her Present reasons for ridesharing
way to work. Data that can be found about the reasons for ridesharing is quite
outdated or regionally incompatible with the situation in The
It seems that the psychological factors that have influence on Netherlands. Therefore, at the start of this report a preliminary study
ridesharing have not been taken into account in traditional literature. was performed to access the likelihood that social aspects are an
For example, recent literature tries to handle the complexities of influencing factor of the success of a system like Pooll. Using a
interactions between individuals by research into the activity carpooling website described in the next paragraph called
systems of households. Examples are agent-based micro ‘meerijden.nu’, some information was gathered about the reasons
simulations (Roorda, 2009) in which each agent represents a for carpooling.
decision maker which can choose a destination, mode and also
combining trips with other (household) individuals. Here personal
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The text that accompanied the offered or requested trip was the Netherlands and internationally. The following have been
investigated for terms that matched one or more of the reasons for researched:
ridesharing below. The percentage of offers and requests that
contained this reason is shown in the table. It seems that cost is still The Netherlands:
the governing factor behind the reason to carpool. 80% contained http://ride4cents.net
some reference to some sort of a payment agreement and 30% http://www.meerijden.nu
mentioned cost as a main reason. http://www.marktplaats.nl

Another reason that was frequently given was ‘cosiness’ or other International
social aspects in general. While these were not mentioned in http://www.smartcommute.ca
previous literature of the subject of carpooling, it seems nowadays http://www.mitfahrgelegenheit.de
they have become a key part of carpooling behaviour.

Reason It seems that existing ridesharing systems in Europe are similar to
notice boards. Users can pin messages to announce a trip or
Occasional carpool 23% request a pickup point and a destination. The functionality more or
less ends there. The first three solutions share that they are
Payment agreement 80%
relatively low tech solutions. They do not really try to match trips in
Costs mentioned as main reason 30% an efficient way; they are rather like message boards and do not
match or filter to generate matches efficiently.
Social aspects mentioned as reason 24%
The fact that Marktplaats.nl, which is actually a generic marketplace
system offering all kinds of products and services, is even used for
State of the art of ridesharing systems ridesharing ads might indicate that there currently is no successful
dedicated ridesharing system in the Netherlands.
Some research has been conducted in order to find out the status
quo of other carpool systems that are available both nationally in

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On the contrary, the Canadian smartcommute.ca and the German hosts the web server, email server and database, but also connects
mitfahrgelegenheid.de, reveal what a more powerful system can to other servers like the text message server and the web server of
look like and how it performs. These try to match trips based on the social network. The diagram depicts the system graphically, the
criteria such as origin, destination, date and time and radius. The in arrows being data flow and direction.
Germany popular mitfahrgelegenheid.de uses radius around origin
and destination as one of the criterions for a match.
Versioning schedule
Smartcommute.ca is superior in the sense that is filters based on
The schedule at which functionality is added is an important factor
radius (in this case buffer) around the shortest route path of the
to ensure that the system is a success. This success is mostly
planned trip instead of only the origin and destination. This
dependent on two factors, first the user base and secondly creating
increases the probability of a match for a trip, especially for long
revenue in order to continually expand the service. A versioning
trips.
schedule that could accomplish this is shown below.
In short, the user base is created by providing the basic service for
Concluding, even the basic version of Pooll would be
free. Then revenue is created by adding components which are
advantageous to the current Dutch situation, providing a dedicated
paid for by the customer (premium services) and by creating equity
platform for ridesharing instead of the message board
(payment service with a prepaid balance).
workarounds.

Version Added component
System description 1 Web client Free
2 Web client Premium

System overview 3 Add SMS integration

The Pooll system can be broadly classified as a traffic information 4 Mobile client
system. It uses the well known client-server model as its 6 Payment service
architecture. The clients can be all sorts of devices, ranging from
7 Mobility management and brokerage
mobile clients like cell phones and PDA to a desktop computer at
home. The server is a major component in the architecture. It is

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Workflow Trips pages
The workflow for creating a new trip should be as easy as possible. For each trip a user can indicate what his role will be. Roles can be
It is depicted below. The user starts with navigating to the website driver, passenger or left open. A role left open can be inserted only
by entering the URL in web browser. The first page is the landing when the user is a car owner (sets in the user profile) and means
page, where there is a short presentation about Pooll for new users that the user is open to being either driver or passenger. If a
that are unfamiliar with the system. Users can then continue to the (partial) trip match is found with another user having an open role,
login screen or to the signup screen if they haven’t yet registered. the users can decide who will be the driver for that trip.
After the login screen the user is sent to the main screen.
The origin and destination are inserted together with date and time
From the main screen, the user can access all the other screens. of the trip. The user can also select a gender for filtering purposes.
The admin screen shows information about the history of his trips The allowed values are ‘all genders’ or ‘same gender’. This ensures
and matches. This is for tax purposes which could be major reason that it is impossible for male profile to specifically search for female
to use the system for lease car owners to use Pooll for every trip. profiles possible increasing (perceived) safety.
This helps to create the large initial user base.

For each of these values flexibility values can also be inserted.
The Profile page is to update the user profile. The profile stores the
These constraints can be the total detour for the trip in kilometres or
basic user information that cannot be extracted from the social
a time range for departure or arrival time. These constraints and
network. The Settings screen shows the system and user settings,
ranges are prefilled into the user interface based on preset values in
like visibility and privacy options. The rest of the screens all relate
the user profile. This ensures minimal workload to the user.
directly with trips and the matching of trips. Trips can be
added, edited, viewed or deleted. Also confirmed matched
Signup
trips, be it one time or recurring, can be viewed, edited or Administration Profile

deleted.

Landing
Login Main screen Settings
Page

Current 12
Add trips Search trips
matches

Profile page If the user has not completed the Pooll profile sufficiently by
The user profile is used to store the personal information of a user. granting access to the social network, the user has to manually
The profile is created during signup to the Pooll system. Only if all enter additional information. After validation of this data the profile
the mandatory information is inserted will the user be able to add can be stored.
trips.
Settings page
It contains the name, email address, phone number, home and Privacy and therefore visibility is of key importance. In the settings
(multiple) work addresses of a user. The integration with the social page people can select which information is visible to other users of
network is also arranged here. The user can specify (multiple) the system. However, by default friends of the user can see all their
social networks and his or her username. By clicking on a link, a information. For both friends of friends (second level, indirect
popup is opened which enables the user to grant Pooll access to friends) and non-friend (third level and up) personal information can
his or her profile of the social network. This is possible to a be individually selected to be available for matching purposes.
common interface that is being developed by a consortium of large However, if an invitation is sent or accepted during a trip match, all
social networks called Opensocial, which is lead by Google. information is shown.

The social network usually contains other necessary basic
information of the user such as age and gender which is then
stored into the Pooll user profile. The information about the friends
of the user is not stored on the Pooll server as this violates the
terms of use of most social networks. Instead, during the actual
matching process the friend network information is used. While
technically, this is very inefficient it is the only possible way at the
time of writing. However, this workaround ensures that in the usually
continually expanding friend network of a user, the most current
version is used.

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Choice modelling
As a part of this research, a choice experiment was conducted. The
first goal was to test a certain hypothesis, the second goal being to
act as a technology demonstrator or prototype for the first version
of Pooll. Therefore, a dedicated web based questionnaire was
created which uses the Hyves API to gather data from the social
network. The data is used in the questionnaire to personalise the
questions.

The questionnaire can be accessed at http://www.pooll.nl/poll/

The questionnaire aims to find out the relationship between
ridesharing pickup behaviour and the personal connection between
the driver and the passenger that can be picked up. The hypothesis
is that the pickup propensity is influenced by friend level, with a gender, income and age. In the second part the choice situations
higher propensity for friends or known persons than for strangers. are a choice between driving alone (no ridesharing) or driving with
To find out what the relationship is, a choice experiment was
conducted.
someone else (ridesharing). These are paired questions, one
Experiment design question of a pair consists of picking up a friend, the other of
picking up one unknown passenger. The destination for both the
The questionnaire consists of two parts. The first part is about the
driver and passenger are assumed to be exactly the same.
personal attributes of the decision maker, the second part consists
of the actual choice situations. The personal attributes consist of

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The routes for driving alone or ridesharing are displayed on a map The respondents were asked to answer 20 choice situations. These
together with trip attributes consisting of travel time, departure time 20 questions consisted of 10 pairs of questions, each pair with
based on a preset arrival time minus travel time that is necessary identical route. The order of these routes was randomised so that
for the chosen alternative and travel cost based on distance in respondents were unlikely to recognise the routes as being a
kilometres multiplied by 20 eurocents. Because picking up a particular pair.
passenger will always increase travel distance and thus travel cost,
a trade-off situation was created by allowing the option to split cost
(50%-50%) in case of ridesharing. This option is however not
mandatory as picking up a friend might lead to the decision of not
splitting the travel costs.

15

Experiment testing
Welcome
After building a prototype of the questionnaire a usability test was
conducted to test the interface and workflow. The results lead to
Version changes in the instructions pages and the interface accompanying
Selection the choice situations. Furthermore, the graphical design was
adjusted to create a more pleasing user experience, increasing the
likelihood of joining the experiment and subsequent completion.
Instruction Instruction
Personal Qs Personal Qs
To act as a technology demonstrator it seemed wise to actually
connect the questionnaire to the social network. In this case the
Personal Personal Dutch social network Hyves was chosen because it has a large
Attribute Attribute
Questions Questions national user base (52% Dutch of population). However, to account
for non-users of the social network a second version of the
questionnaire was developed in parallel. Both versions can be filled
Instructions in using the same interface. Respondents can select which version
Hyves API
Hyves
Login
Login of the questionnaire they would like to participate in at the start of
the questionnaire. The final questionnaire workflow is shown in the
diagram.
Instructions Instructions
Map (choice) Map (choice)
Questions Questions Questionnaire distribution
Because the questionnaire can only be completed electronically it
Choice Choice
Situations Situations was chosen to invite respondents by email. The personal network
(Map) (Map) as well as the Hyves community was asked to fill in the
questionnaire. The Hyves API account manager also provided an
advertising budget of 400 Euros in order to advertise people to fill in
Results
the questionnaire. The adverts were initially targeted to persons
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between 10 and 70+. However it seemed that users aged 10-20 denominator being the shortest route path between origin and
years were predominant in the page views, but did not at all join the destination.
test. At the same time persons of the personal network of the author In the questionnaire the distances were automatically calculated by
did complete the experiment easily, only by inviting via email. the Google Maps API based on the provided waypoints.
Therefore the target for the ads was adjusted to 20-55 years of age.
Also different ads were tried in parallel to different target groups. The lower bound of df is 1 meaning that the chosen route is the
This resulted in a higher click-through rate but not in any significant shortest route possible in term of travel time, which of course
increase in experiment completion. occurs when the respondent drives alone or when the pickup
location is exactly on the route (starting and stopping is not taken
into account). The highest value of df in the questionnaire was 3.6,
Experiment results the lowest value 1.26. The two question pairs were observed
individually, the first group being the ridesharing with friends and
In total 58 respondents successfully completed the questionnaire.
the second one ridesharing with strangers.
Of these respondents it seems that only a small fraction (10%) has
filled out the questionnaire due to advertising on Hyves.
For all respondents, the detour factors based on their selection
In order to test the hypothesis of the pickup propensity increasing
were averaged. The percentile increase is the time multiplier which
when a friend rather than a stranger has to be picked for share ride,
an average respondent states he or she is willing to have in order to
the detour factor was picked as a suitable measure. The detour
pickup either a friend or a stranger. As seems likely, drivers want to
factor is defined as

df =
ℎ
‘go the extra mile’ for picking up a friend. The difference between a

ℎ
friend and a stranger in terms of time is about 17%.

Friend Stranger Difference

With df being a ratio called the detour factor, the numerator being Average detour factor (time) 23% 6% 17%

the travel time for the chosen route between origin and destination
(possibly via the pickup location of passenger) and finally the Some data was also gathered about the respondents’ gender and
subsequent pickup behaviour. Analysis confirms another

17

assumption, namely that males are more likely to engage in revealed some problems with the used utility function which
ridesharing with unknown passengers. included all personal attributes. The optimization algorithm did not
converge and could therefore not generate usable attribute
Friend Stranger coefficients for the utility function.
Male 21% 8%
Female 23% 2% Consulting the BIOGEME internet users group revealed some ways
to counter this problem. The most frequent reason for the problem
Another observation could be that females are more likely to was that the utility function is just too complicated and the package
engage in ridesharing with friends than males, the difference is cannot generate the coefficients. The solution is to simplify the utility
however not significant given the low total number of respondents function, i.e. decrease the number of choice attributes.
and gender split (n=58 of which 34 male and 24 female).
In the next BIOGEME runs, the attributes were removed one by one.
Concluding, an average detour of 25% in terms of time for picking This way the algorithm used by BIOGEME was able to converge to
up a friend seems acceptable. This information can be used in the a result and to provide the attribute coefficients of the alternatives.
filter algorithm of Pooll, which will broaden the constraints of a trip The utility function and parameters are shown in the appendix
match, provided the matched users are friends of each other.
The devised utility function shows that on average (friends and
The detour is purposely expressed as time, because passenger strangers combined) ridesharing is likely to occur more with
pickup in clogged urban traffic may require a detour in distance in increasing age and that income is of relative little importance.
terms of a few percent, but an increase in time of a multitude. However, a further analysis by plotting both age group and income
Therefore, travel time is selected for this measure to account for this versus detour factors reveals the following when plotted as linear
variability. trend line of a scatter plot.

In order to create utility functions of both alternatives based on the
gathered data, the software package BIOGEME (Bierlaire, 2007)
was used. However, the first runs of the BIOGEME package

18

CONVERGE assessment
The assessment and validation is a key step in the development and implementation process. The means focus of this step is deciding
whether and how the Pooll service should be technically implemented and the verifying that the application performs as expected based on
the results.

Application description

Application Technologies Function/service Verification
Interface for controlling user account, Functional testing, unit testing and
Web based client Software module add, editing, deleting matches and compatibility testing (cross browser)
general communication between users. Regression testing per iteration
Software module Functional testing, unit testing and
Identical, plus added wireless connection
compatibility testing (cross platform,
Mobile software client Wireless connection and localisation by GPS. Plotting map
Windows Mobile, Symbian and Apple
GIS data of users and trips
Localisation (GPS) Iphone) Regression testing per iteration
Software module On the fly trip matching, filtering, Load testing (performance + stress)
Trip matching module
Optimisation algorithms scheduling, optimising carpools Integration testing

Database manager (DBMS) Storing, retrieving data used for the trip
Load testing (performance + stress)
Database module matching modules and the user profile
Database servers Integration testing
system
Email servers Communication between different users, Conformance testing(SMS)
User communication module
SMS servers system to cellphone Integration testing

Connection to the API of the social Conformance testing(API connection)
Social network API module Software web service module
network. Integration testing
E-payment service provider Transactions of trips, keeping user Conformance testing(E-payment)
Payment
Financial management balances, transactions to bank accounts Integration testing

19

Assessment objectives, assessment category and user groups

Assessment category Assessment Objective User groups involved in validation

• Very high uptime
• High availability
Technical Assessment • Low latency System operator, Software developers
• High redundancy
• Fast trip matching algorithm
• Increased vehicle occupancy
• Decreased traffic intensities
Impact assessment • Increased demand for pickup/dropoff stations System operator, Users
• Decreased user travel flexibility
• Increased driver distraction
• Providing high ease of use
User acceptance assessment • Providing efficient and reliable communication System operator, Users, Software developers
systems for invitation and matching
• Providing highly secure payment system
Financial assessment • Providing real-time transactions System operator, E-payment provider
• Providing highly redundant setup

20

Decision makers, user groups involved and assessment objectives (two descision makers)

Application Decision Maker Assessment Objectives

• Increasing vehicle occupancy
• Decrease cost per travelled unit of distance
• Improving safety of ridesharing
Web based client End user
• Improving reliability of ridesharing
• Increasing flexibility of ridesharing
• Increase mobility options
• High performance of the matching algorithms
Trip matching module System operator (Pooll) • Achieve high quality of information to Pooll users
• Providing a high probability of trip match

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Expected impacts Assessment method
Impacts Target Increased vehicle
System Impact* Impact
expected groups occupancy
Equip and monitor a test group
Increased
Driver, vehicle Mobile client Assessment method of users
vehicle ++
manufacturer software
occupancy
Matched trips, vehicle
Indicator(s)
occupancy
Increased
• Trip matching
demand for
Road operator software module +/- Reference case Before and after
pickup/dropoff
• Optimisation
stations

Data collection Through application
Increased
• Mobile client
driver Driver -
software
workload Conditions of measurement Homogeneous group

(* ++ very positive; + positive; 0 neutral/uncertain; - negative; -- very negative) Large sample size (1000+) in
Statistical considerations order to have some probability
of matched trips
Usage data is sent to server
Measurement plan
then analysed

22

Conclusion
This investigation into combining social networks into a
ridesharing system seems quite promising. This paper provides
a description, high-level design and high-level implementation
schedule for the development of such a social network-attached
ridesharing system.
Choice modelling evolved into a questionnaire which has the
basic client-side technical properties of the proposed client
(version 1) of the software.

The choice modelling revealed that drivers are willing to
encounter about 17% extra travel time as a detour to pick up a
friend rather than to pick up an unknown person. The addition
of a social network might therefore be a key part of a new
ridesharing system. Furthermore, this addition will increase (at
least perceived), safety, thrust and reliability.

Research into user needs for users of a ridesharing system
needs to be conducted. Moreover, extra research should be
conducted to gain insight into the psychological factors that
increase trust and perceived safety.

23

Literature
Dailey, D.J., Loseff, D., Meyers, D. (1999) Seattle smart traveler:
Bierlaire, M. (2003). BIOGEME: A free package for the estimation of
dynamic ridematching on the World Wide Web. Transport. Res. Part
discrete choice models , Proceedings of the 3rd Swiss
C 7, 17–32
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24

Appendix
Utility function and parameters
Driving alone
0 -0.00565*ageGroup -0.001*incomeGroup -0.0289*aloneTravelTime -0.183*aloneTravelCost

Ridesharing
1.05 + 0.00565*ageGroup -0.001*incomeGroup -0.0819*carpoolTravelTime + 0.00878*carpoolTravelCost

25

Combining Ridesharing& Social Networks

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