Pooll is a ridesharing service that combines social networks to address issues of flexibility, trust, safety, and reliability. It allows travelers to announce trips that are matched with others' trips. When trips coincide, travelers are notified and can invite each other. Confirmed trips provide meeting details. Future versions include mobile apps and payment systems. Pooll innovates by using social networks to provide profile information to evaluate trustworthiness of other travelers and address the main problems preventing ridesharing adoption.
Carsharing, Ridesharing, Carpooling and all...Hugo Guyader
Slides used in a class on Car Sharing. I present existing studies on car sharing, ride sharing, P2P rentals and various other forms of mobility services.
Platform Business Models: A Case from Mobility ServicesHugo Guyader
Presentation of my paper at QUIS14, the 14th International Research Symposium on Service Excellence in Management Theme, in Shanghai, China.
Read more at: http://bit.ly/quis2015
Paper published in the Proceedings "Accelerate the Impact of Service Research" (abstract available at: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-117150).
Carpool In India ,carpool , car pool,carpool mumbai,carpool delhi,carpool mumbaicarpool
Carooling is only option of reducing pollution and saving our environmet. Poolmycar.in offers corporate carpooling. So opt for this slogan" Car Pool Mind Cool"
This presentation was given to Broward County, FL Commuter Services in 2005. It is a basic explanation of what car sharing is, and how it works. Car Sharing 101!
Carsharing, Ridesharing, Carpooling and all...Hugo Guyader
Slides used in a class on Car Sharing. I present existing studies on car sharing, ride sharing, P2P rentals and various other forms of mobility services.
Platform Business Models: A Case from Mobility ServicesHugo Guyader
Presentation of my paper at QUIS14, the 14th International Research Symposium on Service Excellence in Management Theme, in Shanghai, China.
Read more at: http://bit.ly/quis2015
Paper published in the Proceedings "Accelerate the Impact of Service Research" (abstract available at: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-117150).
Carpool In India ,carpool , car pool,carpool mumbai,carpool delhi,carpool mumbaicarpool
Carooling is only option of reducing pollution and saving our environmet. Poolmycar.in offers corporate carpooling. So opt for this slogan" Car Pool Mind Cool"
This presentation was given to Broward County, FL Commuter Services in 2005. It is a basic explanation of what car sharing is, and how it works. Car Sharing 101!
Ride Sharing, Congestion, and the Need for Real SharingJeffrey Funk
Current ride sharing services are not financially sustainable. Although they provide more convenience than do taxi services, they are experiencing massive losses because they have the same cost structure as do taxis and thus must compete through subsidies and lower wages. After all, they use the same vehicles, roads, and drivers, and only GPS algorithms and phones are new.
They also increase congestion. Just as more private vehicles or taxis on the road will increase congestion, more ride sharing vehicles also increase congestion.
These slides describe new ways to use the technologies of ride sharing to reduce congestion along with costs while at the same time keeping travel time low. This can be done through changing public transportation systems or allowing private companies to offer competing services. For instance, current bus services, whether they are private or public, need to use the algorithms, GPS, phones and other technologies of ride sharing to revise routes, schedules and the premises that currently underpin public transportation. There is no reason a bus should be certain size, stop every 200 meters, or follow the same route all day. Algorithms and phones enable new types of routes in which designers simultaneously minimize time travel and maximize number of passengers transported per vehicle.hour.
Commission on Travel Demand Shared Mobility Inquiry: Policy optionsCREDSUK
Evidence Session 4
16 July, Royal Automobile Club
The fourth evidence session covered both the context in which the shared mobility inquiry sits and the policy options which could be deployed to accelerate sharing and other wider initiatives which they might connect to.
Bill Freeman, Chief Executive, Community Transport Association
The Commission on Travel Demand is an expert group established as part of CREDS (Centre for Research into Energy Demand Solutions) to explore how to reduce the energy and carbon emissions associated with transport.
Electric Mobility for All, Jeff Allen and Joel EspinoForth
Forth's Executive Director, Jeff Allen and guest speaker, Joel Espino, Environmental Equity Legal Council at The Greenlining Institute gave this presentation at the February 2019 webinar.
Transit Demand Management_Istanbul IETT Workshop 3_15 June 2015VTPI
Istanbul IETT Professional Development Workshop, #3 of 6
- Presenter: Todd Litman, Victoria Transport Policy Institute
- Assistant: Aysha Cohen, UCLA Institute of Transportation Studies Scholar
- Presentation Date: June 16, 2015
Presented at Communication World, Munich
- Intelligent networking of different means of transportation play a central role.
- Mobile devices are growing strongly - in number as well as functionality, to provide the opportunity for new business models
- Companies need to develop a mobile strategy and address the new challenges on a broad basis
By Andreas Hein
Truy cập http://macftu.vn để cập nhật những tin tức và quan điểm marketing mới nhất.
Báo cáo "Khơi nguồn tiềm lực thành phố" - Unlocking Cities dành cho khu vực Đông Nam Á, thực hiện bởi Uber và Boston Consulting Group (BCG)
CIC IWOM panel:Fudan professor Zou on The new sharing economy powered by onli...Kantar Media CIC
The case is Fudan professor Zou shared during CIC IWOM panel on The new sharing economy powered by online social network. He shared the case of Zipcar to explain the theory of sharing economy is the key cause of the success of social media.
Sharing 2.0 - collaborative consumption. The need to reinvent the personal Mobility systems in urban areas. Brief discription of Mobility sharing Systems and the importance of Shared Space and Public Space
These slides use concepts from my (Jeff Funk) course entitled Biz Models for Hi-Tech Products to analyze the business model for Uber’s taxi service. Uber’s service enables anyone to provide taxi services and it provides dynamic pricing for better matching of supply and demand. Its value proposition for potential drivers is the opportunity to work as driver on their own hours. Its value proposition for user to lower taxi fares during most times of the day and a higher supply of taxis (and higher prices) during peak demand. The customers are tech-savvy and smart phone users who value their time. Uber receives payments directly from customers and keeps a percentage of these payments as its income. Uber’s patents for a demand-price algorithm represent a barrier of entry and thus a method of strategic control.
Ride Sharing, Congestion, and the Need for Real SharingJeffrey Funk
Current ride sharing services are not financially sustainable. Although they provide more convenience than do taxi services, they are experiencing massive losses because they have the same cost structure as do taxis and thus must compete through subsidies and lower wages. After all, they use the same vehicles, roads, and drivers, and only GPS algorithms and phones are new.
They also increase congestion. Just as more private vehicles or taxis on the road will increase congestion, more ride sharing vehicles also increase congestion.
These slides describe new ways to use the technologies of ride sharing to reduce congestion along with costs while at the same time keeping travel time low. This can be done through changing public transportation systems or allowing private companies to offer competing services. For instance, current bus services, whether they are private or public, need to use the algorithms, GPS, phones and other technologies of ride sharing to revise routes, schedules and the premises that currently underpin public transportation. There is no reason a bus should be certain size, stop every 200 meters, or follow the same route all day. Algorithms and phones enable new types of routes in which designers simultaneously minimize time travel and maximize number of passengers transported per vehicle.hour.
Commission on Travel Demand Shared Mobility Inquiry: Policy optionsCREDSUK
Evidence Session 4
16 July, Royal Automobile Club
The fourth evidence session covered both the context in which the shared mobility inquiry sits and the policy options which could be deployed to accelerate sharing and other wider initiatives which they might connect to.
Bill Freeman, Chief Executive, Community Transport Association
The Commission on Travel Demand is an expert group established as part of CREDS (Centre for Research into Energy Demand Solutions) to explore how to reduce the energy and carbon emissions associated with transport.
Electric Mobility for All, Jeff Allen and Joel EspinoForth
Forth's Executive Director, Jeff Allen and guest speaker, Joel Espino, Environmental Equity Legal Council at The Greenlining Institute gave this presentation at the February 2019 webinar.
Transit Demand Management_Istanbul IETT Workshop 3_15 June 2015VTPI
Istanbul IETT Professional Development Workshop, #3 of 6
- Presenter: Todd Litman, Victoria Transport Policy Institute
- Assistant: Aysha Cohen, UCLA Institute of Transportation Studies Scholar
- Presentation Date: June 16, 2015
Presented at Communication World, Munich
- Intelligent networking of different means of transportation play a central role.
- Mobile devices are growing strongly - in number as well as functionality, to provide the opportunity for new business models
- Companies need to develop a mobile strategy and address the new challenges on a broad basis
By Andreas Hein
Truy cập http://macftu.vn để cập nhật những tin tức và quan điểm marketing mới nhất.
Báo cáo "Khơi nguồn tiềm lực thành phố" - Unlocking Cities dành cho khu vực Đông Nam Á, thực hiện bởi Uber và Boston Consulting Group (BCG)
CIC IWOM panel:Fudan professor Zou on The new sharing economy powered by onli...Kantar Media CIC
The case is Fudan professor Zou shared during CIC IWOM panel on The new sharing economy powered by online social network. He shared the case of Zipcar to explain the theory of sharing economy is the key cause of the success of social media.
Sharing 2.0 - collaborative consumption. The need to reinvent the personal Mobility systems in urban areas. Brief discription of Mobility sharing Systems and the importance of Shared Space and Public Space
These slides use concepts from my (Jeff Funk) course entitled Biz Models for Hi-Tech Products to analyze the business model for Uber’s taxi service. Uber’s service enables anyone to provide taxi services and it provides dynamic pricing for better matching of supply and demand. Its value proposition for potential drivers is the opportunity to work as driver on their own hours. Its value proposition for user to lower taxi fares during most times of the day and a higher supply of taxis (and higher prices) during peak demand. The customers are tech-savvy and smart phone users who value their time. Uber receives payments directly from customers and keeps a percentage of these payments as its income. Uber’s patents for a demand-price algorithm represent a barrier of entry and thus a method of strategic control.
Startup Stage - Transportation - Presentation by Gunnar Froh, Founder & CEO of Wunder Urban Carpooling at the Axel Springer NOAH Conference Berlin 2016, Tempodrom on the 9th of June 2016.
As a pioneer within the radio taxi service in India, Meru Cabs once again launched Carpool by Meru, an initiative to make people travel together and give back to others around them.
The Digital Marketing campaign, #DilKaDarwazaKholo, revolved around the sentiment of giving back to people by offering them a ride whilst also enjoying the company of others.
Digital marketing solutions right from social media campaigns to emailers, SMS pushes and banner ads created an outreach providing Meru Cabs with 3x the amount of downloads for its app, whilst successfully creating a MindShift amongst the Indian audiences towards sharing a car versus riding alone.
Lyft in a New Era of Technology-Enabled Mobility: Implications for Policy and...Emily Castor
Over the last two and a half years, Lyft has achieved mass adoption extremely quickly, heralding a new era of consumer transportation behavior based on smartphones and “access over ownership.” Now, as Lyft begins to mature, it is reaching the density necessary to achieve real-time dynamic carpooling, with major implications for congestion reduction and environmental benefit.
This presentation provides insight into the development of this new industry, how it will impact mobility and consumer behavior, and the implications for transportation planners and policymakers as Lyft continues to evolve.
Real time city-scale taxi ridesharing
Do Your Projects With Technology Experts
To Get this projects Call : 9566355386 / 99625 88976
Visit : www.lemenizinfotech.com / www.ieeemaster.com
Mail : projects@lemenizinfotech.com
PMBOK fifth edition data flow diagram by englishKose Jumnichi
Develop Project Management Plan Data Flow Diagram.
Almost processes are topological sorted.
This figure is drawn with a vertical line "the new data model"
(work performance data / infomation / reports,and "Change requests").
One page of PMBOK5 edition Data flow Diagrams by Japanease Broked english.
PMBOK6 editions is heare https://www.slideshare.net/kosejumnichi/pmbok-six-editiondataflow-diagram-by-english-a3-printable
CORSA: An Open Solution for Social Oriented Real-time Ride SharingGreenapps&web
Simone Bonarrigo, Vincenza Carchiolo, Alessandro Longheu, Mark Philips Loria, Michele Malgeri and Giuseppe Mangioni
The combination of the interest in environmental questions on one hand and the massive use of web based social networks on the other recently led to a revival of carpooling. In particular, the exploitation of social networks promotes the information spreading for an effective service (e.g. reducing the lack of confidence among users) and endorses carpooling companies via viral marketing, finally acting as a basis for trust based users recommendation system In this work we outline CORSA, an open source solution for a real time ride sharing (RTRS) carpooling service that endorses the role of social networks by using them as a conveying scenario for the virtual credits reward mechanism CORSA is based on.
Submitted Publication in the Transportation Research Record
November 23, 2015
ABSTRACT
A pilot program in Austin, Texas, tested the practicality of integrating a real-time ridesharing application with a toll operator to process toll discounts for carpools. The toll discounts appeared on monthly toll transaction statements. The program lasted for almost a year on the 183A Toll Road and the US 290 Manor Expressway. Travelers used a smartphone application to track, record, and submit their trips for discounts. Two-person carpools that used the application received a 50 percent discount, and carpools of three or more people could travel toll-free. The program was a partnership between the Central Texas Regional Mobility Authority, the local toll systems operator, and a private ridesharing vendor. Back-office processes matched trip data from the smartphone application to transactions recorded by the toll systems. A total of 95 unique drivers were provided toll rebates for 2,213 trips during the 10.5-month pilot period. Most trips during the pilot program were rebated for two-person carpools. Individual driver behavior varied considerably. A select few drivers had a high number of carpool trips, while others took a sporadic or infrequent trip. Drivers took a median of 7 trips during the pilot. Future rideshare programs should consider showing higher-dollar rebates that represent annual savings to incentivize behavior. Timely feedback was found to be an important factor for success. Additionally, program sponsors should provide positive customer service and engage users when problems exist that are not under their direct purview.
Smart Card: A study of new invention on bus fare in Dhaka cityMd. Abdul Munem
Technology is developing day to day. So we have to be familiar with technology. Digital payment system
is one of them. Our government will launch a pilot project for transportation under 22 buses on 42 routes.
It will be better if the smart card will included in that project. In the term paper I have focused the problems
we faced on public transport.
Keolis, a major player in digital mobility, has announced at the 2017 Netexplo Forum the results of its first international digital mobility observatory.
The observatory targeted 13 smart cities across five continents, to better understand the impact of the digital revolution on the use of public transport.
Three common expectations and 10 fundamentals for the passenger experience of tomorrow have emerged from the studies.
This research illustrates Keolis’ proximity with cities, its commitment to enhance the passenger experience, and to create the smart transport networks of tomorrow.
Research & Innovation and user-centered solutions have been the hallmark of our growth, reflecting our culture of technology and shared ideas. Since 2007, we have fostered a culture of innovation and creativity by delivering the solutions that our clients need to succeed.
Presentation 1: Web 2.0 - Leading Applications in Government
Presenters:
Eric Bristow - Senior Manager, Deloitte Consulting
Doug Shoupp – Principal, Deloitte Consulting
Ecomoco aims to be a representative body for co-mobility and shared-moblity service providers in Europe.
This Charta is a draft document. It is sharing the principles of Collaborative Mobility.
Similar to Combining Ridesharing& Social Networks (20)
Manypedia: Comparing Language Points of View of Wikipedia CommunitiesPaolo Massa
Manypedia is at http://www.manypedia.com
These slides have been presented by Paolo Massa at WikiSym, 8th International Symposium on Wikis and Open Collaboration, 29 August 2013, Linz, Austria.
Manypedia is joint work of Paolo Massa and Federico Scrinzi (and it is open source too!)
The paper is at http://www.gnuband.org/papers/manypedia-comparing-language-points-of-view-of-wikipedia-communities/
If you like Manypedia and you have a chance, don't forget to cite our paper, thanks!
Presentazione di Paolo Massa nell'ambito del Seminario residenziale “L’approccio territoriale tra aiuto e crescita” - 22-23 giugno 2012 - Villa Flangini - Asolo - Organizzato dal SerAT (Servizio Alcologia e Tabagismo Ulss 8)
Con il contributo di ACAT-ULSS 8 onlus e Cooperativa Sonda. Con il patrocinio di Alcologia Ecologica
DESIGN PRINCIPLES OF WIKIS AND THEIR IMPACT ON KNOWLEDGE EXCHANGE PROCESSES Paolo Massa
DESIGN PRINCIPLES OF WIKIS AND THEIR IMPACT ON KNOWLEDGE EXCHANGE PROCESSES
From Analyzing Wiki-based Networks to Improve Knowledge Processes in Organizations by Claudia Müller, Benedikt Meuthrath, Anne Baumgraß Slides by Paolo Massa
Collective Memory building in Wikipedia: the case of North African uprisingsPaolo Massa
Paper presented at Wikisym 2011, 7th International Symposium on Wikis and Open Collaboration
Read the paper at http://www.gnuband.org/papers/collective_memory_building_in_wikipedia_the_case_of_north_african_uprisings/
Authors: Michela Ferron, Paolo Massa
Abstract:
Since December 2010, a series of protests and uprisings have shocked North African countries such as Tunisia, Egypt, Libya, Syria, Yemen and more. In this paper, focusing mainly on the Egyptian revolution, we provide evidence of the intense edit activity occurred during these uprisings on the related Wikipedia
pages. Thousands of people provided their contribution on the content pages and discussed improvements and disagreements on the associated talk pages as the traumatic events unfolded. We
propose to interpret this phenomenon as a process of collective memory building and argue how on Wikipedia this can be studied empirically and quantitatively in real time. We explore and suggest possible directions for future research on collective memory formation of traumatic and controversial events in Wikipedia.
Social networks of Wikipedia - Paolo Massa - Presentation at (2011). ACM Hype...Paolo Massa
The paper is at http://www.gnuband.org/papers/social_networks_of_wikipedia/
Wikipedia, the free online encyclopedia anyone can edit, is a live social experiment: millions of individuals volunteer their knowledge and time to collective create it. It is hence interesting trying to understand how they do it. While most of the attention concentrated on article pages, a less known share of activities happen on user talk pages, Wikipedia pages where a message can be left for the specific user. This public conversations can be studied from a Social Network Analysis perspective in order to highlight the structure of the “talk” network. In this paper we focus on this preliminary extraction step by proposing different algorithms. We then empirically validate the differences in the networks they generate on the Venetian Wikipedia with the real network of conversations extracted manually by coding every message left on all user talk pages. The comparisons show that both the algorithms and the manual process contain inaccuracies that are intrinsic in the freedom and unpredictability of Wikipedia growth. Nevertheless, a precise description of the involved issues allows to make informed decisions and to base empirical findings on reproducible evidence. Our goal is to lay the foundation for a solid computational sociology of wikis. For this reason we release the scripts encoding our algorithms as open source and also some datasets extracted out of Wikipedia conversations, in order to let other researchers replicate and improve our initial effort.
Scripts (Python) has been released as open source and networks datasets (in GraphML format) too. See http://sonetlab.fbk.eu/data/social_networks_of_wikipedia/
An Empirical Analysis on Social Capital and Enterprise 2.0 Participation in a...Paolo Massa
An Empirical Analysis on Social Capital and Enterprise 2.0 Participation in a Research Institute
by
Ferron Michela, Frassoni Marco, Massa Paolo, Napolitano Maurizio, Setti Davide
SoNet project - Fondazione Bruno Kessler (FBK) - Trento, Italy
http://sonet.fbk.eu
2010 International Conference on Advances in Social Networks Analysis and Mining
Odense, Denmark
August 09-August 11
ISBN: 978-0-7695-4138-9
The paper is at http://www.gnuband.org/papers/an_empirical_analysis_on_social_capital_and_enterprise_20_participation_in_a_research_institute
Supporting Collaborative Networks in Organizational Settings using an Enterpr...Paolo Massa
Presentation of the paper "Supporting Collaborative Networks in Organizational Settings using an Enterprise 2.0 platform" at NETSCI 09 International Workshop and Conference on Complex Networks and their Applications, Venezia, Italy. July 2009
The paper is at http://www.gnuband.org/papers/supporting_collaborative_networks_in_organizational_settings_using_an_enterprise_20_platform/
The Future of Work, Fun, and Being Social: an introduction to the nascent adv...Paolo Massa
How Internet Reputation Systems and
The Online Coordination of Offline Life are
Changing the Fundamental Structure of Society
v1.0 28 Feb 2007 Joe Edelman <joe>
on
CouchSurfing Int’l & Emergency Communities
CC-SA-BY
Feedback Effects Between Similarity And Social Influence In Online CommunitiesPaolo Massa
SoNet Research Meeting presentation
Feedback Effects Between Similarity And Social Influence In Online Communities.
Authors: David Crandall, Dan Cosley, Daniel Huttenlocher, Jon Kleinberg, Siddharth Suri
Cornell University Ithaca, NY
2008 KDD: Proceeding of the 14th ACM KDD international conference on Knowledge discovery and data mining
#citations at 2010/04/09 from Google Scholar:44
Presenter: Paolo Massa, SoNet group, http://sonet.fbk.eu
Bowling Alone and Trust Decline in Social Network SitesPaolo Massa
In this paper we analyze the community of a social network site, Advogato. The peculiar characteristics of Advogato is that users can explicitly express weighted trust relationships among themselves. We conduct a longitudinal analysis of the trust network over a time period of 4 years, exploring the community as it grew from a knit circle of 300 users to an society of almost 6500 individuals. We report the changes over time of standard indexes in social network analysis such as clustering and degrees of separation. We then focus on specific measures about trust such as reciprocity and changes over time of average trust. A decline in trust is observed as the community grows. Following what we believe to be the first empirical analysis of trust evolution over time in a real community, we conclude suggesting how the availability of data about human relationships in social network sites is opening up the possibility of monitoring changes in trust in real time. In order to foster this research line, we released the datasets and the code we used in our analysis.
Fukuyama' trust - The role of trust and trust networks in the societyPaolo Massa
Presentation about how Fukuyama describes the concept of trust. NOT A PRESENTATION CREATED BY ME, I just placed it on slideshare in order to embed it in my blog.
4. 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
4
5. 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.
5
6. 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
8. 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
8
9. 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
9
10. 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
10
11. 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
11
12. 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
13. 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.
13
14. 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
14
15. 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
16. 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
16
17. 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
18. 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
19. 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
20. 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
21. 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
21
22. 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
23. 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
24. 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
Transportation Research Conference, Ascona, Switzerland.
Srinivasan, K.K. , Raghavender, P.N (1977). Impact of mobile
Bierlaire, M. (2008). An introduction to BIOGEME Version 1.7,
phones on travel: Empirical analysis of activity chaining,
biogeme.epfl.ch
ridesharing, and virtual shopping
Teal, RF (1987) Carpooling: who, how and why. TRANSP. RES. Vol.
2006, Transportation Research Record, 258-267
21A, no. 3, pp. 203-214.
Matthew J. Roorda, Juan A. Carrasco, Eric J. Miller (2009). An
Ferguson, E. (1997): The rise and fall of the American carpool:
integrated model of vehicle transactions, activity scheduling and
1970—1990. Transportation 24, 349–376
mode choice, Transportation Research Part B: Methodological,
Volume 43, Issue 2, Modeling Household Activity Travel Behavior,
Pages 217-229
24