A simple open source framework for carpools within companies reduces traffic in daily commute and fosters ridesharing acceptance.
Guidance on collaborative pilot
This is a pilot test of a new, collaborative approach for getting work done in the Climate CoLab. It will run during March and April of 2012.
Just like in the 2011 activities, anyone can create a proposal. But there is also a community proposal, where members are encouraged to work together in a collaborative way. Any member can contribute to the community proposal as long as they are logged in.
The community proposal is like a wiki, so the history of edits is tracked, and you can revert to prior versions of the proposal if desired.
Please also use the Comments to express your opinion on whether or not you would like to see this collaborative approach used in the Climate CoLab in 2012.
Feel free to organize the proposal as you see fit. One thoughtâ€”it's good to have a brief summary of the overall proposal at the top, as an aid to readers.
Car pooling or ride sharing is the usage of free seats for passengers who would like to drive the same route at the same time. It’s an old idea. The main reason why car pools haven’t been successful on a broad scale so far is simply the lack of this information combined with a low matching probability and a lack of trust [1, 2, 3]. Members of the eBay Green Team have developed a lean concept which tackles these issues:
- information gap
- matching probability
- lack of trust
Closing the information gap
That’s easy. You just need to gather the driver’s route information and departure times in a data base and make it available to potential passengers. With mobile devices this can be done on the fly.
Increasing the matching probability
That’s a little bit trickier to solve: What is the probability that somebody will drive exactly the same route at the same time? Between two points in a wide area, the matching probability might be 0%. Whereas between two exits on a highway it will be 100%: every other driver goes exactly the same route between the two exists. The area has an infinite number of points with an n:m relationship whereas the highway is a fixed route with just two points in a 1:1 relationship: the exits. So we can increase the matching probability via a limitation of route points. If we limit a car pool to a company one fixed end point in the route is shared by all participants: the office - an 1:n relationship with 1 office and n starting points. If we also reduce the number of starting points to a few highly frequented ‘hubs’ such as bus stops, the matching probability increases again.
Would you feel comfortable to give someone completely unknown a lift? Probably not. But what about giving a lift to a colleague? Probably you would. So limiting a car pool to a closed society such as a company will also solve the trust gap. Limiting car pools to companies will assure that it works well on a small scale - sowing the seeds for large scale carpools.
Category of the action
Reducing emissions from transportation
What actions do you propose?
A pilot system is already available connects drivers and passengers based on time and routes. It also provides complementing public transport schedules in order to efficiently combine individual and public transport modes. It creates synergies by leveraging proven concepts of simplification and trust in closed societies in combination with Open Source information technology. Companies can use the system for all of their offices by simply joining the shared system or set up their own system.
From a technical point of view it consists of:
- A database for user management and matching car pools. It is designed for multiple companies and with multiple office sites.
- The software providing web services for data exchange between the database and the user interfaces, i.e. the Web, cell phones via an Asterisk IVR and Outlook® calendars for recurring appointments. The web servises also allow to read data feeds of public transport and taxi services as well as a data exchange with other car pools in order to leverage network effects.
- Server hosting for the database, the web services, the IVR and the text message service.
To make significant CO2 reduction via Open CarPool happen, many large companies need to make use of the system. This requires a robust and user-friendly system as well as a mature deployment based on the lessons learned from the crowd.
To achieve this, the following actions are recommended:
- Integration of public transport as an alternative mean of transportation in case no car pool is available. This can be done using the Google Transit protocol  which allows public transport companies to provide their bus and train schedules for other applications such as Google Maps via standardized files. The GTFS-realtime protocol may also be utilized to share carpool data with other carpool and route planing applications.
- Enhance the system via the integration of real-time route planning capabilities considering current traffic flow and public transport delays and so better predict pick-up and arrival times. .
- Enhance the architecture to support multiple languages and better reporting.
- Integration of taxis as a backup.
- Add additional user interfaces such as iPhone or Android apps, route planners or add-ons for car navigation systems. Here is a brief description to illustrate the usage of the simple low-tech phone/SMS interface:
Offer a ride:
Request a ride:
- Engage scientists to estimate the CO2 saving potential in other regions, apply advanced technologies to enhance the system efficiency, e.g. by automated identification of relevant routes  and support the sociological aspects of this socio-technical system.
- Conduct research and run pilots in different countries and cultures. Developed countries with a high number of cars per capita bear a high CO2 saving potential. But considering the immense growth of urban population and traffic in the BRIC states (Brazil, Russia, Inida and China), these countries might play an even bigger role.
Deployment and scaling:
- Create a playbook to enable companies to successfully implement it off the shelf with low effort.
- Develop and continuously improve an internal communications guide for companies implementing a car pool. Gaining the critical mass - or more precise the critical density is key for a sufficient matching probability and a successful implementation. Several attempts to establish car pools failed due to a too low matching probability . Applying the 1:n relationship in a closed company car pool with the office as a common destination at common shifts, increases the matching probability significantly . Nevertheless, a high number of participants from the first day on will be key.
- Develop a marketing campaign and press relations in order to make additional companies aware of the system and its benefits.
- Test-run it on several locations to gain further experience and best practices and drive continuous improvement of the system and the playbook.
- Allow companies to provide professional services around hosting, consulting, deployment or customer support.
- As soon as the pilots have been successful: promote the system and scale it globally. Cultural differences may play an important role . Companies have the ability to shape company-internal cultures and so positively influence the culture in countries where car pooling might not be common. Former employees who move to another employer may plant the seed at their new office. Car pooling may become more common within closed societies and so lay the ground for a widespread acceptance.
Through the joint development of the system and joint utilization of hosting and support infrastructure, the companies will benefit from economies of scale. In case multiple companies sharing the same corporate park premises 'pool their carpools' they will benefit from additional network effects.
Who will take these actions?
Two groups of stakeholders will take the actions:
- The further development and marketing of the open car pooling system requires an interdisciplinary and complementing team of the open source community from all over the world. It will require skills and experiences in the following areas:
- Multipliers such as marketing professionals , journalists or politicians - to create awareness at the primary audience that this system exists free of charge and offers benefits for all
- Software developers – to create apps for different mobile devices, integrate public transport schedules and route planners, build user-friendly interfaces for Open Street Map or Google Maps and scheduling tools, further develop the data exchange protocol, build interfaces to car navigation systems ... and so on
- Traffic experts - from different regions with insights in local public transport and the taxi business to avoid conflicts of interests with these groups and assure synergies in an optimal modal split.
- Language and country experts – to support translations, localizations and regional adjustments to legal requirements and cultural differences
- Scientists to give guidance on technical, socio-economical and environmental questions
- Evangelists in companies and organizations with the respective size - to check its feasibility and convince decision makers to give it a try
- Open Source project managers – to coordinate the efforts and keep the team well informed and motivated
- The target audiences for the usage and benefit creation of Open Car Pools are companies and organizations with 500+ employees working on one premise. At these companies the facilities department, any kind of Green Teams or the Corporate Social Responsibility departments will probably have the best chance to get it started and keep it rolling.
Where will these actions be taken?
The further development and marketing will take place in the open source and Internet community
The usage and creation of its benefits will take place in companies and organizations across the globe. Especially premises and business parks in the outskirts of cities with poor public transport will benefit mostly but also offices in inner cities where parking space is rare.
How much will emissions be reduced or sequestered vs. business as usual levels?
The daily commute to work is one of the main traffic drivers and therefore a significant cause for CO2 emissions.
Based on data from the German Ministry of Transport, Building and Urban Affairs  we estimated an annual reduction of CO2 emissions of 20 million tons per year – just for Germany. This estimation is based on 41 mio. cars driving 580 billion kilometers p.a., a CO2 emission of 175 g/km in average and the assumption that we can increase the average car occupancy by 0.2 passengers/car .
The CO2 reduction on a global level needs to be determined based on car usage patterns and car occupancy in different regions. Under the very conservative assumption that Germany accounts for a maximum of 2% of the global population and may have at most a 10 times higher CO2 reduction potential than on global average, the global CO2 reduction potential through car pooling will be ~100 million tons of CO2 per year or even more - considering the traffic increase in the BRIC countries.
What are other key benefits?
Benefits for our environment:
- Less cars on the street lead to lower resource consumption, less noise and an improved traffic flow through less congestions 
- Awareness that lean consumption and environmental-friendly behavior can also save money
Benefits for drivers and passengers:
- Shared commuting costs
- Permission to use High Occupancy Vehicle (HOV) lanes
- Relationship building and latest informal news on projects from other departments
Benefits for the participating companies:
- Reduced need for parking space
- Improved relations and informal cross-departmental communication between colleagues
- Reduced CO2 emissions for an improved GHG balance sheet
- Improved green company image and Corporate Social Responsibility
What are the proposal’s costs?
Only economically viable systems will succeed. Therefore the revenues side of the system is as important as the cost side. The main monetary benefit will be the savings through carpooling. Depending on the company’s monetization model these savings may be shared between drivers and passengers with the share to be paid by the passenger. The driver’s revenues need to be worth the inconvenience to pick up passengers. Additional revenues for third parties can be created via complementing services, implementation support or application hosting.
Development cost so far were ~$50,000. They are written off. Further development effort may be covered by the Open Source community free of charge.
Set up effort
Each set up of a new company or office location will cause effort:
- In case OpenCarPool should not be used as Software as a Service (SaaS): PostGre SQL Database, Python, and Asterisk servers and set up of the SMS service: ~2 days
- Initial set up of the company and users: ~0.5 days
- Identification and configuration of highly frequented routes: ~1 day
- Integration into the company’s intranet and reporting: at least 0.5 days
- Training for administrators and users: 1 day
Based on these assumptions one time set up costs will be up to $5,000/company. Internal communication, training effort, customization and kick-off incentives to gain the critical mass may cause additional costs. 
Fixed running costs: In the SaaS model the server hosting is about $50/month. For user administration and support an effort of 1 day/month for a 500 user population is expected which can be outsourced for ~$300/month. This totals up to ~$350/month.
Variable running costs: in a shared cost model, driver compensations will be charged from the passenger. Common fees range between $0.20 to $0.40/mile. Text message fees: depending on the system configuration. Text messages start at $0.05/SMS and economies of scale may apply.
The idea was born back in 2008 when a strike in public transportation led to an improvised intranet car pool at eBay’s Berlin office. In 2009 a prototype of the software has been finalized and tested successfully. The gathered improvement suggestions led to user interfaces for basic cell phones, intranet pages and Outlook® calendars. Just when the roll out was about to begin a reorganization hit the site and most supporters left the company. The concept went asleep in the drawer. Now the site is prospering again and it is time to wake up the concept again. In order to maximize the impact for our environment it will now be shared with the community as Open Source.
The following milestones are planned:
- Documentation of the system and upload to Sourceforge.net for the Open Source community
- Finalization of the playbook for participating companies
- Release of the test environment for other companies:
- Re-start of the system at several office sites of a leading eCommerce company
Other development activities are heavily dependent on the contribution of the Open Source community as well as the cooperation with existing car pool companies or navigation system providers.
Proposals with some relation to the OpenCarPool concept within the Climate CoLab are:
- Public transport as the only way of everyday commute – which is not what we propose. We see public transport as a very important but complementing means of transport.
- Sustainable Digital Dividend (driverless cars) – which could be integrated into the information system to automatically pick up potential passengers
- Smart Mobility to the 21st century – which would be a potential additional user interface for the car pooling information
- Thermodynamics of human mobility – which might provide essential information about where to locate hubs with a high matching probability
 Michael Buchmann, Stephan Hartwig
Empty Seats Travelling
Nokia Research Center (2007)
 Francesca Pick
Why has carpooling taken off in Europe, but not the U.S.?
 Jürg Artho, Armida Wegmann, Heinz Gutscher
Machbarkeitsstudie: Ride Message Service RMS
Universität Zürich (2007)
 General Transit Feed Specification Reference (2013)
 Alameda County Congestion Management Agency
RideNow! Evaluation Draft Report
 G Correia, JM Viegas (Lisbon Technical University)
Matching via clubs: A conceptual model for carpooling systems simulation
Journal of Simulation (2009)
 Wen He, Deyi Li, Tianlei Zhang, Lifeng An, Mu Guo, Guisheng Chen (Tsinhua University, Beijing, China)
Mining regular routes from GPS data for ridesharing recommendations
Proceedings of the ACM SIGKDD International Workshop on Urban Computing (2012)
 Deutsches Institut für Wirtschaftsforschung DIW (Editor)
Transport in Figures (2008)
 H. Dürholt et al. (Editor)
Strategien zur Erhöhung des Besetzungsgrades im PKW-Verkehr
Abschlussbericht zum FE-Projekt Nr. 70502/96 (1998)
 Pravin Varaiya
Effectiveness of California’s High Occupancy Vehicle (HOV) System
California PATH Research Report (2007)
A good overview on existing carpooling or ride sharing applications can be obtained at http://dynamicridesharing.org.
Do you want to see how all this works in more detail? Check out www.opencarpool.org