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Ridesharing and crowdshipping Niels Agatz Dagstuhl 2016 New ways - - PowerPoint PPT Presentation
Ridesharing and crowdshipping Niels Agatz Dagstuhl 2016 New ways - - PowerPoint PPT Presentation
Ridesharing and crowdshipping Niels Agatz Dagstuhl 2016 New ways of business: collaborative consumption Make use of journeys that are already happening Low occupancy rate of cars (1.2-1.8) People: dynamic ridesharing Dynamic ridesharing
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Make use of journeys that are already happening
Low occupancy rate of cars (1.2-1.8)
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People: dynamic ridesharing
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Dynamic ridesharing features
- Dynamic: established on short-notice
- Non-recurring trips: different from carpooling
- Automated matching: different from online notice-boards
- Independent drivers: different from taxis
- Cost-sharing: variable trip related expenses
- Prearranged: different from spontaneous, casual ride-
sharing
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Various providers
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Freight: crowdsourced delivery
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Various providers
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Dynamic ride-share variants
Single driver Multiple drivers Single rider Multiple riders Easy (Bipartite Matching) Difficult (Routing) Difficult (Transfers) Difficult (Routing + Transfers)
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Who are the drivers?
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What motivates drivers?
Help others /neighbors / the community Save the environment Make some extra money
Different driver payment schemes: hourly payment, per mile,
per task…
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Business model of providers
Platform to create matches and arrange payments Platform takes a cut for providing the infrastructure Backup option to guarantee timely service?
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Critical success factors
Drivers: ↓ inconvenience Society: ↓ traffic and congestion Rider/ sender: ↓ costs ↑ speed, convenience, mobility 1.
Maximize the number of matched riders/ parcels
2.
Minimize total vehicle miles in system
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How to establish matches?
Centralized automated matching Decentralized approach
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Dynamics
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Driver considerations
How much time does the driver have available? Information exchange: departure time alone may not
suffice
- departure time flexibility?
- travel time flexibility?
- stops flexibility?
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Driver time information
Departure time Latest arrival time
direct travel time flexibility time window for matching Lead-time
Earliest Latest Announcement time
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How many stops is the driver willing to make?
One stop Two stops Task Driver
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Other considerations
friends ↔ strangers neighbors ↔ strangers Enable trust/ safety / reliability
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Ensure safety/ reliability
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Project 1: dynamic ridesharing
Two-way matching of drivers and riders Impact of dynamics Impact of role flexibility
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Project 2: stable rideshare matching
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Project 3: ridesharing meeting points
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Project 4: ridesharing flexibility
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Project 5: crowdsourced delivery
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Key challenges to make this work
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- 1. Building demand and supply
How to reach a critical mass fast? What incentives can be offered? How to organize the backup?
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- 2. Dealing with uncertainty
How to make sure that you have enough drivers when
you need them?
Dynamic incentives?
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- 3. Regulatory issues
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Work in progress
Simulation study based on actual traffic data Combined ridesharing and public transport Crowdsourcing with transfers
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Papers
Stiglic, M, Agatz, N.A.H., Savelsbergh, M.W.P. & Gradisar, M. (2016). The
Benefits of Meeting Points in Ride-Sharing Systems. Transportation Research. Part B, Methodological,
Agatz, N.A.H., Erera, A., Savelsbergh, M.W.P. & Wang, X. (2012). Optimization
for Dynamic Ride-Sharing: A Review. European Journal of Operational Research, 223 (2), 295-303.
Agatz, N.A.H., Erera, A., Savelsbergh, M.W.P. & Wang, X. (2011). Dynamic
Ride-Sharing: A Simulation Study in Metro Atlanta. Transportation Research. Part B, Methodological, 45 (9), 1450-1464.
X Wang, N Agatz, A Erera, Stable matching for dynamic ride-sharing systems,
ERIM Report Series Reference No. ERS-2015-006-LIS
Arslan, Alp and Agatz, Niels and Kroon, Leo G. and Zuidwijk, Rob A.,
Crowdsourced Delivery -- A Pickup and Delivery Problem with Ad-Hoc Drivers (February 2, 2016). ERIM Report Series Reference.
Stiglic, M, Agatz, N.A.H., Savelsbergh, M.W.P. & Gradisar, M. (2016). Making
Dynamic Ride-sharing Work:The Impact of Driver and Rider Flexibility
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