Details
| Original language | English |
|---|---|
| Title of host publication | 2021 IEEE International Intelligent Transportation Systems Conference, ITSC 2021 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 2272-2277 |
| Number of pages | 6 |
| ISBN (electronic) | 978-1-7281-9142-3 |
| ISBN (print) | 978-1-7281-9143-0 |
| Publication status | Published - 2021 |
| Event | 2021 IEEE International Intelligent Transportation Systems Conference, ITSC 2021 - Indianapolis, United States Duration: 19 Sept 2021 → 22 Sept 2021 |
Publication series
| Name | IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC |
|---|---|
| Volume | 2021-September |
Abstract
Shared mobility systems such as ride-hailing services transform urban mobility and have the potential to increase the efficiency of road transport. In this paper, we examine the possibility to establish the collection and daily updating of highly dynamic environmental data as a side-business for autonomous ride-hailing companies. We suggest a rebalancing heuristic that lets the vehicles drive through as many roads of the city as possible to collect data without neglecting the ride-hailing customers. To quantify this routing scheme's effects, we perform a case study with 100 vehicles for 24 hours in Hamburg, Germany, based on an on-demand mobility provider's vehicle data. We observe a gain of gathered data of almost 28% while there is a service decline of 1.6% with respect to the number of served customers. If we want to increase the share of daily gathered data to 95% of the road network, we need at least 131 ride-hailing vehicles. The presented rebalancing policy is also transferable to other fleet service operations or regular commuting vehicles like taxis and buses.
ASJC Scopus subject areas
- Engineering(all)
- Automotive Engineering
- Engineering(all)
- Mechanical Engineering
- Computer Science(all)
- Computer Science Applications
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2021 IEEE International Intelligent Transportation Systems Conference, ITSC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 2272-2277 (IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC; Vol. 2021-September).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Environmental Data Collection as a Byproduct for Autonomous Ride-Hailing Services
AU - Frantzen, Leonie
AU - Liedtke, Patrick
AU - Graen, Timo
AU - Fiege, Andrea
AU - Nolting, Michael
AU - Nejdl, Wolfgang
N1 - Funding Information: ACKNOWLEDGEMENT The work was partially funded by the Federal Ministry of Economics and Technology, Germany, through the project “d-E-mand” (grant ID 01ME19009B).
PY - 2021
Y1 - 2021
N2 - Shared mobility systems such as ride-hailing services transform urban mobility and have the potential to increase the efficiency of road transport. In this paper, we examine the possibility to establish the collection and daily updating of highly dynamic environmental data as a side-business for autonomous ride-hailing companies. We suggest a rebalancing heuristic that lets the vehicles drive through as many roads of the city as possible to collect data without neglecting the ride-hailing customers. To quantify this routing scheme's effects, we perform a case study with 100 vehicles for 24 hours in Hamburg, Germany, based on an on-demand mobility provider's vehicle data. We observe a gain of gathered data of almost 28% while there is a service decline of 1.6% with respect to the number of served customers. If we want to increase the share of daily gathered data to 95% of the road network, we need at least 131 ride-hailing vehicles. The presented rebalancing policy is also transferable to other fleet service operations or regular commuting vehicles like taxis and buses.
AB - Shared mobility systems such as ride-hailing services transform urban mobility and have the potential to increase the efficiency of road transport. In this paper, we examine the possibility to establish the collection and daily updating of highly dynamic environmental data as a side-business for autonomous ride-hailing companies. We suggest a rebalancing heuristic that lets the vehicles drive through as many roads of the city as possible to collect data without neglecting the ride-hailing customers. To quantify this routing scheme's effects, we perform a case study with 100 vehicles for 24 hours in Hamburg, Germany, based on an on-demand mobility provider's vehicle data. We observe a gain of gathered data of almost 28% while there is a service decline of 1.6% with respect to the number of served customers. If we want to increase the share of daily gathered data to 95% of the road network, we need at least 131 ride-hailing vehicles. The presented rebalancing policy is also transferable to other fleet service operations or regular commuting vehicles like taxis and buses.
UR - http://www.scopus.com/inward/record.url?scp=85118450699&partnerID=8YFLogxK
U2 - 10.1109/ITSC48978.2021.9564467
DO - 10.1109/ITSC48978.2021.9564467
M3 - Conference contribution
AN - SCOPUS:85118450699
SN - 978-1-7281-9143-0
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 2272
EP - 2277
BT - 2021 IEEE International Intelligent Transportation Systems Conference, ITSC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Intelligent Transportation Systems Conference, ITSC 2021
Y2 - 19 September 2021 through 22 September 2021
ER -