TY - JOUR
T1 - Intermodal Autonomous Mobility-on-Demand
AU - Salazar, Mauro
AU - Lanzetti, Nicolas
AU - Rossi, Federico
AU - Schiffer, Maximilian
AU - Pavone, Marco
N1 - Publisher Copyright:
© 2000-2011 IEEE.
PY - 2020/9
Y1 - 2020/9
N2 - In this paper we study models and coordination policies for intermodal Autonomous Mobility-on-Demand (AMoD), wherein a fleet of self-driving vehicles provides on-demand mobility jointly with public transit. Specifically, we first present a network flow model for intermodal AMoD, where we capture the coupling between AMoD and public transit and the goal is to maximize social welfare. Second, leveraging such a model, we design a pricing and tolling scheme that allows the system to recover a social optimum under the assumption of a perfect market with selfish agents. Third, we present real-world case studies for the transportation networks of New York City and Berlin, which allow us to quantify the general benefits of intermodal AMoD, as well as the societal impact of different vehicles. In particular, we show that vehicle size and powertrain type heavily affect intermodal routing decisions and, thus, system efficiency. Our studies reveal that the cooperation between AMoD fleets and public transit can yield significant benefits compared to an AMoD system operating in isolation, whilst our proposed tolling policies appear to be in line with recent discussions for the case of New York City.
AB - In this paper we study models and coordination policies for intermodal Autonomous Mobility-on-Demand (AMoD), wherein a fleet of self-driving vehicles provides on-demand mobility jointly with public transit. Specifically, we first present a network flow model for intermodal AMoD, where we capture the coupling between AMoD and public transit and the goal is to maximize social welfare. Second, leveraging such a model, we design a pricing and tolling scheme that allows the system to recover a social optimum under the assumption of a perfect market with selfish agents. Third, we present real-world case studies for the transportation networks of New York City and Berlin, which allow us to quantify the general benefits of intermodal AMoD, as well as the societal impact of different vehicles. In particular, we show that vehicle size and powertrain type heavily affect intermodal routing decisions and, thus, system efficiency. Our studies reveal that the cooperation between AMoD fleets and public transit can yield significant benefits compared to an AMoD system operating in isolation, whilst our proposed tolling policies appear to be in line with recent discussions for the case of New York City.
KW - Autonomous vehicles
KW - networks
KW - optimization
KW - public transportation
UR - http://www.scopus.com/inward/record.url?scp=85090400993&partnerID=8YFLogxK
U2 - 10.1109/TITS.2019.2950720
DO - 10.1109/TITS.2019.2950720
M3 - Article
AN - SCOPUS:85090400993
SN - 1524-9050
VL - 21
SP - 3946
EP - 3960
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
IS - 9
M1 - 8894439
ER -