TY - JOUR
T1 - Autonomous mobility on demand: from case studies to standardized evaluation
AU - Alotaibi, Ebtehal T.
AU - Alhuzaymi, Thaqal M.
AU - Herrmann, J. Michael
N1 - This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) through the EPSRC Centre for Doctoral Training in Robotics and Autonomous Systems (CDT-RAS) [grant number EP/S023208/1].
PY - 2023/10/2
Y1 - 2023/10/2
N2 - We present an overview of ten case studies of Autonomous Mobility on Demand (AMoD) transportation systems, which are based on realistic data from different urban contexts. Comparing AMoD systems with Conventionally Driven Vehicles (CDV), the limits of reduction of vehicles, the cutting-back of parking spaces, and the increase of empty miles are investigated. As a result of introducing a shared fleet of autonomous vehicles (AV), the analysis demonstrated that 88%–93% of CDV are not required to meet realistic requirements. Parking spaces can be reduced by 83%–97%, while empty miles could be increased by 6%–15%. Nonetheless, fleet dispatching techniques that use the advanced optimization algorithms can reduce the ratio of empty miles by as much as 40%. Consequently, we propose a standard procedure for conducting intelligent transportation system studies (ITS) that can assist in the planning of traffic on urban environments at operational, tactical, and strategic levels. Furthermore, the case studies enabled us to design an Intelligent Transportation System Readiness Level (ITS-RL) scale to assess the realism of case studies, facilitate risk assessment, and provide guidance on how to incorporate AMoD system within a local context.
AB - We present an overview of ten case studies of Autonomous Mobility on Demand (AMoD) transportation systems, which are based on realistic data from different urban contexts. Comparing AMoD systems with Conventionally Driven Vehicles (CDV), the limits of reduction of vehicles, the cutting-back of parking spaces, and the increase of empty miles are investigated. As a result of introducing a shared fleet of autonomous vehicles (AV), the analysis demonstrated that 88%–93% of CDV are not required to meet realistic requirements. Parking spaces can be reduced by 83%–97%, while empty miles could be increased by 6%–15%. Nonetheless, fleet dispatching techniques that use the advanced optimization algorithms can reduce the ratio of empty miles by as much as 40%. Consequently, we propose a standard procedure for conducting intelligent transportation system studies (ITS) that can assist in the planning of traffic on urban environments at operational, tactical, and strategic levels. Furthermore, the case studies enabled us to design an Intelligent Transportation System Readiness Level (ITS-RL) scale to assess the realism of case studies, facilitate risk assessment, and provide guidance on how to incorporate AMoD system within a local context.
KW - autonomous vehicles
KW - autonomous shared mobility-on-demand
KW - smart cities
KW - smart mobility
KW - urban traffic
KW - simulation TRL
KW - ITS-RL
U2 - 10.3389/ffutr.2023.1224322
DO - 10.3389/ffutr.2023.1224322
M3 - Article
SN - 2673-5210
VL - 4
SP - 1
EP - 13
JO - Frontiers in Future Transportation
JF - Frontiers in Future Transportation
M1 - 1224322
ER -