Decision Support Tool for Planning Neighborhood-Scale Deployment of Low-Speed Shared Automated Shuttles

Abstract

Increasing interest and investment in connected, automated, and electric vehicles as well as mobility-as-a-service (MaaS) concepts are paving the way for the next major transformation in transportation through automated and shared mobility. The initial excitement toward rapid deployment and adoption of automated vehicles (AVs) has subsided, and low-speed automated shuttles are emerging as a more pragmatic pathway for introducing automated mobility in geofenced districts. Such shuttles hold the promise to provide a viable alternative for serving short trips in urban districts with high travel densities. As interest in low-speed automated shuttle systems (to improve urban mobility) increases, the need for tools that can inform communities in relation to benefits or disadvantages of automated shuttle deployments is imminent. However, most of the existing transportation planning and simulation tools are not capable of handling emerging shared automated mobility options. This paper presents a microscopic simulation toolkit that can be used by cities and communities to plan for the deployment of low-speed automated shuttles systems, as well as other shared mobility options. Labeled as the Automated Mobility District modeling and simulation toolkit, the proposed decision support tool intends to help cities evaluate the mobility and sustainability impacts of deploying shared automated vehicles (SAVs) in geofenced regions. This paper describes the toolkit, as well as a sample scenario analysis for the deployment of low-speed automated shuttles in Greenville, South Carolina, U.S. Results from the scenario study demonstrate the effectiveness of the proposed simulation toolkit in planning for advanced mobility systems.

Mode Split Equilibrium Microsimulation Approach for Early-Stage On-Demand Shared Automated Mobility

“…The VEC is calculated using the detailed second-by-second driving cycles from SUMO along with the FASTSim simulation model. More details of the vehicle powertrain and model can be found in [ 5 ]; Vehicle travel time (VTT) in seconds for DTD, FXR, and CAR modes; Vehicle deadheading distance (VDH) in miles for DTD and FXR modes; Vehicle loading rate (VLR) for DTD and FXR mode. VLR defines the number of passengers onboard weighted by the vehicle distance traveled for all SAVs.…”

“…The VEC is calculated using the detailed second-by-second driving cycles from SUMO along with the FASTSim simulation model. More details of the vehicle powertrain and model can be found in [ 5 ];…”

“…In the short term, shared automated vehicles (SAV) [ 2 ] are being deployed in high-density geofenced neighborhoods (e.g., airports, university campuses, and downtown or uptown districts). Such deployments are labeled as automated mobility districts (AMDs), defined as district-scaled deployments of shared and automated mobility services to realize the full benefits of SAV technology in the near term [ 3 , 4 , 5 ]. AMDs have the dual advantage of serving as a cost-effective solution to short- and medium-distance trips and providing a firsthand experience of SAV technology to the public, eliminating the need to privately own an SAV.…”

Shared Automated Mobility with Demand-Side Cooperation: A Proof-of-Concept Microsimulation Study

“…The proposed system, built upon a microscopic simulation architecture of SUMO with background traffic, consists of a group of customers, a fleet of shared automated vehicles (SAVs), and a service coordinator. SUMO has been used for describing emerging on-demand shared mobility in several studies [41,42]. The customer's demand is generated randomly over the simulation network.…”

Systemic Design Strategies for Shaping the Future of Automated Shuttle Buses

“…With the advent of emerging vehicular technologies such as automated driving, connected cars, and electric vehicles, as well as the concept of Mobility as a Service (MaaS) [1], public transport systems are undergoing a profound transformation. A new type of mobility based on autonomous, connected, electric, and shared vehicles [2] is coming into being. As such, expectations are rising for those vehicular technologies to be applied in public transportation, putting Shared Autonomous Vehicles (SAV) in the spotlight.…”