In this paper we advocate a forward-looking, ambitious and disruptive smart cloud commuting system (SCCS) for future smart cities based on shared AVs. Employing giant pools of AVs of varying sizes, SCCS seeks to supplant and integrate various modes of transport in a unified, on-demand fashion, and provides passengers with a fast, convenient, and low cost transport service for their daily commuting needs. To explore feasibility and efficiency gains of the proposed SCCS, we model SCCS as a queueing system with passengers' trip demands (as jobs) being served by the AVs (as servers). Using a 1-year real trip dataset frommore »
Dynamic Integration of Heterogeneous Transportation Modes Under Disruptive Events
An integrated urban transportation system usually
consists of multiple transport modes that have complementary
characteristics of capacities, speeds, and costs, facilitating smooth
passenger transfers according to planned schedules. However,
such an integration is not designed to operate under disruptive
events, e.g., a signal failure at a subway station or a breakdown
of a bus, which have rippling effects on passenger demand
and significantly increase delays. To address these disruptive
events, current solutions mainly rely on a substitute service
to transport passengers from and to affected areas using adhoc
schedules. To fully utilize heterogeneous
transportation systems under disruptive events, we design
a service called eRoute based on a hierarchical receding horizon
control framework to automatically reroute, reschedule, and
reallocate multi-mode transportation systems based on real-time
and predicted demand and supply. Focusing on an integration of
subway and bus, we implement and evaluate eRoute with large
datasets including (i) a bus system with 13,000 buses, (ii) a subway
system with 127 subway stations, (iii) an automatic fare collection
system with a total of 16,840 readers and 8 million card users
from a metropolitan city. The data-driven evaluation results show
that our solution improves the ratio of served passengers (RSP)
by up to 11.5 times and reduces the average traveling time by
up to 82.1% compared with existing solutions.
- Award ID(s):
- 1521722
- Publication Date:
- NSF-PAR ID:
- 10059942
- Journal Name:
- ACM/IEEE International Conference on Cyber-Physical Systems
- ISSN:
- 2375-8317
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Urban public transit planning is crucial in reducing traffic congestion and enabling green transportation. However, there is no systematic way to integrate passengers' personal preferences in planning public transit routes and schedules so as to achieve high occupancy rates and efficiency gain of ride-sharing. In this paper, we take the first step tp exact passengers' preferences in planning from history public transit data. We propose a data-driven method to construct a Markov decision process model that characterizes the process of passengers making sequential public transit choices, in bus routes, subway lines, and transfer stops/stations. Using the model, we integrate softmaxmore »
-
Rapid urbanization has posed significant burden on urban transportation infrastructures. In today's cities, both private and public transits have clear limitations to fulfill passengers' needs for quality of experience (QoE): Public transits operate along fixed routes with long wait time and total transit time; Private transits, such as taxis, private shuttles and ride-hailing services, provide point-to-point transits with high trip fare. In this paper, we propose CityLines, a transformative urban transit system, employing hybrid hub-and-spoke transit model with shared shuttles. Analogous to Airlines services, the proposed CityLines system routes urban trips among spokes through a few hubs or direct paths,more »
-
During recent years there have been several efforts from city and transportation planners, as well as, port authorities, to design multimodal transport systems, covering the needs of the population to be served. However, before designing such a system, the first step is to understand the current gaps. Does the current system meet the transit demand of the geographic area covered? If not, where are the gaps between supply and demand? To answer this question, the notion of transit desert has been introduced. A transit desert is an area where the supply of transit service does not meet the demand formore »
-
We study real-time routing policies in smart transit systems, where the platform has a combination of cars and high-capacity vehicles (e.g., buses or shuttles) and seeks to serve a set of incoming trip requests. The platform can use its fleet of cars as a feeder to connect passengers to its high-capacity fleet, which operates on fixed routes. Our goal is to find the optimal set of (bus) routes and corresponding frequencies to maximize the social welfare of the system in a given time window. This generalizes the Line Planning Problem, a widely studied topic in the transportation literature, for whichmore »