arrow
Return

Two-Phase Scheduling for Efficient Vehicle Sharing

delete2022-01-01
delete8
delete
OA
AI
J
Ji Liu *
C
Carlyna Bondiombouy
L
Lei Mo
P
Patrick Valduriez
DOI:10.1109/TITS.2020.3011952delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
Cooperative Intelligent Transport Systems (C-ITS) is a promising technology to make transportation safer and more efficient. Ridesharing for long-distance is becoming a key means of transportation in C-ITS. In this paper, we focus on private long-distance ridesharing, which reduces the total cost of vehicle utilization for long-distance journeys. In this context, we investigate journey scheduling problem with shared vehicles to reduce the total cost of vehicle utilization. Most of the existing works directly schedule journeys to vehicles with long scheduling time and only consider the cost of driving travellers instead of the total cost. In contrast, to reduce the total cost and scheduling time, we propose a comprehensive cost model and a two-phase journey scheduling approach, which includes path generation and path scheduling. On this basis, we propose two path generation methods: a simple near optimal method and a reset near optimal method as well as a greedy based path scheduling method. Finally, we present an experimental evaluation with different path generation and path scheduling methods with synthetic data generated based on real-world data. The results reveal that the proposed scheduling approach significantly outperforms baseline methods in terms of total cost (up to 69.8%) and scheduling time (up to 84.0%) and the scheduling time is reasonable (up to 0.16s). The results also show that our approach has higher efficiency (up to 141.7%) than baseline methods.
Keywords:
Scheduling
Schedules
Vehicles
Urban areas
Task analysis
Scheduling algorithms
Vehicle sharing
path planning problem
scheduling
optimization
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Intelligent Transportation Systems cover
IEEE Transactions on Intelligent Transportation Systems
IF:
8.4
Papers:
9.5K
Citations:
6.3W

Organization

C
centre national de la recherche scientifique (cnrs)
Scholars:
24.5W
Papers: 18.2W
Citations: 279
I
Inria
Scholars:
3.5K
Papers: 2.5K
Citations: 343
S
southeast university - china
Scholars:
5.3W
Papers: 4.9W
Citations: 57
B
baidu
Scholars:
578
Papers: 471
Citations: 1
researcher View more organizations