Operating Time Division for a Bus Route Based on the Recovery of GPS Data

Joint Authors

Wang, Jian
Cao, Yang

Source

Journal of Sensors

Issue

Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2017-08-14

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Civil Engineering

Abstract EN

Bus travel time is an important source of data for time of day partition of the bus route.

However, in practice, a bus driver may deliberately speed up or slow down on route so as to follow the predetermined timetable.

The raw GPS data collected by the GPS device equipped on the bus, as a result, cannot reflect its real operating conditions.

To address this concern, this study first develops a method to identify whether there is deliberate speed-up or slow-down movement of a bus.

Building upon the relationships between the intersection delay, link travel time, and traffic flow, a recovery method is established for calculating the real bus travel time.

Using the dwell time at each stop and the recovered travel time between each of them as the division indexes, a sequential clustering-based time of day partition method is proposed.

The effectiveness of the developed method is demonstrated using the data of bus route 63 in Harbin, China.

Results show that the partition method can help bus enterprises to design reasonable time of day intervals and significantly improve their level of service.

American Psychological Association (APA)

Wang, Jian& Cao, Yang. 2017. Operating Time Division for a Bus Route Based on the Recovery of GPS Data. Journal of Sensors،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1186812

Modern Language Association (MLA)

Wang, Jian& Cao, Yang. Operating Time Division for a Bus Route Based on the Recovery of GPS Data. Journal of Sensors No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1186812

American Medical Association (AMA)

Wang, Jian& Cao, Yang. Operating Time Division for a Bus Route Based on the Recovery of GPS Data. Journal of Sensors. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1186812

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1186812