Simulation-based sensor location model for arterial street

3Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

Abstract

Traffic sensors serve as an important way to a number of intelligent transportation system applications which rely heavily on real-time data. However, traffic sensors are costly. Therefore, it is necessary to optimize sensor placement to maximize various benefits. Arterial street traffic is highly dynamic and the movement of vehicles is disturbed by signals and irregular vehicle maneuver. It is challenging to estimate the arterial street travel time with limited sensors. In order to solve the problem, the paper presents travel time estimation models that rely on speed data collected by sensor. The relationship between sensor position and vehicle trajectory in single link is investigated. A sensor location model in signalized arterial is proposed to find the optimal sensor placement with the minimum estimation error of arterial travel time. Numerical experiments are conducted in 3 conditions: synchronized traffic signals, green wave traffic signals, and vehicle-actuated signals. The results indicate that the sensors should not be placed in vehicle queuing area. Intersection stop line is an ideal sensor position. There is not any fixed sensor position that can cope with all traffic conditions.

References Powered by Scopus

Optimal traffic counting locations for origin-destination matrix estimation

272Citations
N/AReaders
Get full text

Online learning solutions for freeway travel time prediction

176Citations
N/AReaders
Get full text

Trip matrix and path flow reconstruction and estimation based on plate scanning and link observations

175Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Optimization of traffic count locations for estimation of travel demands with covariance between origin-destination flows

23Citations
N/AReaders
Get full text

Optimization of multi-type traffic sensor locations for estimation of multi-period origin-destination demands with covariance effects

18Citations
N/AReaders
Get full text

Optimization of multi-type traffic sensor locations for network-wide link travel time estimation with consideration of their covariance

7Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Yu, Q., Zhu, N., Li, G., & Ma, S. (2015). Simulation-based sensor location model for arterial street. Discrete Dynamics in Nature and Society, 2015. https://doi.org/10.1155/2015/854089

Readers over time

‘16‘17‘18‘19‘20‘21‘2201234

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 4

67%

Professor / Associate Prof. 2

33%

Readers' Discipline

Tooltip

Engineering 4

80%

Agricultural and Biological Sciences 1

20%

Save time finding and organizing research with Mendeley

Sign up for free
0