scholarly journals Journey time estimation using single inductive loop detectors on non-signalised links

2002 ◽  
Vol 53 (6) ◽  
pp. 610-619 ◽  
Author(s):  
T Cherrett ◽  
F Mcleod ◽  
H Bell ◽  
M McDonald
Keyword(s):  
Time Estimation ◽  
Inductive Loop ◽  
Journey Time ◽  
Loop Detectors

scholarly journals Online Travel Time Estimation in Urban Areas Using the Occupancy of Long Loop Detectors

2009 ◽  
Vol 42 (15) ◽  
pp. 383-390
Author(s):  
W.K. Mak ◽  
F. Viti ◽  
S.P. Hoogendoorn ◽  
A. Hegyi
Keyword(s):  
Travel Time ◽  
Urban Areas ◽  
Time Estimation ◽  
Travel Time Estimation ◽  
Loop Detectors ◽  
Online Travel

Estimation of Truck Traffic Volume from Single Loop Detectors with Lane-to-Lane Speed Correlation

2003 ◽  
Vol 1856 (1) ◽  
pp. 106-117 ◽  
Author(s):  
Jaimyoung Kwon ◽  
Pravin Varaiya ◽  
Alexander Skabardonis
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
The United States ◽  
Truck Traffic ◽  
Single Loop ◽  
Loop Detectors ◽  
Time Estimates ◽  
Surveillance Technology ◽  
Traffic Volumes ◽  
Urban Freeway

An algorithm for real-time estimation of truck traffic in multilane freeways was proposed. The algorithm used data from single loop detectors—the most widely installed surveillance technology for urban freeways in the United States. The algorithm worked for those freeway locations that have a truck-free lane and exhibit high lane-to-lane speed correlation. These conditions are met by most urban freeway locations. The algorithm produced real-time estimates of the truck traffic volumes at the location. It also can be used to produce alternative estimates of the mean effective vehicle length, which can improve speed estimates from single loop detector data. The algorithm was tested with real freeway data and produced estimates of truck traffic volumes with only 5.7% error. It also captured the daily patterns of truck traffic and mean effective vehicle length. Applied to loop data on Interstate 710 near Long Beach, California, during the dockworkers’ lockout October 1 to 9, 2002, the algorithm found a 32% reduction in five-axle truck volume.

Traffic Management Parameters from Single Inductive Loop Detectors

2000 ◽  
Vol 1719 (1) ◽  
pp. 112-120 ◽  
Author(s):  
Tom Cherrett ◽  
Hugh Bell ◽  
Mike McDonald
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Fixed Time ◽  
Urban Traffic ◽  
Flow Conditions ◽  
Inductive Loop ◽  
Loop Detectors ◽  
Time Period ◽  
S Period ◽  
Urban Traffic Control

Investigated are potential new uses for the digital output produced by single inductive loop detectors (2 m x 1.5 m and 2 m x 6.5 m) used in most European urban traffic control systems. Over a fixed time period, the average loop-occupancy time per vehicle (ALOTPV) for a detector being sampled every 250 ms is determined by taking the number of 250-ms occupancies and dividing by the number of vehicles. In a similar way, the average headway time between vehicles (AHTBV) is determined by taking the number of 250-ms vacancies and dividing by the number of vehicles. Over a 30-s period, the minimum and maximum values of ALOTPV and AHTBV ranged from 1 to 120 (an ALOTPV of 1 and an AHTBV of 120 representing free-flow conditions, an ALOTPV of 120 and an AHTBV of 1 representing a stationary queue). Identifying periods when a link was operating under capacity and at capacity and when it had become saturated could be more clearly identified by using plots of ALOTPV and AHTBV data over time compared to the more traditional percentage occupancy output. ALOTPV also was used to successfully identify long vehicles from cars down to speeds of 15 km/h.

Development of Head-On Conflict Model for Overtaking Maneuvers on Two-Lane Rural Roads Using Inductive Loop Detectors

2013 ◽  
Vol 5 (4) ◽  
pp. 273-284 ◽  
Author(s):  
Afshin Shariat-Mohaymany ◽  
Ali Tavakoli Kashani ◽  
Hadi Nosrati ◽  
Sanaz Kazemzadehazad
Keyword(s):  
Rural Roads ◽  
Inductive Loop ◽  
Loop Detectors ◽  
Conflict Model
Sign in / Sign up

Export Citation Format

Share Document