Benefits to the Academic Community of Standardization of Bus Transit Automatic Vehicle Location Data

2013 ◽  
Vol 2352 (1) ◽  
pp. 61-67
Author(s):  
Steve Robinson
Keyword(s):  
Academic Community ◽  
Automatic Vehicle Location ◽  
Location Data ◽  
Bus Transit ◽  
Vehicle Location

scholarly journals Transfer’s monitoring in bus transit services by Automatic Vehicle Location data

2022 ◽  
Vol 60 ◽  
pp. 402-409
Author(s):  
Sara Mozzoni ◽  
Massimo Di Francesco ◽  
Giulio Maternini ◽  
Benedetto Barabino
Keyword(s):  
Automatic Vehicle Location ◽  
Location Data ◽  
Bus Transit ◽  
Vehicle Location ◽  
Transit Services

scholarly journals Characteristics Analysis of Bus Stop Failure Using Automatic Vehicle Location Data

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Rui Li ◽  
Xin Xue ◽  
Hua Wang
Keyword(s):  
Cumulative Distribution ◽  
Distribution Fitting ◽  
Automatic Vehicle Location ◽  
Failure Characteristics ◽  
Location Data ◽  
Bus Stop ◽  
Traffic Characteristics ◽  
Vehicle Location ◽  
Characteristics Analysis ◽  
Bus Stops

Queue forming behind a bus stop on an urban street is common and a traffic bottleneck usually occurs around the bus stop area. The bus stop failure means arriving buses cannot move into the bus stop due to limited capacity but have to wait for available loading areas. It is related with the transit operation level. Traditionally, the failure rate (FR), defined as the percentage of buses that arrives at the bus stop to find all loading areas occupied, is adopted in bus capacity analysis. However, the concept of FR is unable to quantitatively analyze failure characteristics in terms of its dispersion and uncertainty over time. Therefore, in this paper, we propose a new index called failure duration rate (FDR) to evaluate the bus stop failure, which can characterize waiting time for traffic delay calculation and capacity drop estimation. The automatic vehicle location data at eight bus stops in Wujiang District Suzhou, China, over 56 working days, are used to analyze the temporal characteristics of FR and FDR. We next examined the failed service duration characteristics during peak hours at the eight bus stops. Based on these characteristics analyses, we then proposed a Distribution Fitting and Cumulative Distribution Correlation (DF-CDC) approach to explore the correlation between FDR and FR at the same cumulative distribution function levels and validated the bus stop failure performance using the cross-validation method. The analysis results revealed that (i) FR fluctuates more significant than FDR, (ii) FDR is a more robust index than FR in describing the traffic characteristics incurred by bus stop failures, and (iii) FDR performs better in failure characteristics analysis than FR.

scholarly journals Measuring temporal and spatial travel efficiency for transit route system using low-frequency bus automatic vehicle location data

2018 ◽  
Vol 10 (10) ◽  
pp. 168781401880212 ◽  
Author(s):  
Fengping Yang ◽  
Liqun Peng ◽  
Chenhao Wang ◽  
Yuelong Bai
Keyword(s):  
Travel Time ◽  
Low Frequency ◽  
Travel Speed ◽  
Automatic Vehicle Location ◽  
Current Time ◽  
Minimum Requirement ◽  
Location Data ◽  
Vehicle Location ◽  
Transit Route ◽  
Temporal And Spatial

Although the bus probe data have been widely adopted for examining the transit route efficiency, this application cannot guarantee the accuracy in special temporal and spatial segments due to the inadequate probe samples. This study evaluates the feasibility of automatic vehicle location data as probes for the bus route travel time evaluation. Our techniques explore the minimum requirement of transit automatic vehicle location data to recover the bus trajectories in various spatial–temporal dimensions along the scheduled transit routes. First, a three-dimensional tensor is established to infer the uncovered link traveling information in current time slots and the last short-term period. Then, a general form is proposed to calculate the local mean travel speed and the average link travel time in each separated time slot of day. Finally, a case study has been conducted using field transit automatic vehicle location data running on a bus route corridor in Edmonton, Canada. The results demonstrate the effectiveness and efficiency of low-frequency bus automatic vehicle location data as probes for transit route efficiency measurement by comparing with baseline approaches. This work also supports the feasibility of using automatic vehicle location–equipped buses as customized buses for choosing alternate path based on evaluating the current transit efficiency on all routes.

Sign in / Sign up

Export Citation Format

Share Document