Estimation of Short-Term Bus Travel Time by Using Low-Resolution Automated Vehicle Location Data

2016 ◽  
Vol 2539 (1) ◽  
pp. 113-118 ◽  
Author(s):  
Yashar Zeinali Farid ◽  
Eleni Christofa ◽  
Laurel Paget-Seekins
Keyword(s):  
Travel Time ◽  
Low Resolution ◽  
Short Term ◽  
Automated Vehicle ◽  
Location Data ◽  
Vehicle Location ◽  
Bus Travel Time

Rethinking Transit Time Reliability by Integrating Automated Vehicle Location Data, Passenger Patterns, and Web Tools

2017 ◽  
Vol 18 (4) ◽  
pp. 756-766 ◽  
Author(s):  
Benedetto Barabino ◽  
Cristian Lai ◽  
Carlino Casari ◽  
Roberto Demontis ◽  
Sara Mozzoni
Keyword(s):  
Transit Time ◽  
Automated Vehicle ◽  
Location Data ◽  
Web Tools ◽  
Vehicle Location

Modeling Bus Travel Time Reliability with Supply and Demand Data from Automatic Vehicle Location and Smart Card Systems

2015 ◽  
Vol 2533 (1) ◽  
pp. 17-27 ◽  
Author(s):  
Zhen-Liang Ma ◽  
Luis Ferreira ◽  
Mahmoud Mesbah ◽  
Ahmad Tavassoli Hojati
Keyword(s):  
Travel Time ◽  
Smart Card ◽  
Supply And Demand ◽  
Seemingly Unrelated Regression ◽  
Regression Equations ◽  
Travel Time Reliability ◽  
Automatic Vehicle Location ◽  
Different Types ◽  
Vehicle Location ◽  
Bus Travel Time

Travel time reliability is an important aspect of bus service quality. Despite a significant body of research on private vehicle reliability, little attention has been paid to bus travel time reliability at the stop-to-stop link level on different types of roads. This study aims to identify and quantify the underlying determinants of bus travel time reliability on links of different road types with the use of supply and demand data from automatic vehicle location and smart card systems collected in Brisbane, Australia. Three general bus-related models were developed with respect to the main concerns of travelers and planners: average travel time, buffer time, and coefficient of variation of travel time. Five groups of alternative models were developed to account for variations caused by different road types, including arterial road, motorway, busway, and central business district. Seemingly unrelated regression equations estimation were applied to account for cross-equation correlations across regression models in each group. Three main categories of unreliability contributory factors were identified and tested in this study, namely, planning, operational, and environmental. Model results provided insights into these factors that affect bus travel time and its variability. The most important predictors were found to be the recurrent congestion index, traffic signals, and passenger demand at stops. Results could be used to target specific strategies aimed at reducing unreliability on different types of roads.

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.

Use of Automated Vehicle Location Data for Route- and Segment-Level Analyses of Bus Route Reliability and Speed

2017 ◽  
Vol 2649 (1) ◽  
pp. 9-19 ◽  
Author(s):  
Wen Xun Hu ◽  
Amer Shalaby
Keyword(s):  
Evaluation Framework ◽  
Transit Signal Priority ◽  
Automated Vehicle ◽  
Location Data ◽  
Vehicle Location ◽  
Beneficial Impact ◽  
Level Model ◽  
Intersection Density ◽  
Transit Reliability ◽  
Transit Routes

Reliability and speed are arguably the most important indicators of surface transit performance for both operators and passengers. They can be influenced by a variety of factors, including service characteristics of bus routes, physical infrastructure, signal settings, traffic conditions and ridership patterns. These factors have often been analyzed individually for their impact on transit reliability or speed. Studies considering more than one factor tend to use one or two transit routes to explore their effects. The study that is the subject of this paper proposed an evaluation framework to guide the selection of an appropriate reliability measure. Regression analysis was applied subsequently to determine the factors that exhibit a statistically significant relationship with transit reliability and speed at both the route and segment levels. Automated vehicle location data of a bus route sample that is representative of the entire bus network in the City of Toronto, Ontario, Canada were used. Features significantly associated with reliability and speed were compared. The results showed that lower transit reliability and speed are significantly associated with the increase in service distance, signalized intersection density, stop density, volume of boarding and alighting passengers, and traffic volume. By segregating bus route segments on the basis of the presence of transit signal priority, the results of the segment-level model demonstrated the beneficial impact of transit signal priority on improving transit reliability.

Evaluating the Performance of Coordinated Signal Timing: Comparison of Common Data Types with Automated Vehicle Location Data

2018 ◽  
Vol 2672 (18) ◽  
pp. 128-142 ◽  
Author(s):  
Stephen M. Remias ◽  
Christopher M. Day ◽  
Jonathan M. Waddell ◽  
Jenna N. Kirsch ◽  
Ted Trepanier
Keyword(s):  
Performance Metrics ◽  
Essential Element ◽  
Transportation Systems ◽  
Signal Timing ◽  
Trajectory Data ◽  
Data Types ◽  
Automated Vehicle ◽  
Signal Coordination ◽  
Location Data ◽  
Vehicle Location

Performance measures are essential for managing transportation systems, including signalized corridors. Coordination is an essential element of signal timing, enabling reliable progression of traffic along corridors. Improved progression leads to less user delay, which leads to user cost savings and lower vehicle emissions. This paper presents a comparative study of signal coordination assessment using four different technologies. These technologies include detector-based high-resolution controller data, Bluetooth/Wi-Fi sensors, segment-based probe vehicle data, and automated vehicle location data consisting of GPS-based vehicle trajectories, representing the data anticipated from emerging connected vehicle technologies. The data were compiled for a 4.2-mi corridor in Holland, Michigan. The results show that all of the data sources were able to identify, at some level, where coordination issues existed. Detector-based controller data and GPS-based vehicle trajectory data were capable of showing greater detail, and could be used to make offset adjustments. The paper concludes by demonstrating the identification of signal coordination issues with the use of visual performance metrics incorporating automated vehicle location (AVL) trajectory data.

scholarly journals Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Cong Bai ◽  
Zhong-Ren Peng ◽  
Qing-Chang Lu ◽  
Jian Sun
Keyword(s):  
Travel Time ◽  
Dynamic Model ◽  
Kalman Filtering ◽  
Prediction Models ◽  
Support Vector ◽  
Travel Times ◽  
Travel Time Prediction ◽  
Real World Data ◽  
Time Prediction ◽  
Bus Travel Time

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

scholarly journals Joint Discussion 4 UV astronomy: stars from birth to death

2006 ◽  
Vol 2 (14) ◽  
pp. 169-194
Author(s):  
Ana I. Gómez de Castro ◽  
Martin A. Barstow
Keyword(s):  
High Resolution ◽  
Uv Spectroscopy ◽  
Broad Band ◽  
Mission Planning ◽  
High Resolution Spectroscopy ◽  
Low Resolution ◽  
Short Term ◽  
Uv Astronomy ◽  
Optical Telescope ◽  
The Moment

AbstractThe scientific program is presented as well a the abstracts of the contributions. An extended account is published in “The Ultraviolet Universe: stars from birth to death” (Ed. Gómez de Castro) published by the Editorial Complutense de Madrid (UCM), that can be accessed by electronic format through the website of the Network for UV Astronomy (www.ucm.es/info/nuva).There are five telescopes currently in orbit that have a UV capability of some description. At the moment, only FUSE provides any medium- to high-resolution spectroscopic capability. GALEX, the XMM UV-Optical Telescope (UVOT) and the Swift. UVOT mainly delivers broad-band imaging, but with some low-resolution spectroscopy using grisms. The primary UV spectroscopic capability of HST was lost when the Space Telescope Imaging Spectrograph failed in 2004, but UV imaging is still available with the HST-WFPC2 and HST-ACS instruments.With the expected limited lifetime of sl FUSE, UV spectroscopy will be effectively unavailable in the short-term future. Even if a servicing mission of HST does go ahead, to install COS and repair STIS, the availability of high-resolution spectroscopy well into the next decade will not have been addressed. Therefore, it is important to develop new missions to complement and follow on from the legacy of FUSE and HST, as well as the smaller imaging/low resolution spectroscopy facilities. This contribution presents an outline of the UV projects, some of which are already approved for flight, while others are still at the proposal/study stage of their development.This contribution outlines the main results from Joint Discussion 04 held during the IAU General Assembly in Prague, August 2006, concerning the rationale behind the needs of the astronomical community, in particular the stellar astrophysics community, for new UV instrumentation. Recent results from UV observations were presented and future science goals were laid out. These goals will lay the framework for future mission planning.

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