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.

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

Analysis of requirements for secure automated vehicle location devices for public transportation systems in Colombia

2018 ◽  
Vol 36 (2) ◽  
pp. 298-326
Author(s):  
Santiago Morales ◽  
◽  
César Pedraza ◽  
Felipe Restrepo-Calle ◽  
Félix Vega ◽  
...  
Keyword(s):  
Public Transportation ◽  
Transportation Systems ◽  
Automated Vehicle ◽  
Vehicle Location ◽  
Public Transportation Systems

scholarly journals Improving method of real-time offset tuning for arterial signal coordination using probe trajectory data

2017 ◽  
Vol 9 (1) ◽  
pp. 168781401668335 ◽  
Author(s):  
Jian Zhang ◽  
Yang Cheng ◽  
Shanglu He ◽  
Bin Ran
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
Travel Speed ◽  
Transportation Systems ◽  
Detection Methods ◽  
Trajectory Data ◽  
Traffic Condition ◽  
Signal Coordination ◽  
Cycle Basis ◽  
Vehicle Data

In the environment of intelligent transportation systems, traffic condition data would have higher resolution in time and space, which is especially valuable for managing the interrupted traffic at signalized intersections. There exist a lot of algorithms for offset tuning, but few of them take the advantage of modern traffic detection methods such as probe vehicle data. This study proposes a method using probe trajectory data to optimize and adjust offsets in real time. The critical point, representing the changing vehicle dynamics, is first defined as the basis of this approach. Using the critical points related to different states of traffic conditions, such as free flow, queue formation, and dissipation, various traffic status parameters can be estimated, including actual travel speed, queue dissipation rate, and standing queue length. The offset can then be adjusted on a cycle-by-cycle basis. The performance of this approach is evaluated using a simulation network. The results show that the trajectory-based approach can reduce travel time of the coordinated traffic flow when compared with using well-defined offline offset.

Inference of Public Transportation Trip Destinations by Using Fare Transaction and Vehicle Location Data

2017 ◽  
Vol 2652 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Gabriel E. Sánchez-Martínez
Keyword(s):  
Public Transportation ◽  
Programming Model ◽  
Transportation Systems ◽  
Service Planning ◽  
Operations Planning ◽  
Location Data ◽  
Vehicle Location ◽  
And Performance ◽  
Public Transportation Systems ◽  
Temporal Coverage

Origin–destination matrices provide vital information for service planning, operations planning, and performance measurement of public transportation systems. In recent years, methodological advances have been made in the estimation of origin–destination matrices from disaggregate fare transaction and vehicle location data. Unlike manual origin–destination surveys, these methods provide nearly complete spatial and temporal coverage at minimal marginal cost. Early models inferred destinations on the basis of the proximity of possible destinations to the next origin and disregarded the effect of waiting time, in-vehicle time, and the number of transfers on path choice. The research reported here formulated a dynamic programming model that inferred destinations of public transportation trips on the basis of a generalized disutility minimization objective. The model inferred paths and transfers on multileg journeys and worked on systems that served a mix of gated stations and ungated stops. The model is being used to infer destinations of public transportation trips in Boston, Massachusetts, and is producing better results than could be obtained with earlier models.

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.

Selection of Materials and Sensors for Health Monitoring of Composite Structures

2003 ◽  
Vol 785 ◽  
Author(s):  
Seth S. Kessler ◽  
S. Mark Spearing
Keyword(s):  
Health Monitoring ◽  
Lamb Wave ◽  
Composite Structures ◽  
Structural Damage ◽  
Performance Metrics ◽  
Full Range ◽  
Transportation Systems ◽  
Health Monitoring Systems ◽  
The Relationship ◽  
Selection Of

ABSTRACTEmbedded structural health monitoring systems are envisioned to be an important component of future transportation systems. One of the key challenges in designing an SHM system is the choice of sensors, and a sensor layout, which can detect unambiguously relevant structural damage. This paper focuses on the relationship between sensors, the materials of which they are made, and their ability to detect structural damage. Sensor selection maps have been produced which plot the capabilities of the full range of available sensor types vs. the key performance metrics (power consumption, resolution, range, sensor size, coverage). This exercise resulted in the identification of piezoceramic Lamb wave transducers as the sensor of choice. Experimental results are presented for the detailed selection of piezoceramic materials to be used as Lamb wave transducers.

scholarly journals Measuring Accessibility Based on Improved Impedance and Attractive Functions Using Taxi Trajectory Data

2020 ◽  
Vol 13 (1) ◽  
pp. 112
Author(s):  
Helai Huang ◽  
Jialing Wu ◽  
Fang Liu ◽  
Yiwei Wang
Keyword(s):  
Waiting Time ◽  
Urban Areas ◽  
Transportation Systems ◽  
Trajectory Data ◽  
Peak Period ◽  
Important Indicator ◽  
Destination Attractiveness ◽  
Urban Accessibility ◽  
Spatio Temporal ◽  
Taxi Trajectory

Accessibility has attracted wide interest from urban planners and transportation engineers. It is an important indicator to support the development of sustainable policies for transportation systems in major events, such as the COVID-19 pandemic. Taxis are a vital travel mode in urban areas that provide door-to-door services for individuals to perform urban activities. This study, with taxi trajectory data, proposes an improved method to evaluate dynamic accessibility depending on traditional location-based measures. A new impedance function is introduced by taking characteristics of the taxi system into account, such as passenger waiting time and the taxi fare rule. An improved attraction function is formulated by considering dynamic availability intensity. Besides, we generate five accessibility scenarios containing different indicators to compare the variation of accessibility. A case study is conducted with the data from Shenzhen, China. The results show that the proposed method found reduced urban accessibility, but with a higher value in southern center areas during the evening peak period due to short passenger waiting time and high destination attractiveness. Each spatio-temporal indicator has an influence on the variation in accessibility.

scholarly journals Plant and Controller Optimization for Power and Energy Systems With Model Predictive Control

2021 ◽  
Vol 143 (8) ◽  
Author(s):  
Donald J. Docimo ◽  
Ziliang Kang ◽  
Kai A. James ◽  
Andrew G. Alleyne
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Hybrid Electric Vehicle ◽  
Performance Metrics ◽  
Control Strategies ◽  
Transportation Systems ◽  
Thermal Dynamics ◽  
Plant Optimization ◽  
Power And Energy Systems ◽  
And Control

Abstract This article explores the optimization of plant characteristics and controller parameters for electrified mobility. Electrification of mobile transportation systems, such as automobiles and aircraft, presents the ability to improve key performance metrics such as efficiency and cost. However, the strong bidirectional coupling between electrical and thermal dynamics within new components creates integration challenges, increasing component degradation, and reducing performance. Diminishing these issues requires novel plant designs and control strategies. The electrified mobility literature provides prior studies on plant and controller optimization, known as control co-design (CCD). A void within these studies is the lack of model predictive control (MPC), recognized to manage multi-domain dynamics for electrified systems, within CCD frameworks. This article addresses this through three contributions. First, a thermo-electromechanical hybrid electric vehicle (HEV) powertrain model is developed that is suitable for both plant optimization and MPC. Second, simultaneous plant and controller optimization is performed for this multi-domain system. Third, MPC is integrated within a CCD framework using the candidate HEV powertrain model. Results indicate that optimizing both the plant and MPC parameters simultaneously can reduce physical component sizes by over 60% and key performance metric errors by over 50%.

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