Characterizing Traffic-Signal Performance and Corridor Reliability Using Crowd-Sourced Probe Vehicle Trajectories

Waddell, Jonathan M.; Remias, Stephen M.; Kirsch, Jenna N.

doi:10.1061/jtepbs.0000378

Cited by 27 publications

(18 citation statements)

References 21 publications

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“…Table 4 provides further numerical analyses for travel times. The LOTTR index in all of the evaluated scenarios was less than 1.5, which is the threshold suggested by the National Performance Management Measures ( 42 ). Therefore, the travel time reliability of the control strategy was within an acceptable range.…”

Section: Resultsmentioning

confidence: 76%

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Effects of Connectivity and Traffic Observability on an Adaptive Traffic Signal Control System

Islam

Tajalli

Mohebifard

et al. 2021

Transportation Research Record: Journal of the Transportation R

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The effectiveness of adaptive signal control strategies depends on the level of traffic observability, which is defined as the ability of a signal controller to estimate traffic state from connected vehicle (CV), loop detector data, or both. This paper aims to quantify the effects of traffic observability on network-level performance, traffic progression, and travel time reliability, and to quantify those effects for vehicle classes and major and minor directions in an arterial corridor. Specifically, we incorporated loop detector and CV data into an adaptive signal controller and measured several mobility- and event-based performance metrics under different degrees of traffic observability (i.e., detector-only, CV-only, and CV and loop detector data) with various CV market penetration rates. A real-world arterial street of 10 intersections in Seattle, Washington was simulated in Vissim under peak hour traffic demand level with transit vehicles. The results showed that a 40% CV market share was required for the adaptive signal controller using only CV data to outperform signal control with only loop detector data. At the same market penetration rate, signal control with CV-only data resulted in the same traffic performance, progression quality, and travel time reliability as the signal control with CV and loop detector data. Therefore, the inclusion of loop detector data did not further improve traffic operations when the CV market share reached 40%. Integrating 10% of CV data with loop detector data in the adaptive signal control improved traffic performance and travel time reliability.

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Section: Resultsmentioning

confidence: 76%

“…We also report the level of travel time reliability (LOTTR) index, which is the ratio of the 80 th to the 50 th percentile of travel times. LOTTR values less than 1.5, which is recommended by the National Performance Management Measures ( 42 ), show a reliable travel time performance.…”

Section: Experiments Designmentioning

confidence: 99%

Effects of Connectivity and Traffic Observability on an Adaptive Traffic Signal Control System

Islam

Tajalli

Mohebifard

et al. 2021

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

show abstract

“…Recently, high-fidelity connected vehicle (CV) trajectory data has become commercially available. This new CV data provides opportunities to develop scalable traffic signal performance measures for conventional intersections [14] [15] [16] [17] [18], roundabouts [19], diamond interchanges [20], and diverging diamond interchanges (DDIs) [21]. However, no study has used CV trajectory data to evaluate the operational performance of CFIs.…”

Section: Most Of the Cfi Performance Studies Have Been Based On Micro...mentioning

confidence: 99%

Continuous Flow Intersection Performance Measures Using Connected Vehicle Data

Saldivar-Carranza¹,

Li²,

Taylor³

et al. 2022

JTTs

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Continuous flow intersections (CFIs), also known as displaced left turns (DLTs), are a type of alternative intersection designed to improve operations at locations with heavy left-turn movements by reallocating these vehicles to the left side of opposing traffic. Currently, simulation is commonly used to evaluate operational performance of CFIs. However, this approach requires significant on-site data collection and is highly dependent on the analyst's ability to correctly model the intersection and driver behavior. Recently, connected vehicle (CV) trajectory data has become widely available and presents opportunities for the direct measurement of traffic signal performance measures. This study utilizes CV trajectory data to analyze the performance of a CFI located in West Valley City, UT. Over 4500 trajectories and 105,000 GPS points are analyzed from August 2021 weekday data. Trajectories are linear-referenced to generate Purdue Probe Diagrams (PPDs) and extended PPDs to estimate split failures (SF), arrivals on green (AOG), traditional Highway Capacity Manual (HCM) level of service (LOS), and the distribution of stops. The estimated operational performance showed effective progression during the PM peak period at all the critical internal storage areas with AOG levels at exit traffic signals between 83% and 100%. In contrast, all external approaches with longer queue storage areas had AOG values ranging from 2% to 81% during the same time period. The presented analytical techniques and summary graphics provide practitioners with tools to evaluate the performance of any CFI where CV trajectories are available without the need for on-site data collection.

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“…This type of probe or ''trajectory'' data offered by commercial providers typically contains latitude, longitude, timestamp, speed, heading, and a unique obfuscated trip identifier. Studies have demonstrated that metrics such as travel time, delay, arrivals on green, and queue length can be produced using trajectories (9)(10)(11)(12)(13). A major benefit is that it leapfrogs the requirement to build and maintain communication and detection systems (4).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Day et al (9) concluded that a penetration rate between 0.09% and 0.80% was sufficient to optimize offsets with similar performance to data collected by physical loop detectors by aggregating data over multiple days. Waddell et al (12) determined that even after extensive data cleaning, the remaining dataset with a penetration rate below 0.04% can still be used to identify offset adjustment opportunities. Zhao et al (10) explored data with penetration rates as high as 15% to estimate queue lengths and volume, which approached the recommended rate proposed by Argote-Caban˜ero et al (14) to estimate average delay in the oversaturated regime.…”

Section: Literature Reviewmentioning

confidence: 99%

Deriving Operational Traffic Signal Performance Measures from Vehicle Trajectory Data

Saldivar-Carranza

Mathew

et al. 2021

Transportation Research Record: Journal of the Transportation R

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Operations-oriented traffic signal performance measures are important for identifying the need for retiming to improve traffic signal operations. Currently, most traffic signal performance measures are obtained from high-resolution traffic signal controller event data, which provides information on an intersection-by-intersection basis and requires significant initial capital investment. Over 400 billion vehicle trajectory points are generated each month in the United States. This paper proposes using high-fidelity vehicle trajectory data to produce traffic signal performance measures such as: split failure, downstream blockage, and quality of progression, as well as traditional Highway Capacity Manual level of service. Geo-fences are created at specific signalized intersections to filter vehicle waypoints that lie within the generated boundaries. These waypoints are then converted into trajectories that are relative to the intersection. A case study is presented that summarizes the performance of an eight-intersection corridor with four different timing plans using over 160,000 trajectories and 1.4 million GPS samples collected during weekdays in July 2019 between 5:00 a.m. and 10:00 p.m. The paper concludes by commenting on current probe data penetration rates, indicating that these techniques can be applied to corridors with annual average daily traffic of ~15,000 vehicles per day for the mainline approaches, and discussing cloud-based implementation opportunities.

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Characterizing Traffic-Signal Performance and Corridor Reliability Using Crowd-Sourced Probe Vehicle Trajectories

Cited by 27 publications

References 21 publications

Effects of Connectivity and Traffic Observability on an Adaptive Traffic Signal Control System

Effects of Connectivity and Traffic Observability on an Adaptive Traffic Signal Control System

Continuous Flow Intersection Performance Measures Using Connected Vehicle Data

Deriving Operational Traffic Signal Performance Measures from Vehicle Trajectory Data

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