Estimating Phase Duration for SPaT Messages

Ibrahim, Shahana; Kalathil, Dileep; Sanchez, Rene O.; Varaiya, Pravin

doi:10.1109/tits.2018.2873150

Cited by 25 publications

(29 citation statements)

References 16 publications

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“…This information is needed to compute the SPaT message. (The phase data itself can be obtained from the controller or its conflict monitor as in (Ibrahim et al, 2018).) Third, sensors must be installed at strategic locations along guideways upstream of conflict zones to detect whether a blind zone is occupied.…”

Section: Discussionmentioning

confidence: 99%

“…the signal phases faced by users at all legs) and an estimate of the time when the phase will change. (In an actuated signal phase durations are not deterministic, and must be estimated (Ibrahim et al, 2018).) We now see how SPaT information can help resolve conflicts.…”

Section: An I2v System For Intersection Safetymentioning

confidence: 99%

“…If this message is not received, the vehicle should wait for its signal to change to green. messages in real time, for example using the algorithms described in (Ibrahim et al, 2018). The intersection broadcasts in real time the SPaT message and the occupancy of the blind zones.…”

Section: An I2v System For Intersection Safetymentioning

confidence: 99%

See 2 more Smart Citations

Making intersections safer with I2V communication

Grembek

Kurzhanskiy

Medury

et al. 2019

Transportation Research Part C: Emerging Technologies

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Intersections are hazardous places. Threats arise from interactions among pedestrians, bicycles and vehicles, more complicated vehicle trajectories in the absence of lane markings, phases that prevent determining who has the right of way, invisible vehicle approaches, vehicle obstructions, and illegal movements. These challenges are not fully addressed by the "road diet" and road redesign prescribed in Vision Zero plans, nor will they be completely overcome by autonomous vehicles with their many sensors and tireless attention to surroundings. Accidents can also occur because drivers, cyclists and pedestrians do not have the information they need to avoid wrong decisions. In these cases, the missing information can be computed and broadcast by an intelligent intersection. The information gives the current full signal phase, an estimate of the time when the phase will change, and the occupancy of the blind spots of the driver or autonomous vehicle. The paper develops a design of the intelligent intersection, motivated by the analysis of an accident at an intersection in Tempe, AZ, between an automated Uber Volvo and a manual Honda CRV and culminates in a proposal for an intelligent intersection infrastructure. The intelligent intersection also serves as a software-enabled version of the 'protected intersection' design to improve the passage of cyclists and pedestrians through an intersection.

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Section: Discussionmentioning

confidence: 99%

Section: An I2v System For Intersection Safetymentioning

confidence: 99%

See 1 more Smart Citation

Making intersections safer with I2V communication

Grembek

Kurzhanskiy

Medury

et al. 2019

Transportation Research Part C: Emerging Technologies

Self Cite

View full text Add to dashboard Cite

show abstract

“…Historical data can be relevant for planning problems, like vehicle routing and reference velocity generation. Examples include traffic congestion on highways [41], and signal phase and timing data [53,54]; in both cases, historical data give deeper insight on traffic patterns, that is generally not found in maps.…”

Section: Cloud Infrastructurementioning

confidence: 99%

Control of connected and automated vehicles: State of the art and future challenges

Guanetti

Kim

Borrelli

2018

Annual Reviews in Control

509

260

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Autonomous driving technology pledges safety, convenience, and energy efficiency. Challenges include the unknown intentions of other road users: communication between vehicles and with the road infrastructure is a possible approach to enhance awareness and enable cooperation. Connected and automated vehicles (CAVs) have the potential to disrupt mobility, extending what is possible with driving automation and connectivity alone. Applications include real-time control and planning with increased awareness, routing with micro-scale traffic information, coordinated platooning using traffic signals information, eco-mobility on demand with guaranteed parking. This paper introduces a control and planning architecture for CAVs, and surveys the state of the art on each functional block therein; the main focus is on techniques to improve energy efficiency. We provide an overview of existing algorithms and their mutual interactions, we present promising optimization-based approaches to CAVs control and identify future challenges.

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“…As seen in the earlier section, the beginning and ending of a phase can have different confidence values (Figure 4.8). Other studies have also emphasized that it might be worthwhile providing two estimates of the residual time (Ibrahim, 2019). Connected vehicle applications such as green light advisory and eco-driving require an accurate estimation of the traffic signal status for both BOG and EOG.…”

Section: Opportunities For Further Clarification Of Sae J2735mentioning

confidence: 99%

Developing the Collision Diagram Builder: Phase II Corridor Edition

Tarko¹,

Thomaz²,

Romero³

2019

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In November 2016, the American Association of State Highway and Transportation Officials (AASHTO) announced the Signal Phase and Timing (SPaT) challenge to state and local agencies to kick start infrastructure deployments for V2I communications. The challenge involved the deployment of Dedicated Short Range Communication (DSRC) infrastructure with SPaT broadcasts (current intersection signal light phase) on at least 20 signalized intersections in all of the 50 states by 2020. Although the roadmap for agencies to partner with the automotive industry is still evolving, it is important for Indiana to not only support the SPaT challenge, but also identify mutually beneficial opportunities for INDOT to partner with the automotive industry as Indiana has the second largest automotive related Gross Domestic Product (GDP) in the country. During this study, connected traffic signal infrastructure was deployed at several locations around the state. The West Lafayette corridor SPaT message deployment was done using both traditional Dedicated Short Range Communication (DSRC) as well cellular communication. This report details the deployment locations, the various public and private sector stakeholders that were engaged during the field testing, and several vehicle-infrastructure communication experiments that were used to evaluate connected vehicle use cases. The findings of this research were as follows: 1. The team successfully demonstrated use cases for placing virtual vehicle detection calls to a traffic signal controller using Basic Safety Message (BSM) messages and evaluated latency. 2. The team developed a scalable methodology for characterizing the probability of a traffic signal phase changing by time of day. This methodology of using agency traffic signal data for green light prediction and engine shut down at red lights is particularly useful to the automotive industry. 3. The team successfully demonstrated that split failures, reduced roadway friction and hard braking events can be identified on the vehicle and transmitted to an agency. This enhanced probe data information is particularly valuable to agencies for identifying traffic signal timing problems, segments impacted by winter weather and location where drivers are encountering roadway conditions required hard braking. 4. DSRC provides the lowest latency communication, but in general commercial cellular interface between vehicles and infrastructure provided acceptable latency for most use cases. For most applications, the team believes a commercial cellular interface between vehicles and infrastructure is the most scalable and feasible for an agency to maintain.

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Estimating Phase Duration for SPaT Messages

Cited by 25 publications

References 16 publications

Making intersections safer with I2V communication

Making intersections safer with I2V communication

Control of connected and automated vehicles: State of the art and future challenges

Developing the Collision Diagram Builder: Phase II Corridor Edition

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