Using detection of vehicular presence to estimate shockwave speed and upstream traffics for a signalized intersection

Cho, Hsun‐Jung; Tseng, Ming Te; Hwang, Ming Chorng

doi:10.1016/j.amc.2013.12.180

Cited by 10 publications

(3 citation statements)

References 14 publications

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“…The capacity and control mechanism significantly impact the level of service (LOS) and the connectivity of urban road networks 37 . Signalized intersections are also frequent locations of traffic congestion 38 . The queue length of each link at the intersection can represent the road traffic state intuitively and is the most common index to identify spillovers.…”

Section: Technical Validationmentioning

confidence: 99%

Real-world sensor dataset for city inbound-outbound critical intersection analysis

et al. 2022

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This paper reports the release of dataset that describes the critical city inbound-outbound intersection in the central business district’s Sathorn area of Bangkok, Thailand. The available traffic volume and occupancy are captured by sensors located on the Sathorn area’s links. Induction loop coil sensors and thermal and CCTV cameras have been installed at the approaching links of the critical Sathorn-Surasak intersection. Traffic volume data have been collected from the CCTV cameras every 5 s from 2016 to 2019, and occupancy and volume data have been collected from the loop coil sensors every 5 s from May to September 2016 during a social experiment that was part of Sathorn Model project. Occupancy and volume data have also been collected from the thermal cameras every 5 s from May to June 2016. The dataset provides temporal and spatial coverage of Sathorn Road’s primary urban areas, including weekdays, weekends, and public holidays. This dataset can be resources for research on traffic state estimation, traffic light control optimization, and the analysis of critical intersections.

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Section: Technical Validationmentioning

confidence: 99%

Real-world sensor dataset for city inbound-outbound critical intersection analysis

et al. 2022

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“…Time-dependent queue evolution is essential to evaluate the queuing delay and compute the starting and ending times of turning bay spillbacks, if they occur. One of the most efficient ways to reflect dynamic queue evolution at intersections is to adopt the shockwave theory ( 28–34 ). Figure 3a illustrates a typical queue evolution process for through vehicles, consisting of three queue formation shockwaves.…”

Section: Model Formulationsmentioning

confidence: 99%

Incorporating Delay Minimization in Design of the Optimized Arterial Signal Progression

Chen

Cheng

Chang

2021

Transportation Research Record: Journal of the Transportation R

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Despite the abundance of studies on signal progression for arterial roads, most existing models for bandwidth maximization cannot concurrently ensure that the resulting delays will be at a desirable level, especially for urban arterials accommodating high turning volume at some major intersections or constrained by limited turning bay length. Extending from those models that aim to address delay minimization in the progression design, this study provides two enhanced progression maximization models for arterials with high turning volumes. The first model aims to select the signal plan that can produce the lowest total signal delays for all movements from the set of non-inferior offsets produced by MAXBAND. Failing to address the impact of potential turning bay spillback at some critical intersections under such a design may significantly degrade the quality of through progression and increase the overall delay. For this reason, the second model proposed in this study offers the flexibility to trade the progression bandwidths within a pre-specified level for the target delay reduction, especially for turning traffic. The evaluation results from both numerical analyses and simulation experiments have shown that both proposed models can produce the desirable level of performance when compared with the two benchmark models, MAXBAND and TRANSYT 16. The second model yielded the lowest average network delay of 117.2 seconds per vehicle (s/veh), compared with 121.7 s/veh with TRANSYT. Moreover, even its average delay of 141.8 s/veh for through vehicles is comparable with that of 141.2 s/veh by MAXBAND, which is designed mainly to benefit through-traffic flows.

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“…Therefore, the success of this method hinges on an accurate way to observe the maximum queue length under oversaturated conditions. There are various approaches for queue length estimation at signalized intersections that rely on loop detector (2)(3)(4)(5) and probe vehicle (7)(8)(9)(10)(11)(12) data. While these methods are promising, not all intersections are equipped with advance detectors or high-resolution sensors to collect the data needed for some of the proposed methods (3,6).…”

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confidence: 99%

Estimating Demand Volume for Signalized Corridors Under Oversaturated Conditions Using Aggregated Probe Vehicle Speed Data

Kattepogu,

Cetin,

Salahshour

et al. 2023

Transportation Research Record: Journal of the Transportation R

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Measuring demand directly with vehicle sensors is not possible when demand is larger than capacity for an extended period, as the queue grows beyond the sensor, and the flow measurements at a given point cannot exceed the capacity of the section. The main objective of this study is to develop methods that could be implemented in practice based on readily available data. To this end, two methods are proposed: an innovative method based on shockwave theory and the volume delay function adapted from the Highway Capacity Manual (7th edition). Both methods primarily rely on probe vehicle speeds (e.g., from INRIX) as the input data and the capacity of the segment or bottleneck being analyzed. Probe vehicle data are used to determine the critical times when the queue reaches the end or beginning of a road segment. From these critical times, the shockwave speed for the boundary between congested (high density) traffic and arriving (low density) traffic is estimated. The proposed methods are tested with simulation data generated in VISSIM and validated based on volume data from the field. The field data are collected from a congested arterial in Virginia Beach, VA, and include the ground truth volumes and INRIX speed data aggregated at one-minute intervals. The results show that both methods are effective for estimating the demand volume and produce less than 4% error when tested with field data.

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Using detection of vehicular presence to estimate shockwave speed and upstream traffics for a signalized intersection

Cited by 10 publications

References 14 publications

Real-world sensor dataset for city inbound-outbound critical intersection analysis

Real-world sensor dataset for city inbound-outbound critical intersection analysis

Incorporating Delay Minimization in Design of the Optimized Arterial Signal Progression

Estimating Demand Volume for Signalized Corridors Under Oversaturated Conditions Using Aggregated Probe Vehicle Speed Data

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