Vehicle Reidentification With Self-Adaptive Time Windows for Real-Time Travel Time Estimation

Wang, Jiankai; Indra-Payoong, Nakorn; Sumalee, Agachai; Panwai, Sakda

doi:10.1109/tits.2013.2282163

Cited by 14 publications

(18 citation statements)

References 26 publications

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“…The state of the smartphones was configured in order to study the detection period at various states. The results are consistent with the previous study [16] which showed that the average detection period of some smartphone models exceeds five minutes for an idle state but never reaches ten minutes.…”

Section: B Activity Segmentationsupporting

confidence: 93%

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Temporal Signatures of Passive Wi-Fi Data for Estimating Bus Passenger Waiting Time at a Single Bus Stop

Wepulanon

Sumalee

Lam

2020

IEEE Trans. Intell. Transport. Syst.

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This paper proposes an alternative method for bus passenger waiting time estimation using passive Wi-Fi data. With the underlying mechanism for Wi-Fi communication, the presence of Wi-Fi enabled devices in a particular area can be passively discoverable. The mobile devices carried by bus passengers can be exploited to estimate passenger waiting time at a bus stop without the passengers' direct participation. Passenger waiting time estimation using such opportunistic data is challenging due to the particular characteristics of the Wi-Fi data collected from bus stop environments. This paper proposes a methodology to handle massive noise in Wi-Fi data and identify the potential Wi-Fi records which are derived from passengers' devices. The filtered data can then be used to estimate passenger waiting time. Wi-Fi data collected from a bus stop in Hong Kong are used as a case study for evaluating the proposed system. The practicality is investigated in terms of estimation accuracy and insightful analysis.

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Section: B Activity Segmentationsupporting

confidence: 93%

“…The matching solution is adopted from the vehicle matching problem proposed by Wang et al [16] as the nature of the matching problem is equivalent when the modified bipartite graph is applied. The objective function (6) aims to find a solution with the minimum of overall weight.…”

Section: ) a Modified Bipartite Matching Methodsmentioning

confidence: 99%

Temporal Signatures of Passive Wi-Fi Data for Estimating Bus Passenger Waiting Time at a Single Bus Stop

Wepulanon

Sumalee

Lam

2020

IEEE Trans. Intell. Transport. Syst.

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“…Fig. 3 illustrates the overall framework of a state-of-the-art link-based V-ReID method [26], which consists of following four major steps.…”

Section: State-of-the-art Link-based Methodsmentioning

confidence: 99%

“…Results of case study demonstrate that the developed V-ReID method is capable for accurately estimating lane-based travel time distributions during peak and non-peak hours. The developed V-ReID method outperforms the state-of-the-art link-based V-ReID method [26] with respect to both vehicle matching accuracy and travel time estimation accuracy.…”

Section: Related Workmentioning

confidence: 97%

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Vehicle Re-identification for Lane-level Travel Time Estimations on Congested Urban Road Networks Using Video Images

Zhang

Chen

Lam

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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The provision of lane-level travel time information can enable accurate traffic control and route guidance in urban roads with distinctive traffic conditions among lanes. However, few studies in the literature have been conducted to estimate lanelevel travel time distributions. This study proposes a new vehicle re-identification (V-ReID) method for estimating lane-level travel time distributions using video images from widely deployed surveillance cameras. In the proposed method, a lane-based bipartite graph matching is introduced to obtain optimal matches between upstream and downstream vehicles by considering lanelevel traffic conditions and vehicles' lane changing behaviors and visual features. A lane-based travel time estimation technique is introduced to real-time estimate full spectrum of lane-level distribution parameters, including not only the mean but also the standard deviation and the distribution type. A comprehensive case study is carried out on a congested urban road in Hong Kong. Results of case study show that the proposed method outperforms the state-of-the-art link-based V-ReID method and is capable for providing accurate lane-level travel time distribution information on congested urban roads. Index Terms-Vehicle re-identification, lane-level travel time, lane changing behaviors, video images. I. INTRODUCTION CCURATE and updated travel time information is a crucial requirement for many traffic monitoring, traffic Manuscript

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A survey of advances in vision-based vehicle re-identification

Khan

Ullah

2019

Computer Vision and Image Understanding

129

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Vehicle re-identification (V-reID) has become significantly popular in the community due to its applications and research significance. In particular, the V-reID is an important problem that still faces numerous open challenges. This paper reviews different V-reID methods including sensor based methods, hybrid methods, and vision based methods which are further categorized into hand-crafted feature based methods and deep feature based methods. The vision based methods make the V-reID problem particularly interesting, and our review systematically addresses and evaluates these methods for the first time. We conduct experiments on four comprehensive benchmark datasets and compare the performances of recent hand-crafted feature based methods and deep feature based methods. We present the detail analysis of these methods in terms of mean average precision (mAP) and cumulative matching curve (CMC). These analyses provide objective insight into the strengths and weaknesses of these methods. We also provide the details of different V-reID datasets and critically discuss the challenges and future trends of V-reID methods.

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Vehicle Reidentification With Self-Adaptive Time Windows for Real-Time Travel Time Estimation

Cited by 14 publications

References 26 publications

Temporal Signatures of Passive Wi-Fi Data for Estimating Bus Passenger Waiting Time at a Single Bus Stop

Temporal Signatures of Passive Wi-Fi Data for Estimating Bus Passenger Waiting Time at a Single Bus Stop

Vehicle Re-identification for Lane-level Travel Time Estimations on Congested Urban Road Networks Using Video Images

A survey of advances in vision-based vehicle re-identification

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