Automated Incident Detection Using Real-Time Floating Car Data

Houbraken, Maarten; Logghe, Steven; Schreuder, Marco; Audenaert, Pieter; Colle, Didier; Pickavet, Mario

doi:10.1155/2017/8241545

Cited by 11 publications

(6 citation statements)

References 23 publications

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“…Sensor data by automated vehicles can improve the identification of accident hotspots in two ways. First, in-vehicle sensors (so-called floating car data) cover a much larger portion of the road network than current road-side radar measurements [23,24]. Second, if sensor data by automated vehicles are sent via a wireless connection and stored in a central database, researchers could use these data to pinpoint where not only accidents but also errors and violations occur.…”

Section: Where Do Errors and Violations Occur?mentioning

confidence: 99%

Will vehicle data be shared to address the how, where, and who of traffic accidents?

et al. 2019

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Vehicles are increasingly equipped with sensors that measure the state of the vehicle and surrounding road users. Although most of these sensor data currently remain local to the vehicle, the data could be shared with the aim to improve road safety. We postulate that there is a range of scenarios regarding data sharing, with two extremes: In scenario 1, the acquired shared data will be analysed regarding the how, where, and who of road traffic errors, violations, and accidents; actions can then be taken to improve automated driving systems, manage accident hotspots, and provide personalised feedback, rewards, or penalties to road users. In scenario 2, the recorded data will not be shared, because of privacy concerns. We conclude that there exists a tension between a position of utilitarian use of data and a position of privacy.

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Section: Where Do Errors and Violations Occur?mentioning

confidence: 99%

Will vehicle data be shared to address the how, where, and who of traffic accidents?

et al. 2019

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“…FCD has been widely used in traffic analysis, such as travel time estimation [19,20], traffic state estimation [21], and congestion detection [22]. However, the quality of FCD and its true potential to be used in traffic analysis have been concerned about for a long time, as the FCD only monitors a limited sample of the total traffic [23]. Some studies discussed the penetration of probe vehicles required for FCD use.…”

Section: Literature Reviewmentioning

confidence: 99%

Estimation of Hourly Traffic Flows from Floating Car Data for Vehicle Emission Estimation

Jiang

Song

Zhang

et al. 2021

Journal of Advanced Transportation

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In order to model air quality in heavy pollution days, a dynamic emission monitoring system is implemented in the Beijing road network, which requires the input of hourly traffic flows. Floating car data (FCD) is increasingly employed for flow estimation based on the fundamental diagrams to supplement data provided by stationary detectors. However, existing studies often used a typical fundamental diagram without considering the hysteresis phenomena and the uncertainty of traffic flow estimation. This study aims to develop a multiperiod fundamental diagram for the traffic flow estimation from FCD considering the hysteresis phenomena. The result shows that the proposed multiperiod fundamental diagram can improve the accuracy of flow estimation. The uncertainty of traffic flow estimation at both 10 minutes and 1 hour is also quantified, and the result indicates that the variation of the estimation uncertainty at 1 hour is lower than that at 10 minutes, with an average 7% reduction of the range of 95% confidence interval (CI). But there is no significant difference in magnitudes of the estimation uncertainty at 1 hour compared with that at 10 minutes. Moreover, the uncertainty for congested flows is lower than that for free flows. In the case study, the proposed model is employed to develop the spatial and temporal distributions of flows and emissions for the metropolitan area in Beijing.

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“…Data coming from probe vehicle resulted fundamental in understanding and improving traffic safety. Researchers analyzed road safety speed [342,343], safety at roundabouts [344]; others proposed techniques for incident detection [345,346].…”

Section: Advanced Traffic Management System (Atms)mentioning

confidence: 99%

Sustainable Mobility: A Review of Possible Actions and Policies

Gallo

Marinelli

2020

Sustainability

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In this paper, a review of the main actions and policies that can be implemented to promote sustainable mobility is proposed. The work aims to provide a broad, albeit necessarily not exhaustive, analysis of the main studies and research that from different points of view have focused on sustainable mobility. The structure of the paper enables the reader to easily identify the topics covered and the studies related to them, so as to guide him/her to the related in-depth studies. In the first part of the paper, there is a preliminary analysis of the concept of sustainable mobility, the main transport policies implemented by the European Union and the USA, and the main statistical data useful to analyze the problem. Next, the main policies that can promote sustainable mobility are examined, classifying them into three topics: Environmental, socio-economic, and technological. Many of the policies and actions examined could be classified into more than one of the three categories used; for each of them, there is a description and the main literature work on which the topic can be analyzed in more detail. The paper concludes with a discussion on the results obtained and the prospects for research.

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Automated Incident Detection Using Real-Time Floating Car Data

Cited by 11 publications

References 23 publications

Will vehicle data be shared to address the how, where, and who of traffic accidents?

Will vehicle data be shared to address the how, where, and who of traffic accidents?

Estimation of Hourly Traffic Flows from Floating Car Data for Vehicle Emission Estimation

Sustainable Mobility: A Review of Possible Actions and Policies

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