Operating speed: review and recommendations for future research

Tottadi, Kiran Kumar; Mehar, Arpan

doi:10.1007/s41062-021-00669-9

Cited by 9 publications

(6 citation statements)

References 52 publications

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“…In order to characterize and describe the trend of operating speeds with a continuous function, it was decided to use the smoothing cubic spline in order to interpolate the 85th %-ile values of the vehicle speeds recorded (Transportation Officials., 2011;Tottadi and Mehar, 2022) and obtained by collecting the HCD. Furthermore, through an original methodology and the implementation of a specific calculation code (Cantisani and Del Serrone, 2021), the trend of the theoretical speeds was also obtained as a function of the curvilinear abscissa, in analogy to the theoretical model for the design speed of the new roads in Italy (Ministero delle Infrastrutture e dei Trasporti, 2001).…”

Section: Resultsmentioning

confidence: 99%

Blending of Floating Car Data and Point-Based Sensor Data to Deduce Operating Speeds under Different Traffic Flow Conditions

Serrone¹

2023

European Transport/Trasporti Europei

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Nowadays, smart mobility can rely on innovative tools for the knowledge of road system conditions, like operating speed data extracted from the so-called Floating Car Data (FCD). Probe vehicles in the traffic flow send to operation centres a large amount of travel information, collected through GPS detection systems, especially with regard to geolocation, date and time, direction and speed. As the sample deriving from these vehicles represents a tiny portion of the entire vehicular fleet, in this paper an analysis and a comparison with data obtained by point-based traffic sensors is proposed. Therefore, the study analyses data collected by inductive loop detectors and microwave radar sensors, that provide information on the entire traffic flow in the time domain, in particular with the aim to identify free flow speed time bands. Afterwards, by means of the fusion between the results obtained from the data coming from these point-based control units and the ones coming from the probe vehicles, a comparison of the operating speeds in the two conditions of constrained and unconstrained traffic flow is performed.

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Section: Resultsmentioning

confidence: 99%

Blending of Floating Car Data and Point-Based Sensor Data to Deduce Operating Speeds under Different Traffic Flow Conditions

Serrone¹

2023

European Transport/Trasporti Europei

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“…Generally, according to scientific literature, the operating speed is assumed to be the 85th percentile of the distribution of the actual speeds practiced by users [40,41]. Therefore, it is necessary that the data source adopted is as reliable as possible, in order to obtain operating speed profiles that effectively represent the actual trend.…”

Section: Methodsmentioning

confidence: 99%

Reliability of Historical Car Data for Operating Speed Analysis along Road Networks

Cantisani

Serrone

Peluso

2022

Sci

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In recent years, innovative progress in information and communication technology (ICT) has introduced new sources for traffic data collection and analysis. On-board sensors like GPS-GPRS boxes, generally installed for insurance purposes, communicate information from circulating vehicles to data centers. Geographic location, date and time, vehicles’ speed and direction, are systematically transmitted and stored as Historical Car Data (HCD) from probe vehicles in the traffic stream. These databases provide a good opportunity to analyze the vehicles’ motion both in the temporal and spatial domains. The aim of this study is to pay attention to the reliability of this kind of data gathering. Since instrumented vehicles account for a small percentage of the entire vehicle fleet, it is important to understand if they can be considered as a sample representative of the whole population. The paper presents a comparison of speed data obtained from HCD with the ones recorded by inductive-loop detectors and microwave radar sensors; the performed analysis required the definition of specific methodologies and procedures. The obtained results show a high correspondence between the two sets of data. Therefore, HCD can be proposed for the detailed monitoring of, and studies on, the operating conditions of mobility along road networks.

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“…Stochastic models are based on the correlation between operating speed and road infrastructure, while including geometric elements and elements of the cross section of the road, environment, speed limit, type of terrain, etc. [24]. A smaller number of studies also included the driver factor [25][26][27].…”

Section: Operating Speed Prediction Modelsmentioning

confidence: 99%

Operating Vehicles’ Speed Prediction Models

VERTLBERG,

ŠVAJDA,

JAKOVLJEVIĆ

et al. 2024

PROMTT

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Vehicle speed is one of the main factors that influence the occurrence and severity of the consequences of road traffic accidents. Operating speed can be defined, among other things, as the actual speed at which the largest number of road users drive in conditions of free traffic flow. It can be measured on existing roads, however, on newly designed roads it can only be predicted. For this reason, many researchers have examined the correlation between the elements of the road as well as its surroundings and operating speed. By determining the correlation, models for predicting operating speed were created. As part of this paper, the most significant models for predicting operating speed were analysed. Of course, the largest number of models are stochastic, but in recent years, models based on artificial intelligence, more precisely on deep learning, have also been created. Accordingly, the goal of this paper is to review the model for predicting the operating speed of vehicles while identifying opportunities for further research and improvement in this area.

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Operating speed: review and recommendations for future research

Cited by 9 publications

References 52 publications

Blending of Floating Car Data and Point-Based Sensor Data to Deduce Operating Speeds under Different Traffic Flow Conditions

Blending of Floating Car Data and Point-Based Sensor Data to Deduce Operating Speeds under Different Traffic Flow Conditions

Reliability of Historical Car Data for Operating Speed Analysis along Road Networks

Operating Vehicles’ Speed Prediction Models

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