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Publications (10 of 16) Show all publications
Jomaa, D. & Yella, S. (2018). Predicting automatic trigger speed for vehicle-activated signs. Journal of Intelligent Systems
Open this publication in new window or tab >>Predicting automatic trigger speed for vehicle-activated signs
2018 (English)In: Journal of Intelligent Systems, ISSN 0334-1860, E-ISSN 2191-026XArticle in journal (Refereed) In press
Abstract [en]

Vehicle-activated signs (VAS) are speed-warning signs activated by radar when the driver speed exceeds a pre-set threshold, i.e. the trigger speed. The trigger speed is often set relative to the speed limit and is displayed for all types of vehicles. It is our opinion that having a static setting for the trigger speed may be inappropriate, given that traffic and road conditions are dynamic in nature. Further, different vehicle classes (mainly cars and trucks) behave differently, so a uniform trigger speed of such signs may be inappropriate to warn different types of vehicles. The current study aims to investigate an automatic VAS, i.e. one that could warn vehicle users with an appropriate trigger speed by taking into account vehicle types and road conditions. We therefore investigated different vehicle classes, their speeds, and the time of day to be able to conclude whether different trigger speeds of VAS are essential or not. The current study is entirely data driven; data are initially presented to a self-organising map (SOM) to be able to partition the data into different clusters, i.e. vehicle classes. Speed, time of day, and length of vehicle were supplied as inputs to the SOM. Further, the 85th percentile speed for the next hour is predicted using appropriate prediction models. Adaptive neuro-fuzzy inference systems and random forest (RF) were chosen for speed prediction; the mean speed, traffic flow, and standard deviation of vehicle speeds were supplied as inputs for the prediction models. The results achieved in this work show that RF is a reliable model in terms of accuracy and efficiency, and can be used in finding appropriate trigger speeds for an automatic VAS. 

Keywords
adaptive neuro-fuzzy inference systems, random forest, self-organising maps, trigger speed, vehicle-activated signs
National Category
Information Systems
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-29039 (URN)10.1515/jisys-2016-0329 (DOI)2-s2.0-85057306921 (Scopus ID)
Available from: 2018-12-10 Created: 2018-12-10 Last updated: 2018-12-10Bibliographically approved
Jomaa, D., Yella, S. & Dougherty, M. (2017). A comparative study between vehicle activated signs and speed indicator devices. Paper presented at 19th EURO Working Group on Transportation Meeting, EWGT2016, 5-7 September 2016, Istanbul, Turkey. Transportation Research Procedia, 22, 115-123
Open this publication in new window or tab >>A comparative study between vehicle activated signs and speed indicator devices
2017 (English)In: Transportation Research Procedia, ISSN 2324-9935, E-ISSN 2352-1465, Vol. 22, p. 115-123Article in journal (Refereed) Published
Abstract [en]

Vehicle activated signs and Speed indicator devices are safety signs used to warn and remind drivers that they are exceeding the speed limit on a particular road segment. This article has analysed and compared such signs with the aim of reporting the most suitable sign for relevant situations. Vehicle speeds were recorded at different test sites and the effects of the signs were studied by analyzing the mean and standard deviation. Preliminary results from the work indicate that both types of signs have variable effects on the mean and standard deviation of speed on a given road segment. Speed indicator devices were relatively more effective than vehicle activated signs on local roads; in contrast their effectivity was only comparable when tested on highways.

Place, publisher, year, edition, pages
Elsevier, 2017
Keywords
vehicle activated signs; speed indicator devices; trigger speed; effect on drivers
National Category
Computer and Information Sciences
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-21502 (URN)10.1016/j.trpro.2017.03.017 (DOI)000404633300012 ()2-s2.0-85019409576 (Scopus ID)
Conference
19th EURO Working Group on Transportation Meeting, EWGT2016, 5-7 September 2016, Istanbul, Turkey
Available from: 2016-05-30 Created: 2016-05-30 Last updated: 2018-01-10Bibliographically approved
Jomaa, D. (2016). A data driven approach for automating vehicle activated signs. (Doctoral dissertation). Borlänge: Dalarna University
Open this publication in new window or tab >>A data driven approach for automating vehicle activated signs
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Vehicle activated signs (VAS) display a warning message when drivers exceed a particular threshold. VAS are often installed on local roads to display a warning message depending on the speed of the approaching vehicles. VAS are usually powered by electricity; however, battery and solar powered VAS are also commonplace. This thesis investigated devel-opment of an automatic trigger speed of vehicle activated signs in order to influence driver behaviour, the effect of which has been measured in terms of reduced mean speed and low standard deviation. A comprehen-sive understanding of the effectiveness of the trigger speed of the VAS on driver behaviour was established by systematically collecting data. Specif-ically, data on time of day, speed, length and direction of the vehicle have been collected for the purpose, using Doppler radar installed at the road. A data driven calibration method for the radar used in the experiment has also been developed and evaluated.

Results indicate that trigger speed of the VAS had variable effect on driv-ers’ speed at different sites and at different times of the day. It is evident that the optimal trigger speed should be set near the 85th percentile speed, to be able to lower the standard deviation. In the case of battery and solar powered VAS, trigger speeds between the 50th and 85th per-centile offered the best compromise between safety and power consump-tion. Results also indicate that different classes of vehicles report differ-ences in mean speed and standard deviation; on a highway, the mean speed of cars differs slightly from the mean speed of trucks, whereas a significant difference was observed between the classes of vehicles on lo-cal roads. A differential trigger speed was therefore investigated for the sake of completion. A data driven approach using Random forest was found to be appropriate in predicting trigger speeds respective to types of vehicles and traffic conditions. The fact that the predicted trigger speed was found to be consistently around the 85th percentile speed justifies the choice of the automatic model.

Place, publisher, year, edition, pages
Borlänge: Dalarna University, 2016
Series
Dalarna Doctoral Dissertations in Microdata Analysis ; 4
Keywords
Optimal trigger speed, vehicle activated sign, mean speed, standard deviation, calibration, driver behaviour, data driven approach, automatic model
National Category
Computer and Information Sciences
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-21504 (URN)978-91-89020-96-2 (ISBN)
Public defence
2016-06-16, Clas Ohlson, Borlänge, 13:00 (English)
Supervisors
Available from: 2016-05-30 Created: 2016-05-30 Last updated: 2019-06-17Bibliographically approved
Jomaa, D. & Yella, S. (2016). Dynamic trigger speed for vehicle activated signs. In: : . Paper presented at 11th ITS European Congress, 6-9 June 2016, Glasgow. Scotland
Open this publication in new window or tab >>Dynamic trigger speed for vehicle activated signs
2016 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Optimal trigger speeds for vehicle activated signs were not considered in previous studies. The main aim of this paper is to summarise the findings of optimum trigger speed for vehicle activated signs. A secondary aim is to be able to build and report a dynamic trigger speed based on an accurate predictive model to be able to trigger operation of vehicle activated signs. A data based calibration method for the radar used in the experiment has been developed and evaluated. Results from the study indicate that the optimal trigger speed should be primarily aimed at lowering the standard deviation. Results also indicate that the optimal trigger speed should be set near the 85th percentile speed, to be able to lower the standard deviation. A comparative study investigating the use of several predictive models showed that random forest is an appropriate model to dynamically predict trigger speeds.

Place, publisher, year, edition, pages
Scotland: , 2016
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-22550 (URN)
Conference
11th ITS European Congress, 6-9 June 2016, Glasgow
Available from: 2016-07-01 Created: 2016-07-01 Last updated: 2016-07-01Bibliographically approved
Jomaa, D., Dougherty, M., Yella, S. & Edvardsson, K. (2016). Effectiveness of trigger speed of vehicle-activated signs on mean and standard deviation of speed. Journal of Transportation Safety and Security, 8(4), 293-309
Open this publication in new window or tab >>Effectiveness of trigger speed of vehicle-activated signs on mean and standard deviation of speed
2016 (English)In: Journal of Transportation Safety and Security, ISSN 1943-9962, Vol. 8, no 4, p. 293-309Article in journal (Refereed) Published
Abstract [en]

Excessive or inappropriate speeds are a key factor in traffic fatalities and crashes. Vehicle-activated signs (VASs) are therefore being extensively used to reduce speeding to increase traffic safety. A VAS is triggered by an individual vehicle when the driver exceeds a speed threshold, otherwise known as trigger speed (TS). The TS is usually set to a constant, normally proportional to the speed limit on the particular segment of road. Decisions concerning the TS largely depend on the local traffic authorities. The primary objective of this article is to help authorities determine the TS that gives an optimal effect on the Mean and Standard Deviation of speed. The data were systematically collected using radar technology whilst varying the TS. The results show that when the applied TS was set near the speed limit, the standard deviation was high. However, the Standard Deviation decreased substantially when the threshold was set to the 85th percentile. This decrease occurred without a significant increase in the mean speed. It is concluded that the optimal threshold speed should approximate the 85th percentile, though VASs should ideally be individually calibrated to the traffic conditions at each site.

Keywords
mean speed and standard deviation, trigger speed, vehicle-activated signs
National Category
Transport Systems and Logistics Vehicle Engineering
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-21427 (URN)10.1080/19439962.2014.976690 (DOI)000380365800001 ()2-s2.0-84963593330 (Scopus ID)
External cooperation:
Available from: 2016-05-09 Created: 2016-05-09 Last updated: 2016-08-26Bibliographically approved
Jomaa, D., Yella, S. & Dougherty, M. (2016). Speed prediction for triggering vehicle activated signs.
Open this publication in new window or tab >>Speed prediction for triggering vehicle activated signs
2016 (English)Report (Other academic)
Abstract [en]

Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.

Publisher
p. 16
Series
Working papers in transport, tourism, information technology and microdata analysis, ISSN 1650-5581 ; 2016:01
Keywords
vehicle activated signs; trigger speed; adaptive neuro-fuzzy inference systems; classification and regression tree; Random forest; multiple linear regression; mean speed; traffic flow
National Category
Computer Engineering
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-20614 (URN)
Available from: 2016-01-05 Created: 2016-01-05 Last updated: 2018-01-10Bibliographically approved
Jomaa, D., Yella, S., Dougherty, M. & Edvardsson, K. (2014). Data based Calibration System for Radar used by Vehicle Activated Signs. Journal of Data Analysis and Information Processing (2), 106-116
Open this publication in new window or tab >>Data based Calibration System for Radar used by Vehicle Activated Signs
2014 (English)In: Journal of Data Analysis and Information Processing, ISSN 2327-7203, no 2, p. 11p. 106-116Article in journal (Refereed) Published
Abstract [en]

The accurate measurement of a vehicle’s velocity is an essential feature in adaptive vehicle activated sign systems. Since the velocities of the vehicles are acquired from a continuous wave Doppler radar, the data collection becomes challenging. Data accuracy is sensitive to the calibration of the radar on the road. However, clear methodologies for in-field calibration have not been carefully established. The signs are often installed by subjective judgment which results in measurement errors. This paper develops a calibration method based on mining the data collected and matching individual vehicles travelling between two radars. The data was cleaned and prepared in two ways: cleaning and reconstructing. The results showed that the proposed correction factor derived from the cleaned data corresponded well with the experimental factor done on site. In addition, this proposed factor showed superior performance to the one derived from the reconstructed data.

Place, publisher, year, edition, pages
Scientific Research Publishing, 2014. p. 11
Keywords
Vehicle activated signs, Doppler radar, vehicle velocity, experiment, calibration
National Category
Engineering and Technology
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-16267 (URN)10.4236/jdaip.2014.24013 (DOI)
Projects
Allmänt Mikrodataaanalys - transporter
Available from: 2014-10-27 Created: 2014-10-27 Last updated: 2016-05-30Bibliographically approved
Jomaa, D., Dougherty, M., Yella, S. & Edvardsson, K. (2014). Effectiveness of vehicle activated signs on mean speed and standard deviation of vehicle speed. Borlänge: Högskolan Dalarna
Open this publication in new window or tab >>Effectiveness of vehicle activated signs on mean speed and standard deviation of vehicle speed
2014 (English)Report (Other academic)
Place, publisher, year, edition, pages
Borlänge: Högskolan Dalarna, 2014. p. 31
Series
Working papers in transport, tourism, information technology and microdata analysis, ISSN 1650-5581 ; 2014:06
Keywords
Vehicle activated signs, Trigger speed, Mean speed and Standard deviation
National Category
Computer and Information Sciences
Research subject
Komplexa system - mikrodataanalys, General Microdata Analysis - transports
Identifiers
urn:nbn:se:du-13977 (URN)
Available from: 2014-04-02 Created: 2014-04-02 Last updated: 2018-01-11Bibliographically approved
Jomaa, D. (2014). The Optimal trigger speed of vehicle activated signs. (Licentiate dissertation). Borlänge: Dalarna University
Open this publication in new window or tab >>The Optimal trigger speed of vehicle activated signs
2014 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The thesis aims to elaborate on the optimum trigger speed for Vehicle Activated Signs (VAS) and to study the effectiveness of VAS trigger speed on drivers’ behaviour. Vehicle activated signs (VAS) are speed warning signs that are activated by individual vehicle when the driver exceeds a speed threshold. The threshold, which triggers the VAS, is commonly based on a driver speed, and accordingly, is called a trigger speed. At present, the trigger speed activating the VAS is usually set to a constant value and does not consider the fact that an optimal trigger speed might exist. The optimal trigger speed significantly impacts driver behaviour.

In order to be able to fulfil the aims of this thesis, systematic vehicle speed data were collected from field experiments that utilized Doppler radar. Further calibration methods for the radar used in the experiment have been developed and evaluated to provide accurate data for the experiment. The calibration method was bidirectional; consisting of data cleaning and data reconstruction. The data cleaning calibration had a superior performance than the calibration based on the reconstructed data.

To study the effectiveness of trigger speed on driver behaviour, the collected data were analysed by both descriptive and inferential statistics. Both descriptive and inferential statistics showed that the change in trigger speed had an effect on vehicle mean speed and on vehicle standard deviation of the mean speed. When the trigger speed was set near the speed limit, the standard deviation was high. Therefore, the choice of trigger speed cannot be based solely on the speed limit at the proposed VAS location.

The optimal trigger speeds for VAS were not considered in previous studies. As well, the relationship between the trigger value and its consequences under different conditions were not clearly stated. The finding from this thesis is that the optimal trigger speed should be primarily based on lowering the standard deviation rather than lowering the mean speed of vehicles. Furthermore, the optimal trigger speed should be set near the 85th percentile speed, with the goal of lowering the standard deviation.

Place, publisher, year, edition, pages
Borlänge: Dalarna University, 2014
Series
Dalarna Licentiate Theses in Microdata Analysis ; 2
Keywords
optimal trigger speed, vehicle activated sign, vehicle mean speed, standard deviation, calibration, Doppler radar, driver behaviour, data analysis
National Category
Computer and Information Sciences
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-17538 (URN)978-91-89020-91-7 (ISBN)
Available from: 2015-05-26 Created: 2015-05-26 Last updated: 2019-06-17Bibliographically approved
Jomaa, D., Yella, S. & Dougherty, M. (2014). Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means. In: : . Paper presented at The Third International Conference on Intelligent Systems and Applications, INTELLI 2014, June 22 - 26, 2014 - Seville, Spain.
Open this publication in new window or tab >>Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means
2014 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.

Keywords
Solar-powered vehicle activated signs; Self Organising Maps; K-means clustering; Trigger speed
National Category
Computer and Information Sciences
Research subject
Komplexa system - mikrodataanalys
Identifiers
urn:nbn:se:du-14133 (URN)
Conference
The Third International Conference on Intelligent Systems and Applications, INTELLI 2014, June 22 - 26, 2014 - Seville, Spain
Available from: 2014-05-25 Created: 2014-05-25 Last updated: 2018-01-11Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-6526-6537

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