A Bee Colony Optimization (BCO) and Type-2 Fuzzy Approach to Measuring the Impact of Speed Perception on Motor Vehicle Crash Involvement

A Bee Colony Optimization (BCO) and Type-2 Fuzzy Approach to Measuring the Impact of Speed Perception on Motor Vehicle Crash Involvement | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Bee Colony Optimization (BCO) and Type-2 Fuzzy Approach to Measuring the Impact of Speed Perception on Motor Vehicle Crash Involvement Marjana Čubranić-Dobrodolac, Libor Švadlenka, Svetlana Čičević, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-266309/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Nov, 2021 Read the published version in Soft Computing → Version 1 posted 4 You are reading this latest preprint version Abstract This paper examines how a driver’s perception of various speed levels, as well as driver’s speed perception from different positions, affect the propensity for motor vehicle crashes (MVCs). Data collection is performed in twelve experiments. 178 young drivers assessed the speed level from four positions; three of them relate to the speed perception of other vehicles on the road, while the remaining one represents the assessment of own speed. At each position, three speed levels were assessed: 30, 50, and 70 km/h. To process data, seven Type-2 fuzzy inference systems (T2FISs) are designed and tested in a sense of compliance with the empirical data. As a result, a relationship between the various forms of speed perception and participation in MVCs can be quantified. To examine the initial conclusions, the optimization of each of these T2FISs is performed by implementing the bee colony optimization (BCO) metaheuristic. The BCO based algorithm proposed in this paper achieved an average improvement of 21.17% in the performance of the initial T2FIS structures. The final results indicate that the drivers whose speed perception of the vehicle they are looking at from the rear side, as well as of the own vehicle, is poor have an elevated risk toward participation in MVCs compared to other forms of speed perception. The best-found T2FIS structures can be used as a decision-making tool that quantifies the driver propensity for MVCs, which can be useful in various educational and recruitment procedures in the field of transportation and traffic safety. Theoretical Computer Science oad safety motor vehicle crashes speed perception fuzzy inference system bee colony optimization metaheuristic optimization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Full Text Cite Share Download PDF Status: Published Journal Publication published 12 Nov, 2021 Read the published version in Soft Computing → Version 1 posted Reviews received at journal 16 May, 2021 Reviewers invited by journal 16 May, 2021 Editor assigned by journal 25 Feb, 2021 First submitted to journal 21 Feb, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-266309","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":27372444,"identity":"eaf82fdd-253e-4bc8-bc37-d9e45588e1cc","order_by":0,"name":"Marjana Čubranić-Dobrodolac","email":"","orcid":"","institution":"Univerzitet u Beogradu Saobracajni Fakultet","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Marjana","middleName":"","lastName":"Čubranić-Dobrodolac","suffix":""},{"id":27372445,"identity":"b88ddc4e-409c-42bc-8ae7-4fee3e792b0d","order_by":1,"name":"Libor Švadlenka","email":"","orcid":"","institution":"University of Pardubice Faculty of Transport Engineering: Univerzita Pardubice Dopravni Fakulta Jana Pernera","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Libor","middleName":"","lastName":"Švadlenka","suffix":""},{"id":27372446,"identity":"edcfc9dd-63bf-4938-acad-786232bc6b8e","order_by":2,"name":"Svetlana Čičević","email":"","orcid":"","institution":"Univerzitet u Beogradu Saobracajni Fakultet","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Svetlana","middleName":"","lastName":"Čičević","suffix":""},{"id":27372447,"identity":"efbe98ea-af3b-4c32-9555-1e4158b8cef9","order_by":3,"name":"Aleksandar Trifunović","email":"","orcid":"","institution":"Univerzitet u Beogradu Saobracajni Fakultet","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Aleksandar","middleName":"","lastName":"Trifunović","suffix":""},{"id":27372448,"identity":"4823e2e7-708f-43e0-989b-63fa03278a75","order_by":4,"name":"Momčilo Dobrodolac","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYHACA2YgwdjADiQ/MMgxGBCvBUgyzmAwJlELMw8xWnQbmDc+LtxjI9vPzPzws80fAwZz/gWMH34w3LPHpcXsAFux8YxnacYzm9mMpXPbDBgsZzxgluxhKE5swKmFx0ya58DhxA2HGcyYcxv+MBjcOMAgzcCQkIDbFrgW9m/MFkCHAbUw/wZqweMwuBYeM2YGNqCW8w1sIFsYcTrsMMgvB0B+4SmW7G0z4LGcwdhm2WOQgNsvx5s3Pi44AAwx9vaNH378MZAz5z98+MaPCtwOY2BG4/MwSIDMJyZCEYD/AEnKR8EoGAWjYPgDAGi+UICCglk3AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-8112-8329","institution":"Univerzitet u Beogradu Saobracajni Fakultet","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Momčilo","middleName":"","lastName":"Dobrodolac","suffix":""}],"badges":[],"createdAt":"2021-02-22 09:49:46","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-266309/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-266309/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00500-021-06516-4","type":"published","date":"2021-11-12T08:45:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":9293668,"identity":"0746f909-15af-4c41-a0cf-0f4cd8f90d18","added_by":"auto","created_at":"2021-05-18 11:31:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":218323,"visible":true,"origin":"","legend":"A configuration of the research: the parameter Si (i=1,3) takes the following values: S1 = 30 km/h, S2 = 50 km/h, and S3 = 70 km/h; the parameter Pj (j=1,4) takes the following values: P1 = Front view, P2 = Rear view, P3 = Side view, and P4 = Driver’s seat perspective ","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-266309/v1/627f4a88b2d753b9362044dd.png"},{"id":9293667,"identity":"7b6b5ec8-cd2e-400f-a7fb-4c520f9a9113","added_by":"auto","created_at":"2021-05-18 11:31:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":209368,"visible":true,"origin":"","legend":"Presentation of vehicle speed perception for four different perspectives A) four different perspectives B) appearance of the vehicle from the perspective of the respondents ","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-266309/v1/d22a405164a39d79f013c1e4.png"},{"id":9293291,"identity":"b7520387-2933-420f-bbae-d0fa00f9f453","added_by":"auto","created_at":"2021-05-18 11:25:51","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":110121,"visible":true,"origin":"","legend":"The proposed model of speed perception: (a) the parameter Si (i=1,3) takes the following values: S1 = 30 km/h, S2 = 50 km/h, and S3 = 70 km/h; (b) the parameter Pj (j=1,4) takes the following values: P1 = Front view, P2 = Rear view, P3 = Side view, and P4 = Driver’s seat perspective ","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-266309/v1/8de7c0cf25b65bbf79154693.png"},{"id":9293452,"identity":"37783ea4-33dd-4d70-a948-f5d871d6b566","added_by":"auto","created_at":"2021-05-18 11:28:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":308810,"visible":true,"origin":"","legend":"nput variables for T2FIS_30; Part a) variable x1 – Front view: 30km/h; Part b) variable x4 – Rear view: 30km/h; Part c) variable x7 – Side view: 30km/h; Part d) variable x10 – Driver’s perspective: 30km/h ","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-266309/v1/5328a4594c9aae5293260444.png"},{"id":9293448,"identity":"28435f48-b636-440a-b115-1900bf2d4880","added_by":"auto","created_at":"2021-05-18 11:28:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":359404,"visible":true,"origin":"","legend":"The concept of the BCO algorithm for T2FIS optimization in the case B=4, NC=2. ","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-266309/v1/f351e1c5d2c989cdf750c172.png"},{"id":9293450,"identity":"2b0cfbd8-173c-4551-bc71-508ab4fc4d7b","added_by":"auto","created_at":"2021-05-18 11:28:51","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":293638,"visible":true,"origin":"","legend":"A part of the notation used in the constraints ","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-266309/v1/7a3d1147ad7f4cefaecf0769.png"},{"id":9293876,"identity":"38df5a1b-3b15-48d9-b3bd-32b4cfd49bf5","added_by":"auto","created_at":"2021-05-18 11:34:51","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":284036,"visible":true,"origin":"","legend":"A presentation of Overlapping and Distance Constant (ODC): (a) the minimum allowed overlapping in the proposed algorithm; (b) the minimum allowed distance between two membership functions for the points with the maximum degree (µ(x)=1) ","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-266309/v1/1889fd8503331de184b53bb9.png"},{"id":9293875,"identity":"0cd27484-5bdf-40df-9c3b-983fcfb852c0","added_by":"auto","created_at":"2021-05-18 11:34:51","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":40697,"visible":true,"origin":"","legend":"The initial results of testing different T2FIS structures – the obtained CD values ","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-266309/v1/6df6968317b88f1619cb0eda.png"},{"id":9293671,"identity":"bb1c331e-3c40-4f6f-ba98-c0acc1e5adbe","added_by":"auto","created_at":"2021-05-18 11:31:51","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":75272,"visible":true,"origin":"","legend":"The results of different T2FIS structures optimization – mean values of 8 experiments ","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-266309/v1/a71695b6da0161f460b9a910.png"},{"id":9293455,"identity":"b0483418-a301-41ac-9003-7106ce5d0821","added_by":"auto","created_at":"2021-05-18 11:28:51","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":493823,"visible":true,"origin":"","legend":"Input and output variables for T2FIS_D after optimization procedure; Part a) variable x10 – Driver’s perspective: 30km/h; Part b) variable x11 – Driver’s perspective: 50km/h; Part c) variable x12 – Driver’s perspective: 70km/h; Part d) variable y – The number of motor vehicle crashes ","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-266309/v1/f5786218ca2fb3965e7e7b86.png"},{"id":15469083,"identity":"1b35b689-1f7f-4a7d-a078-cbf556a441b6","added_by":"auto","created_at":"2021-11-12 08:45:18","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1344206,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-266309/v1_covered.pdf"},{"id":13633699,"identity":"a4c556b4-f6ef-4173-914e-afff64874028","added_by":"auto","created_at":"2021-09-17 08:29:12","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1339101,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-266309/v1_covered.pdf"},{"id":9293935,"identity":"925e5311-53c0-4721-9fc7-14cb920ca80d","added_by":"auto","created_at":"2021-05-18 11:38:00","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1335622,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-266309/v1_covered.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eA Bee Colony Optimization (BCO) and Type-2 Fuzzy Approach to Measuring the Impact of Speed Perception on Motor Vehicle Crash Involvement\u003c/p\u003e","fulltext":[{"header":"Full Text","content":"This preprint is available for \u003ca href='/article/rs-266309/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e."}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"soft-computing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"soco","sideBox":"Learn more about [Soft Computing](https://www.springer.com/journal/500)","snPcode":"500","submissionUrl":"https://submission.nature.com/new-submission/500/3","title":"Soft Computing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"oad safety, motor vehicle crashes, speed perception, fuzzy inference system, bee colony optimization, metaheuristic optimization ","lastPublishedDoi":"10.21203/rs.3.rs-266309/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-266309/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This paper examines how a driver’s perception of various speed levels, as well as driver’s speed perception from different positions, affect the propensity for motor vehicle crashes (MVCs). Data collection is performed in twelve experiments. 178 young drivers assessed the speed level from four positions; three of them relate to the speed perception of other vehicles on the road, while the remaining one represents the assessment of own speed. At each position, three speed levels were assessed: 30, 50, and 70 km/h. To process data, seven Type-2 fuzzy inference systems (T2FISs) are designed and tested in a sense of compliance with the empirical data. As a result, a relationship between the various forms of speed perception and participation in MVCs can be quantified. To examine the initial conclusions, the optimization of each of these T2FISs is performed by implementing the bee colony optimization (BCO) metaheuristic. The BCO based algorithm proposed in this paper achieved an average improvement of 21.17% in the performance of the initial T2FIS structures. The final results indicate that the drivers whose speed perception of the vehicle they are looking at from the rear side, as well as of the own vehicle, is poor have an elevated risk toward participation in MVCs compared to other forms of speed perception. The best-found T2FIS structures can be used as a decision-making tool that quantifies the driver propensity for MVCs, which can be useful in various educational and recruitment procedures in the field of transportation and traffic safety.","manuscriptTitle":"A Bee Colony Optimization (BCO) and Type-2 Fuzzy Approach to Measuring the Impact of Speed Perception on Motor Vehicle Crash Involvement","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-05-18 11:25:49","doi":"10.21203/rs.3.rs-266309/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2021-05-17T00:20:00+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-05-16T08:37:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-02-26T00:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Soft Computing","date":"2021-02-22T04:49:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"soft-computing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"soco","sideBox":"Learn more about [Soft Computing](https://www.springer.com/journal/500)","snPcode":"500","submissionUrl":"https://submission.nature.com/new-submission/500/3","title":"Soft Computing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"bfb299d1-f88f-4dad-925e-4ca14a3dee27","owner":[],"postedDate":"May 18th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":4385976,"name":"Theoretical Computer Science"}],"tags":[],"updatedAt":"2021-11-12T08:45:04+00:00","versionOfRecord":{"articleIdentity":"rs-266309","link":"https://doi.org/10.1007/s00500-021-06516-4","journal":{"identity":"soft-computing","isVorOnly":false,"title":"Soft Computing"},"publishedOn":"2021-11-12 08:45:04","publishedOnDateReadable":"November 12th, 2021"},"versionCreatedAt":"2021-05-18 11:25:49","video":"","vorDoi":"10.1007/s00500-021-06516-4","vorDoiUrl":"https://doi.org/10.1007/s00500-021-06516-4","workflowStages":[]},"version":"v1","identity":"rs-266309","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-266309","identity":"rs-266309","version":["v1"]},"buildId":"-HB7Z8yhvgn0wM9Nzuekk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}