Relating Freeway Traffic Accidents to Inductive Loop

Transcription

1 Relatng Freeway Traffc Accdents to Inductve Loop Detector t Data Usng Logstc Regresson Junhyeong Park, Graduate Student Researcher Cheol Oh, Ph.D. Assstant Professor Department of Transportaton Systems Engneerng Hanyang Unversty at Ansan Hanyang Unversty

2 Contents 1. Introducton 2. Data Preparaton 3. Methodology and Model Development 4. Applcaton and Techncal Issues 5. Concluson 1

3 1. Introducton Background Malfunctonng components Vehcle Characterstcs Behavor/Aggressveness Drvng Skll/Experence Psycho-physologcal loads Drver Characterstcs [Accdent] Traffc Dynamcs Flow Occupancy Speed Envronment Weather Condtons Geometrc Desgn elements 2

4 1. Introducton Background Freeway Traffc Survellance System Traffc accdent ndcator Accdent occurs Real-tme traffc data collecton Implcaton starts Detecton of dsruptve traffc condton Analyss of traffc varables n abnormal traffc condton Normal traffc condton T-x Dsruptve traffc condton T Tme 3

5 1. Introducton Data Seohaean Freeway : Seoul - Mokpo(339.51km) Seohaean freeway loop data from detectors and traffc accdent data for 3 years 2004, 2005 and Occupancy, Speed, Volume Traffc accdent data Loop data Traffc accdent data from Loop data from Seohaean Seohaean freeway for three freeway for three years (2004~2006) years (2004~2006) Extracton of traffc data from Date, Tme, Locaton, Postmle, accdent-nvolved nvolved loop data Drecton, Type Dervaton of explanatory varables for traffc condtons 4

6 2. Data Preparaton Conceptual llustraton for loop detector data processng up 2 up 1 dn 1 dn 2 Space Accdent occurrence tme (t) Tme Upstream Loop 2 Upstream Loop 1 Downstream Loop 2 Downstream Loop 2 (t-15) ~ (t- 30) (t) ~ (t- 15) up2_t2_o_o up2_t2_v Accdent Occurr- ence up2_t2_s up2_t1_o_o up2_t1_v_v up2_t1_s_s up2_t2_do up2_t2_dv_dv up2_t2_ds_ds up2_t1_do up2_t1_dv up2_t1_ds up1_t2_o up1_t2_v up1_t2_s up1_t1_o up1_t1_v up1_t1_s up1_t2_do up1_t2_dv up1_t2_ds_ds up1_t1_do_do up1_t1_dv_dv up1_t1_ds dn1_t2_o dn1_t2_v_v dn1_t2_s_s dn1_t1_o dn1_t1_v dn1_t1_s dn1_t2_do_do dn1_t2_dv dn1_t2_ds dn1_t1_do_do dn1_t1_dv dn1_t1_ds dn2_t2_o dn2_t2_v dn2_t2_s_s dn2_t1_o_o dn2_t1_v dn2_t1_s dn2_t2_do_do dn2_t2_dv dn2_t2_ds dn2_t1_do dn2_t1_dv dn2_t1_ds_ds Accdent occurrenc etme (t) up2_t_o up2_t_v up2_t_s up2_t_do up2_t_dv up2_t_ds up1_t_o up1_t_v up1_t_s up1_t_do up1_t_dv up1_t_ds dn1_t_o dn1_t_v dn1_t_s dn1_t_do dn1_t_dv dn1_t_ds dn2_t_o dn2_t_v dn2_t_s dn2_t_do dn2_t_dv dn2_t_ds O t : Occupancy 사고발생시각 DO : Dffer. Occupancy up : upstream` 1 : 첫번째검지기 t1 사고시각 15분전 Up1_t1_O V : Volume DV : Dffer. Volume dn : downstream 2 : 두번째검지기 t2 S : Speed 사고시각 30분전 DS : Dffer. Speed 5

7 2. Data Preparaton Loop data processng procedure STEP 1 Archvng loop detector data for analyss STEP 2 Mssng data mputaton STEP 3 Allocaton of ndvdual accdent ID Drecton Tme ID : Route Date Postmle STEP 4 Dervaton of explanatory Varables for traffc condtons STEP 5 Dataset establshment for normal traffc condtons Spato-temperaltemperal traffc varable analyss 6

8 3. Methodology and Model Development Bnary Logstc Regresson BLR can be appled to bnary classfcaton problem 1 : Hazardous traffc condton 2 : Accdent-free condton Bnary Classfcaton Accdent probablty Low Hgh Level of ndependent varable Pr( ACC where, Pr( X f X ACC = 1 X ) ) = exp[ f ( X, β )] 1 + exp[ f ( X, β )] : Probablty of accdent lkelhood : accdent nvolved traffc varables (, β ) : Functon of and parameters X 7

9 3. Methodology and Model Development Result of Model Development Case 4 R-square CASE -2 Log Lkelhood Cox와 Snell의 R-Square Nagelkerke R-Square Number of accdent CASE 건 Correct classfcaton Rate(CCR) Predcted CASE Observed Accdent Percent Accdent Percent Accdent Percent Occurrence Correct (%) Occurrence Correct (%) Occurrence Correct (%) case4 Accdent Occurrence Total %

10 3. Methodology and Model Development Result of Model Development Case 4 Sgnfcant Varables CASE Varable Beta Sg. up1_t1_o up1_t2_v up2_t1_o 2t1O up2_t2_v case 4 collson and rearend collson up1_t1_do up1_t2_do up2_t1_ds dn2_t1_dv dn2_t1_ds dn2_t2_ds Constant

11 3. Methodology and Model Development Sgnfcant traffc varables for accdent lkelhood Sgnfcantf traffc varables n Case4 Up2 Up1 Dn1 Dn2 t-30mn (t2) up2_t2_o up2_t2_v up2_t2_s up2_t2_do up2_t2_dv up2_t2_ds up1_t2_o up1_t2_v up1_t2_s up1_t2_do up1_t2_dv up1_t2_ds dn1_t2_o dn1_t2_v dn1_t2_s dn1_t2_do dn1_t2_dv dn1_t2_ds dn2_t2_o dn2_t2_v dn2_t2_s dn2_t2_do dn2_t2_dv dn2_t2_ds t-15mn (t1) up2_t1_o up2_t1_v up2_t1_s up2_t1_do up2_t1_dv up2_t1_ds 2t1DS up1_t1_o up1_t1_v up1_t1_s up1_t1_do up1_t1_dv up1_t1_ds dn1_t1_o dn1_t1_v dn1_t1_s dn1_t1_do dn1_t1_dv dn1_t1_ds dn2_t1_o dn2_t1_v dn2_t1_s dn2_t1_do dn2_t1_dv dn2_t1_ds t up2_t_o up2_t_v up2_t_s up2_t_do up2_t_dv up2_t_ds up1_t_o up1_t_v up1_t_s up1_t_do up1_t_dv up1_t_ds Acc Occurrence dn1_t_o dn1_t_v dn1_t_s dn1_t_do dn1_t_dv dn1_t_ds dn2_t_o dn2_t_v dn2_t_s dn2_t_do dn2_t_dv dn2_t_ds 10

12 3. Methodology and Model Development Accdent Lkelhood Estmate probablty of accdent lkelhood exp[ f ( X, β )] Pr( ACC = 1 X ) = usng Bnary Logstc Regresson 1+ exp[ f ( X, β )] f (X, β) = 0.636X 0.007X X X X X X X X X X 11 up1_t1_o up1_t2_v up2_t1_o up2_t2_v up1_t1_do up1_t2_do up2_t1_ds dn2_t1_dv dn2_t1_ds dn2_t2_ds 상수 Accdent-free traffc Condton Abnormal traffc Condton 11

13 4. Applcaton and Techncal Issue Applcaton Warnng Informaton System - Varable speed lmt - Accdent lkelhood nformaton Real-tme Traffc Montorng Real-tme safety surrogate measure Estmate accdent lkelhood exp[f (X, β)] Pr( ACC = 1 X ) = 1+ exp[f (X, β)] Traffc condton s safe? Pr(ACC ) threshol d No Yes Provde warnng nformaton usng VMS Accdent lkelhood nformaton Varable Speed Lmt 12

14 4. Applcaton and Techncal Issue Techncal Issue Resoluton of traffc data Duraton and frequency for warnng nformaton provson threshold Tme(mn) Warnng Informaton Rate % % % When accdent lkelhood ndex exceeds the threshold, provde warnng nformaton 13

15 5. Concluson Future studes Adaptve Varable Speed Lmt system Study for varous traffc accdent type and model applcaton Feld tests for enhancng transferablty 시간 공간 상류부루프검지기 2 (up2) 상류부루프검지기 1 (up1) 하류부루프검지기 1 (dn1) 하류부루프검지기 2 (dn2) t-30분 (t2) t-15분 (t1) up2_t2_o up2_t2_v up2_t2_s up2_t1_o up2_t1_v up2_t2_do up1_t2_o up1_t2_do dn1_t2_o dn1_t2_do dn2_t2_o???? up2_t2_dv up2_t2_ds up2_t1_do up2_t1_dv up1_t2_v up1_t2_s up1_t1_o up1_t1_v up1_t2_dv up1_t2_ds up1_t1_do up1_t1_dv dn1_t2_v dn1_t2_s dn1_t1_o dn1_t1_v dn1_t2_dv dn1_t2_ds dn1_t1_do dn1_t1_dv dn2_t2_v dn2_t2_s dn2_t1_o dn2_t1_v dn2_t2_do dn2_t2_dv dn2_t2_ds dn2_t1_do dn2_t1_dv up2_t1_s up2_t1_ds up1_t1_s up1_t1_ds dn1_t1_s dn1_t1_ds dn2_t1_s dn2_t1_ds 사고발생시간 t up2_t_o up2_t_v up2_t_s up2_t_do up2_t_dv up2_t_ds up1_t_o up1_t_v up1_t_s up1_t_do up1_t_dv up1_t_ds 교통사고발생지점 dn1_t_o dn1_t_v dn1_t_s dn1_t_do dn1_t_dv dn1_t_ds dn2_t_o dn2_t_v dn2_t_s dn2_t_do dn2_t_dv dn2_t_ds 14

16 5. Concluson Concluson Proposed a model to estmate traffc accdent lkelhood usng real-tme traffc data Applcaton for Warnng nformaton and VSL Proposed system can lead to safer drvng leadng to accdent preventon Warnng nformaton Varable Speed Lmt Safe Drvng Reducng vehcle speed Decrease accdent lkelhood 15