Investigating Critical Driver Behavioral Patterns during the Yellow Phase at Signalized Intersections

Transcription

1 Investigating Critial Driver Behavioral Patterns uring the Yellow Phase at Signalize Intersetions Yue Liu, Gang-Len Chang, an Jie Yu Abstrat This paper presents the investigation results of river behavioral patterns uring a yellow phase, base on fiel observations of 1123 rivers at six signalize intersetions of high aient frequeny in Marylan. By lassifying rivers at eah intersetion into aggressive pass, onservative stop, an normal groups base on their responses (i.e., stop or pass) an their istanes to the stop line when the signal turns yellow, the statistial tests with the orere-probit moel learly iniate the impats of some ritial fators on a river s eision. Suh fators inlue: average traffi flow spees, traffi volume rate, the green split, the number of through an rossing lanes in the target approah, signal oorination, the ifferene between iniviual vehile s approahing spee an average traffi flow spees, iniviual river s gener, age, an talking over ell phone or not, iniviual vehile s type an moel, an et. The analysis results offer the basis for assessing the safety onitions at hazarous intersetions, an for esign of ontra measures. I. INTRODUCTION VER the past eaes, intersetion relate rashes O onstitute about 30 perent of the total aients on Marylan state routes (e.g., 34% in 2002 an 35% in 2003). Among those, about 20 perent involve re-light-runnings, whih ause either fatal rear-en or sie-rash ollisions [1]. A tremenous amount of resoures have been investe in projets an programs to improve the safety an effiieny at signalize intersetions. Despite the progress of those programs, signifiantly reue traffi signal relate rashes remain a hallenging task. One of the main ontributors to this ilemma is the lak of suffiient unerstaning on how iniviual fators as well as external traffi environments an ultimately have an impat on a river s eision making proess uring the yellow phase [2][3]. In review of literature, Horst an Wilmink [4] iniate that suh a proess is governe by a multitue of fators, inluing river attitue an emotional states, the rossing ability before the re phase, onsequene of stopping an passing, interations with other rivers, an the vehile approahing spee. Their employe parameters were also aopte in later stuies by Milazzo, et al. [5], Koppa [6], Shultz, et al. [7], BMI [8], an the Green Book [9]. In lassifying river responses uring the yellow phase an Manusript reeive June 1 st, Y. Liu is Researh Assistant at University of Marylan at College Park, College Park, MD USA troybest@ um.eu). G. L. Chang is Professor at University of Marylan at College Park, College Park, MD USA ( gang@glue.um.eu). J. Yu is Researh Assoiate at University of Marylan at College Park, College Park, MD USA ( yujie@um.eu). ientifying potential affeting fators, Shinar an Compton [10] observe more than 2000 rivers over a total of 72 hours at six intersetions. Patten [11] investigate the impats of mobile-phone usage on rivers from the perspetive of ognitive workloa an attention resoure alloation. Cair et al. [12] use a riving simulator to measure the performane of 77 partiipants (oler an younger rivers) when traffi signals hange from green to yellow. Liu, et al. [13] performe an extensive investigation of river responses uner ifferent populations an vehile harateristis. A stuy by El-Shawarby et al. [14] haraterizes river behavior at the onset of a yellow-phase transition on highspee signalize intersetion approahes using fiel ata gathere from 60 test subjets. Most previous stuies onlue that male rivers are more likely than female rivers in taking aggressive ations; senior rivers, in omparison with young rivers, are less likely to manifest aggressive riving patterns uring a yellow-light phase; the presene of passengers was assoiate with lower rates of aggressive riving; an the likelihoo of taking aggressive ations inreases with the river s value of time. It has also been reognize that a river s response to a yellow-light phase may vary with some other fators suh as talking on the phone or not talking on the phone. Despite the informative results provie by the previous stuies, the following issues remain to be further aresse: Only the impat of iniviual river relate fators were investigate, however the impats of other affeting fators suh as signal ontrol features, vehile mehanial ynamis, intersetion geometri features, an average traffi flow harateristis on river behavior were not analyze in a systemati way. Furthermore, the omplex interations between those fators an their olletive impats on rivers were not fully investigate; The ata olletion proess of previous stuies have either been onute in a riving simulator or implemente through stritly ontroller fiel experiments. Driver behavior extrate from suh environments oul be biase an unrealisti without onsiering its interation with surrouning traffi environment; an Due to the onstraints of the sample size an the measurement metho, the results of previous stuies were not suffiient for efinitely ientifying key fators affeting river behavior patterns in ifferent riving

2 populations. The researh presente in this paper attempts to aress the above issues from the following aspets: Colleting etaile information on the harateristis of rivers, roaway geometri features, ongestion levels, average traffi flow spees, vehile ynamis, an vehile types an performanes through a speially esigne vieo-base system; Classifying rivers into three groups: aggressive, onservative, an normal, base on the ritial istane to the stop line an their stop/go eision at the onset of yellow-phase transition; Employing a multi-stage, isrete statistial test for exploring the omplex interrelations between a river s response (i.e., isrete in nature) to an intersetion yellow phase, his/her iniviual an vehile s performane harateristis, traffi environments, an key intersetion geometri features; an Proposing potential safety improvement strategies an measures for traffi safety pratitioners, researhers, an authorities, groune on a better unerstaning of those ientifie vital fators an their iniviual as well as olletive influenes on the behavior of riving populations. II. DATA COLLECTION With assistane from the Offie of Traffi an Safety of Marylan State Highway Aministration, this stuy selete six intersetions (MD193 at MD201, MD650 at Metzerott R., Ranolph R. at Glenallan R., MD410 at Belrest R., MD410 at Aelphi R., an MD193 at Mission Dr.) for fiel ata olletion using a speially esigne vieo-base system [15]. The key information assoiate with eah intersetion is shown in Table I. inlue this sample in the analysis ataset. Also, for some ambiguous harateristis suh as river age, we first lassifie the riving population into several age groups in our laboratory experiments an traine our fiel observers to have onsistent lassifiations of various sample iniviuals. Suh pre-training enables all fiel observers to proue the onsistent results. Through the aforementione proeure, only 1123 iniviual river responses were finally aepte for use in the analysis. All ollete variables are organize into the ifferent groups for analysis as shown in Table II: TABLE II FIELD COLLECTED VARIABLES TABLE I SURVEY INTERSECTION CHARACTERISTICS *Intersetion inies (1-6) refer to: MD193 at MD201, MD650 at Metzerott R., Ranolph R. at Glenallan R., MD410 at Belrest R., MD410 at Aelphi R., an MD193 at Mission Dr respetively. A total of 56 near-sie an far-sie vieos were ollete, from whih about more than 3000 samples were extrate. To ensure the ata reliability, we ompare eah sample from the stop-line observers, near-sie vieos, an far-sie vieos. Only after the three soures are well mathe, we then III. METHODOLOGY This stuy has ollete a total of 1,123 observations of iniviual river responses uring the yellow phase at six intersetions. For onveniene of analysis, this stuy has first lassifie the riving population into three istint patterns: aggressive, onservative, an normal, base on their response uring a yellow phase, an then evaluate the omplex interrelations between ifferent river behavior patterns an assoiate fators. A. Classifiation of Response Behaviors Prior to the analysis of behavior relate fators, this stuy nees to lassify all observe river eisions into three

3 istint groups: aggressive, normal, an onservative. The Group 3: Aggressive pass Drivers who aggressively lassifiation is base on the assumption that there exists a passe the intersetion uring the yellow phase even ritial istane ( ) pereive by a normal river at eah though they were quite far away ( x > ). intersetion when he/she noties the beginning of a yellow B. Statistial Analysis phase. A river, if neither aggressive nor onservative, is most likely to take the stop ation if his/her urrent loation Sine the epenent variables are isrete an orere in to the stop line ( x ) is longer than the pereive ritial nature, this stuy has employe the orere-probit moel [18] to investigate the impats of assoiate variables on the istane ( ). By the same token, the river may hoose to resulting riving responses. The ore onept of an orereprobit moel for a epenent variable of three lasses an be pass the intersetion uring the yellow phase if his/her pereive is longer than. Note that suh a ritial x presente with the following latent regression expression: * ' istane, is not iretly observable from the fiel ata (i.e., y = β x + ε 1) either x, or ) an it may vary with iniviual < x > Where, y * is unobservable, its observable outomes are: river harateristis an surrouning onitions, suh as y = 1 if y * 0 intersetion geometri features an traffi volume. Hene, y = 2 if 0 < y * μ1 this stuy has employe a isrete hoie moel for y = 3 if μ 1 < y * estimating the average for riving populations at eah The unknown parameter μ, representing the bounaries 1 intersetion (see Table III). between orere responses will be estimate along with β (parameters for explanatory variables). TABLE III Prob( y = 1) = norm(0 β ' x) 0 THE ESTIMATED AVERAGE CRITICAL DISTANCE FOR THE DRIVING POPULATIONS AT EACH INTERSECTION Pr ob( y = 2) = norm( μ1 β ' x) norm(0 β ' x) Pr ob( y = 3) = 1 norm( μ1 β ' x) The unobservable latent variable y *, in the above moel is the ifferene between the estimate istane to the stop line an the threshol value, for a river, the isrete epenent variable is a refletion of his/her response, whih is: onservative stop, normal, or aggressive pass. The inepenent variables are all observable an potentially assoiate fators liste in Table II. TABLE IV DISTRIBUTION OF DRIVING POPULATIONS AT INTERSECTIONS C. Multi-stage Statistial Tests The statistial test with the orere-probit moel for all assoiate fators has been ivie into three stages. The fous of Stage-I analysis is to ientify ritial traffi fators, whih serve as the set of bakgroun variables for Stage-II an Stage-III analyses. Table V summarizes the test proeure for Stage I an Stage II analysis: A etaile esription of this estimation approah is not the fous of this paper, an is available elsewhere [16][17]. A summary of the efinition for lassifiation is shown below, an the resulting istribution of riving population at eah intersetion is shown in Table IV: Group 1: Conservative stop Drivers who took the stop ation even though they oul have proeee through the intersetion uring the yellow phase (i.e., the river makes a stop even his/her istane to the stop line is less than the ritial istane, ); Group 2: Normal Drivers who took the stop ation when x > or the pass ation when x < ; an

4 TABLE V STATISTICAL TESTS PERFORMED IN STAGE-I AND STAGE-II In ontrast, rivers in the minor approah of a major-minor roaway intersetion ten to be more aggressive to go through the intersetion uring the yellow phase. TABLE VI ESTIMATION RESULTS OF TEST 1-8 IV. ANALYSIS RESULTS AND FINDINGS The results of Test-1 in Table VI show the impats of Stage-I fators on a river s eision uring the yellow phase. A positive an signifiant oeffiient for the average traffi flow spee implies that the rivers are more likely to take aggressive passing ations in response to the observe yellow phase uring the high-spee traffi onitions. This seems to justify the nee to plae spee enforement at highspee intersetions so as to improve traffi safety. A negative oeffiient for the traffi volume an green splits iniates that rivers ten to be self-restrite or onstraine uring the onitions of high volume or long green times, an are less likely to take the aggressive-pass ation uring the yellow phase. Tests 2-8 shown in Table VI present the estimate impats of intersetion relate fators on the response of rivers uring the yellow phase. As expete, fators exhibite statistial signifiant signs inlue: the number of through an rossing lanes in the target approah, an signal oorination. A negative sign for the number of through lanes, THRUL (-.187), an a positive sign for the require rossing lanes, CROSSL (.112) imply that rivers in a major intersetion approah of multiple lanes are more likely to take non-aggressive responses uring a yellow phase. This may be ue to the olletive impats of various fators, suh as experiening more volume (as reflete in the same estimation), having a longer green uration, an thus showing less esire to take the risk uring the yellow phase. Also reveale is the goo signal oorination (COOR) between ajaent intersetions tens to make rivers take aggressive ations uring the yellow phase. This may be ue to the efiieny of traitional signal progression moels to take river behavior an safety relate issues into aount. Most stuies on signal progression try to fous on maximizing the operational effiieny of intersetions, but not to minimize the total number of vehiles trappe in the ilemma zones or to minimize the total number of potential aggressive riving maneuvers. Other fators suh as the yellow phase uration, the yle length, an poste spee limit o not exhibit any signifiant impat on a river s eision making uring a yellow phase among those available sample observations. Table VII-VIII reports the estimate results of iniviual an vehile relate fators on a river s response uring the yellow phase. Tests 9-10 are fouse on investigating the impat ue to an iniviual vehile s approahing spee, while tests are mainly on evaluating the response ifferenes ue to the gener an age fators. Also inlue in the evaluation are the impats ue to having passengers an talking over the ell-phone (through Tests 16-17), vehile types (Tests 18-24), an vehile mae (Tests 25-28). Although the estimate relations are not onsistent aross all six observe intersetions, their statistial iniations have reveale the following interesting behavioral patterns: Drivers having their approahing spees higher than the average flow spee are more likely to behave aggressively when enountering a yellow phase (PER_ABOVE: 4.160/p-value < 0.1, see Test 10 in Table VII); Male rivers are more likely to take aggressive ations when approahing the yellow phase (MALE:.652, see Test 11 in Table VII); Female rivers ten to take onservative ations when approahing the yellow phase (FEMALE: -.652/p-value < 0.1, see Test 12 in Table VII); Young rivers ten to take aggressive ations when

5 approahing the yellow phase (YOUNG:.925/p-value < 0.1, see Test 13 in Table VII), but senior rivers are more likely to be onservative (SENIOR: -.977/p-value < 0.1, see Test 14 in Table VII); Drivers talking on phone ten to take onservative ations when approahing the yellow phase (PHONE: /p-value < 0.1, see Test 17 in Table VII); Drivers in vans ten to take onservative ations when approahing the yellow phase (VAN: -.851/p-value < 0.1, see Test 19 in Table VIII); Drivers in sports ars ten to take aggressive ations when approahing the yellow phase (SPORTCAR: 1.263/p-value < 0.1, see Test 22 in Table VIII); an Drivers in Japan mae ars exhibite the pattern of taking aggressive eisions uring the yellow phase (JAPAN:.666/p-value < 0.1,see Test 25 in Table VIII); TABLE VII ESTIMATION RESULTS OF STAGE-II ANALYSIS (TEST 9-17) gener. As iniate in Table IX, female rivers ten to be onservative when having passengers (FEMALE*PASSENGER: /p-value <0.1), but not for male rivers. Similar isrepanies also exist between young an senior rivers with passengers. Some of ritial behavioral patterns reveale in Table IX are liste as follows: Young female rivers ten to take aggressive ations when approahing the yellow phase, while senior an mile-age female rivers ten to take onservative ations uner the same situation (see tests 45-47); Female rivers talking over phone ten to take onservative ations when approahing the yellow phase, but not male rivers (see tests 33 an 49); Female van-rivers ten to take onservative ations when approahing the yellow phase, but not male rivers(see tests 35 an 51); Male rivers in SUVs ten to take aggressive ations when approahing the yellow phase, but not female rivers (see tests 36 an 52); an Female an young rivers in sports ars ten to take aggressive ations when approahing the yellow phase (see tests 54 an 66); TABLE IX RESULTS OF THE STAGE III ANALYSIS (COMPOUND VARIABLES) TABLE VIII ESTIMATION RESULTS OF STAGE-II ANALYSIS (TEST 18-28) Stage-III analysis, shown in Table IX, is esigne to explore the ompoun impats of iniviual an vehile relate fators on a river s behavior. It is notieable that some fators, shown insignifiant uring iniviual tests in Stage-II, reveal signifiant olletive impats on a river s response uring the yellow phase. For examples, the numbers of passengers that exhibit a negative but insignifiant sign when the test is base on all samples, shows ifferent an signifiant relations when the samples were ivie by V. POTENTIAL APPLICATIONS The empirial information presente in this paper offers some valuable information for unerstaning the omplex interrelations between the eision of rivers an all ontribution fators. More importantly, with some aitional moeling work, traffi safety engineers an esign effetive strategies to ounter ilemma zone relate aients an estimate the istribution of ilemma zones. For instane, one an: Enhane traitional signal timing moels for possible reution of aggressive riving relate fators ientifie

6 in this stuy without muh loss of operational effiieny; Propose river euation guielines base on the behavioral finings in this stuy to epress aggressive maneuvers uring the yellow phase; Develop a river response lassifiation an preition moule to support the ilemma zone protetion system; an Construt an inex of traffi safety for eah intersetion base on the istribution of riving populations an all ritial fators ientifie in this stuy an loal speifi observations. Responsible traffi agenies an then apply this inex to prioritize the resoures for safety improvement an esign effetive poliies. VI. CONCLUSIONS AND RECOMMENDATIONS This stuy has observe the behavior of 1123 rivers in response to an enountere yellow phase an their surrouning traffi onitions at six signalize intersetions. The omprehensive fiel ata obtaine with a reliable system offers the basis for this stuy to rigorously profile river behavioral patterns an analyze the impats of various behavioral an environmental fators. Through extensive fiel observations an statistial analyses, this stuy has reahe the following tentative onlusions: Driving populations at most signalize intersetions, base on their responses uring the yellow phase, an be lassifie into three istint groups: aggressive, normal, an onservative; A variety of fators may affet a river s eision on taking an aggressive or a onservative ation uring the yellow phase. Examples of fators inlue: average traffi flow spee, green splits, traffi volume, signal oorination, number of approah lanes, talking on the phone or not, vehile type, age, an gener; The spee of a vehile approahing the intersetion in omparison with the average flow spee seems to be the best iniator for ientifying the aggressive level of a river; The intersetion geometri features may affet a river s response to the enountere yellow phase. For example, rivers on the minor street are more likely to take an aggressive pass eision uring a yellow phase ue to the alloate short green phase; A oorinate signal system may enourage rivers to take an aggressive passing eision uring the yellow phase; Multiple behavioral variables oul have signifiant ompoun impat on a river s response uring the yellow phase. For example, male rivers in SUVs ten to take aggressive ations when approahing the yellow phase, but not female rivers; an Unerstaning the istribution of ifferent riving behavioral patterns an the ritial ontributing fators is essential for researhers an responsible agenies to esign of improvement strategies at signalize intersetions. It shoul be mentione that all above reporte finings are exploratory in nature an muh remains to be extene ue to the omplex interations between rivers, their experiene traffi onitions, an the large number of potentially relate fators. Further researh along the followings lines will be essential: Conuting omprehensive spee profile analyses with appropriate traffi sensors at all major intersetions plague by aients so as to verify the istribution of riving populations; Performing an in-epth riving population lassifiation for intersetions experiening a high aient frequeny with the vieo-base approah evelope in this stuy; Refining the set of ontributing variables propose in this stuy, an estimate the istribution of various river responses to the yellow-light phase with more ata from intersetions of ifferent geometri features an riving populations; Performing extensive analyses on ompoun impats of multiple behavioral variables for ientifying various river behavioral patterns; an Applying all the researh finings to evelop a set of intersetion safety evaluation moels, an test their effetiveness in ientifying unerlying fators that egrae the quality of traffi safety at intersetions of high rash frequeny. 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