User Equilibrium in a Disrupted Network with Real-Time Information and Heterogeneous Risk Attitude

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1 University of Massachusetts Amherst Amherst Masters Theses February User Equilibrium in a Disrupted Network with Real-Time Information and Heterogeneous Risk Attitude Ryan J. Pothering University of Massachusetts Amherst Follow this and additional works at: Part of the Civil Engineering Commons Pothering, Ryan J., "User Equilibrium in a Disrupted Network with Real-Time Information and Heterogeneous Risk Attitude" (2012). Masters Theses February Retrieved from This thesis is brought to you for free and open access by ScholarWorks@UMass Amherst. It has been accepted for inclusion in Masters Theses February 2014 by an authorized administrator of ScholarWorks@UMass Amherst. For more information, please contact scholarworks@library.umass.edu.

2 US ER EQU ILIBR IUM IN A D IS R UP TED NET W OR K W ITH R EA L-T IM E IN FOR M AT ION AND H ETER OGENEOUS R IS K ATT IT UDE A Th es i s P res en t ed B y RYAN J. P OTHER ING S ub m i t t ed t o t h e Grad u at e S ch o o l o f t h e Un i v ers i t y o f M as s ach u s et t s Am h ers t i n p art i al fu l fi l l m en t o f t h e req u i r em en t s fo r t h e d e gre e o f M AS TER OF C IV IL A N D ENV IR ONM EN TA L ENG INEER IN G M a y Dep art m en t o f C i v i l an d En v i ro n m en t al En gi n eeri n g

3 US ER EQU ILIBR IUM IN A D IS R UP TED NET W OR K W ITH R EA L-T IM E IN FOR M AT ION AND H ETER OGENEOUS R IS K ATT IT UDE A Th es i s P res en t ed B y RYAN J. P OTHER ING Ap p r o ve d a s t o st yl e a nd c on t e nt b y: _ So n g Ga o, Ch a i r _ J oh n Co ll ur a, M e mb e r Ri c h ar d Pal me r, De p a rt me n t He a d Ci vi l a n d En vi r o n me n t al En gi n e e ri n g

4 DED IC AT IO N I wo u l d l i k e t o d ed i cat e t h i s t h es i s t o m y l o v i n g an d s up p o rt i v e fam i l y fo r ch eeri n g m e o n t h ro u gh t h i s i n t en s e yet v e r y r e wardi n g ex p eri en ce. S p e ci al d ed i c at i o n go es t o m y p ar en t s, S h ar o n an d G eo rge, wh o s e a d v i ce h as al wa ys s u cce e d ed i n p u s h i n g m e i n t h e ri gh t d i rect i o n, an d t o m y s i s t er, J es s i ca, wh o h el p ed gi v e m e a p erfe ct d o s e o f l i gh t -h ea rt ed en co u ra g e m en t t o m ak e m y t h es i s a fu n ex p eri en ce wi t h l o t s o f l au gh s.

5 AC KNOW LED GEM EN TS I wo u l d l i k e t o t h an k m y ad v i s er, D r. S o n g Gao, f or t h e p l en t i fu l an d o u t s t an d i n g ad v i ce s h e h as p ro v i d ed m e s i n ce t h e b e gi n n i n g. Her p at i en c e an d fai t h i n h er s t u d en t s i s i m m eas u rab l e an d en co u ra ged m e t o p u t m y b es t fo o t fo rward an d p ro v i d e h er wi t h m y b es t wo rk. I wo u l d l i k e t o a ck n o wl e d ge Dr. J o h n C o l l u ra fo r serv i n g o n m y t h es i s co m m i t t ee an d s h o wi n g i n t e res t i n t h e wo rk o f each s t u d en t i n t h i s p ro gr am. I wo u l d al s o l i k e t o ack n o wl ed g e t h e UM as s Tr an s p ort at i o n C en t er fo r al l o wi n g m e t o co n d u ct m y res e ar ch an d p ro v i d i n g an y as s i s t an ce o r ad v i ce wh en n e ed ed. Xu an Lu al s o d es erv es s p eci al a ck n o wl ed g em en t as he r d o ct o r at e wo rk s erv es as t h e b as i s fo r t h i s t h es i s. Hel p i n g h er s et up ex p eri m en t s es s i o n s an d an al ys i s d at a fro m t h e ex p eri m en t u l t i m at el y l e d m e t o ch o o s i n g m y t h e s i s t op i c. Fi n al l y, I wo u l d l i k e t o t h an k al l m y fri en d s fo r t h e i r s up p o rt t h ro u gh o u t m y t h es i s an d u n d ers t an d i n g wh en I wo u l d b e u n av ai l ab l e w h en m y t h es i s n e ed ed at t en t i o n. i v

6 ABS TR AC T US ER EQU ILIBR IUM IN A D IS R UP TED NET W OR K W IT H R EA L-T IM E IN FOR M AT ION A ND HETER O GENEOUS R IS K ATT ITU DE M AY R YAN J. P OTHER ING, B.S., UN IVER S ITY OF M AS S AC HUS ETT S AM HER S T M.S., UN IVER S IT Y OF M AS S AC HUS ETTS AM HER S T Di rect ed b y: D r. S o n g G ao Th e t raffi c n et wo rk i s s ub j ect t o ran d o m d i s rup t i o ns, s u ch as i n ci d en t s, b ad weat h er, o r o t h er d ri v ers ran d o m b eh av i o r. A t r a v el er s ro u t e ch o i ce b eh a v i o r i n s u ch a n et wo rk i s t h u s affect ed b y t h e p rob ab i l i t i es o f s uch d i s rup t i o n s, h i s / h er at t i t u d e t o ward s ri s k, an d real -t i m e i n fo r m at i o n o n rev eal ed t raffi c co n d i t i o n s t h at co u l d po t en t i al l y red u c e t h e l ev el o f u n cert ai n t y d u e t o t h e d i s rup t i o n s. As t h e ro ad n et wo rk s p er f o rm an ce i s d e - t erm i n ed co l l ect i v el y b y al l t rav el ers ch o i c es, i t i s al s o affect ed b y t h es e fact o rs. Th i s t h es i s feat u res t h e d ev el o p m en t o f a m u l t i -cl as s user eq u i l i b ri u m m o d el b as ed o n h et ero - gen eo u s ri s k at t i t u d e d i s tri b u t i o n s an d a u s er eq u il i b ri u m m o d el b as ed o n v ari o u s d i s rup - t i o n p rob ab i l i t i es an d i n fo rm at i o n p en et rat i o n r at e s t h at can b e u s ed t o p erf o rm s en s i t i v i t y an al ys es fo r a t raf fi c n et wo rk. Th e m et h o d o f s u c ces s i v e av er a ge (M S A ) i s u s ed t o s o l v e fo r t h e eq u i l i b ri u m co n d i t i o n s. Lab o rat o r y ex p eri m en t al d at a are u s ed t o c al i b rat e t h e ri s k at t i t u d e m o d el. A s am p l e s en s i t i v i t y an al ys i s i s p e rfo rm ed t o s h o w t h e d i s r up t i o n an d i n - fo rm at i o n p en et rat i o n ef f ect s o n n et wo rk p er fo rm an ce. In i t i al cal i b r at i o n s s h o w p ro m i s - i n g res u l t s fo r ro u t e fl o w p red i ct i o n s i n a co n g es t ed n et wo rk wi t h res p e ct t o h et ero gen e - o u s at t i t u d e. W i t h res p e ct t o d i s rup t i o n p rob ab i l i t y an d i n fo rm at i o n ac ce s s, h av i n g t o o v

7 h i gh i n fo rm at i o n p en et ra t i o n wi l l n o t im p ro v e t h e net wo rk s p erfo rm an ce, wh i l e h av i n g a s m al l d i s rup t i o n p rob ab i l i t y can i m p ro v e t raf fi c co n d i t i o n s i n t h e n et wo rk. v i

8 T ABLE OF CONT ENT S PAGE ACK NOW LEDGEM ENTS i v ABST RACT v L IST OF T ABLES vi i i L IST OF FIGU RES i x CHAPT ER 1. INT RODUCT ION Re s ea r ch Obj ec ti ve s Co n tr i bu ti o n s Lit e ra t ur e Re vi e w Us er Eq ui li b ri u m M o d e l s Ri s k Att it u d e M o d el s Re al -T i me In f o r ma t i on M o d el s EX PERIM ENT DESIG N M ODELIN G USER EQ U IL IB R IUM W IT H HET EROGENEOUS R IS K ATT IT UDE Us e r Eq u il ib ri u m Co n d i ti o n s wi t h He t er o ge n e o us Ri s k At t it u de So l ut io n Al go r it h m M o de l Cal ib r at io n Di sa ggr e ga t e An a l ys is Aggr e ga t e An a l ys i s M ODELIN G USER EQ U IL IB R IUM W IT H ADAPT IV E ROUT E CHOICE U NDER REAL - T IM E INFORM AT IO N Us e r Eq u il ib ri u m Co n d i ti o n s wi t h Re a l -T i me In f or ma t i o n So l ut io n Al go r it h m Ap p li c at io n s CONCLUS IONS AND FUT URE W ORK REFERENCES v i i

9 LIS T OF TAB LES Tab l e P age 1. Di s ag g re gat e R es u l t s fo r S es s i o n A Di s ag g re gat e R es u l t s fo r S es s i o n A Di s ag g re gat e R es u l t s fo r S es s i o n A Di s ag g re gat e R es u l t s fo r S es s i o n A A g gre g at e R i s k At t i t u d e Di s t ri b u t i o n P red i ct i o n R es u l t s A g gre g at e P at h Fl o w P red i ct i o n s an d R M S N R es u l t s v i i i

10 LIS T OF F IG UR ES Fi gu re P age 1. Ex p eri m en t R o ad Net wo rk R i s k At t i t u d es wi t h R es p ect t o Ex p ect ed Di s u t i l it y P red i ct ed R i s k P aram e t er Di s t ri b u t i o n fo r S es s i on A P red i ct ed R i s k P aram e t er Di s t ri b u t i o n fo r S es s i on A P red i ct ed R i s k P aram e t er Di s t ri b u t i o n fo r S es s i on A P red i ct ed R i s k P aram e t er Di s t ri b u t i o n fo r S es s i on A S am p l e Net wo rk fo r S en s i t i v i t y An al ys i s To t al Tr av el Ti m e An a l ys i s u n d er Vari o u s Di s ru p t i o n P rob ab i l i t i es To t al Tr av el Ti m e An a l ys i s u n d er Vari o u s M P R i x

11 C HAP TER 1 IN TR ODUC T IO N P eop l e m ak e ro u t e ch o i c es ev er y d a y i n an y gi v e n road n et wo rk f o r v ari o u s reas o n s (m i n i m i z e t rav el t i m e, av o i d co n ges t i o n, et c.). In fo rm at i o n ab o u t t h e t ra ffi c co n d i - t i o n s i n t h e n et wo rk, e.g., t h at p ro v i d ed b y an ad van ced t r av el e r i n fo r m at i o n s ys t em (AT IS ), co u l d p o t en t i al l y en ab l e t rav el ers t o m ak e b et t er ro u t e ch o i ces t h at can h el p t h em s at i s f y t h ei r go al s m o re e ffect i v el y. Ho wev e r, wh at m o s t d o n o t real i z e i s t h at t h ei r ro u t e ch o i ce an d t h e ro u t e ch o i ces o f o t h ers i n t h e n et work h av e an i m p act o n t h e o v eral l p e r- fo rm an c e o f t h e n et wo rk. Th e wel l -k n o wn Bra es s P arad o x s t at es t h at ad d i n g c ap a ci t y t o a n et wo rk wi t h t h e i n t en t i o n t o al l ev i at e p o o r t raf f ic co n d i t i o n s can act u al l y d ecr eas e t h e n et wo rk s e ffi ci en c y as t rav el ers wi l l co n s i d er m i ni m iz i n g t h ei r p ers o n al t rav el t i m e wi t h o u t co n s i d eri n g t h e e ffect s i t h as o n t h e n et wo rk. Li k e wi s e, ad d i n g m o r e i n fo rm at i o n ab o u t t raffi c co n d i t i o n s i n t h e n et wo rk co u l d c re ate s i m i l ar eff ect s. Ad d i t i o n al l y, an o t h e r i m p o rt an t fact o r t h at co u l d affect t h e p erfo rm a n ce o f a n et wo rk i s t rav el ers ri s k at t i t u d e wh en m ak i n g a ro u t e ch o i ce. Trav el ers s en s i t i v i t y t o t raffi c co n d i t i o n s o n a n et wo rk d et erm i n es wh et h er o r n o t t h e y wi l l t ak e a ch an ce o n m i n i m iz i n g t h ei r t rav el t i m e at t h e p o s s i b l e co s t of gre at er p ers o n al d e l a y, av o i d t h e s i t u at i o n al t o get h er, o r rem ai n i n d i ffe ren t t o t h e m at t er. Th es e o u t l o o k s affe ct ev er y t rav el er s ro u t e ch o i c e, a n d wh en ap p l i ed t o t h e e nt i re p op u l at i o n, h av e an eff ect o n t h e effi ci en c y o f t h e n et wo rk. 1

12 1.1 Research Objectives Th e t h es i s p res en t s t h e d ev el op m en t o f t wo m o d el s th at p red i ct u s er eq u i l i b ri u m co n d i t i o n s fo r a gi v en n et wo rk b as ed o n h et er o gen eou s ri s k at t i t u d e an d i n fo rm at i o n acc es s, res p ect i v el y. He t e r o ge n e o u s r i sk at ti t u de in c o rp o r at e s mu l ti p le r i sk a t ti t u de s ( r i sk - se e k i n g, r i sk - a ve r se, o r r i sk - n e u t ra l ) a c r o ss a ll use r s i n a r o u t e c h o ic e m o d e l, u nl ike h o m o ge n e o u s r i sk a t ti t ud e, wh i c h o n l y i n c o rp o r a t e s o n e. Th e ri s k at t i tu d e m o d el i s cal i b rat ed u s i n g ex p eri m en t al d at a fro m t h e ro u t e ch o i c e s t u d y p er fo rm e d i n Lu et al. ( ). Th e t r av el er i n f o rm at i o n m o d el h as t h e o ret ical ap p l i c at i o n s o n t h e eff ect s o f i n fo rm at i o n acc es s an d d i s rup t i o n p rob ab i l i t y o n t he p erfo rm an c e o f t h e ro ad n et wo rk. 1.2 Contributions Th ere i s a gap i n t h e d e v el op m en t o f t raffi c eq u i l ib ri u m m o d el s i n a st och as t i c n et wo rk. Trav el ers i n h er en t l y d i ffer i n t e rm s o f th ei r ri s k at t i t u d e an d a cc e s s t o real -t i m e i n fo rm at i o n. Th ere ar e s o m e eq u i l i b ri u m mo d el s t h at i n co rp o rat e ri s k at t i t u de (h o m o ge n eo u s o r h et e r o gen eo u s ) an d t h o s e t h at i n co rp o rat e i n fo rm at i o n acces s an d d i s rup t i o n p rob ab i l i t y ( M i rch an d an i an d S o ro u s h, ; Lo an d Tu n g, ; Gao, ; Uk k u s u ri et al., ). Ho wev e r, t h ere h as b e e n n o res e arch o n t h e d e v el op m en t an d cal i b rat i o n o f an eq u i l i b ri u m m o d el t h at i n cl u d es bo t h h et ero gen eo u s ri s k at t i t u d es an d i n fo rm at i o n acc es s. Th e res ea rch p rop o s ed co n t ri b u tes t o t h e s t art o f t h e art b y t ack l i n g t wo i m p o rt an t s ub -p rob l em s wh o s e s o l u t i o n s can b e l at er co m b i n ed t o b u i l d s u ch a m o d el : 1. Dev el op m en t an d c al i b ra t i o n o f a u s er eq u i l i b ri u m mo d el wi t h h et ero g en eo u s ri s k at t i t u d e b as ed o n t h e ex p ect ed u t i l i t y t h eo r y. 2. Dev el op m en t o f a m o d el s h o wi n g t h e co m b i n ed effect o f i n fo rm at i o n p en e t rat i o n an d d i s rup t i o n p rob ab i l i t y o n i n d i v i d u al ro u t e ch o ice an d n et wo rk p er fo rm an ce. 2

13 1.3 Literature Review Fo r t h e p u rp o s e o f t h i s res ea rch, i t i s i m p o rt a n t t o res ear ch i m p o rt an t s t u d i es co n cern i n g m o d el i n g u s er eq u i l i b ri u m, h et ero ge n eo u s ri s k at t i t u d e, an d ro u t e ch o i ce m o d el s b as ed o n i n fo rm a t i o n acces s User Equilibrium Models In an y g en er al n et wo rk, t rav el ers w an t t o ch o o s e t h e ro u t e t h at b es t s u i t s t h ei r n eed s ( e. g. m i n i m i z e t ra v el t i m e, av o i d co n ges t i o n, et c.); h o wev e r, t h e y d o n o t al wa ys ch o o s e t h e b es t ro u t e. Al s o, wh i l e a ro u t e m a y n o t al wa ys b e t h e b es t ch o i c e fo r a t rav el er, i t d o es h av e a ch an ce t o b e. P rob ab i l i s t i c ch o i ce th eo r y as s u m es t h at b o t h t rav el ers w an t t o ch o o s e t h e b es t ro u t e an d each ro u t e h as a c h an ce o f b ei n g t h e b es t. Ap p l i cat i o n o f p rob ab i l i s t i c ch o i ce t h eo r y can t h en b e u s ed i n t h e d ev el op m en t o f t ra ff i c as s i gn m en t m o d el s t h at can creat e s t o ch as t i c u s er eq u i l i b ri u m (S UE) co n d i t i o n s (Dag a n z o an d S h effi, ). Un d e r S UE, fl o w s are as s i gn ed t o ro u t es b as ed o n t h e p rob ab i l i t y t h at ea ch ro u t e wi l l b e ch o s en. Lo gi t m o d el s (Di al, ; Fi s k, ; Bel l, ; M ah er, ) as s u m e t h e erro r t erm s o f e ach ro u t e ch o i ce a re i n d ep en d e nt l y an d i d en t i cal l y d i s t ri b u t ed Gu m b el v ari ab l es, al l o wi n g fo r a cl o s ed fo rm p rob ab i l i t y (Ben - Ak i v a an d Le rm a n, ). Th e d i s t ri b u t i o n as s u m p t i o n can b e t ro ub l es o m e fo r ro u te ch o i c e m o d el i n g, h o wev er, as ran d o m erro rs o f d i ff ere n t o v erl ap p i n g ro u t es ca n hav e h i gh co rr el at i o n s an d d i ffer en t v ari an c es (S h effi, ). P rob i t m o d el s as su m e t ravel t i m e d i s rup t i o n s fo l l o w m u l t i v ari at e n o rm al d is t ri b u t i o n s, al l o wi n g fo r fl ex i b l e v ari an ce a n d co v ari an c e rel at i o n s h i p s. Th i s m ak e s t h e p rob i t m o d el eas i l y ap p l i cab l e fo r ro u t e ch o i ce p r ed i ct i o n s. Th e m o d el l ack s a cl o s e d fo rm p rob ab i l i t y l i k e l o git m o d el s an d c an h av e l i m i t ed l arg e- 3

14 s cal e ap p l i c at i o n s d u e t o ru n n i n g c o s t s (Ni e, ). Th es e m o d el s i n t h ei r o ri gi n al fo rm s, h o w e v er, d o no t t ak e i n t o ac co u n t d i s rup t i o n s t o t h e n et wo rk ex p l i ci t l y an d t h e u n d er l yi n g t rav el t i m es a re d et erm i n i s t i c Risk Attitude Models Th e n u m b er o f s t u d i es d o n e o n m o d el i n g ri s k at t i t ud e i s ex t en s i v e, yet t h e ev al u at i o n m et h o d s fo r r i s k at t i t u d e s t u d i es can res u l t i n d i fferen t cl as s i fi cat i o n s o f ri s k at t i t u d e (S l o v i c ; MacC ri m m o n an d Weh ro n g ). A r eas o n fo r t h i s i s b ecau s e ri s k at t i t u d e m a y n o t b e d et ect ab l e b y j u s t l o o k i n g at peop l e s ch o i ces. Ot h er s i t u at i o n al fact o rs c an cau s e d i ffe ren t cl as s i fi cat i o n s (S ch o em ak er ). Web e r et al. ( ) s u rm i s e fro m t h ei r s t u d y t h at t h ree m et h o d s t h at can h el p m eas u re ri s k at t i t u d e i n v ari o u s wa ys : ex p ect ed u t i l i t y, r e l at i v e ri s k at t i t u d e, an d p ercei v ed ri s k at t i t u d e. Ut i l i t y i s t h e rel at i v e b e n efi t o r u s efu l n es s an ob j ect h as fo r an i n d i v i d u al. W h en ap p l i ed t o a s et o f ri s k y al t ern at i v es, s u ch as a ga m b l e, t h i s b en efi t i s k n own as ex p ect ed u t i l i t y. W h en an al yz i n g a s et o f ch o i ces, i t i s h ypo t h es i z ed t h at an i n d i vi d ual wi l l p i ck an al t ern at i v e t h at m ax i m i zes t h e ex p ect ed u t i l i t y. The at t i t u d e o f an i n d i v i d u al can b e d et erm i n ed b y t h e ch o i c es m ad e d u ri n g ea ch ga m b l e prop o s ed an d fo rm u l at i n g a u t i l i t y fo rm u l a fo r t h at p ers o n. P rat t ( ) an d Arro w ( ) h el p ed d efi n e t h e c h aract eri z at i o n o f ri s k at t i t u d es t h ro u gh u s e o f u t i l i t y fo rm u l as. Th ere ar e t wo as s u m p t i o n s as s o ci at ed wi t h ex p ect ed u t i l i t y t h e o r y: 1 ) ri s k p r efe ren c es can b e d es cri b ed b y a u t i l i t y fu n ct i o n k n o wn o n l y b y t h e m o d el er an d 2 ) at t i t u d es t o ward s ri s k can b e r at i o n al i z ed b y t h e ex p ect ed u t i l i t y fu n ct i o n. Ex p ect ed u t i l i t y c an b e v er y u s e fu l i n i d en t i f yi n g an d d es c ri b i n g p eop l e s ch o i c e p at t ern s o v er a s p eci fi ed p e ri o d, bu t q u an t i f yi n g t h e p e rs o n s ri s k at t i t u d e 4

15 i s rel at i v el y i n s i gn i fi can t (Web er et al ). On e t h eo r y t h at c an i l l u s t rat e t h e d i s ad v an t a g es in ex p ect ed u t i l i t y t h eo r y i s cal l e d cu m u l at i v e p ro s p ect t h eo r y (C P T), wh i ch s t at es t h at i n d i v i d u al s h av e a b i as ed p ercep t i o n o f t h e p rob ab i l i t i es i n a gi v en ch o i ce. Ac co rd i n g to C PT, p eop l e t en d t o o v er-es t i m at e s m al l p rob ab i l i t i es an d u n d er-es t i m at e l arg e p rob a bi l i t i es (Kah n n em an an d Tv ers k y ). R el at i v e ri s k s h o ws t h at t h e d i ff eren ces i n ri s k a t t i t u d e wi t h res p ect t o e x p ect ed u t i l i t y m a y b e a r es u l t o f t h e d i ffer en ces i n m argin al v al u es. R i s k p referen c es m a y r em ai n u n ch an ged wi t h t h i s ap p ro ach, r es u l t i n g i n a m o re st ab l e p er cep t i o n o f ri s k. Us i n g rel at i v e ri s k can m eas u re p eop l e s at t i t u d es t o wards u n c ert ai n o u t co m es rat h er t h an cert ai n o u t co m es (D ye r a n d S ari n ). P ercei v ed ri s k at t i t u d e i s t h e as s u m p t i o n t h at deci s i o n m ak ers a re at t r a ct ed o r rep el l ed b y al t ern at i v e c h o i ces t h at t h e y fe el are ri s k i er t h an ch o i ces t h ey fe el are l es s ri s k y (Web e r an d Bo t t o m ). P ercei v ed ri s k at t i tu d e h as s i gn i fi can t l y s t ro n ge r cro s s - s i t u at i o n al s t ab i l i t y t h an b o t h ex p ect ed u t i l i t y and rel at i v e ri s k. Th i s m et h o d i s p refer ab l e fo r m eas u ri n g p eop l es t en d en c y t o ch o o s e b et w een ri s k y an d s afe ch o i c es (Web er an d M i l l i m an ). W h i l e t h ere are n u m ero u s s t u d i es o n v ari o u s mo d el s t o d et erm i n e p eop l es ri s k at t i t u d e, t h ere i s n o t m u ch res e arch d et ai l i n g t h e cal i b rat i o n o f v a ri o u s ri s k at t i t u d e d i s t ri b u t i o n s t o a fi n d a gen e ral t ren d i n t rav el e r b eh av i o r. Th er e are, h o wev er, m an y ex p eri m en t s wi t h res u l t s t h at s h o w a p o s s i b l e p at t ern i n t rav el er ri s k at t i t u d e. Web er an d Bo t t o m ( ) d et erm i n ed p eop l es ri s k at t i t u d es b y ex am i n i n g t h ei r ch o i ces o n t h eo ret i cal l o t t eri es wi t h v ari o u s p rob ab i l i t i es. U s i n g C P T, t h e y fo u n d t h at 7 6 % o f al l p art i ci p an t s we re ei t h e r ri s k -av ers e o r ri s k -n eu t r al. An o t h er s t u d y, d e P a l m a an d P i card 5

16 ( ), co n cl u d ed t h at 6 6 % o f p art i ci p an t s w ere r i sk -av ers e o r ri s k -n eu t ral an d 3 3 % wer e ri s k -s eek i n g. Web er an d M i l l i m an ( ) u s ed ex p ected u t i l i t y t h eo r y t o ch ar act eri z e t rav el er ri s k at t i t u d e i n o n e o f t h ei r ex p eri m en t s. Th e ex p eri m en t req u i red p art i ci p an t s t o ch o o s e v a ri o u s co m m u t i n g t i m es fo r a t r ai n t o d et erm i n e t h ei r u t i l i t y fu n ct i o n s fo r ri s k as s es s m en t. B y ob s e rv i n g t h e s h ap e o f e ach p art i ci pan t s u t i l i t y fu n ct i o n, i t was fo u n d t h at a m aj o ri t y o f p art i ci p an t s wer e ri s k -av e rs e o r ri s k -n eu t r al wh en t h e co m m u t i n g t i m es were s l o wer t h an o r eq u a l t o t h e av er a ge. W h en c o m m u t i n g t i m es we re fa s t er o r eq u al t o t h e av e ra g e, h o w ev er, a m aj o ri t y o f p art i ci p an t s were fo u n d t o b e ei t h er ri s k -s eek i n g ri s k - n eu t ral. Th e r es u l t s o f t h es e s t u d i es an d o t h ers (Bru i n s m a et al ; Lam an d S m al l ) s h o w a s t ro n g i n d i cat i o n t h at p eop l e t en d t o b e ri s k -av e rs e Real-Time Traveler Information Models P re-t ri p an d en -ro u t e i n fo rm at i o n can al l o w t rav ele rs t o p l an an d ad ap t t h ei r t ri p t o eff ect i v el y m eet t h ei r n e ed s. Tr av el e rs wh o h av e acc es s t o t ra ffi c i n fo rm at i o n are m o r e l i k el y t o fo l l o w t h e p ro v i d ed p re-t ri p an d en -r o u t e t raffi c i n fo rm at i o n (Ab d el -At y an d Ab d al l a, ). En - ro u t e r eal -t i m e t r av el i n fo r m at io n al l o ws t rav el ers t o m ak e ro u t e ch o i ces at d eci s i o n n o d e s b as ed o n cu rren t co n d i t i on s t o av o i d d el a y (M cqu een et al., ). Wi t h rega rd s t o e n -ro u t e s h o rt -t e rm ch o i c es, p ro v i d i n g q u al i t at i v e i n fo rm at i o n i s m o re b en efi ci al fo r t r a v el ers t h an q u an t i t at i v e i n fo rm at i o n (Ab d el -At y an d Ab d al l a, ). Uk k u s ru i et al. ( ) co n cl u d ed t h at an y chan ge i n u s er b eh av i o r d u e t o re al -t i m e i n fo rm at i o n m u s t b e acco u n t fo r i n t raffi c as s i gn m en t m o d el s. 6

17 M o d el s t h at i n co rp o rat e i n fo rm at i o n acces s can g i v e fu rt h er i n s i gh t i n t o trav el e r ro u t e ch o i ce b eh av i o r. Gao et al. ( ) d e s cri b e two ro u t e ch o i c e m o d el s t h at i n co rp o rat e re al -t i m e i n fo rm at i o n : ad ap t i v e p at h m od el s an d s t rat e gi c ro u t e ch o i ce m o d el s. Ad ap t i v e p at h mo d el s as s u m e ro u t e ch o i c es are a s eri es o f p at h ch o i ces at ev er y d eci s i o n n o d e. Th i s can acco u n t fo r d i v ers i o n f ro m t h e i n i t i al p at h b ut d o es n o t p l an ah ead fo r up co m i n g i n fo rm at i o n. S t rat egi c ro u t e ch oi ce m o d el s a re b as ed o n a ru l e t h at m ap s s t o ch as t i c n et wo rk co n d i t i o n s t o ro u t i n g d eci si o n s. Th i s m o d el as s u m es t rav el e rs h av e ex p ect at i o n s fo r e n -ro u t e t r av el i n fo rm at i o n. It al s o as s u m es t h a t t rav el e rs a re p ro act i v e wh en p l an n i n g ro u t es. 7

18 C HAP TER 2 EXP ER IM EN T DES IGN Ex peri m ent R oad Net work Th e d ev el op m en t an d ca l i b rat i o n o f t h e u s er eq u i l ib ri u m m o d el s were b a s ed o n d at a ob t ai n ed fro m t h e ro u t e ch o i ce ex p eri m en t featu red i n Lu et al. ( ). Th e ex p eri m en t was co m p o s ed o f ei gh t s es s i o n s, e ach i n vo l v i n g t h e p art i ci p at i o n o f 1 6 i n d i v i d u al s. Du ri n g ea ch s es s i o n, p art i ci p an t s w er e i n s t ru ct ed t o m ak e ro u t e ch o i c es f ro m wo rk t o h o m e i n t h e n et wo rk, s h o wn i n Fi gu re 1, o n a d a y-t o -d a y b a s i s. Th e y w ere s h o wn t h e free- fl o w t rav el t i m es o f each ro u t e b ef ore t h e s t art o f t h e ex p eri m en t an d were t o l d t h at t h e h i gh wa y h as a d i s rup t i o n p rob ab i l i t y o f W h i l e n o t i n fo rm ed o f t h e d u rat i o n o f t h e ex p eri m en t t o p rev en t b i as, p art i cip an t s m ad e ro u t e ch o i ces fo r d a ys. Aft er ev e r y p art i ci p an t m ad e a ro u t e ch o i ce fo r a gi v en d a y, t h e y w ere s h o wn t h e t rav el t i m e fo r t h ei r ch o s en ro u t e. 8

19 Th e ex p eri m en t was s p l i t i n t o t wo s cen ari o s, each co m p o s ed o f fo u r s es s i o n s. Th e fi rs t s cen a ri o, k n o wn as t h e i n ci d en t cas e, h ad p art i ci p an t s m ak e ro u t e c h o i ces wi t h o u t b ei n g i n fo rm ed i f t h e h i gh w a y w as ex p eri en ci n g an in ci d en t t h at d a y t h a t wo u l d great l y i n creas e t h e t rav el t i m e o n t h at p at h. Th e s eco n d scen ari o, k n o wn as t h e i n f o rm at i o n cas e, p ro v i d ed an i n fo rm at i o n n o d e fo r t rav el e rs w h o ch o se t h e co n n e ct o r. On ce at t h e i n fo rm at i o n n o d e, p a rt i ci p an t s wer e t o l d wh et h e r o r n o t t h e h i gh w a y wa s ex p eri en ci n g s o m e fo rm o f d i s rup t i o n t h at d a y. Th e p art i ci p an t s were t h en ab l e t o m ak e an i n fo rm ed d eci s i o n b as ed o n t h e t r affi c co n d i t i o n s o n t h e h i gh wa y. 9

20 C HAP TER 3 M ODE LING US ER EQU ILIBR IUM W ITH HE TER OGENEOUS R IS K ATT ITUDE Th e fo l l o wi n g s e ct i o n d et ai l s t h e d ev el op m en t o f t he u s er eq u i l i b ri u m m o d el t h at i n co rp o rat es h et ero g en e o u s ri s k at t i t u d e i n i t s p red i ct i o n s. Th i s ch ap t er wi l l d et ai l t h e co n d i t i o n s fo r u s er eq u i l i b ri u m wi t h res p ect t o h etero gen eo u s ri s k at t i t u d e, t h e s o l u t i o n al go ri t h m u s ed t o d eri v e t h e u s er eq u i l i b ri u m, an d t h e as s u m p t i o n s u s ed t o cal i b rat e t h e m o d el. 3.1 User Equilibrium Conditions with Heterogeneous Risk Attitude Th e co n v en t i o n al u s e r eq u i l i b ri u m co n d i t i o n i n a st at i c an d d et erm i n i s t i c n et wo rk i s gen e ral i z ed t o t h e s t o ch as t i c n et wo rk wi t h h et ero gen eo u s u s er ri s k at t i t u d e (wi t h n o real -t i m e i n fo rm at i o n ) i n t h i s t h es i s as fo l l o ws : a t u s er eq u i l i b ri u m, al l u s ed p at h s h av e t h e s am e an d m i n i m u m ex p ect ed d i s u t i li t y fo r each ori gi n -d es t i n at i o n p ai r an d ri s k at t i t u d e cl as s. Fo r t h e n e t wo rk i n Fi gu re 1, u s er e q u i l i b ri u m fo r t h e i n ci d en t cas e i s m et wh en t h e ex p ect ed d i s u t i l i t i es fo r al l t h ree p at h s (t h e art e ri al, h i gh w a y, a n d d et o u r) ar e eq u al an d m i n i m i z ed. It was p rev i o u s l y s t at ed t h at wh en an i n d i v i d u al faces a s et o f ch o i ces, h e/ s h e wi l l p i ck an al t ern at i v e t h at m ax i m iz es t h e ex p ect ed u t il i t y. Ho w ev e r, i n t h e co n t ex t o f ro u t e ch o i ces i n a ro ad n et wo r k, t rav el ers ar e as s u m ed t o m i n i mi z e t h ei r ex p ect ed d i s u t i l i t y, o r t h e rel at i v e co s t a ch o i c e h as fo r an i n d i v i d u al. Th e re as o n ex p ect ed d i s u t i l i t y i s u s ed i n s t ead o f ex p ect ed u t i l i ty i s t h at re ga rd l es s o f c h o i ce, a ro u t e i s as s o ci at ed wi t h a co s t (e. g. t rav el t i m e). 1 0

21 Fi gu re 1: R i s k At t i t udes wi t h R espect t o Ex pect ed Di s ut i l i t y Th e cu rv at u re o f t h e d i s u t i l i t y fu n ct i o n o f ro u t e t rav el t i m es wi l l ch ara ct e ri z e t h e t rav el er s ri s k at t i t u d e as s h o wn i n Fi gu r e 2. Th e ex p ect ed d i s u t i l i t y fo r a t rav el er o n a ch o s en ro u t e i s c al cu l at e d b y t h e f o l l o wi n g eq u at i on : minutes Th e c-v al u e i n t h e eq u at i o n h el p s d en o t e a t r av el e r's ri s k at t i t u d e. R i s k n eu t ral i t y can b e rep r es en t ed wi t h d i s u t i l i t y as t h e s t rai gh t l i n e s h o wn i n Fi gu r e 2, a n d t h e m argi n a l d i s u t i l i t y i s co n s t an t. Un d er ri s k n eu t ral i t y, a t rav el er 's ex p ect ed d i s u t i l i t y fo r a ro u t e i s eq u al t o t h at ro u t e 's t rav el t i m e. Th er efo r e, p eop le wh o a re ri s k n eu t ral wi l l h av e a c- v al u e o f 1.0. Trav el ers e x h i b it i n g a ri s k -av ers e at t i t u d e can b e rep r es en t ed b y t h e co n v ex fu n ct i o n, wh e re t h e m argi n al d i s u t i l i t y i s i n c reas in g. As t h e m argi n al d i s u t i l i t y i s 11

22 i n creas i n g, ri s k - av e rs e t r av el ers wi l l h av e c -v al u e s gr eat e r t h an 1.0. Th e co n cav e fu n ct i o n b es t rep res en t s ri s k -s e e k i n g b eh av i o r, as t h e m argi n al d i s u t i l i t y i s d ecre as i n g. R i s k s eek i n g i n d i v i d u al s wi l l h av e c-v al u es t h at are gr eat er t h an z ero b u t l es s t h an 1.0. Th e c- v al u e i s a p ar am et er t h at m u s t b e cal i b rat ed f ro m dat a. No t e t h at u s er eq u i l i b ri u m i s u s u al l y u s ed t o d es cri b e a s t e ad y s t at e o f a t raffi c n et wo rk. In a n et wo rk s u b j ect t o ran d o m cap a ci t y red u ct i o n, h o w t o d efi n e a s t ead y s t at e i s b y i t s el f a res e ar ch q u es t i o n. In t h i s t h es i s, t h e m ean t rav el t i m e (o r d i s u t i l i t y) t ak en o v er a l a rge n u m b er o f d a ys i s u s ed t o d es cri b e t h e s t at e o f t h e n et wo rk, as b y d efi n i t i o n t h e t rav el t i m e i s a r an d o m v ari ab l e d i s t ri b u t ed o v er d a ys, an d o n e c an n o t ex p ect a fi x ed t rav el t i m e fro m d a y t o d a y. 3.2 Solution Algorithm Th e s o l u t i o n al go ri t h m u s ed t o d e ri v e eq u i l i b ri u m ro u t e ch o i ces (t r affi c fl o ws ) i n t h e n et wo rk i s b as ed o n t h e m et h o d o f s u c ces s i v e ave ra ges (M S A). M S A i s an i t erat i v e p ro ces s t h at wi l l h eu ri s t i cal l y s o l v e fo r eq u i l i b riu m co n d i t i o n s (S h effi an d P o wel l ). Th e al go ri t h m wi l l ru n m u l t i p l e i t erat i o n s an d d i s tri b u t e fl o ws t o an op t i m al p at h wi t h t h e s m al l es t ex p ect ed d i s u t i l it y fo r ea ch ri s k gro up. Th e fi rs t i t erat i o n fo r a g i v en ri s k gro up b e gi n s b y l o o k i n g at t h e f ree fl o w t rav el t i m e o f ev er y p at h i n t h e n et wo rk. Th e p at h wi t h t he l o wes t fre e fl o w t rav el t i m e wi l l t h en h av e t h e en t i re d em an d o f t h e n et wo rk. Fo r t h e n ex t i t erat i o n, t h e ex p ect ed d i s u t i l i t y fo r each p at h wi l l b e cal cu l at ed. Th e p at h wi t h t h e l o wes t ex p ect ed d i s u t i l i t y wi l l t h en b eco m e t h e n ew op t i m al ro u t e ch o i ce. Fl o ws f ro m al l p at h s ar e t h en re- a l l o cat ed b y t h e fo l l o wi n g al go ri t h m. 1 2

23 1. For All Paths: 1 h h h 2. Aggregate Re-allocated Flow: h h 3. Add Aggregate Flow to Optimal Routing Policy: + h 1 3

24 On ce al l t h e fl o ws h av e b een re -al l o cat ed t o t h e opt i m al ro u t e ch o i ce fo r a gi v en ri s k gro up, t h e ex p ect e d d i s u t i l it y fo r ea ch ro u t e ch o i ce wi l l b e re- c al cu l at ed. Th e d i ffer en ce b et ween t h e c u rren t an d p rev i o u s i t erat io n s ex p ect ed d i s u t il i t i es fo r each ro u t e ch o i ce wi l l b e cal cu l at ed. If t h e ab s o l u t e v al u e o f t h i s d i fferen ce i s l es s t h an o r eq u al t o t h e d es i red l i m i t acro s s a l l p at h s fo r each ri s k gro up, t h en t h e M S A an al ys i s wi l l s t op an d eq u i l i b ri u m co n d i t i o n s a re m et. Ot h erwi s e, t h e i t erat i o n p ro ces s wi l l b e c arri ed t h ro u gh u n t i l t h e l i m it co n d i t i o n is m et. 3.3 Model Calibration Two d i ffe ren t t yp es o f cal i b rat i o n s wer e p e rf o rm ed t o d ev el op ri s k at t i t u d e p aram et e rs an d d i s t ri b u t i o n s. Th e fi rs t is a d is ag gre gat e an al ys i s t o d eri v e a ri s k p aram et e r fo r ea ch p art i ci p an t b as ed o n t h e i nd i v i du al l ev el ro u t e ch o i ces o v er t h e d u rat i o n o f t h e ex p eri m en t. Th e s eco n d cal i b rat i o n i s an ag gre g at e an al ys i s t h at cal i b rat es t h e ri s k p aram et er d i s t ri b u t i o n am o n g al l t h e p art ici p an t s o f a gi v en s es s i o n b as ed o n ag g re gat e p at h fl o ws av e ra ged o v er t h e s t e ad y p e r i od o f t h e ex p eri m en t. Th e d i s a g gr e gat e an al ys i s i s u s ed t o p ro v i d e s up p o rt fo r t h e ri s k p aram et e r d i s t ri b u t i o n as s u m p t i o n s i n t h e ag g re gat e an al ys i s. Du e t o a l i m i t ed n u m b er o f co m bi n at i o n s o f p aram e t er v al u es, t h e d i s ag gr e gat e an al ys i s i s n o t yet co m p l et e b u t s t i l l ab l e t o p ro v i d e res u l t s Disaggregate Analysis Th e d i s a g gr e gat e cal i b r at i o n an al ys i s at t em p t s t o ch ar act e ri z e an ex p eri m en t s es s i o n s ri s k at t i t u d e d i s t ri b u t i o n b y ch a ract e ri z i n g ea ch p art i ci p an t s ro u t e ch o i c e b eh av i o r an d as s i gn i n g a c-v al u e b as ed o n t h ei r d ail y ro u t e ch o i ces. T h i s i s d o n e b y 1 4

25 as s es s i n g wh at c-v al u e a n d ad d i t i o n al p aram et e rs p ro d u ce t h e m o s t ac cu ra t e ro u t e ch o i c e p red i ct i o n s fo r each i n d i v i d u al. Th e i n d i v i d u al mo del i n g i s d o n e b y an al yz i n g each d a y s ro u t e ch o i ce, cal cu l at i n g t h e ex p ect ed d i s u t i l i t y f o r each p o s s i b l e ro u t e c h o i ce fo r e ach d a y, cal cu l at i n g t h e p rob ab i l i t y o f an i n d i v i d u al ch o o s i n g a s p eci fi c ro u t e u s i n g a l o gi t m o d el, an d cal cu l at i n g t h e l i k el i h o o d t h e p red i ct e d ro u t e ch o i c es ar e co rre ct b as ed o n t h e gi v en p aram et ers. Th e i np u t fi l e co n t ai n s t h e ro u t e ch o i ce i n fo rm at i on o n a p art i ci p an t o f an ex p eri m en t s es s i o n, i n clu d i n g t h e p art i ci p an t s r o ut e ch o i ce, t h e ro u t e s t rav el t i m e, an d wh et h er o r n o t t h ere w as an i n ci d en t o n t h e h i gh wa y fo r e ach d a y o f t h e ex p eri m en t. Al l 6 4 p art i ci p an t s i n t h e i n ci d en t cas e w er e an al yz ed t h ro u gh t h i s m et h o d. W h en a p art i ci p an t s fi l e i s re ad i n t o t h e p ro gra m, t h e y ar e as s i gn ed wi t h t h re e p aram et e rs t h at wi l l v ar y t h ro u gh o u t t h e cal i b r at i on : a c-v al u e, an art eri al b i as (α ), an d a p rob ab i l i s t i c s cal e ( λ). T h e c -v al u e wi l l h el p d et er m i n e h o w ri s k -s eek i n g o r ri s k -av ers e an i n d i v i d u al i s. Th e art eri al b i as wi l l cap t u re an y bi a s fo r t h e s afe art e ri al n o t acco u n t ed fo r b y t h e ex p ect ed u t i l i t i es, fo r ex am p l e, t o o ffs et an y co m p l i cat i o n s cau s ed b y p art i ci p an t s s el ect i n g t h e art e ri al j u s t b ecau s e l es s cl i ck s w ere req u i re t o fi n i s h t h at d a y s ro u t e ch o i ce s el ect i o n. Fi n al l y, t h e l o g i t m o d el s cal e i s u s e d to d es cri b e t h e s en s i t i v i t y o f t h e ch o i ce t o t h e d i ffer en c e i n ex p ect e d d i s u t i l i ti es. On ce al l t h e p aram et er s are as s i gn ed t o an i n d i v i du al, t h e fi rs t s t ep i n t h e cal i b rat i o n al go ri t h m i s t o an al yz e t h ei r ro u t e ch o i ces fo r ea ch d a y o f t h e e x p eri m en t. Fo r each d a y o f t h e ex p eri m en t, t h e m o d el d et erm i n es whet h er o r n o t t h e art e ri al, d et o u r, o r t h e h i gh wa y w as ch o s en t h at d a y. If t h e h i gh w a y was ch o s en o n t h at d a y, t h e m o d el al s o n o t es wh et h er o r n o t t h e re was an i n ci d en t o n t h e hi gh w a y t h at d a y. W h i l e n o t i n g each 1 5

26 d a y s ro u t e ch o i ce, t h e m o d el wi l l al s o reco rd t h e t o t al n u m b er o f t i m es a ro u t e h as b een ch o s en b y an i n d i v i d u al as t h e m o d el an al yz es t h e rem ai n i n g d a ys o f t h e e x p eri m en t. Th e m o d el wi l l al s o reco rd t h e t o t al n u m b er o f t i m es the h i gh w a y w as ch o s en wh en t h ere w as an i n ci d en t an d wh en t h e re was n o i n ci d en t. Aft er t h e d a y s ro u t e ch o i ce was reco rd ed, e ach ro u t e s av era g e ex p ect ed d i s u t i l i t y was cal cu l at ed fo r t h at d a y. C al cu l at i n g t h e ex p ected d i s u t i l i t y fo r t h e a rt eri al an d t h e d et o u r fo r each d a y u s e t h e s am e p ro c ed u re wh i l e cal cu l at i n g t h e ex p ect e d d i s u t i l i t y fo r t h e h i gh w a y i s m o re co m p l ex. If t h e a rt eri al o r t h e d et o u r w as ch o s en, t h en t h e ex p ect ed d i s u t i l i t y i s cal cu l at ed n o rm al l y u s i n g t h e ch o s en r o u t e s t rav el t i m e. If t h e ro u t e h as b ee n ch o s en o n p r ev i o u s d a ys, t h en i t s ex p ect ed d i s u t i l it y i s av e ra g e wi t h i t s p rev i o u s d i s u t i l i ti es t o cre at e a n e w av e ra ge ex p ect ed d i s u ti l i t y fo r t h at d a y. If a ro u t e h as n o t b een ch o s en at al l, t h en i t s ex p ect ed d i s u t i l i t y i s cal cu l a t ed u s i n g i t s fr ee- fl o w t r a v el t i m e. Th i s i s u n d er t h e as s u m p t i o n t h at p art i ci p an t s rem em b er b ei n g s h o wn e ach ro u t e s fr ee -fl o w t rav el t i m e at t h e b e gi n n i n g o f t h e s es s i o n. Th e r ou t e s ex p ect ed d i s u t i l i ty b as ed o n i t s free -fl o w t rav el t i m e wi l l s erv e as i t s av er a ge ex pect ed d i s u t i l i t y u n t i l i t h as b een ch o s en b y t h e i n d i v i d u al. If an i n d i v i d u al ch o o s es a p r ev io u s l y u n ch o s en ro u t e fo r t h e fi rs t t i m e, t h en i t s ex p ect ed d i s u t il i t y wi l l b eco m e t h e n ew aver a ge ex p ect ed d i s u t i l i t y, as t h e i n d i v i d u al h as m o re ac cu rat e i n fo rm at i o n o n t h e r o ut e t h an t h ei r i n i t i al as s u m p t i o n. W h i l e t h e p ro ces s fo r an al yz i n g t h e h i gh w a y s av er a ge ex p ect ed d i s u t i l i t y i s s i m i l ar t o t h e p r ev i o u s m et h o d u s ed fo r t h e art e ri al an d t h e d et o u r, t h e i n ci d en t p rob ab i l i t y fo r t h e n et wo rk cre at es d i ffer en t co n d it i o n s fo r cal cu l at i n g t h e ex p ect ed d i s u t i l i t y. As t h e h i gh w a y i s s t o ch as t i c, t h ere a re fo u r co n d i t i o n s fo r c al cu l at i n g t h e ex p ect ed d i s u t i l i t y fo r t h e h i gh wa y, d ep en d i n g o n th e n u m b er o f t i m es t h e h i gh w a y w as 1 6

27 ch o s en an d wh et h e r o r n o t an i n ci d en t o c cu rr ed o n th at d a y. If t h e h i gh wa y h as n o t b een ch o s en, t h en t h e ex p ect e d d i s u t i l i t y i s cal cu l at ed u s i n g t h e fo l l o wi n g fo rm u l a: 1 + h h h h Th e fre e-fl o w t r av el t i m e (2 0 m i n u t es ) wh en t h e re was n o i n ci d en t w as p ro v i d ed fo r p art i ci p an t s at t h e b egi n n i n g o f t h e ex p eri m en t, b u t t h ere was n o d es cri p t i o n t o d es cri b e h o w l a rge t h e fr ee-fl o w t r av el t i m e wo u l d i n creas e i f t h ere w as a n i n ci d en t. It i s as s u m ed t h at p art i ci p an t s co u l d t h i n k o f s om e u n reas o n ab l y l o n g t rav el t i m e t o v i s u al iz e t h e h i gh w a y d u ri n g an i n ci d en t, s o u s i n g an i n ci d e nt free -fl o w t r av el t i m e o f m i n u t es was ch o s en fo r an al ys i s. Th e ex p ect ed d i s u t i l i t y cal cu l at ed wi t h t h es e fr ee-fl o w t r av el t i m es i s u s ed as t h e av er a ge ex p ect ed d i s u t i l i t y u nt i l t h e h i gh wa y i s ch o s en. On ce t h e h i gh wa y i s c h o s en, t h e ex p ect ed d i s u t i l i t y i s cal cu l at ed u n d er t h ree p o s s i b l e co n d i t i o n s. On e co n d i t i o n i s i f t h e h i gh w a y h as o n l y b een ch o s en wh en t h er e h as n o t b een an i n ci d en t, wh ere t h e ex p ect ed d i s u t i l i ty eq u at i o n i s : 1 + h h h h 1 7

28 Th e n ex t co n d i t i o n i s i f t h e h i gh wa y h as o n l y b e e n ch o s en wh en t h e re h as b een a n i n ci d en t. It s eq u at i o n i s g i v en as : 1 + h h h h Fi n al l y, t h e l as t ex p ect e d d i s u t i l it y eq u at i o n fo r t h e h i gh wa y ap p l i es w h en t h e h i gh wa y h as b e en ch o s en d u ri n g an i n ci d en t an d n o i n ci d en t at l eas t o n ce, cal cu l at ed wi t h t h e fo l l o wi n g eq u at i o n : 1 + Th e an al ys i s o f a p art i ci p an t s ro u t e ch o i ce an d t he cal cu l at i o n o f i t s resp ect i v e ex p ect ed d i s u t i l i t y co n t i n u e t h ro u gh o u t t h e d u rat i on o f t h e d a y ex p e ri m en t, b u t t h e ro u t e ch o i ce p red i ct i o n p ro ces s o n t h e m o d el s t art s o n t h e 3 1 st s et o f ca l cu l at i o n s. Th i s rep res en t s t h e en d o f t h e ex p l o rat i o n p eri o d p ar t i ci p an t s ex p eri en ce d u ri n g t h e fi rs t 3 0 d a ys o f t h e ex p eri m en t. Th e n ex t 9 0 ro u t e ch o i c e an al ys es fo r t h e i n d i v i d u al re fl ect t h e i d ea t h at i n d i v i d u al s are m ak i n g ro u t e ch o i ces t h a t refl ect t h ei r ri s k at t i t u d e. Th e fi rs t s t ep i n t h e p r ed i ct i o n p ro ces s i s t o d et erm i n e t h e p rob ab i l i t y t h at an i n d i v i d u al wi l l ch o o s e a s p eci fi c ro u t e. A l o gi t m od el i s u s ed t o h el p d et erm i n e t h e p rob ab i l i t y a ro u t e wi l l b e ch o s en ea ch d a y. Th e p rob ab i l i t i es ar e b as ed o n t h e p rev i o u s d a y s av er a ge ex p ect ed d i s u t i l i t y fo r ea ch ro u t e. T h e art e ri al b i as i s ad d ed t o t h e av er a ge ex p ect ed d i s u t i l i t y t o d et erm i n e i f t h e i n d i v i d u al wi l l b e m o re p referen t i al t o t h e art eri al 1 8

29 t h an t h e o t h e r ro u t es i f e v er yt h i n g el s e i s eq u al. Th e av era g e ex p ect ed d i s u t i l i t y fo r ea ch ro u t e i s m u l t i p l i ed b y t h e s cal e an d n e gat ed as t h e ex p ect ed d i s u t i l i t y i s an a s s o ci at ed co s t an d s up p o s ed t o b e m i n im i z ed. Th e l o gi t m o d el eq u ati o n s fo r ro u t e ch o i c e p rob ab i l i t i es are s h o wn b el o w: Th e n ex t an d fi n al s t ep i n t h e p red i ct i o n p ro ces s is t o cal cu l at e t h e i n d i v i d u al s l o g l i k el i h o o d t h at t h e y wi l l ch o o s e t h e ch o s en ro u t es o v er t h e 9 0 -d a y p er i o d, fo u n d b y s u m m i n g t h e n at u ral l o g s o f t h e l i k el i h o o d o f ch o o si n g t h e ch o s en ro u t es fo r ea ch o f t h e 9 0 d a ys i n t h e p red i ct i o n p eri o d. Th e g en er al fo rm ul a fo r t h i s cal cu l at i o n i s s h o wn b el o w: ln h ; 31 h Th e t o t al l o g l i k el i h o o d i s u s ed t o co m p are h o w well t h e d i s a g gre g at e an al ys i s p red i ct s an i n d i v i d u al s r o u t e ch o i ce. Th e cl o s er t h e l o g l i k el i h o o d i s t o z e ro (l i k el i h o o d cl o s er t o 1 ), t h en t h e b et t er t h e m o d el h as p red i c ted an i n d i v i d u al s ro u t e ch o i ce wi t h a gi v en s et o f ri s k p ar am et er, art eri al b i as an d s cale p aram et ers. Th e l i k el i h o o d fo r an 1 9

30 i n d i v i d u al i s cal cu l at ed f o r al l p o s s i b l e p ar am et er gro up i n gs b et we en t h e c -v al u e, a rt eri a l b i as, an d l o gi t s c al e. Th e c-v al u e i n t h e g ro up i n g wi t h t h e t o t al l i k el i h o o d th at i s cl o s es t t o z ero wi l l b e u s ed t o rep res en t t h at p ers o n i n co n s t ru ct i o n o f t h e ri s k at t i t ud e d i s t ri b u t i o n fo r t h e en t i re ex p eri m en t s es s i o n. Calibration Results Th i s s ect i o n p res en t s t h e d i s ag g re g at e an al ys i s res u l t s fo r ea ch s es s i o n i n t h e i n ci d en t cas e. Tab l es 1, 2, 3, an d 4 b el o w s h o w s t he i n d i v i d u al ri s k an a l ys i s o f ev er y p art i ci p an t i n s es s i o n s A1, A2, A3, an d A4, res p ect i v el y. Fo r ea ch i n d i v i d u al, t h ei r p red i ct ed c-v al u e, art eri a l b i as, l o gi t s cal e, an d o p t i m al l i k el i h o o d are p re s en t ed. Fi gu res 3, 4, 5, an d 6 res p ect i v el y p res en t t h e ri s k d i s t rib u t i o n s o f A1, A2, A 3, an d A4, as p red i ct ed b y t h e d i s a g g re gat e an al ys i s. Tab l e 1 : Di s a g gre g at e R e s u l t s fo r S es s i o n A1 User c α λ Likelihood A1u A1u2* A1u A1u A1u A1u A1u A1u8* A1u A1u A1u A1u A1u A1u A1u A1u

31 5 4 Frequency 3 2 A C-Value Fi gu re 2 : P red i ct ed R i s k P aram et er Di s t ri b u t i o n fo r S es s i o n A1 Tab l e 2 : Di s a g gre g at e R e s u l t s fo r S es s i o n A2 User c α λ Likelihood A2u A2u A2u A2u4 1.5 Multiple 0 A2u A2u A2u A2u A2u A2u A2u A2u A2u A2u14* A2u A2u

32 Frequency C-Value A2 Fi gu re 3 : P red i ct ed R i s k P aram et er Di s t ri b u t i o n fo r S es s i o n A2 Tab l e 3 : Di s a g gre g at e R e s u l t s fo r S es s i o n A3 User c α λ Likelihood A3u1* A3u A3u A3u A3u A3u A3u7* A3u A3u A3u10* A3u11* A3u A3u A3u A3u15* A3u

33 12 10 Frequency A C-Value Fi gu re 4 : P red i ct ed R i s k P aram et er Di s t ri b u t i o n fo r S es s i o n A3 Tab l e 4 : Di s a g gre g at e R e s u l t s fo r S es s i o n A4 User c α λ Likelihood A4u A4u A4u A4u4* A4u A4u A4u A4u A4u A4u A4u A4u A4u A4u A4u A4u

34 8 7 6 Frequency A C-Value Fi gu re 5 : P red i ct ed R i s k P aram et er Di s t ri b u t i o n fo r S es s i o n A4 Th e res u l t s s u g ges t t h at m o s t o f t h e i n d i v i d u al s i n t h e s es s i o n a re ri s k -s ee k i n g, b u t t h ere ar e cert ai n i n d i v i d u al s wh o s e op t i m al l i k el i ho o d s s eem ed q u es t i o n ab l e, as i n d i cat ed b y t h e s t a rred u s er IDs. Th e re as o n t h es e l i k el i h o od s are q u es t i o n ab l e i s t h at t h ei r v al u es are s o cl o s e t o t h e l o g l i k el i h o o d o f a p u rel y ran do m gu es s (as s i gn i n g 1 / 3 ch o i c e p rob ab i l i t y t o ea ch al t ern at i v e), , s u g ges t i n g t h at t h e m o d el d o es n o t ex p l ai n t h e p art i ci p an t s b eh av i o r b et t er t h an a p u r el y ran d o m gu es s. Th ere a re a fe w reas o n s as t o wh y t h e d i s a g g re ga t e cal i b rat i o n m a y n o t co rrect l y ch ara ct eri z e t h e i n d i v i d u al ri s k at t i t u d es fo r al l p art i ci p an t s, p a rt i cu l arl y f o r s es s i o n A3. Th e s i m p l es t ex p l an at i o n co u l d b e t h at t h e ran g e o f v al u es fo r t h e a rt eri al b i as an d t h e l o gi t s cal e i s l i m i t ed. Th e art eri al b i as r an ges b et ween an d i n i n crem en t s o f fact o rs o f 1 0, i n cl u d i n g z ero. Th e l o gi t s c al e h as t h e s am e r an ge an d i n crem en t s, ex cl u d i n g z ero. Th e op t i m al b i as an d s c al e v al u e s co u l d b e wi t h i n t h e l i m i t s o f t h e ran g e o r ev en o u t s i d e t h e as s u m ed ran ge. Ex p eri m en t at i o n wi t h t h e ran g e o f v al u es co u l d 2 4

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