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A-1 A p p e n d i x A Recent Examples of Long-Distance Travel Demand Studies (ORNL, UMD)
Mo de l/ St ud y G eo gr a phi c De ta il Mo de s T ri p Purp os es De ma nd Co mp on en ts Mo de l Ob je ct iv es Me th od Ex pl an at or y Va ri ab le s D at a So ur ce s UN I TED ST AT ES TS AM (Ash ia bor , Ba ik et al (2 00 7- 20 08 )) Co unt y le ve l C ar , Ai r, SA TS , (B us , Ra il) Bu si ne ss / No n- Bu si ne ss TG (t ri p ge ne ra ti on ), TD (t ri p di st ri bu ti on ), MC (m od e ch oi ce) , TA (t ra ff ic as si gnm en t) Ne st ed an d mi xe d lo gi t mo de ls we re de ve lo ped to st ud y na ti on al -l ev el in te rc it y tra ns po rt at io n in th e Un it ed St at es. Th e Tr an sp or ta ti on Sy st em s An al ys is Mo del Ne st ed Lo gi t/ Mi xe d Lo gi t T ra ve l ti me, Tr av el Co st , Ho us eh ol d In co me , Re gi on Ty pe AT S 19 95 fo r m odel cal ib ra ti on . In addi ti on Vi rg in ia T ech con du ct ed tr av el su rv ey s Ko ppe lm an (1 99 0) Ci ty /M et ro Pa ir s (u si ng da ta fr om NT S 1 977 ) Ca r, Ai r, Bu s, Ra il Bu si ne ss / No n- Bu si ne ss TG , TD , MC , Se rv ic e Cl as s Ch oi ce De ve l op a beh av io ra l fr am ew or k an d mo de l sy st em fo r in te rc it y tr av el Di sa ggr eg at e Ne st ed Lo gi t Model Tr av el ti me , cost , dep ar tu re fr eq ue nc y, di st an ce be tw ee n ci ty pa ir s, ho us eh ol d in co me , stru ct ur e, an d si ze , em pl oy me nt , mu se um i d ti i d 19 77 NT S, su ppl em en te d wi th da ta on in te rc it y le ve rl of ser vi ce Ko ppel ma n an d Se th i (2 005 ) O nl y mo de ch oi ce/ se rv i ce cl as s ch oi ce fr om su rv ey s Ca r, Ai r, Ra il Sl ee pe r, Ra il Pr em iu m Co ach , Ra il Ec on om y Sl eeper NA MC , Se rv ic e Cl ass Ch oi ce Th is re sear ch in te gr at es th e co ns id er abl e pr og re ss th at ha s been ma de in re la xi ng th e ass um pt io n of in dep en den ce ac ros s al te rn at iv es an d th e ho mo ge ne it y of e rro r va ri an ce/ co va ri an ce acr os s ob se rv at io ns wi th in th e con te xt of cl osed fo rm ex te ns io ns of th e MN L/ NL mo del s. MN L Mo de l, ne st ed lo gi t, an d ge ne ra li ze d ne st ed lo gi t Co st , sc he du le co nve ni en ce, ov er ni ght du mm y, qu a lit y of se rv i ce, gr ou p si ze , in com e, di st an ce Th e da ta fo r th is st ud y is dr aw n fr om St at ed Pr ef er en ce, SP, su rv ey s of bo th ex is ti ng ra il us er s (1, 000 resp on de nt s) an d tr av el er s us i ng ot he r in te rc it y tr av el mo de s; ai r, au to m obi le , an d bu s; re fe rre d to as no n- us er s (4 00 re spon de nt s) . Ra il us er s we re r ecr ui te d by a sel f- ad mi ni st er ed su rv ey co nd uc te d in Fa ll 1 998 on -b oa rd in te rc it y tr ai ns se rv i ng lo ng di st an ce tr av el ma rk et s, mo re th an 250 mi le s. Th e no n- us er sa mp le , sel ec te d to pr ov id e a com pr eh en si ve ge og ra ph ic al co ve ra ge acr os s th e US , wa s re cr ui te d fr om a ra nd om sa mp le of ho us eh ol ds in wh ic h at le as t on e me mb er ha d ma de a lo ng di st an ce in te rc it y tr ip in th e re ce nt pa st . Co ld re n et al (2 003) Ci ty pa ir s in th e U. S. Ai r N A I ti ne ra ry Sh ar e Mode ls Th is st ud y re po rts th e re su lt s of a ggr eg at e ai r- tr av el it in erar y sh ar e mo de ls est im at ed at th e ci ty -p ai r le ve l fo r al l ci ty -p ai rs in th e US . Th ese mo del s de te rm in e th e f act or s th at in fl ue n ce ai r lin e ri de rs hi p at th e it in er ar y le ve l an d su ppor t ca rri er deci si on - ma ki ng. A ggr eg at e mu lt in om ia l lo gi t L ev el -o f- se rv ic e, co nne ct io n qu a lit y, car ri er , ca rri er ma rk et pr esen ce, fa re s, ai rc ra ft si ze an d ty pe, an d ti me of da y. Pa ss e nge r bo ok i ngs da ta we re ob ta in ed fr om a co mp il at io n of Co mp ut er Re se rv at io n Sy st em s (C RS ). Ai r ca rr ie r sc he du le in fo rm at io n wa s ob ta in ed an d is co mme rc ia lly av ai la bl e fr om th e Of fi ci al Ai rl in e Gu id e (O AG ). Fi na ll y, ma rk et si ze an d fa re da ta we re ob ta in ed fr om th e âS up er se tâ da ta so ur ce (D at a Ba se Pr od uc ts , In c. ). Th is is qu ar te rl y ma rk et si ze an d fa re da ta ge ne ra te d fr om th e ra w 10 % sa mp le of fl ow n da ta co ll ec te d by th e US De pa rt me nt of Tr an sp or ta ti on . Ji n an d Ho ro wi tz (2 00 8) Ti me of Da y Ch oi ce Mo de li ng ba se d on NH TS Ca r, Ai r, Ot he r W or k/ Sc ho ol , Re tu rn Ho me , Pe rs on al Bu si ne ss , Soci al Re cr eat io n Ti me of Da y Ch oi ce Th is st ud y ex pl or es th e ti mi ngâ sc he du li ng deci si on -m aki ng be ha vi or fo r lo ng, occasi on al , an d ex cept io na l tr av el , rat he r th an ha bi tu al , re pe ti ti ve tr ip s. mu lt in om ia l lo gi t mo de l T ra ve l ti me , trav el co mp an io ns , act iv it y du ra ti on , ag e, ge nd er , ed u cat io n le ve l, ho us eh ol d in co me , ho us eh ol d si ze , au to mo b ile ow ne rs hi p, pr esen ce of a ch ild 20 01 Na ti on al Ho us eh ol d Tr av el Su rv ey dai ly -t ri p su rv ey da ta E nha nc ed wi th th e us e of a pref er en ce su rv ey th at wa s con du ct ed by e- ma il or by fa ce- to -f ace in te rv ie ws . Fo ur te en re spon ses we re co lle ct ed an d 20 lo ng tri ps we re re corded . Ep st ei n et al 2009 Mi cr os im ul at io n I NDI VI DU AL ST A TE ST UD IE S Mi ch ig an 23 07 in st at e TA Zs , 85 ou ts ta te TAZs Ca r H B wo rk /b iz , HB so c/ r ec/ v ac, HB O, NH B wo rk /b iz , NH B TG , TD , TA De ve l opm en t, ma in te na nc e an d app li cat io n of a St at ew id e Tr av el De ma nd Mo de l. Us ed Tr an sPl an an d Tr an sC AD Ho us eh ol d si ze , in co me , tr av el co st , ar ea ty pe NP TS da ta us ed fo r cal ib ra ti on , CT PP fo r va li dat io n Or eg on 29 50 zo ne s (i ns ta te an d wi th in a 50 mi le ra di us ). Ea ch zo ne fi ts wi th in abou t 14 .5 m ill io n gr id ce lls ran gi ng fr om 30 x3 0 me te rs to 300 x3 00 me te rs Ca r dr iv e, ca r sh ar ed, ur ba n tr an si t, ai r, AMT RA K, in te rc it y bu s, wa lk , bi cy cl e ho me -b ased, wo rk - bas ed TG , TD , MC , TA De ve l op a tr an po rt at io n la nd us e mo de l to und er st an d da ily tr af fi c pa tte rn s by us i ng mi cr osi mu la ti on t ec hni qu es Mi cr os im ul at io n (M on te Ca rl o) an d lo gi t mo de ls re gi on al econ om ic s an d de mo gr ap hi cs, pr odu ct io n al lo cat io ns an d in te ra ct io ns , ho us ho ld al lo cat io ns , la nd dev el op me nt , co mm er ci al mo ve me nt s, ho us eh ol d tr av el , an d tr an spo rt su ppl y Ho us eh ol d su rv ey s, OD su rv ey s, on -b oa rd su rv ey s, speci al iz ed su rv ey s Ma ry la nd 16 07 zo ne s (M ar yl an d, De la wa re an d Wa sh in gt on DC as a wh ol e, an d par ts of Ne w Je rs ey , Pe nns yl va ni a, Vi rg in ia , an d West Vi rg in ia . A re gi on al m ode l (U .S, Me xi co, an d Ca na da) in cl ud es in fo rm at io n on lo ng- di st an ce tr av el dem an d fo r 18 9 zo ne s. Ca r, ai r, ra il , bu s H om e Ba se d Wo rk , Jo ur ne y to Wo rk , Jo ur ne y at Wo rk , Sch oo l, Ho me Ba sed Sh op , Ho me Ba se d Ot he r TG , TD , MC , TA De ve l opm en t of a St at ew id e Tr av el De ma nd Mo de l. Gr av it y mo de l an d ne st ed lo gi t m ode l. A mi cr os im ul at io n te c hni qu e is in tr od u ced fo r lo ng - di st an ce tr av el us i ng th e NH TS . So ci oecon om ic s an d dem og ra ph ic s (pop ul at io n, in com e, occu pa ti on st at us , ho us eh ol d si ze , num be r of wo rker s) , tr av el ti me , tr av el cost Tr av el su rv ey s, NH TS , CT PP, Ce ns us Table A.1. Recent examples of long-distance travel demand studies (ORNL, UMD).
(continued on next page) CORRIDOR STUDIES (N. Amer.) Cambridge Systematics (2006) TAZs Main mode: car, air, conventional rail, and HSR. For Access/Egress: Drive/Park, Drop off, Rental, Taxi, Transit, Walk/Bike Business, Commute, Recreation, Other TG, TD, MC, Access/Egress MC To develop a new ridership forecasting model that would serve a variety of planning and operational purposes: To evaluate high-speed rail ridership and revenue on a statewide basis; To evaluate potential alternative alignments for high- speed rail into and out of the San Francisco Bay Area; and To provide a foundation for other statewide planning purposes and for regional agencies to b d d i i l l Trip frequency. Multinomial Logit Models Employment & Household Characteristics ⢠Trip Purpose/Distance Class ⢠Level of Service ⢠Accessibility ⢠Region ⢠Traveling Party Size The travel survey data used for this project was a combination of new surveys collected for the project and existing surveys from regional and state agencies. After combining these surveys, 6,882 completed surveys were available to use for model estimation Volpe Center (2008) County and MSA level Car, air, existing and high speed rail, bus Business / Non-Business Direct demand modeling Evaluation of High-Speed Rail Options in the Macon-Atlanta-Greenville-Charlotte Rail Corridor Logit model travel time, travel cost, frequency, income Base year demand statistics from Amtrak, DOT Office of Aviation Analysis, 1995 OD Data. Direct Demand Modeling Bhat (1995) Corridor: Toronto-Montreal. car, air, train Paid Business Mode choice The model is estimated to examine the impact of improved rail service on business travel in the Toronto-Montreal corridor.Travel demand models used to forecast future intercity travel and estimate shifts in mode split in response to a variety of potential rail service improvements (including high-speed rail) in the Toronto- Montreal corridor. Heteroscedastic extreme value model using a maximum likelihood technique travel time, travel cost, income, frequency, city type Travel surveys were conducted in the corridor to collect data on intercity travel by four modes (car, air, train and bus). Sample size = 2,769 business travelers. See KPMG Peat Marwick & Koppelman, 1990 for a detailed description of this data. Bhat (1997) Canadian interciy dataset: Toronto Montreal Corridor car, air, train Paid Business Mode choice This article uses an endogenous segmentation approach to model mode choice. This approach jointly determines the number of market segments in the travel population, assigns individuals probabilistically to each segment, and develops a distinct mode choice model for each segment group. Endogenous Segmentation Mode Choice Model income, sex (female or male), travel group size (traveling alone or traveling in a group), day of travel (weekend travel or weekday travel), (one-way) trip distance, frequency of service, total cost, in-vehicle travel time and out-of-vehicle travel time, large city indicator Canadian interciy dataset from VIA Rail, assembled in 1989. The data includes soeiodemographie and general trip-making characteristics of the traveler, and detailed information on the current trip (purpose, party size, origin and destination cities, etc.). The assembly of level-of-service data was done by KPMG Peat Marwick for VIA Rail. Sample size = 3593 business travelers EUROPEAN STUDIES LMS (Netherlands) National. 1308 Zones plus 55 external zones Car driver, car passenger, train, bus/tram/metro, slow traffic 1. home-work 2. business (home-based) 3. business (non-home based) 4. Shopping 5. education (<12) 6. other, children 7. education (12+) 8. social-recreative TG, TD, MC, TA To predict the long-term impact of (policy) measures with respect to reducing traffic congestion, traffic unsafety, and air pollution in the future. The outcomes of the model may contribute to new or adapted policy measures. Three types of policy decisions are supported by LMS: 1. calculate situations without new policies; 2. estimate effects of a package of policy measures; 3. estimate effects of one policy measure. Disaggregate tour frequency model TG: Most important are: structure of household, licence holding and car availability in household, sex, age, educational level, income, licence holding and activity of person. TD/MC: Attraction variables of destination (employees, education places, number of residents, density of employees or population, business district) Accessibility variables (travel time, costs) Socio-economic attributes (licence holding, car availability, part/full time, age band, income band). National Travel Survey. Especially from 1995 with 68.000 households SISD (Italy) Italy. 270 national zones, 62 external Car, Bus, air, interregional train, intercity train, sleeping train 1. workplace commuting 2. work and professional business 3. university education 4. leisure and tourism 5. other purpose TG, TD, MC, TA 1. to simulate the behavior of transportation systems 2. formulate management and planning policies 3. check the effectiveness of proposed interventions 4. official data source Disaggregate tour frequency model TG: Attraction variables (number of residents, employees, location, accessibility logsum) Socio- economic attributes of individual/ household (income category, age band, sex, employment status, education level, license holding dummies, car availability). TD/MC: Employees, hotel beds, same region dummy, travel time and cost per mode, frequency, income group, cars available, license holding dummies. Interviews with 16.000 families, border-crossing interviews, traffic counts.
Mo de l/ St ud y G eog ra ph ic De ta il Mo de s T ri p Purp os es De ma nd Co mp on en ts Mo de l Obj ect iv es Me th od Ex pl an at or y Va ri ab le s D at a So ur ce s ST RE AM S (E U) Me mb er Co unt ri es of th e EU . 201 In te rn al zo ne s, 27 ex te rn al ou ts id e EU , 4 ex te rn al zo ne s fo r th e re st of th e wo rl d Ca r, ai r, coach , ra il, ai r 1. co mm ut in g an d bu si ne ss (< 40 km ) 2. sh oppi ng , per so na l bu si ne ss , ed uc at io n, vi si ts (< 40 km ) 3. ch ar te r ho ld id ay (> 40 km ) 4. bu si ne ss an d co mm ut in g (> 40 km ) 5. in te rn at io na l in de pe nd en t ho li day (> 40 km ) 6. do me st ic ho lid ay (> 40 km ) TG , TD , MC , TA 1. to de ve lo p a mu lt i- mo da l ne tw or k b as ed tr an sp or t mo del of th e EU co ve ri ng pa ss en ge rs an d fr ei gh t 2. to pr od u ce an in it ia l re fe re n ce fo r ecast of tr an spo rt in th e EU 3. to de ve lo p ne w mo de lin g so ft wa re Ag gr eg at e tr ip fr eq ue nc y mo de l T G: Ag e, em pl oy me nt , car av a ila b ili ty , ho us eh ol d st ru ct ur e (a gg re ga te av er ag e per di sti ngu is he d p op ul at io n gr ou p) . TD /M C: Fu ll ti me em pl oy ed per so ns , to ta l pop ul at io n, to ur is m a rri va ls (b ed sp ace s) , gr os s va lu e add ed . NT S UK , NT S ot he r co un tr ie s, Eu ro ba ro me te r su rv ey (1 99 8) NT M 4 (N or wa y) 454 do me st ic zo ne s 1 . car dr iv er 2. car pa ss en ge r 3. pu b lic tr an spor t 4. sl ow tr af fi c 5. ai r (l on g- di st an ce mo del ) 6. sea (l on g- di st an ce mo de l) Sh or t di st an ce: 1. ho me based com mu ti ng 2. ho me ba se d bu si ne ss 3. Ed u cat io n 4. wo rk based bu si ne ss 5. sh oppi ng /p er so na lb us in e ss 6. soci al vi si t 7. r ecr eat io n, ot he r Lo ng di st an ce (> 10 0k m) : 1. wo rk /e du cat io n 2. Bu si ne ss 3. soci al vi si t 4. R ecr eat io n 5. se rv ic es an d ot he r TG , TD , MC , TA Or ig in al obj ect iv e: To ma ke pr ed ic ti on s of th e imp act of po lic y m easu re s to r edu ce th e en vi ro nm en ta l e ff ect s of pr iv at e tr av el . Ad de d: capab ilit y of fo r ecas ti ng tr a ffi c on speci fi c in fr as tr uc tu re lin ks Di sa ggr eg at e to ur fr eq ue nc y mo de l Co mp ar ab le an d ba se d on LM S (N et he rl an ds ) Na ti on al Tr av el Su rv ey (5 ,8 00 ho us eh ol ds ) SA MP ER S (S we de n) 700 do me st ic zo ne s, wh ic h ar e di sa gg re ga te d in to 9000 su bz on es. 1 80 zo ne s in fo re i gn co un tr ie s. 1. car 2. tr ai n (s ev er al ty pes ) 3. co ach / re gi on al bu s 4. ai r (f or lo ng di st an ces) 5. car +f e rry (f or lo ng di st an ces) 6. wa lk -o n fe rry (f or lo ng di st an ces) 7. Wal k 8. bi cy cl e Sh or t di st an ce: 1. Wo rk 2. Bu si ne ss 3. Sch ool 4. So ci al 5. R ecr eat io n 6. Ot he r Lo ng di st an ce (d om est ic pl us in te rn at io na l) : 1. pr iv at e 2. Bu si ne ss TG , TD , MC , TA To pr ed ic t de ma nd ef f ect s of ne w in fr ast ru ct ur e an d se rv i ces , ch an gi ng in co me s, di ff er en t po pu la ti on st ru ct ur e, ch an ge s in tr ade an d in du st ry . To ser ve as a basi s fo r cal cu la ti on of tr af fi c saf et y e ff ect s, en vi ro nm en ta l ef f ect s, en er gy co ns um pt io n, acces si bi lit y e ff ect s, e ff ect s of po lic y me as ur es . Di sa ggr eg at e to ur fr eq ue nc y mo de l Co mp ar ab le an d ba se d on LM S (N et he rl an ds ) NT S Sw eden 1994- 199 8 an d in te rv ie ws fr om fi xe d li nk pr oj ect s NT M (Den ma rk ) 130 0 zo ne s 1 . car 2. tr ai n (s ev er al ty pes ) 3. co ach / re gi on al bu s 4. ai r Sh or t di st an ce: 1. Wo rk 2. Bu si ne ss 3. Sh opp in g 4. R ecr eat io n 5. Ot he r Lo ng di st an ce (d om est ic ): 1.pr iv at e 2. Bu si ne ss TG , TD , MC , TA To pr edi ct ef f ect s of lo ng -d is ta n ce hi gh - speed tr ai n se rv i ces an d ot he r in fr as tr uc tu re in ve st me nt s Di sa ggr eg at e to ur fr eq ue nc y mo de l Co mp ar ab le an d ba se d on LM S (N et he rl an ds ) NT S De nm ar k 19 93 NT M (S wi tz er la nd ) 755 do me st ic zo ne s, 67 fo re ig n zo ne s car , tr ai n w or k, v acat io n, ot he r T G, TD , MC , TA To m ake pr ed ic ti on s of th e im pact of po li cy an d in fr ast ru ct ur e m easu re s. Ag gr eg at e tr ip fr eq ue nc y mo de l, lo gi t m ode ch oi ce . Ag en t- bas ed si mu la ti on Ho us eh ol d su rv ey 1994, O- D Su rv ey , tr af fi c cou nt s BV WP (A us tr ia ) 676 do me st ic zo ne s, 205 fo re ig n zo ne s car , tr ai n, co ach /r eg io na l bu s 1. wo rk 2. Bu si ne ss 3. Sc ho ol 4. Sh opp i ng 5. Le is ur e 6. ot he r TG , TD , MC , TA To pr ed ic t de ma nd ef f ect s of ne w in fr ast ru ct ur e an d se rv i ces , ch an gi ng in co me s, di ff er en t po pu la ti on st ru ct ur e, ch an ge s in tr ade an d in du st ry . Op ti mi ze of Na ti on al Tr an spo rt Co n cept io n, en vi ron me nt al ef f ect s Ag gr eg at e tr ip fr eq ue nc y mo de l H ou se ho ld s ur ve y 19 95 -1 996 , O- D Su rv ey , tr af fi c co unt s BV WP (G er ma ny) 360 do me st ic zo ne s, 83 fo re ig n zo ne s 1. car , 2. Tr ai n 3. bu s (r eg io na l) 4. ai r 5. Bi cy cl e 6. Wal k 1. wo rk 2. Bu si ne ss 3. Sh opp in g 4. Ed u cat io n 5. V acat io n 6. le is ur e an d ot he r TG , TD , MC To pr edi ct dem an d ef f ect s of ne w pol it i cal si tu at io ns in Eu ro pe an d in fr ast ru ct ur e an d tr an spor t po lic y, soci o- de mo gr aph y an d eco no mi c, ch an ge s in tr ade an d in du st ry . Ag gr eg at e tr ip fr eq ue nc y mo de l H ou se ho ld su rv ey , pr ev io us BV WP MA TI SS E (F ra n ce) Li nk s wi th OD di st an ces va ry in g fr om 50 -2 500 km Ca r, ai r, ra il Bu si ne ss , pr iv at e T G, TD , MC , TA Th e mo del wa s dev el oped to an al ys e lo ng di st an ce pass en ge r tr a ffi c (tri ps >5 0 km ), fo cu si ng on Fran ce . Di sa ggr eg at e tr ip fr eq ue nc y m ode l T ra ve l ti me , co st , gr ou p si ze , ti me of day , car av ai la bi li ty , fa re re du ct io n, qu al it y of se rv ic e Fr en ch ho us eh ol d su rv ey "T ra ns po rts 19 81 -1 982 ". Table A.1. (Continued).
Mo de l/ St ud y G eog ra phi c De ta il Mo de s T ri p Purp os es De ma nd Co mp on en ts Mo de l Obj ect iv es Me th od Ex pl an at or y Va ri ab le s D at a So ur ce s NT M (Gr eat Br it ai n) 249 6 Na ti on al Tr ip En d Mo de l (N TEM ) Zo ne s Ca r Dr iv er , Ca r Pa ss e nge r, Bu s, Ra il, Me tr o, Ta xi , Cy cl e, Wa lk HB wo rk , HB Em pl oy er 's Bu si ne ss , HB Ed u cat io n, HB PB /S ho ppi ng, HB R ecr eat io n/ Vi si ti ng Fr ie nd & Re la ti ve s, HB ho li day s an d da y tr ip s, NH B Em pl oy er 's Bu si ne ss , NH B Ot he r TG , TD , MC , Ro ut e Ch oi ce, TA Th e De pa rt me nt fo r Tr an spor tâ s Na ti on al Tr an sport Mo de l (N TM ) ha s b een de ve lo pe d ov er a nu mb er of y ear s, an d ha s b een us ed by th e De par tm en t fo r fo r ecast in g tr av el tr en ds fo r ov er 10 y ear s, pr im ar ily fo r th e pu rp oses of pr od uc i ng th e an nu al ro ad tr af fi c fo r ecast re po rt, po li cy fo rm at io n, an d stra te gi c an al ys is of op ti on s, pr edom in an tl y fo r E ngl an d an d Wa le s. Ne st ed Lo gi t M odel Pe rs on ty pe, Ho us eh ol d in co me (i nd ir ect ly th ro ugh car ow ne rs hi p m odel ), ho us eh ol d ty pe , ge nd er , tr av el cost , tr av el ti me NT S 2 000 Be l (199 7) Spai n S pa ni sh ra il ne twor k by pr ov in ce tr ai n, car NA NA Th is paper speci fi es an d em pi ri ca lly est im at es, an ex pl an at or y mo del to ev al ua te th e im pact of tr av el ti me ch an ge s on in te r- ur ba n ra il de ma nd . Do ub le lo ga ri th mi c fo rm Tr av el ti me , du mm y va ri ab le fo r 'i nc reas e in ai r se rv i ce fr equ en cy ' 19 87 an d 19 91 op er at i ng dat a fr om tr ai n op er at or : Re d Na ti on al de Fe rro ca rri le s Es pa iio le s (R EN FE ) TR AN S- T OOL S N UT S3 ba sed zo na l sy st em of 1 269 zo ne s wi th in Eu ro pe Ro ad, ra il, ai r B us in es s, pr iv at e, to ur is m TG, TD , MC , TA TRA NS -T OOL S ha d th e ob j ect iv e to pr od u ce a Eu ropean tr an sp or t ne tw or k mo de l cov er i ng bo th pass en ge r an d fr ei gh t, as we ll as in te rm od al tr an spo rt , wh ic h ov er com es th e sh ort co mi ng s of cu rre nt Eu ropean tr an sp or t ne tw or k mo de ls an d prov id ed th e Co mm i ssi on wi th an in ho us e up da te d in st ru me nt of si mu la ti on . Th e ob j ect iv e of th e pr oj ec t wa s to bu il d on th e ex per ie n ce of ex is ti ng tr an spor t mo del s an d im pl em en t a num be r of im pr ov em en ts th at ar e th e ba si s of th e de ve lo pm en t of an in te gr at ed po li cy su pp or t to ol fo r tr an spo rt at EU le ve l. No n- lin ear lo gi t fu nc ti on Tr av el cost , tr av el ti me , fr equ en cy , nu mb er of tr an sf er s, po pu la ti on , GD P, em pl oy me nt , car ow ne rs hi p ET IS -B AS E (d at a cat eg or ie s: so ci o- ec on om ic , fr ei gh t dem an d, pa ss e nge r dem an d, tr an sport in fr as tr uc tu re ne tw or k, fr ei ght ser vi ces an d co sts, pass en ge r se rv i ces an d cost , ex te rn al e ffe ct s) . S ee TR AN S- T OOL S Re po rt fo r mo re in fo rm at io n MY ST IC Pr oj ect (P DC 2000 ) S TEM M 126 9 zo ne s car , ai r, rai l B us in es s, pr iv at e, v acat io n TG , TD , MC OT HER NO N- U. S. ST UD IE S Ya o an d Mo ri kaw a (2 005 ) - Japan 6 zo ne s fr om qu es ti on ai re s, 147 zo ne s fr om th e NT S Ca r, ai r, Ra il (c on ve nt io na l, HS R, Sh in ka ns en ), bu s bu si ne ss , no n- bu si ne ss , ho me -b as ed, no n ho me based tr ip ge ne ra ti on , di st ri bu ti on , mo de ch oi ce, ro ut e ch oi ce to dev el op an in te gr at ed in te rc it y tr av el de ma nd mo de lin g sy st em su it ab le fo r su bs ta nt ia l ch an ge s in se rv i ce le ve l. Re gr es si on mo de l an d Ne st ed Lo gi t Mo del s wi th ro ut e ch oi ce TG : A cces si b ilit y, po pu la ti on , wo rk in g po pu la ti on in se rv i ce sect or . TD : lo gs um MC , zo na l GD P pe r capi ta , sh ar e of wo rk in g po pu la ti on , bu si ne ss at tr act iv en ess , no n- bu si ne ss at tr act iv en ess . MC : Tr av el cost , tr av el ti me , acc ess ti me , fr equ en cy , va lu e of tr av el ti me sav in gs . Th e mo de l ut il iz es com bi ne d est im at io n acr os s mu lt ip le dat a sou r ces su ch as SP/ RP su rv ey s at si x ma jo r ra il st at io ns , an d ag gr eg at e dat a fr om th e 20 00 NT S Al di an an d Ta yl or (A us tra lia - 2003 ) - In do ne si a In te rc it y Ce nt ra l Ja va . Nu mb er of zo ne s unk no wn Ca r on ly NA TG , TD , TA A ne w ap pr oach to mo de lli ng in te r- ci ty tr av el th at com bi n es a be ha vi ou ra l tr av el de ma nd mo de l an d a di r ect de ma nd mo de l. Fu zz y mu lt ic ri te ri a an al ys is is ap pl ie d to cal cu la te a ggr eg at e ut ili ti es (tri p pr od uc ti on po we r an d zo ne a ttr act iv en ess ). Fu zz y mu lt ic ri te ri a an al ys is . It adop ts th e stru ct ur e of di sa ggr eg at e m odel s, bu t th e det er mi ni st ic par t of ut i lit y fu nc ti on is de ve l oped at ag gr eg at e le ve l. Th e mu lt in om ia l lo gi t mo de l is appl ie d to cal cu la te tr ip di st ri bu ti on TG : po pu la ti on den si ty , gr oss do me st ic re gi on al produ ct . TD : ro ad us er co st (d is tan ce, ro ad ge om et ry , ri de qu a lit y) , num be r of ho te l ro om s 19 96 na ti on al ori gi n dest in at io n su rv ey Note: Demand Components: TG = Trip Generation, TD = Trip Distribution, MC = Modal Choice, TA = Traffic (Route) Assignment.
