自動駕駛汽車（AV）時代的停車即乘：私人到共享的自動駕駛汽車傳輸系統.pdf

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1、Conference on Innovations in Travel Analysis and PlanningSession B3:Sustainability and Multimobility(June 5,2023,at 3:30 PM)Conference on Innovations in Travel Analysis and Planning1.Research Background2.Methodology3.Case Study4.Discussions382030Conference on Innovations in Travel Analysis and Plann

2、ingMotivationPAV-SAV Transfer SystemResearch QuestionsConference on Innovations in Travel Analysis and Planning Park-and-ride(PNR)system-Private vehicle-to-public transit-Implemented since 1960s-Low-density suburbs(high-capacity transit are unreachable)urban core(#of private vehicles needs to be con

3、trolled)-Park,walk,wait,and ride Inconvenient With autonomous vehicles(AVs)-Waitand ride-Privately owned AV(PAV)to shared-ride AV(SAV)We suggest a new PAV-SAV transfer systemQuality of ServiceCapacityTaxiFixed-route transitDemand-responsive busRidesharingVanpoolConference on Innovations in Travel An

4、alysis and Planning SOV travelers have two options:PAV-only and PAV-SAV transfer system-Each SOV traveler has a person trip:origin-to-destination trip.-Each person tripconsists of one or multiple vehicle trips.-A vehicle trip can be either:origin-to-destination(Option 1,PAV),ororigin-to-station(Opti

5、on 2,PAV),station-to-destination(Option 2,SAV),or destination-to-destination(Option 2,SAV)trip.Conference on Innovations in Travel Analysis and PlanningTransfer StationConference on Innovations in Travel Analysis and Planning How many travelers would use the PAV-SAV transfer system?How much can the

6、PAV-SAV transfer system reduce VMT and congestion?What is the optimal,or at least a good,design for the PAV-SAV transfer system?Conference on Innovations in Travel Analysis and PlanningSystem ConfigurationProblem FormulationSolution ApproachConference on Innovations in Travel Analysis and PlanningPA

7、V-SAV transfer stationFreeway linksSAV laneFreeway exitsUpstreamDestinations(downtown)DownstreamOrigins(suburb)Conference on Innovations in Travel Analysis and Planning,=1(,),(1),=2(,),(2),=3(),(3)#of vehicle trips from node to node market share for traveler O/D pair-cost for traveler O/D pair-by mo

8、de,=231,=(),(4)Formulation in system level-updates market shareTotal travel demand and mode choice(market share)determinevehicle tripsMode choice(market share)is stochastically decided by path travel costVehicle trips determinepath travel costFixed-point Problemcompact(closed&bounded)and convex 0,1c

9、ontinuousAt least one fixed point existsConference on Innovations in Travel Analysis and Planning,=1(,),=2(,),=3()avgrel=,+1,(5)maxabs=max,+1,(6)Two stopping criteria using gaps:-Average relative gap(Eqn.5)-Maximum absolute gap(Eqn.6)Conference on Innovations in Travel Analysis and Planning12345123,

10、matrix,matrix1123451231-1-2-3-4-5-12Group 3:station-to-destination trip(SAV)Group 1:PAV-only travelGroup 2:origin-to-station trip(PAV)PAV-SAVtravel4Group 4:SAV return trip(optional)333Cluster 1Cluster 2Vehicle trips:The vehicle travel patterns of PAV-only and PAV-SAV transfer serviceNon-service user

11、sService users-origin to transfer station-transfer station to destinationAfter dropping off all passengersConference on Innovations in Travel Analysis and Planning,matrix1123451231-1-2-3-4-5-12Group 1:PAV-only travelGroup 2:origin-to-station trip(PAV),=,1 ,(8),=,=,(9)With service rate,Eqn.8:Trips he

12、ading for persons destination are non-service trips.Eqn.9:Trips heading for a transfer station are service trips.Conference on Innovations in Travel Analysis and Planning,matrix1123451231-1-2-3-4-5-Group 3:station-to-destination trip(SAV)333Cluster 1Cluster 2,=1,|=,|=,(10),1,+,2,=1|,1,1+,2,2(11),1,=

13、1|,1,1+,2,2 1 ,1(12)1,2,=1|,1,1+,2,2 1 ,1,2(13),2,=1|,1,1+,2,2,1(14)Eqn.10:Probability that a passengers destination zone is NOT(for simplification of following equations)Eqn.1114 are under assumption of only 2 destination zones within a cluster.Eqn.11:The total number of vehicles from a station to

14、destinations 1and 2is the number of travelers heading for 1and 2divided by the number of onboard passengers per vehicle.Eqn.12:The number of SAVs traveling from to 1(excludes the vehicles that have no passengers traveling to 1).Eqn.13:Destination-to-destination trips for SAVs having passengers for b

15、oth destinations.Eqn.14:Vehicles skipping 1(no passenger going to 1in the vehicle)Conference on Innovations in Travel Analysis and Planning,1,=1|,1,1+,2,2 1 ,1(12)1,2,=1|,1,1+,2,2 1 ,1,2(13),2,=1|,1,1+,2,2,1(14),1,+,2,=1|,1,1+,2,2(11),=1,|,1 ,+,+,1=+11,+22 ,|(16),=1,|,1 ,=11,+21(17),=1,|,(15)General

16、izationLarger possible numbers of destination zonesEqn.15:Vehicles from station destination zones is the total number heading for the cluster divided by the number of onboard passengers.Eqn.16:Vehicles from to considers the probability that a vehicle has both passenger and passenger.Eqn.17:Vehicles

17、from station to considers the probability that a vehicle has no passengers heading for 1,2,1.Conference on Innovations in Travel Analysis and Planning=!e(18),=,|,(19),=1max1,()+1=1max1,max(20),=1max1,()+1=1max1,max(21),matrix1123451231-1-2-3-4-5-Group 3:station-to-destination trip(SAV)333Cluster 1Cl

18、uster 2Lets assume travelers arrive at station with Poisson distributionEqn.20:Arrival rate for each destination clusterThe number of onboard passenger is variable since the waiting time at station is limited.Variation of Eqn.1617Eqn.2021:Considers stochasticity of the number of onboard passengersCo

19、nference on Innovations in Travel Analysis and Planning,matrix1123451231-1-2-3-4-5-4Group 4:SAV return trip(optional)Cluster 1Cluster 2Options:-Go to nearby parking space(within zone)-Return to transfer station-Serve other passengers in downtownConference on Innovations in Travel Analysis and Planni

20、ngmin()=0()(22a)subject to,=,(22b),=(22c),0(22d)UE AssignmentLink Performance(BPR)=01+(23)Calculate travel costs using user-equilibrium static traffic assignmentWe can use other volume delay functions as well.Conference on Innovations in Travel Analysis and Planning,=,+,+(24),=,+,+,+,+1(25),=,+,(26)

21、Binomial LogitService choice model:choice between PAV-only and PAV-SAV transfer serviceConference on Innovations in Travel Analysis and PlanningGreater Los Angeles Area and DTLAScenario SettingsAnalysis ToolsResultsConference on Innovations in Travel Analysis and PlanningAxes 1&4Axes 2&3Downtown TAZ

22、ClusterFreeway exitTAZs(Subarea/SCAG region)3,072/4,192O/D trips7,536,809To-DTLA trips134,279Time6 AM to 9 AMConference on Innovations in Travel Analysis and Planning#VariablesDescriptionScenario LabelCases0Do-nothing+1116Base scenarios+16116Number of stationsDefault One station per axis(4 stations)

23、Best of Base scenarios11720Three axes(3 stations)Scenario 1720+421Two stations per axis(8 stations)Scenario 21+1121SAV capacityDefault Four seats per vehicleBest of Base scenarios122Six seats per vehicle(Best of Base scenarios)-6+123Eight seats per vehicle(Best of Base scenarios)-8+1123Station acces

24、s linksDefault Freeway and arterial access1 from 116,1 from 1720,21,2242427Freeway access-onlyF scenarios+42831Arterial access-onlyA scenarios+4123Destination zone clustersDefault Five clusters(46 TAZs per cluster)1 from 116,1 from 1720,21,2243235Nine clusters(3 TAZs per cluster)C scenarios+43639No

25、clusters(1 TAZ per SAV)N scenarios+4123Initial market shareDefault Initial market share of 0%1 from 116,1 from 1720,21,2214049Initial market shares of 10%to 100%Different initial market share+10Conference on Innovations in Travel Analysis and PlanningPythonTransCADConference on Innovations in Travel

26、 Analysis and Planning0.0%1.0%2.0%3.0%4.0%5.0%6.0%7.0%2345Average Relative GapIteration1(AAAA)2(BAAA)3(ABAA)4(BBAA)5(AABA)6(BABA)7(ABBA)8(BBBA)9(AAAB)10(BAAB)11(ABAB)12(BBAB)13(AABB)14(BABB)15(ABBB)16(BBBB)Average Relative Gap of base scenarios0.0%1.0%2.0%3.0%4.0%5.0%6.0%7.0%2345678910Average Relati

27、ve GapIterationAverage Relative Gap of Scenario 160.0%1.0%2.0%3.0%4.0%5.0%6.0%2345Maximum Absolute GapIteration1(AAAA)2(BAAA)3(ABAA)4(BBAA)5(AABA)6(BABA)7(ABBA)8(BBBA)9(AAAB)10(BAAB)11(ABAB)12(BBAB)13(AABB)14(BABB)15(ABBB)16(BBBB)Maximum Absolute Gap of base scenarios0.0%1.0%2.0%3.0%4.0%5.0%6.0%2345

28、678910Maximum Absolute GapIterationMaximum Absolute Gap of Scenario 1611%12%13%14%15%16%17%18%19%12345Market ShareIteration1(AAAA)2(BAAA)3(ABAA)4(BBAA)5(AABA)6(BABA)7(ABBA)8(BBBA)9(AAAB)10(BAAB)11(ABAB)12(BBAB)13(AABB)14(BABB)15(ABBB)16(BBBB)Market Share of base scenarios17.4%17.6%17.8%18.0%18.2%18.

29、4%18.6%12345678910Market ShareIterationMarket Share of Scenario 16Conference on Innovations in Travel Analysis and Planning0%50%100%150%200%250%300%350%400%1234Average Relative GapIteration0%10%20%30%40%50%60%70%80%90%100%Average Relative Gap of different staring points0%10%20%30%40%50%60%70%80%90%1

30、00%1234Maximum Absolute GapIteration0%10%20%30%40%50%60%70%80%90%100%Maximum Absolute Gap of different starting points0%10%20%30%40%50%60%70%80%90%100%01234Market ShareIteration0%10%20%30%40%50%60%70%80%90%100%Market Share of different starting pointsConference on Innovations in Travel Analysis and

31、Planning-0.28%-0.34%-0.31%-0.36%-0.30%-0.35%-0.32%-0.37%-0.31%-0.35%-0.32%-0.36%-0.32%-0.37%-0.33%-0.38%-300000-250000-200000-150000-100000-5000001(AAAA)2(BAAA)3(ABAA)4(BBAA)5(AABA)6(BABA)7(ABBA)8(BBBA)9(AAAB)10(BAAB)11(ABAB)12(BBAB)13(AABB)14(BABB)15(ABBB)16(BBBB)VMT Change(vehicle-mile)Scenario(st

32、ation locations)-1.05%-1.20%-1.11%-1.25%-1.10%-1.23%-1.16%-1.30%-1.13%-1.25%-1.16%-1.26%-1.18%-1.29%-1.20%-1.31%-35000-30000-25000-20000-15000-10000-500001(AAAA)2(BAAA)3(ABAA)4(BBAA)5(AABA)6(BABA)7(ABBA)8(BBBA)9(AAAB)10(BAAB)11(ABAB)12(BBAB)13(AABB)14(BABB)15(ABBB)16(BBBB)VHT Change(vehicle-hour)Sce

33、nario(station locations)VMT change from do-nothing scenarioVHT change from do-nothing scenario05000100001500020000250001(AAAA)2(BAAA)3(ABAA)4(BBAA)5(AABA)6(BABA)7(ABBA)8(BBBA)9(AAAB)10(BAAB)11(ABAB)12(BBAB)13(AABB)14(BABB)15(ABBB)16(BBBB)Passengers(person)Scenario(station locations)Axis 1Axis 2Axis

34、3Axis 40 1 2 3 4 5 6 7 8 1(AAAA)2(BAAA)3(ABAA)4(BBAA)5(AABA)6(BABA)7(ABBA)8(BBBA)9(AAAB)10(BAAB)11(ABAB)12(BBAB)13(AABB)14(BABB)15(ABBB)16(BBBB)Passengers(person/vehicle)Scenario(station locations)Axis 1Axis 2Axis 3Axis 4max=4Number of PAV-SAV service usersAverage onboard passengers per vehicle by a

35、xisConference on Innovations in Travel Analysis and Planning-0.38%-0.28%-0.34%-0.36%-0.34%-0.38%-300000-250000-200000-150000-100000-50000016(BBBB)17(XBBB)18(BXBB)19(BBXB)20(BBBX)21(ALL)VMT Change(vehicle-mile)Scenario(station locations)-1.31%-1.02%-1.21%-1.24%-1.14%-1.39%-35000-30000-25000-20000-150

36、00-10000-5000016(BBBB)17(XBBB)18(BXBB)19(BBXB)20(BBBX)21(ALL)VHT Change(vehicle-hour)Scenario(station locations)VMT&VHT changes for 3-station and 8-station scenarios-300000-250000-200000-150000-100000-50000016(4 stations)19(3 stations)21(8 stations)16-6(6 seats)VMT Change(vehicle-mile)ScenarioDefaul

37、t(both)Freeway access-onlyArterial access-only-35000-30000-25000-20000-15000-10000-5000016(4 stations)19(3 stations)21(8 stations)16-6(6 seats)VHT Change(vehicle-hour)ScenarioDefault(both)Freeway access-onlyArterial access-onlyVMT&VHT changes for different station access link scenarios 4 stations vs

38、.3 stations vs.8 stations Freeway+arterial access vs.Freeway access-only vs.Arterial access-onlyConference on Innovations in Travel Analysis and PlanningDowntown TAZClusterFreeway exitAxes 1&4Axes 2&3Downtown TAZFreeway exit9 ClustersUnclustered-300000-250000-200000-150000-100000-50000016(4 stations

39、)19(3 stations)21(8 stations)16-6(6 seats)VMT Change(vehicle-mile)Scenario5 clusters(default)9 clustersUnclustered-35000-30000-25000-20000-15000-10000-5000016(4 stations)19(3 stations)21(8 stations)16-6(6 seats)VHT Change(vehicle-hour)Scenario5 clusters(default)9 clustersUnclustered0123456785 cluste

40、rs9 clustersUnclustered5 clusters9 clustersUnclustered5 clusters9 clustersUnclustered5 clusters9 clustersUnclustered16(4 stations)19(3 stations)21(8 stations)16-6(6 seats)Passengers(person/vehicle)Scenario1A1B2A2B3A3B4A4Bmax=4max=6VMT&VHT changes for different zone clustering alternativesAverage onb

41、oard passengers per vehicle by zone clusteringConference on Innovations in Travel Analysis and PlanningLocations of 3-mile radius areasDTLA1B1A2B2A3A3B4B4A-0.29%-0.56%-0.31%-0.63%-0.64%-0.27%-0.47%-0.62%-0.55%-0.25%-0.28%-0.33%-0.50%-0.51%-0.27%-0.50%-0.71%-0.59%-0.39%-0.62%-0.39%-0.64%-0.97%-30000-

42、25000-20000-15000-10000-500001B2B3B4BDTLA1B2B4BDTLA1A1B2A2B3A3B4A4BDTLA1B2B3B4BDTLA16(4 stations)19(3 stations)21(8 stations)16-6(6 seats)VMT Change(vehicle-mile)Scenario-Area(within 3 miles of station/DTLA)-1.35%-1.87%-1.00%-2.31%-4.59%-1.32%-1.75%-2.27%-4.29%-1.38%-1.42%-0.68%-2.08%-1.47%-1.06%-1.

43、51%-2.72%-4.89%-1.42%-1.97%-1.06%-2.34%-4.96%-7000-6000-5000-4000-3000-2000-100001B2B3B4BDTLA1B2B4BDTLA1A1B2A2B3A3B4A4BDTLA1B2B3B4BDTLA16(4 stations)19(3 stations)21(8 stations)16-6(6 seats)VHT Change(vehicle-hour)Scenario-Area(within 3 miles of station/DTLA)VMT changes by area and scenarioVHT chang

44、es by area and scenarioConference on Innovations in Travel Analysis and PlanningConference on Innovations in Travel Analysis and Planning How many travelers would use the PAV-SAV transfer system?Up to 25,000 person trips(18%among to-DTLA travels)will use the service during AM peak hours.How much can

45、 the PAV-SAV transfer system reduce VMT and congestion?Up to 288,000 vehicle-miles of VMT reduction,30,000 vehicle-hours of VHT reduction Slight decreases around stations,dramatical decrease in downtown area What is the optimal,or at least a good,design for the PAV-SAV transfer system?Station locati

46、ons near DTLA with larger catchment area serve more travelers.Zone clustering and onboard passengers can be flexible in response to different time-of-day demands.Conference on Innovations in Travel Analysis and Planning The analysis framework only incorporates benefits and not costs.-Facility constr

47、uction and land cost:size of platform and parking space,different rents by location-Number of required SAVs:need to consider return-to-station vehicles The model system does not capture several second order factors.-Intrazonal trips,non-motorized modes(walk,bike)-Household level tours/trips,temporal

48、 travel patternsConference on Innovations in Travel Analysis and Planning Los Angeles in the United States-Has the second largest population,is in the county with the highest population,-Has an extensive network of highways and major arterials high congestion levels during morning peak,-Has surface

49、parking lots that consume a substantial portion of land in Southern California,-Has low mode shares for transit,walking,and biking,despite the moderate year-round weather.Given this context,-Market shares can be lower in Midwest and East Coast cities.VMT VHT benefits can be larger in these cities.-Lower personal vehicle mode share and less comprehensive networks can reduce the market share.-Higher spatial concentration of employment may decrease VHT,VMT more than LA.