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Sequential Demand Forecasting Models CTC-340. Travel Behavior 1. Decision to travel for a given purpose –People don’t travel without reason 2. The choice.

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Presentation on theme: "Sequential Demand Forecasting Models CTC-340. Travel Behavior 1. Decision to travel for a given purpose –People don’t travel without reason 2. The choice."— Presentation transcript:

1 Sequential Demand Forecasting Models CTC-340

2 Travel Behavior 1. Decision to travel for a given purpose –People don’t travel without reason 2. The choice of destination 3. The choice of mode 4. The choice of route or path

3 Trip generation Forecast the number of trips which begin or end in a Traffic Analysis Zone –Must be calibrated –Dependent upon land use socioeconomic factors at both ends

4 Trip Generation –Trip ends (Q) How many trips are being made due to a land use –Production (P) origin of residential based trip –Home - based trip -- begins or ends at home –non-home based trip -- trip does not begin or end at home –Attraction (A) destination of residential based trip

5 Trip purpose work, school, shopping, social, recreational Can be single purpose or multi purpose

6 Zonal model look at trips between zones A zone is a homogeneous area of –land use –population –income –vehicle ownership –same access paths

7 Trip Rate Analysis –Determine the average productions and attractions of a trip generator –ITE Trip Generation Handbook rates by land use based on 1000 sf, employees, students, dwelling units, etc –Need to determine whether the generator or the adjacent street controls volumes generated Why?

8 Pass-by trips Trips not generated by land use –Vehicle deviates from its course to use land use and then continues on its path –What are major land uses where this type of trip is important –can be 25 - 60% of trips –Subtract trips from through traffic, add to turning traffic (in and out)

9 Linked Trips Trips with multiple destinations all within one area and not requiring road access between destinations 10 - 20 % of trips for certain land uses –Used in Malls and shopping centers

10 Example Drive in Bank 5,000 sf w/drive thru 60,000 sf office building AM & PM trips What other times might be important?

11 Grand Vista 131 Single Family Homes 370 Townhouse units 400 Garden Apartments 640K Office Park 257K Shopping center 3 banks & Restaurants 365K Industrial Park 90K Medical Office 180 Room Hotel

12 Grand Vista Spreadsheet

13 Trip Distribution Where do the trips come from? Gravity Model provides answers –force of attraction between two bodies is proportional to the product of their masses and inversely proportional to the product of the distance between them

14 Trip Distribution F is the friction factor proportional to W –F = 1/W^2 P is productions in i A is attractions in j Q is the trips from i to j K is the difference in socio-economic factors from i to j

15 Trip Distribution Gravity model works for large and small developments –may need to calibrate large developments usually use census tracts as zones can use information developed by developer Retail stores use zip codes

16 Trip Distribution Attraction depends on –uniqueness –distance –closeness to other services –urban or rural Shopping Centers usually have a 5 mile radius of influence

17 Grand Vista 6 access roads Need to distribute traffic to each site driveway –Based on destination/start point –This is where judgment comes in Spreadsheet

18 Modal Choice Trip makers choose mode –trip type is a factor –socio-economic status is a factor –transit captives 2 types of models –pre-distribution - attraction has no impact on mode –Post-distribution – attraction does impact mode

19 Models Diversion curves –based on auto costs, transit travel time, auto travel time, transit LOS, auto LOS, income

20 Models Utility and Disutility measures satisfaction or impedance of choice All provide a percentage of trips per mode –As inputs change, outputs also change

21 Network Assignment Determine path Number of paths depends on network person trips vs vehicle trips Transit Assignment –depends on capacity, facilities, connectivity

22 Network Assignment 3 major times - Peak Hours Trip direction is important Diversion Curves –good when only two paths to choose from –arterial vs freeway –many iterations based on travel time of each facility

23 Link Flow Flow that occurs on a link in a network Route Choice Behavior –user equilibrium goes on shortest path –system equilibrium cost of system is minimized –stochastic equilibrium user assigns self to “shortest path”

24 Minimum Path Algorithms Minimizes most important user criteria –cost, time, distance –can also develop trade-offs between criteria to determine “best route” –can determine the traffic on a link

25 Minimum Path Algorithms All or Nothing Multipath Traffic Assignment Capacity Restrained Transit Assignment

26 All or Nothing Need to find minimum path tree for network place traffic on links gives info on most heavily used links not accurate for high volumes

27 Grand Vista Add traffic to links to get build volumes Spreadsheet

28 All or Nothing Example

29 Volumes From/ To ABCDE A0200300100500 B2000100250300 C 2000400100 D400150200050 E1005004002000

30

31 Volumes From/ To 12345 10300200400500 21000400350200 34001500300200 43004503000250 53002003002000


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