Transportation Theory and Applications

Transcription

1 Fall MTAT Transportation Theory and Applications Lecture V: Modal split A. Hadachi

2 General Overview Idea After trip generation process and creating the new OD-matrix we slice it into number of matrices representing different mode of transportation Car Bus OD-Matrix Ship Train

3 objective Factors affecting mode choice Based on available data choose the right mode choice models Estimating model split direct generation models trip end models trip interchange models logit models

4 Mode choice Process by which the trips between traffic analysis zones in study area are allocated to available modes Factors affecting the choice of mode: characteristics of the trip Distance Travel time Purpose characteristics of the transportation system Time schedule Waiting time Transit time Cost characteristics of the trip maker Financial situation Trip members Vehicles available

5 Mode choice The four most common models applied are: Direct generation models Trip End models Trip Interchange Models Logit Models

6 Method 1 Direct generation model

7 Direct generation models Estimate model trips based on population density Population density Transit Assumption We assume that the systems attributes are not relevant to analysis. (e.g. travel times, cost, etc.)

8 Direct generation model Demonstration Example: Let s determine the number of transit trips per day in a specific zone which has 5000 people living on 50 acres (1 acre = 4046m 2 ). 40% no-auto household and 60% one-auto household Transit trips/day/1000 population no-auto/h 1-auto/H Person/Acre

9 Direct generation model Demonstration Example: Calculate population density = 5000/50 = 100 persons/acre Transit trips/day/1000 population no-auto/h 1-auto/H Person/Acre

10 Direct generation model Demonstration Example: Summary from figure: For no-auto household: 510 transit trips/day/ 1000 population For 1-auto household: 250 transit trips/day/ 1000 population Then total trips: (0.4*510*5)+(0.6*250*5)= 1770 transit/day

11 Method 2 Trip end model

12 Trip end model Allocating transit prior trip distribution using mode split curve. Reminder: Trip generation Trip distribution Modal split Transit Estimation Remarks: Transit estimation are based on land use (e.g. population density) Trip end model does not take into account quality of service

13 Trip end model Process: 1.Generating OD- matrix (total trip production and attractions by trip purpose) 2.Compute urban traffic factor (reflect the relationship between the auto ownership and population density ) 3.Determine % of trips using transit using mode choice curve 4.Apply auto occupancy

14 Trip end model Demonstration via example: Determine the % of residents expected to use transit for a zone with 1.8 household per auto and a residential density of persons/km 2 Urban Traffic Factor 100 Transit Mode Split (%) UTF

15 Trip end model Demonstration via example: UTF= (1/1000)*1.8*15000 = 27 Urban Traffic Factor 100 Transit Mode Split (%) % The expected % of transit mode split is ~45% UTF

16 Method 3 Trip interchange model

17 Trip interchange model This model take into account level of service variables in estimating the transit mode split. such as: Travel time Excess time (e.g. waiting time) Travel costs Financial status of trip maker

18 Trip interchange model To perform trip interchange model, we have to compute promotion of trips between zone and impedance factor using QRS method (quick response system). Formula: MS t MS a I ijx I b ijt I b ija MS auto =[ ; or, Iijt b + ] MS transit =[ Ib ija Iijt b + ] Ib ija MS t =(1 MS a ) 100 : proportion of trips between zone i and j using transit : proportion of trips between zone i and j using auto : a value referred to as the impedance of travel of mode m, between i and j, which is a measure of the total cost of the trip impedance =(travel timein vehicle,min)+[2.5(excess time, min)] + (3 trip cost income earned, min ) x : b : an exponent, which depends on trip purpose t : transit mode a : auto mode

19 Trip interchange model travel time in-vehicle is the time spent travelling in the vehicle. excess time is time spent traveling but not in the vehicle, including waiting for any mean of transportation. The impedance factor is determined for each zone pair (i,j) and it represents a measure of the expenditure required to make the trip by either auto or transit.

20 Trip interchange model Information or data needed to estimate mode choice include: Distance between zones transit fare out-of-pocket cost parking cost highway and transit speed exponent value, b median income excess time

21 Trip interchange model Example. For illustrating the application of QRS method, we assume that the data shown in the table have been developed for travel between a suburban zone S and a downtown zone D. Determine the percent of work trips by auto and transit. An exponent value of 2.0 is used for work travel. Median income is euros per year. Table: Travel data between two zones, S and D Auto Transit Distance 10km 8km Cost per km 0,15euros 0,10euros Ecess time 5 min 8 min Parking Cost 1,5euros(or 0,75/ - Speed 30km/h 20km/h

22 Trip interchange model

23 Method 4 logit model

24 logit model the idea behind this model is to consider the relative utility of each mode as a summation of each model attribute. the choice of a mode is expressed as probability distribution

25 logit model in case of two modes: auto (A) and transit (T) are being considered, then the probability pf selecting the auto as a mean of transportation is expressed as follows: P (A) = e U A e U A + e U T Cost for mode A and T out-of-pocket cost Parking cost U x = a 1 t v ij + a 2 t w ij + a 3 t t ij + a 4 t nij + a 5 F ij + a 6 Φ j + δ Travel time in-vehicle Walking time Waiting time Fare charge Parameter for confort

26 logit model

27 logit model