QUESTION 3 a) Describe the factors affecting trip production and trip attraction in a zonal level. Explain their effects on trip generation and why. b) Describe potential travel demand management strategies which can increase average vehicle occupancy during commuter peak hours. Explain how these strategies would change travel patterns, travel time and fuel consumption. c) Explain how residential development in low-density suburban areas affects mode choice and travel distance of work trips.

QUESTION 3 a) Describe the factors affecting trip production and trip attraction in a zonal level. Explain their effects on trip generation and why. b) Describe potential travel demand management strategies which can increase average vehicle occupancy during commuter peak hours. Explain how these strategies would change travel patterns, travel time and fuel consumption. c) Explain how residential development in low-density suburban areas affects mode choice and travel distance of work trips.

Traffic and Highway Engineering

5th Edition

ISBN:9781305156241

Author:Garber, Nicholas J.

Publisher:Garber, Nicholas J.

Chapter12: Forecasting Travel Demand

Section: Chapter Questions

Problem 7P

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Answer the following questions based on your own understanding. Use your own words for answering: 1. Identify and briefly describe the two basic demand forecasting situations in transportation planning. What are the three factors that affect the demand for urban travel? Define the following terms: (a) home-based work (HBW) trips, (b) home-based other (HBO) trips, (c) non-home-based (NHB) trips, (d) production, (e) attractions, (f) origin, and (g) destination.
A large retirement village has a total retail employment of 120. All 1600 of the households in this village consist of two nonworking family members with household income of $20,000. Assuming that shopping and social/recreational trip rates both peak during the same hour (for exposition purposes), predict the total number of peak-hour trips generated by this village using the trip generation models of Example Problems 1 and 2.
12) List and define the 4 steps of the "4-step travel demand model" used in transportation planning.
A model for non-work related trips has been developed by the Texas Department of Transportation for Wheeler, Texas. The model is based on the number of trips per household: Number of peak-hour vehicle-based social trips per household = 0.04+0.018*(household size) + 0.009*(annual household income in thousands of dollars) + 0.16*(number of nonworking household members) For the northeast section of Wheeler, the average household has six members and an annual income of $50,000. If each household has one working member, how many peak-hour social trips are predicted?
A neighborhood has 180 households with the characteristics shown in the table below. A count model for peak-hour work trips is described in the second table. How many trips do you expect from this neighborhood?
Determine the trip distribution matrix using "Gravity Model" of transport system with given the data: Trip Production of Zones 1, 2 and 3, correspondingly are 500, 600, and 800 tpd Trip Attraction of Zones 1, 2 and 3, correspondingly are 600, 700 and 600 tpd
Find at least 5 Case Studies/ Projects related to transportation engineering that utilized Trip Generation, Trip Distribution, Model Split and Trip Assignment.
to no congestion on the road further downstream of the railway grade crossing. QUESTION 5: Consider trip distribution within 5 zones in an area. The total trip production from zone 1 is 1000. The travel times from zone 1 to zones 2, 3, 4 and 5 are 5, 10, 20, and 30 minutes, respectively. The trip attraction to zones 2, 3, 4 and 5 are 50, 200, 75, and 450, respectively. Assume that the number of trips produced from zone 1 to zones 2, 3, 4 and 5 is inversely proportional to the inter-zonal travel time. (a) Estimate the number of trips from zone 1 to zones 2, 3, 4 and 5 using the gravity model. (b) Assume that the future trip production from zone I will increase to 1,250 and the future trip attraction to zones 2, 3, 4 and 5 will increase to 100, 225, 100, and 600, respectively. Predict the number of trips from zone 1 to zones 2, 3, 4 and 5. The inter-zonal travel times remain the same. (c) Compare the number of trips from zone 1 to each destination zone between (a) and (b). Identify the…
The following 3 Travel Demand Forecasting models were created to estimate the number of peak-hour trips in the suburb of Croydon: T1 = 1.0 + 0.3(household size) + 0.01(household income in thousands of $) T2 = 1.5 + 0.2(household size) + 0.01(household income in thousands of $) T3 = 0.5 + 0.5(household size) + 0.01(household income in thousands of $) The suburb has a total of 3500 households with an average of 4 people per household, an average household income of $90,000 and survey data shows that it generates a total of 11,550 trips in the peak-hour. Which of the above models is the most accurate? A. T1 B. T2 C. T3 D. Can't say as 2 or more models are equally accurate.
a) Table 4 indicates an urban zone’s expected household composition at some future year and the calibrated educational-based trip rates. Estimate the total educational-based trips in terms of "y" that the urban zone will produce on a typical day in the horizon year. (A Table 4: Household composition and trip generation rates Number of motor vehicles per household Number of persons per household 1 2793 1.7y 4 5+ 2046 H. 344 2472 3092 R 0.8y 2.Зу 717 3.1x 2.4y 1022 3.1x 2.4y 726 2+ H 294 2.1x R 1.6x 3.3х H= Number of households in category R= Educational trip production rate (per household) in category x-0.5y
Given the following transportation network and the production/attraction data in each zone. 3 min 3 3 min 4 min 3 min 4 min 2 min 4 min 2 7 min Production/Attraction Table Zone 1 2 3 4 5 Production 600 1000 500 Attraction 300 200 350 400 The number of trips that originates from Zone 3 and ends in Zone 1 is 13 88 29 None of the above
A large residential area has 1500 households with an average household income of $15,000, an average household size of 5.2, and, on the average, 1.2 working members. Using the model below, predict the change in the number of peak hour social/recreational trips If employment in the area increased by 20% and household income by 10%. number of peak-hour vehicle-based social/recreational trips per household 0.04 + 0.018(household size)+ 0.009(annual household income in thousands of dollars)+ 0.16(number of nonworking household members)