Trip Generation Example

Summary

The script discusses the crucial process of estimating trip generation for proposed developments using data from the Institute of Transportation Engineers' Trip Generation Manual. It emphasizes selecting the correct land use type, analysis time period, and independent variable. The example provided involves estimating trips for a gasoline station with a convenience market and fast food restaurant, focusing on the PM peak hour. The script outlines the use of average rates over equations when the R-squared value is less than 0.75 and demonstrates the calculation using the given average rate of 21.78 trips per fueling position for 14 fueling positions, resulting in an estimated 305 trips.

Takeaways

• 🚦 Estimating trip generation for a development is crucial for the Traffic Impact Analysis (TIA) or Transportation Impact Study (TIS) process.
• 📚 The primary source for trip generation data is the Institute of Transportation Engineers (ITE) and their Trip Generation Manual, which covers various land use types.
• 🏢 It's essential to select the correct land use type when estimating trips for a proposed facility.
• ⏱️ The process of estimating trips involves choosing the appropriate land use, analysis time period, and independent variable.
• 📊 Developing an estimate includes using either an average rate or an equation, with a preference for the equation if the R-squared value is greater than 0.75.
• 📈 If the R-squared is not provided or is less than 0.75, or the equation is not usable, the average rate should be used, especially if the standard deviation is less than 1.1 times the average rate.
• 🔍 Collecting local data is recommended if available, as it can provide more accurate trip generation estimates.
• 📊 An example in the script involves estimating trips for a gasoline station with a convenience market and fast food restaurant during a weekday PM peak hour.
• 📋 The average vehicle trip ends are calculated based on the number of vehicle fueling positions, which was given as 14 in the example.
• 📊 The data plot and graph provided in the script are similar to those in the ITE Trip Generation Manual, showing a range of vehicle fueling positions and their corresponding trip rates.
• ✅ The final calculation for the example uses the average rate of 21.78 trips per fueling position multiplied by 14 positions, resulting in 305 trips for analysis.

Q & A

What is the primary source of trip generation data mentioned in the script?

The primary source of trip generation data is from The Institute of Transportation Engineers (ITE) and their Trip Generation Manual.

What types of land use are included in the ITE's Trip Generation Manual?

The land use types included are residential, lodging, recreational, institutional, medical, office, retail, and services.

Why is it important to select the correct type of land use when estimating trip generation?

Selecting the correct type of land use is important because it ensures accurate estimation of the trips generated for a proposed facility, which is crucial for the Traffic Impact Analysis (TIA) or Traffic Impact Study (TIS) process.

What are the factors to consider when estimating trips for a proposed facility?

Factors to consider include choosing the appropriate land use, selecting the correct analysis time period, identifying the independent variable, and developing estimates of exiting and entering trips using either an average rate or an equation.

What is the significance of the R-squared value in the context of trip generation data?

The R-squared value indicates how well the equation fits the data. If the R-squared is greater than 0.75, the equation is preferred for estimating trips. If it's less than 0.75 or not provided, the average rate should be used.

How is the decision made between using an equation or an average rate for estimating trips?

The decision is based on the R-squared value of the equation. If R-squared is greater than 0.75, use the equation. If it's less than 0.75 or not provided, use the average rate, especially if the standard deviation is less than 1.1 times the average rate.

What is the example given in the script for estimating trips generated?

The example is estimating the trips generated by all vehicles at a gasoline station with 14 fueling positions, a convenience market, and a fast food restaurant during a weekday PM peak hour.

What is the average number of vehicle fueling positions used in the studies to develop the trip generation information for gas stations?

The average number of vehicle fueling positions used in the studies was 12.

What is the average rate of trips per fueling position for all vehicles at a gas station according to the script?

The average rate of trips per fueling position for all vehicles is 21.78.

What is the significance of the standard deviation in relation to the average rate when estimating trips?

The standard deviation is used to determine the reliability of the average rate. If it's less than 1.1 times the average rate, the average rate can be used for estimation. In the script, the standard deviation of 9.35 is less than 1.1 times the average rate of 21.78, making the average rate suitable for use.

How is the final number of trips calculated for the example given in the script?

The final number of trips is calculated by multiplying the average rate of trips per fueling position (21.78) by the number of fueling positions (14), resulting in 304.92 trips, which is then rounded up to 305 trips for analysis.