Benefit

Delay savings benefit-to-cost ratio of 8.5:1 found with deployment of a traffic incident management system in Knoxville, Tennessee

Experience using incident reports and real traffic data to estimate delay experienced by roadway users with and without a traffic incident management system.


05/01/2012
Knoxville; Tennessee; United States


Summary Information

This paper presented a model that can be used to estimate benefit-to-cost ratios for traffic incident management (TIM) systems. The model was developed using incident data and traffic data (capacity and 30-second aggregated volume, occupancy, and speed data) collected from 200 traffic monitoring locations in the Knoxville, Tennessee area. In Knoxville, the TIM program (known as SmartWay) was designed to use freeway service patrols, roadway traffic sensors, traffic cameras, dynamic message signs, and a traffic management center (TMC) to manage traffic on two major interstates (I-40 which runs east to west and I-75 which runs north to south) and several auxiliary routes (I-640, I-140 and I-275).

To calculate delay savings, the amount of delay is calculated first by applying the fundamental traffic stream relationship (where flow is equal to density multiplied by velocity) to the speed, volume, and occupancy data for every thirty second interval of every day at each station. Then, delay is compared to the log to find total delay for each incident type. Using the speed, flow, and occupancy data the actual duration and number of stations affected by each incident was determined for each incident. After the location was determined, delay was calculated using a filter that finds the delay for the average number of upstream stations for each category for a period of time before and after the incident discovery time. After, the comparable non-incident day was subtracted.

To find the delay benefits of a TIM program, delay caused by an incident without the TIM system must be known. Without historical data, a modified queuing diagram that could represent an incident’s total delay was used to estimate delay in the absence of the TIM program.

According to the Texas Transportation Institute (TTI) the value of time for Knoxville in 2009 was $16.01 per hour for personal travel and $105.67 per hour for trucks. Combining this information with the mix of personal vehicles and trucks in traffic yielded an hourly value of time. The value of delay was calculated by multiplying the amount of delay by the value of time. The value of delay saved was the dollar amount of savings because of the incident management system. Once delay savings were known, a benefit-to-cost ratio was calculated.

This strategy was organized into a matrix model consisting of three layers in a spreadsheet document. Each layer had 16 matrices representing different time and duration categories for incidents. Within these matrices were the categories for incident type and location.
  • Input layer consisted of the number of each type of incident
  • Calculations layer showed the delay savings calculated for each type of incident (adjustable via a ratio factor, or specific values can be adjusted)
  • Savings layer showed the delay savings for the year with the TIM program.
The model was calibrated comparing the calculated delay to the theoretical delay values based on the queuing model to give the appropriate delays for Knoxville for the year 2009.

FINDINGS

The analysis found a total delay savings of $12.1 million while total costs were $1.43 million, yielding a benefit-to-cost ratio of 8.5:1. Note, however, that the benefit-to-cost ratio for Knoxville only accounted for delay savings. Other impacts such as safety, environmental, and goodwill benefits were excluded.

Researchers indicated that this model may be transferable to other areas where the following data types available: demand, capacity, incident response time, and the equations derived from queuing models. Cities with different volumes of demand and different capacities should realize different results.

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Source

A Benefit Cost Model for Traffic Incident Management

Author: Moss, Sam

Published By: University of Tennessee, Knoxville

Source Date: 05/01/2012

URL: http://trace.tennessee.edu/cgi/viewcontent.cgi?article=2208&context=utk_gradthes

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Goal Areas

Productivity

Typical Deployment Locations

Metropolitan Areas

Keywords

freeway service patrol, courtesy patrols, highway helpers, freeway service patrols, road monitoring, sensors, incident detection, vehicle detector, traffic detection, traffic monitoring, congestion monitoring, CCTV, closed circuit television cameras, camera imaging, DMS, CMS, VMS, Changeable Message Signs, Variable Message Signs, traffic incident management, freeway service patrol, traffic management center, incident clearance, SmartWay

Benefit ID: 2016-01119