TEMPORARY LOSSES OF HIGHWAY CAPACITY AND IMPACTS ON PERFORMANCE: PHASE 2

Title | Contents | Acknowledgements | Exec. Summary
1. Intro | 2. Approach | 3. Crashes | 4. Breakdowns | 5. Work Zones | 6. Weather | 7. Signal Timing
8. RR Crossings | 9. Toll Facilities | 10. PUD | 11. Results Summary | 12. Next Steps | 13. References

4. Breakdowns

4.1 Methodology

Capacity reductions and delays due to vehicle breakdowns were estimated using a method similar to the one used for crashes.  However, since national-level data on breakdowns was not available, additional assumptions were necessary to estimate the annual number of breakdowns, the time they occurred, and their location on the national highway network.  The methodology can be summarized into the following steps:

Step 1. The total number of vehicle breakdowns was estimated.

Step 2. The location of each breakdown on the highway network was simulated using a Monte Carlo simulation method based on the VMT on each segment.

Step 3. The time of day each breakdown occurred was simulated using a Monte Carlo simulation method based on hourly vehicle counts.

Step 4. The location of the vehicle on each selected segment was simulated (e.g., right-hand shoulder, left-hand shoulder, right-most lane, etc.).

Step 5. The capacity reduction due to each breakdown was based on the characteristics of the selected highway segment and the location of the vehicle on the segment (e.g., right-hand shoulder, left-hand shoulder, right-most lane, etc.).

Step 6. Delay was estimated based on capacity reduction, vehicle demand on the segment, and the duration of the capacity reduction.

These steps are described in more detail in the paragraphs below.

4.1.1  Estimating the Total Number of Breakdowns

The total number of breakdowns was estimated based on the number of crashes on the highway system. Studies in the literature and data collected from cities with freeway service patrols showed that the ratio of breakdowns to crashes on freeways was roughly eight breakdowns per every crash.  Thus, it was assumed that the total number of breakdowns in the nation would be equal to eight times the number of crashes.  As described in the sections that follow, temporal and location characteristics were assigned to breakdowns based on traffic volume and VMT.

The ratio of breakdowns to crashes was based on a study by the American Trucking Association (ATA) and Cambridge Systematics, Inc. (1991).  In this study, ATA and Cambridge Systematics collected data from Freeway Service Patrols and other agencies that collected crash and breakdown data.  They analyzed this data and produced estimates of the percentage of incidents classified as disablements, crashes, and other events (e.g., clearing debris).  These shares were further broken down by whether or not they blocked lanes.  The study also estimated the average incident duration and the vehicle-hours of delay caused by each type.  The ratio of crashes to breakdowns given in the Cambridge Systematics study was comparable to the ratios observed in both the Giuliano (1989) and Skabardonis et al. (1998) studies.

4.1.2 Assigning Each Breakdown to a Location in the Highway Network

Breakdowns were assigned a location within the highway network using a Monte Carlo simulation method. The probability of a breakdown being assigned to a given segment in HPMS was dependent upon the VMT for that segment. VMT was calculated as the product of the segment’s length and its AADT volume.

4.1.3 Assigning Temporal Characteristics to Each Breakdown

A Monte Carlo simulation was used to assign a day of the week and time of the day to each breakdown. Each hour of the week was assigned a separate bin whose size was dependent upon the traffic volume for that time based on hourly traffic volumes. For breakdowns assigned to urban highways, hourly traffic volume distributions taken from four cities (San Antonio, Texas; Milwaukee, Wisconsin; San Diego, California; and Seattle, Washington) were used in the Monte Carlo simulation (see footnote 5 on page 21). For breakdowns assigned to rural areas, hourly traffic volume distributions taken from the state of Tennessee (T. DOT) were used.

4.1.4 Assigning Each Breakdown a Location within the Selected Link

Each breakdown was assigned a location along the link on which it was placed. This includes the lane, shoulder, or other location at which the vehicle came to rest. Locations on freeways were based on statistics in the literature and from data provided by a few highway service patrols. Principal arterial breakdowns were assumed to have characteristics similar to breakdowns on freeways, except it was assumed that they either came to rest in a lane or were able to get the vehicle to a parking area or side street. It was also assumed that most vehicles breaking down on principal arterials were able to get off the principal arterial (85 percent) onto a side street or into a parking area.

4.1.5 Estimating Capacity Reduction

Capacity reductions were estimated using a methodology similar to the one used for crashes.

4.1.6 Estimating Delay

Delay was estimated using a methodology similar to the one used for crashes.

4.2 Results

This study estimates that, in 1999, over 27 million vehicle breakdowns occurred on freeways and principal arterials, reducing capacity by nearly 7.5 billion vehicles and causing over 440 million vehicle-hours of delay (Table 16). By comparison, crashes caused an estimated 1.7 billion vehicle-hours of delay, nearly four times as much.

This study estimates that breakdowns typically caused only 15.9 vehicle-hours of delay per incident, while crashes caused 505.9 vehicle-hours—over thirty times more delay per occurrence. This is primarily because drivers are usually able to get disabled vehicles off the highway onto the shoulder, a parking area, or a side street with less traffic. Though estimates vary somewhat, studies in the literature and statistics from data sets indicate that approximately 80 percent of vehicle breakdowns do not block highway lanes. This reduces the amount of bottleneck delay significantly although some slowdown from rubbernecking or a vehicle’s proximity to traffic lanes can be expected.

Fig. 12. TLC2 estimates that most delay from breakdowns is experienced on urban principal arterials and rural principal arterials.

4.3 Reliability

4.3.1 Methodology

The methodology for estimating the number of breakdowns is suspect. Breakdowns were estimated to be proportional to crashes. However, no direct relationship between crashes and breakdowns has been established—though both may be related to VMT. This method is accorded a low level of confidence.

The Monte Carlo simulation method used to assign breakdowns to a specific facility (freeway or arterial) should be reasonable since it can be argued that breakdowns are predominantly random, with a probability of a breakdown occurring on a link related to the link's VMT.

The TLC study used standard, well-established procedures and methods derived from traffic flow theory to estimate delay (TRB, Highway Capacity Manual 1985). However, the confidence levels of the methodologies used to determine capacity losses and delays due to non-breakdowns depend on the type of facility where the breakdown occurred.  For freeways, both methodologies can be classified as having a high degree of confidence. However, due to the number of assumptions required to estimate capacity loss and delay on principal arterials, both methodologies can be qualified as having a medium degree of confidence.

It should be noted that due to the low level of confidence for the data and methods used to estimate the total number of breakdowns, the delay estimates produced by TLC2 are accorded a low level of confidence.

4.3.2 Data & Key Assumptions

Number of Breakdowns: The number of breakdowns relative to crashes was assumed based on a few published reports that have compiled limited data on crashes and breakdowns on freeways. TLC2 assumes there are eight times as many breakdowns as crashes, but the level of confidence for this assumption is fairly low.  Even if this assumption for freeways is reasonable, it is unclear whether ratios based on freeway crashes would be equally valid for principal arterials.

Number of Lanes: The number of lanes available under normal conditions was taken from the HPMS data set. This data is considered reliable for all highway types. 

Lane Blockage:  Lane block probabilities were based on statistics in the literature and from data provided by a few highway service patrols (mostly freeway data), as well as assumptions based on engineering judgment. These probabilities and assumptions are considered of medium confidence for freeways and of lower confidence for principal arterials.

Breakdown Duration: Assumptions regarding breakdown duration were based on very limited studies conducted on freeways. Their application to other freeways is only of moderate confidence, and their applicability to arterials is of low confidence.

Traffic Demand and Surface Street Characteristics: The same traffic demand data and surface street assumptions used to estimate crash delays were used for breakdowns. Therefore, the same caveats apply: traffic demand data is accorded a low level of confidence and surface street characteristics are accorded a medium level of confidence (see section 3.3.2).

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