Cost and Benefit Estimates of Partially - Automated Vehicle Collision Avoidance Technologies

Many light-duty vehicle crashes occur due to human error and distracted driving. Partially-automated crash avoidance features offer the potential to reduce the frequency and severity of vehicle crashes that occur due to distracted driving and/or human error by assisting in maintaining control of the vehicle or issuing alerts if a potentially dangerous situation is detected. This paper evaluates the benefits and costs of fleet-wide deployment of blind spot monitoring, lane departure warning, and forward collision warning crash avoidance systems within the US light-duty vehicle fleet. The three crash avoidance technologies could collectively prevent or reduce the severity of as many as 1.3 million U.S. crashes a year including 133,000 injury crashes and 10,100 fatal crashes. For this paper we made two estimates of potential benefits in the United States: 1) the upper bound fleet-wide technology diffusion benefits by assuming all relevant crashes are avoided and 2) the lower bound fleet-wide benefits of the three technologies based on observed insurance data. The latter represents a lower bound as technology is improved over time and cost reduced with scale economies and technology improvement. All three technologies could collectively provide a lower bound annual benefit of about $18 billion if equipped on all light-duty vehicles. With 2015 pricing of safety options, the total annual costs to equip all light-duty vehicles with the three technologies would be about $13 billion, resulting in an annual net benefit of about $4 billion or a $20 per vehicle net benefit. By assuming all relevant crashes are avoided, the total upper bound annual net benefit from all three technologies combined is about $202 billion or an $861 per vehicle net benefit, at current technology costs. The technologies we are exploring in this paper represent an early form of vehicle automation and a positive net benefit suggests the fleet-wide adoption of these technologies would be beneficial from an economic and social perspective.


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U.S. crashes that potentially could be avoided or made less severe by the three technologies is estimated, assuming 100% technology effectiveness. Next, a lower bound in U.S. crash reduction is estimated using current changes in observed insurance collision claim frequency and severity (average loss payment per claim) in motor vehicles with these technologies. After these estimates are made, an annualized cost to equip each vehicle with the technologies enables a cost benefit analysis for the lower bound and upper bound estimates of net benefits in the U.S. The technologies we are exploring in this paper represent an early form of vehicle automation as defined by NHTSA (NHTSA, 2013b) and the estimates in this paper can help inform near-term decisions during the transition to automation.

EXISTING LITERATURE
Several researchers have analyzed the effectiveness of crash avoidance technologies in reducing crashes and severity. For example, Jermakian (2011) estimates that side-view assist and FCW systems could potentially prevent or reduce the severity of as many as 395,000 and 1.2 million crashes involving passenger vehicles annually, respectively, using crash records from the 2004-2008 National Automotive Sampling System (NASS) General Estimate System (GES) and Fatality Analysis Reporting System (FARS) databases (Jermakian, 2011). Kuehn et al. (2009) used insurance collision claims data along with human factors research and determined that equipping all cars with a forward collision warning and lateral guidance system that was 100% effective, could prevent up to 25% of all crashes (Kuehn et al, 2009). Sugimoto and Sauer (2005) estimated that a FCW system with autonomous braking could reduce the probability of a fatality in a rear end collision by as much 44% (Sugimoto and Sauer, 2005). A 2012 study concluded that Blind Spot Monitoring (BSM) systems could potentially prevent or reduce the severity of Please cite the final version of this paper: . Cost and benefit estimates of partially-automated vehicle collision avoidance technologies. Accident Analysis & Prevention, 95, 104-115. http://doi.org/10.1016/j.aap.2016 6 22,000 combination tractor-trailer crashes annually (Jermakian, 2012). Kuanso et al. (2014) developed a crash and injury simulation model in which each crash was simulated twice-once as it occurred and once as if the driver had a LDW system-and determined that a LDW system could potentially prevent up to 29.4 percent of all road departure crashes (Kusano et al., 2014). Blower (2013) used simulations and operational field tests to develop a range of estimates on the effectiveness of ESC, LDW, and FCW systems in reducing target crash types (Blower, 2013).
The American Automobile Association (AAA) along with the MIT AgeLab conducted a study in which they assessed and provided ratings for both the potential and real world benefits of LDW, FCW, ESC, and other crash avoidance technologies based on data gathered from published literature (Mehler et al., 2014). Blanco et al. (2016) estimated and compared crash risks for selfdriving and national crash rates using data from Google's Self-Driving Car program and the Second Strategic Highway Research Program (SHRP 2) Naturalistic Driving Study. This study suggests that less-severe crashes may happen a much lower crash rate for self-driving cars (5.6 per million) when compared to the national crash rate (14.4 per million) (Blanco et al., 2016).
The Insurance Institute for Highway Safety (IIHS) estimates that forward collision systems with automatic braking could reduce rear-end crashes by about 40% while standalone FCW could reduce these crashes by about 23% (IIHS, 2016).
Researchers have also attempted to estimate the economic benefit of crash avoidance technology systems. For a consistent comparison, we used the consumer price index (CPI) to convert all benefits in previous literature to $ (Bureau of Labor Statistics, 2015. One prediction comes from Murray et al. (2009) who found that a FCW system in large trucks could provide a benefit ranging from $1.42 to $7.73 for every dollar spent on the system (Murray et al., 2009). This estimate is based on different vehicle miles traveled (VMTs), system efficacies, and Please cite the final version of this paper: . Cost and benefit estimates of partially-automated vehicle collision avoidance technologies. Accident Analysis & Prevention, 95, 104-115. http://doi.org/10.1016/j.aap.2016 7 technology purchase prices. Battelle (2007) reports that equipping all large trucks with a FCW system could have a negative net benefit approximately anywhere between -$66 and -27$ billion, depending on the cost of system and driver reaction time (Battelle, 2007). In that study, crash reduction frequencies for a FCW system were derived from statistical modeling. Another study found that at a 90 percent market penetration rate FCW along with adaptive cruise control could provide considerable safety benefits-$52 billion in economic costs (lost productivity, travel delay, etc.) and 497,100 functional person-years (Li and Kockelman, 2016 Honda's FCW system is located behind the windshield while Mercedes' and Acura's are located in the front bumper. Similarly, Mazda's BSM system is located in the rear bumpers, while Buick's system is located behind each rear quarter panel. Figure 1 illustrates how the three crash avoidance systems interact with the roadway.  10 regarding the crash that could be used to find and diagnose problems within traffic safety. Along with accident data, the 2012 GES and FARS datasets also include person and vehicle level data.
The 2012 GES attempts to represent the crash characteristics of the United States population on a national level and includes accidents of all severities. A weighting factor is provided for each person, vehicle, and accident included in the datasets. This weighting factor is the computed inference factor, which is intended to represent the total population from which the sample was drawn. The system has a population sample of about 62 thousand accidents that is representative of about 5.6 million crashes nationwide. All of the results presented in this report for non-fatal accidents were found using the full sample weights for the 2012 GES.
The 2012 FARS data contains information on every fatal crash occurring on a public roadway in the year 2012. In order for a crash to be included in the FARS dataset, the crash must result in the death of an occupant of a vehicle or a pedestrian within thirty days of the crash due to injuries suffered from the accident. Unlike the GES database, the FARS dataset does not include any weighted estimates since each fatal accident that meets the criteria outlined above is included in the dataset. All of the results presented in this reported related to fatal accidents were found using the 2012 FARS.

Data Selection Methodology
The 2012 NASS GES and FARS vehicle dataset contains information on in-transport vehicles and passengers. For all crash types, collisions that involved at least one light-duty passenger vehicle in the 2012 NASS GES and FARS files were used while all other crashes were truncated from the dataset. One and two vehicle crashes make up close to 94% of all vehicle crashes; evaluating three or more vehicle crashes adds complexity to the analysis for a small percentage Please cite the final version of this paper:  Analysis of Lane Change Crashes report (Basav et al., 2003).  (Basav et al., 2003).

Lane-Departure Warning
The crashes included in the lane-departure crash target population are assumed to be situations where a LDW system would be active. As a result, lane-departure crashes are defined as one

Forward Collision Warning
FCW systems are designed to prevent or reduce the severity of rear-end collisions by using a camera or radar to detect whether a vehicle is approaching another object-vehicle, bicycle, or pedestrian-at an unsafe speed and issues alerts to the driver. In addition to FCW systems, some vehicles also include crash imminent braking (CIB) systems that apply autonomous braking to the vehicle after a warning has been issued. Rear-end collisions were identified in both the FARS and GES data sets by referring to the accident type variable. Accident type variable codes in GES 20-29 correspond to a rear-end collision and were used to filter out accidents in which FCW systems would be active. Once the crashes that met the desired accident types listed above were identified, vehicle speed, pre-crash movement, and critical event were then taken into account. In cases where a lane change or merge occurred directly before the crash, these entries were eliminated since it is not clear whether or not a FCW system would have been effective in these scenarios. Crashes that occurred during inclement weather were filtered from the target crash population, since rain, snow, etc. could hinder the performance of the system. The pre-crash scenarios examined in this paper that could lead to a rear-end crash are: the lead vehicle stopped, lead vehicle decelerating, and lead vehicle moving at lower constant speed. The rear-end collision target crash population only includes two-vehicle crashes.

Estimation of Crash Frequency and Crash Cost Reduction
To estimate the existing effectiveness of each technology, insurance data on changes in collision claim frequencies and severity (average loss payment per claim) were gathered from the HLDI (HLDI, 2014b(HLDI, , 2012a(HLDI, , 2012b(HLDI, , 2011a(HLDI, , 2011b(HLDI, , 2011c. The HLDI derives its data by comparing

BENEFIT COST ANALYSIS
The annual net benefit of crash avoidance systems is the difference between the total annual benefits and total annual costs and is expressed in Eq. (1): where NB is the annual net benefit, TB the total annual benefits, and TC is the total annual costs.
The total annual benefits are the savings that result from a reduction in crash frequency and crash costs due to the deployment of BSM, LDW, and FCW crash avoidance systems throughout the light-duty vehicle fleet. The total annual benefits of crash avoidance technologies for single and multiple-vehicle accidents are expressed in Eq. (2): where TB is the total annual benefit of equipping all light-duty vehicles with crash avoidance technologies, CS CP the cost savings from crash prevention, CS LS the cost savings from less severe crashes.
The total annual costs are the incremental annualized costs associated with equipping all light-duty vehicles in the vehicle fleet with the technologies. So the total costs can be expressed in Eq. (3): where TC is the total annual costs of equipping all light-duty vehicles in vehicle fleet with BSM, LDW, and FCW crash avoidance systems, TP C is the technology purchasing cost.
(shown below) shows the processes and steps taken to estimate the technology purchasing costs, and upper and lower bound benefits and net benefits.  the severity of as many as 1.3 million crashes annually, including 133,000 injury crashes and 10,100 fatal crashes (See Table 3). Of the three technologies examined in in this paper, FCW has the greatest potential to prevent or reduce the severity of the largest number of crashes overall.
This technology could prevent or reduce the severity of close to 800,000 crashes or 14% of all crashes. The technology that could affect the largest number of fatal crashes is a LDW system, which has the potential to prevent or reduce the severity of up to 9,020 fatal crashes or 29% of all To estimate a lower bound fleet-wide reduction in crashes and severity, we use current insurance data for vehicles with these technologies and project the savings across assumed fleetwide technology diffusion.  (Blincoe et al., 2015). This would result in each crash costing close to $154,000 in $2010. Because the crash data used for this paper is from the year 2012, the Consumer Price Index (CPI) was used to find the total cost of a Please cite the final version of this paper: Less severe crash cost savings describe the savings to private insurers due to lower collision claim loss amounts. Because this paper uses a bounding assumption on 100% effectiveness and deployment of crash avoidance technologies it is assumed that all relevant crashes not prevented will have a reduction in average severity. The calculation of the total lower bound annual cost savings from less severe crashes is based on the following formula: Please cite the final version of this paper:  The total annual benefits (TB) from cost savings due to less severe and prevented crashes were estimated using Eq. (2). As presented in Table 5, the total lower bound annual benefits are approximately $18 billion. The most important sources of benefits are cost savings from crash prevention ($17 billion), and less severe crashes ($180 million). In this estimation, cost savings from people living healthier lives are only based on crashes that were prevented by the crash avoidance technologies, since we are not aware of how each technology impacts injury severity if a crash does occur. Although, more crashes are assumed to have a reduction in average severity than prevented, crash prevention provides a far greater benefit since the cost savings from less severe crashes is very small compared to the cost savings from avoiding a crash.
In order to estimate an upper bound fleet-wide benefit from the three technologies we will assume that each technology is 100% effective in preventing crashes from their respective target crash population. The calculation of the total upper bound annual crash prevention cost savings is based on the following formula: Where,

Total Annual Costs
The total direct costs ( were not a standard option, it is assumed for this analysis that the cost to add BSM, LDW, and FCW technologies to a vehicle is about $600, which is reflective of the current price drop in vehicle safety packages from Toyota (Lienert, 2015). If the same technology was available in 2012 the price would have been about $582. While most other manufacturers offer the same safety package for around $2,100 we assume that they too will eventually decrease the price of their safety features in order to remain competitive. Since this paper is evaluates the annual net benefit, the total unit technology cost was converted to an equivalent uniform annual cost (EUAC) by assuming a vehicle lifetime of 14 years and an average car loan interest rate of Please cite the final version of this paper: . Cost and benefit estimates of partially-automated vehicle collision avoidance technologies. Accident Analysis & Prevention, 95, 104-115. http://doi.org/10.1016/j.aap.2016 29 4.46% (Andriotis, 2013;Ford, 2012;Tuttle, 2012). The total annual cost assumes that this equipment is placed on new vehicles and the cost to purchase the technologies is annualized over the lifetime of the vehicle. This would be the total annual cost to purchase the technologies if all of today's light-duty vehicles were replaced with new cars equipped with these three technologies. This resulted in an annualized cost of approximately $57 for each light-duty vehicle. The calculation of the total annual technology purchasing costs is based on the following formula:

Comparison of Benefits and Costs
In order to analyze the current economic feasibility, the annual net benefit (NB) was estimated from Eq. (1). The total annual benefits (TB) are the benefits that we would expect to accrue each year the vehicle is in operation from prevented and less severe crashes. The equivalent uniform annual costs (TC) are the total fleet-wide technology purchasing costs annualized over the lifetime of a vehicle. The annual net benefit is the difference between these two annual values.
It is shown in Figure 3  Lower Bound

Cost Private Insurers Households Third-Parties Public Revenue QALYs
Please cite the final version of this paper:

Sensitivity Analysis
The current annual net benefit shown above are based on a variety of assumptions, the most significant being the annualized technology purchasing cost and the effectiveness of each technology in reducing crash frequency and severity. Improvements in all three categories could result in a higher annual net benefit. As shown, it is economically feasible to equip the entire light-duty vehicle fleet with the three crash avoidance technologies examined in this paper.
Higher annual net benefits can still be achieved either by lowering the cost of purchasing the   At low cost savings from less severe crashes, the annual net benefit is positive at most technology costs. At much higher technology costs than those assumed for the base case analysis, the net benefit remains positive at high crash prevention cost savings, but is negative at lower cost savings. While there are a much larger number of crashes assumed to be less severe than prevented, less severe crashes have a smaller impact on the net benefit. The sensitivity of the annual net benefit to the annualized technology cost and cost savings from less severe crashes is shown in Table 7.
three technologies could collectively prevent or reduce the severity of as many as 1.3 million crashes a year including 133,000 injury crashes and 10,100 fatal crashes. FCW systems would address the greatest number of crashes overall and injury crashes, while a LDW could affect the largest number of fatal crashes.
In order to conduct a net benefit analysis to evaluate the economic feasibility of crash avoidance systems in light-duty vehicles, it was assumed crash frequency and crash cost mirrored changes in collision claim frequency and severity, respectively. If all three crash avoidance technologies were equipped on all light-duty vehicles, this would provide a lower bound annual benefit of about $18 billion with private insurers, households, and third-parties receiving annual benefits of about $2.9, $1.4, and $0.78 billion, respectively, from prevented and less severe crashes. Most of the benefit can be attributed to prevented crashes that accounts for almost 98% of the total benefit although a very small percentage of crashes are assumed to be  collectively there were about 5,000 and 125,000 pedestrian and pedalcyclist fatalities and injuries, respectively, from crashes involving motor vehicles. While these crashes were not considered for this analysis, FCW could have considerable additional benefits by potentially reducing the frequency and severity of these crashes, resulting in higher economic benefits, which further supports the case that these technologies would provide a benefit if equipped on all vehicles.
The crash avoidance technologies examined in this paper are fairly new and have only recently begun to appear in non-luxury cars. The HLDI estimates that in 2013 the three crash avoidance technologies examined in this paper each came standard on about 2% of new car models. As a result, this is only a preliminary cost analysis as we expect the technologies to improve, costs decline, and diffusion increase -resulting in potentially higher changes in collision claim frequency and severity. In addition, some of the system limitations assumed for the current technologies in this analysis may not exist in the future and as result these technologies could become more effective in circumstances such as inclement weather, which would increase the number of relevant accidents, ultimately providing a larger benefit. As autonomous technology diffuses and starts to improve safety, there is the potential risk of an enhanced immunity fallacy (Will, 2005;Will and Geller, 2004), where occupants perceive a false sense of immunity from risk for injury in crashes. This could result in reduced use of seat belts or child restraints, which is not commensurate with the reduced risks. In the transition to partial vehicle automation, regulators should take best practices from the risk perception literature and build upon previous efforts (Will, 2005) to enhance risk communication.
While the results from this net benefit analysis offer a new understanding of the economic benefits and costs of equipping the entire light-duty vehicle fleet with three crash avoidance technologies, there are several opportunities for improvement. Rather than calculating benefits for crash prevention solely on a per crash basis, future cost analyses should take crash severity in account. Changes to market penetration rates and VMT could also be incorporated, to reflect the influence that consumer demand and VMT could have on the net benefit. Different system efficacies could be taken into account in order to better model a real transportation system where crash avoidance technologies do not work perfectly and could be potentially disabled by the user of the vehicle.