AOP3D The Obsolescence of the Ape: A Forensic Audit of Human Driving vs. Algorithmic Perfection

Executive Summary: The Legacy Hardware Problem

The history of the automobile is a chronicle of rapid mechanical evolution stymied by a singular, persistent bottleneck: the operator. For over a century, we have refined the internal combustion engine, perfected the aerodynamics of the chassis, and introduced complex safety systems ranging from crumple zones to anti-lock brakes. Yet, we continue to install a biological control unit—the human brain—into the driver’s seat. This "legacy hardware," evolved primarily for hunting gatherers on the Pleistocene savannah, is spectacularly ill-equipped for the high-velocity, multi-variable calculus required to navigate modern infrastructure.

The data is unequivocal: the road is a war zone, and the casualties are self-inflicted. In 2023 alone, motor vehicle crashes claimed 40,901 lives in the United States. This statistic does not reflect a failure of automotive engineering; cars do not typically hurl themselves into embankments or veer into oncoming traffic of their own volition. Rather, 94% of serious crashes are attributable to human error. We are a species that eats cheeseburgers with two hands while steering with our knees ; we practice the trumpet in stop-and-go traffic ; and we succumb to a primitive "fight or flight" rage when cut off in a merge lane.

This report posits that the transition to Automated Driving Systems (ADS) is not merely a technological luxury but a moral and safety imperative. By conducting a comparative analysis of human psychology against autonomous sensor fusion, and contrasting biological reaction times with algorithmic determinism, we demonstrate that the "robot" is not merely a convenient chauffeur—it is a superior moral agent. The autonomous vehicle (AV) does not get drunk, it does not get tired, it does not suffer from road rage, and it never needs to lie to a police officer about a loose rat in the car to explain its speeding.

Part I: The Psychology of Incompetence – A Taxonomy of Human Failure

To understand the necessity of the autonomous revolution, one must first perform a rigorous autopsy on the capabilities of the incumbent driver. The human brain, while capable of profound creativity, is fundamentally flawed as a real-time control system for heavy machinery. It is plagued by cognitive biases, limited by sensory bandwidth, and governed by an emotional volatility that turns highways into arenas of dominance rather than arteries of transport.

1.1 The Fundamental Attribution Error and the Illusion of Skill

The psychological architecture of the human driver is built upon a foundation of delusion. The most pervasive of these is the Fundamental Attribution Error (FAE). This cognitive bias dictates how we interpret behavior on the road: we attribute our own mistakes to situational necessity ("I was speeding because I am late for a doctor's appointment") while attributing the identical mistakes of others to inherent character flaws ("He is speeding because he is a reckless idiot").

This bias creates a dangerous feedback loop of self-justification. Drivers routinely excuse their own aggressive maneuvers—tailgating, weaving, running yellow lights—because they have access to their own internal narrative. They know why they are in a rush. However, stripped of that context for other drivers, they view the road as populated by "incompetent" adversaries. This is compounded by the Above-Average Effect, a statistical impossibility where the vast majority of drivers rate their own skills as superior to the average driver. This illusion of competence leads to "Risk Homeostasis," where drivers, feeling safer due to improved car technology (like airbags or ABS), unconsciously compensate by driving more aggressively, negating the safety benefits.

An autonomous vehicle suffers from no such ego. It does not believe it is a "good" driver; it simply calculates probability. It does not judge the BMW that cuts it off; it merely re-calculates the safe stopping distance in milliseconds. The elimination of the ego from the driving equation is perhaps the single greatest safety feature of ADS technology.

1.2 The Distracted Primate: Attention as a Scarcity

The human attention span is a finite resource, easily depleted by competing stimuli. "Distracted driving" is a clinical euphemism for a biological failure to prioritize survival data over trivial entertainment. The anecdotal evidence of human multitasking failures is both humorous and terrifying, painting a picture of a species incapable of enduring boredom.

Case Studies in Biological Multitasking Failure:

• The Cheeseburger Maneuver: Witnesses have reported drivers unwrapping and consuming cheeseburgers with both hands while the vehicle is in motion. In these scenarios, the steering wheel is often controlled by the knees, a joint not evolutionarily designed for precision tactile feedback.

• The Musical Interlude: On the M25, one of the busiest motorways in the UK, a driver was observed practicing the trumpet while in slow-moving traffic. While this may have improved their embouchure, it undoubtedly degraded their situational awareness.

• Hygiene on the Fly: The vehicle is frequently treated as a mobile bathroom. Drivers have been spotted flossing teeth, plucking eyebrow hairs, and even shaving their legs while piloting a two-ton projectile. One particularly harrowing account details a woman pulling down her top to take selfies of her chest while her children were in the back seat.

• The "Ass Out the Window": In a display of baffling judgment, a driver was observed exiting a highway with their posterior hanging out of the driver's side window. The mechanics of how one operates the pedals and steering wheel in this position remain a mystery, but the disregard for safety is crystal clear.

These behaviors are not outliers; they are symptoms of "cognitive overload." The human brain cannot effectively process the road, the radio, the text message, and the cheeseburger simultaneously. Reaction times under these conditions degrade to levels worse than those of intoxicated drivers.

Table 1: The Attention Economy – Human vs. Machine

Metric	Human Driver	Autonomous Vehicle (Waymo/ADS)
Focus	Intermittent; cycles between road, phone, passengers, and internal thoughts.	Continuous; 360-degree monitoring of Lidar/Radar/Camera feeds at 10-100Hz.
Boredom	High susceptibility; seeks distraction during monotonous highway driving.	Immune; performance does not degrade over time or distance.
Multitasking	Catastrophic failure; cognitive load reduces reaction time.	Native capability; processes traffic lights, pedestrians, and routing simultaneously.
Field of View	~180° forward-facing; requires head movement for peripherals.	360° simultaneous coverage; "eyes in the back of the head" is literal.

1.3 The Reptile Brain: Road Rage and Emotional Volatility

Perhaps the most dangerous flaw in the human operating system is the susceptibility to emotional hijacking. Road rage is a manifestation of the primitive "fight or flight" response, triggered by the stress of traffic and the anonymity of the metal box. It turns the vehicle from a mode of transport into a weapon of dominance.

Psychological studies indicate that traffic congestion increases physiological arousal and stress, leading to aggressive behaviors that have nothing to do with efficiency. The road becomes a stage for petty dramas:

• The "Alpha" Standoff: In a documented incident of heavy gridlock, two drivers refusing to merge created what was described as the "slowest crash in history." Neither "alpha" male wanted to back down or yield space. Driving at barely one mile per hour, they allowed their vehicles to grind against each other—bumpers, quarter panels, and doors—sacrificing their paint jobs for the satisfaction of not yielding.

• The S10 Duel: A detailed account from a Reddit user describes a driver in an S10 pickup who engaged in a high-speed duel solely to prevent being passed. The driver slowed to 15 mph to block the lane, then accelerated to over 100 mph when the other driver attempted to overtake. This escalated until the S10 driver spun out, sliding sideways across the road—all to "win" a contest that existed only in his mind.

• Instant Karma: The universe occasionally provides immediate feedback to the reptile brain. In one instance, a driver weaving aggressively through traffic to save seconds ended up blowing his engine on the shoulder, watching the cars he passed cruise by. In another, a road-rager exited his vehicle to scream at another driver, only to have his own car roll away because he forgot to put it in park in his blind fury.

Autonomous vehicles do not feel pride. They do not feel shame. They do not get angry when cut off. A self-driving car will not brake-check a tailgater to "teach them a lesson." It will not accelerate to prevent a merge out of spite. It operates on a utilitarian ethics model, prioritizing safety and traffic flow over dominance hierarchies. By removing the reptile brain from the road, we remove the intentional malice that causes a significant percentage of preventable accidents.

1.4 The "Darwin Awards" of Driving: A Case for Revocation

The depths of human stupidity behind the wheel often defy logical explanation, entering the realm of the "Darwin Awards"—cases where individuals seem intent on removing themselves from the gene pool via vehicular negligence. The following examples highlight judgment failures so severe they suggest a fundamental incompatibility between human survival instincts and automotive technology.

• The Avalanche Challenger: A driver named Marco, after a day of skiing, was driving his van down a mountain when his brakes failed. This mechanical failure was tragic, but the behavior of others is less forgivable. In a separate incident, a snowmobile enthusiast ("sledneck") was warned by State Troopers of high avalanche risk. Having already triggered a small slide and been buried to his waist, he dug himself out and, rather than retreating, continued to rev his machine up the slope until he triggered a second, massive avalanche that claimed his life. The persistence in the face of imminent geological death highlights a risk assessment failure no algorithm would ever make.

• The Jet Ski Electrician: In a feat of electrical ignorance, a man named Rodney attempted to jump-start his jet ski while it was still in the water. He plugged an extension cord into a 110-volt outlet on the shore and walked into the lake carrying live crocodile clips. The result was instantaneous electrocution. While not a car crash, it illustrates the same lack of foresight that leads drivers to ignore "High Water" signs during floods.

• The Septic Tragedy: A driver of a septic truck, attempting to fix a lid, fell into the tank and drowned in human waste. While a workplace accident, it underscores the physical vulnerability of human operators in hazardous environments.

The Archive of Absurd Excuses: When caught violating traffic laws, human creativity shines—not in driving skill, but in fabrication. Police officers have recorded excuses that range from the biological to the surreal:

• "There is a rat in my car": A driver caught speeding claimed a mouse he bought to feed a snake had escaped its box and was running loose in the cabin, forcing him to speed home.

• "I need to use the bathroom": A common excuse, but in one instance, a driver caught speeding in New Jersey insisted it was true. When the officer asked for his license, the driver ran into the woods with a roll of toilet paper. He was ticketed anyway, despite the commitment to the bit.

• "I didn't realize I was speeding": In a survey of speeding ticket excuses, 26% of drivers simply claimed ignorance of their own velocity, a damning indictment of their situational awareness.

An AV is programmed with rigid safety constraints. It knows the speed limit. It knows the road conditions. It does not hallucinate rats, nor does it suffer from sudden gastrointestinal urgency that necessitates breaking the law.

Part II: The Sensorium of the Machine – Beyond Biological Limits

While humans rely on two forward-facing optical sensors (eyes) with a limited field of view, poor night vision, and a "blind spot" caused by the optic nerve, autonomous vehicles utilize a sensor suite that provides a 360-degree, multi-spectral view of reality. The comparison between human vision and machine perception is not a fair fight; it is the difference between looking through a straw and seeing the world in high-fidelity 3D.

2.1 The Holy Trinity of Perception: Lidar, Radar, and Vision

The autonomous vehicle "sees" using a fusion of three primary technologies, each compensating for the weaknesses of the others. This redundancy is critical for safety :

1. Lidar (Light Detection and Ranging): This technology fires millions of laser pulses per second to create a precise, 3D point-cloud map of the environment. Unlike human eyes, which estimate depth based on binocular disparity and size cues (which can be fooled by optical illusions), Lidar measures the exact time-of-flight of light. It knows the exact distance to a pedestrian, the volume of a pothole, and the shape of a barrier with centimeter-level precision. It effectively creates a wireframe model of the world in real-time.

2. Radar (Radio Detection and Ranging): While humans are blinded by fog, heavy rain, or blinding sun glare, radar waves penetrate these atmospheric obscurants. More importantly, Radar provides native data on the velocity of moving objects via the Doppler effect. A human driver estimates the speed of an oncoming car by how quickly it gets bigger in their vision—a cognitively expensive and error-prone process. Radar knows the oncoming car is moving at 45.2 mph instantly.

3. High-Definition Cameras: These provide the semantic layer of the world—color and texture. They read traffic lights (Red/Yellow/Green), brake lights, and lane markings. Modern AV cameras often use wide-angle or fish-eye lenses to stitch together a 360-degree panoramic view, eliminating the concept of a "blind spot" entirely.

2.2 Night Vision and the Invisible Pedestrian

Night driving is disproportionately dangerous for humans. Contrast sensitivity drops, color perception fades, and the glare of oncoming headlights causes temporary blindness. Statistics show that pedestrian fatalities are highest at night because drivers simply do not see the victim until impact.

Research into autonomous sensor performance demonstrates a clear superiority in these conditions. Thermal imaging and Lidar do not require ambient light. They are "active" sensors, meaning they provide their own energy source (lasers or radar waves) or detect heat. A study on nighttime pedestrian detection highlights that while human drivers struggle to distinguish dark-clothed pedestrians from dark backgrounds, multi-sensor fusion systems can detect heat signatures or 3D anomalies in the road surface well before they enter the stopping distance.

Waymo's Data on Vulnerable Road Users (VRU): Waymo's "Safety Impact Hub" data confirms this advantage. In comparisons with human benchmarks over millions of miles, the Waymo Driver demonstrated a 92% reduction in pedestrian crashes with injuries and a 78% reduction in cyclist injury crashes. This is not because the AV is "lucky"; it is because the AV sees the pedestrian in the dark, through the fog, calculates their trajectory, and pre-charges the brakes before a human driver would have even registered a shadow.

2.3 The "Blind Spot" Myth

One of the most common causes of accidents during lane changes is the human "blind spot"—the area alongside the vehicle that is invisible to side mirrors and peripheral vision. Humans attempt to mitigate this by physically turning their heads (the "shoulder check"), a move that takes their eyes off the road ahead.

For an AV, the blind spot does not exist. Sensors overlap to provide redundant coverage. A sensor on the front fender looks backward, a sensor on the rear bumper looks forward, and a Lidar on the roof looks everywhere. The machine possesses omnipresent situational awareness. It knows there is a motorcycle in the left lane, a truck in the right lane, and a pedestrian stepping off the curb simultaneously.

Part III: The Telepathic Network – Connectivity and Hive Mind

One of the most profound advantages of the machine driver is its ability to access information that is physically obstructed from human view. Through Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication, AVs effectively possess telepathy. They do not just "see" the car ahead; they "talk" to it.

3.1 V2V: Seeing Through Obstacles

A human driver's horizon is limited to the bumper of the car in front of them. If a truck five cars ahead slams on its brakes, the human driver has no way of knowing until the brake lights ripple back through the chain. By then, it is often too late, resulting in the classic multi-car pile-up.

The Samsung Safety Truck Concept: Samsung prototyped a visual metaphor for this technology: a semi-truck equipped with wireless front-facing cameras and massive rear-facing video walls. This allowed the driver stuck behind the truck to "see through" it via the screen, making passing maneuvers safe on two-lane roads.

Digital Telepathy: In the digital realm of V2V, this happens without screens. If a V2V-equipped vehicle brakes hard, it broadcasts a "Hard Braking Event" signal. Following vehicles receive this signal instantly, well before their radar or cameras could detect the deceleration visually. This allows the AV to brake simultaneously with the lead vehicle, maintaining safe spacing and preventing the accordion effect. This "electronic brake light" extends the driver's perception miles down the road, around corners, and over hills.

3.2 V2I: Talking to the City

Infrastructure integration allows cars to communicate with the grid itself. Traffic lights, usually a source of frustration and guessing games for humans, become data points for the AV.

• Audi's Traffic Light Information (TLI): This system, already live in select cities, allows the car to receive data from the municipal traffic management center. The car displays a "Time-to-Green" countdown, reducing driver stress. More importantly, it offers a "Green Light Optimized Speed Advisory" (GLOSA). The car calculates exactly what speed to maintain (e.g., 37 mph) to hit the next light on green, creating a "green wave" that reduces stopping, fuel consumption, and emissions.

• Cadillac's Red Light Warning: In V2I demonstrations, Cadillac vehicles received alerts that a traffic light was about to turn red. If the car calculated that its current velocity was too high to stop safely, or if the driver was distracted, it issued an alert. In a fully autonomous future, the car would simply adjust its speed to ensure it never runs a red light—a behavior that accounts for a significant percentage of intersection t-bones.

3.3 The End of the Traffic Light: MIT's Slot-Based Intersections

The traffic light is a relic of the human reaction time. We need red lights because we cannot coordinate with cross-traffic in real-time without stopping. We need explicit "turns" because we are slow.

Researchers at MIT, the Swiss Institute of Technology, and the Italian National Research Council have proposed Slot-Based Intersections (SI), a system possible only with autonomous vehicles. In an SI system, vehicles approaching an intersection communicate with a central manager. The system assigns each vehicle a specific time "slot" to pass through the intersection.

The cars adjust their speed slightly—slowing down or speeding up—so that they glide through the intersection gaps without ever stopping. Simulation videos show cars weaving through cross-traffic like a choreographed ballet. This "slower is faster" approach eliminates idling, reduces emissions, and doubles the efficiency of intersections. Humans, with our inability to judge relative velocity and our tendency to panic, could never operate in such a system.

Part IV: The Algorithmic Ethics – Solving the Trolley Problem with Physics

Critics often cite the "Trolley Problem" (e.g., should the car swerve to hit one person to save five?) as a hurdle for AVs. However, this philosophical debate ignores the reality that humans solve the Trolley Problem poorly. In a panic, humans often freeze, or swerve instinctively without calculating the outcome, sometimes hitting the crowd and the barrier.

4.1 Risk Ethics and the NIEON Model

AVs operate on Risk Ethics. They do not make decisions based on fear. If a child runs into the road, the AV calculates the physics of braking vs. swerving. If a collision is unavoidable, it chooses the path of least kinetic energy transfer.

Waymo's "Collision Avoidance Testing" (CAT): Waymo evaluates its software against a theoretical human model called NIEON (Non-Impaired Eyes On Conflict). This represents a "super-human" driver who is always attentive, never drunk, and looking directly at the conflict. In simulations of real-world fatal crashes that occurred in Arizona, the Waymo Driver consistently outperformed the NIEON model.

In scenarios where humans caused fatal accidents (the "initiator"), the Waymo Driver avoided the collision 100% of the time by obeying traffic laws and maintaining situational awareness. More impressively, when the Waymo Driver was placed in the "responder" role (reacting to another driver's error), it avoided or mitigated the crash in 82% of cases. The robot does not need to "decide" who to hit; it uses physics to ensure it hits nothing, or mitigates the impact to non-lethal levels.

4.2 Solving the Phantom Traffic Jam

One of the most infuriating phenomena on modern highways is the "phantom traffic jam"—a slowdown that occurs for no apparent reason, with no accident or construction to blame. These jams are caused purely by human inability to maintain consistent speed and spacing. A single driver taps their brakes, the person behind taps them harder, and the wave amplifies until traffic comes to a halt miles back.

The Ford/Vanderbilt Experiment: Researchers at Vanderbilt University conducted a definitive experiment to prove this. They placed human drivers in a circle and asked them to drive at a constant speed. Inevitably, the flow collapsed into stop-and-go waves due to human inconsistency. However, when a single AI-equipped vehicle was introduced into the stream, it acted as a traffic stabilizer. By maintaining a precisely calculated distance and speed, it smoothed out the erratic braking of the humans, eliminating the phantom jam entirely.

This implies that we do not need 100% adoption to see benefits. Even a small percentage of automated vehicles can prevent the "domino effect" of human incompetence, acting as pace cars that enforce efficiency on the unruly biological masses.

Part V: The Statistical Reality – Hard Numbers vs. Soft Humans

The argument for human driving supremacy collapses entirely when faced with the raw data. The metrics for safety—crashes per million miles, injury rates, and airbag deployments—overwhelmingly favor the machine.

5.1 Waymo vs. Human Benchmarks

Waymo has released unprecedented safety data comparing its "Rider-Only" (fully driverless) miles to human benchmarks in Phoenix, San Francisco, and Los Angeles. The results are not close; they are a rout.

Table 2: Waymo Driver Performance vs. Human Benchmarks (Through June 2025)

| Crash Metric | Reduction by Waymo Driver | Significance | | :--- | :--- | :--- | | Airbag Deployment Crashes | 84% Fewer | Airbags deploy only in severe, high-energy impacts. An 84% reduction means the Waymo Driver is fundamentally avoiding the most dangerous types of collisions. | | Injury-Causing Crashes | 73% Fewer | This translates to hundreds of hospital visits prevented per million miles. | | Police-Reported Crashes | 48% Fewer | Even minor fender-benders are significantly reduced. | | Pedestrian Injury Crashes | 92% Fewer | The most vulnerable road users are significantly safer around AVs. | | Cyclist Injury Crashes | 78% Fewer | AVs predict cyclist behavior better than frustrated human drivers. |

In the specific category of V2V Intersection Crashes—the classic "T-bone" caused by running red lights or failing to yield—Waymo showed a 96% reduction in injury crashes. This confirms the hypothesis that removing the human tendency to "beat the light" virtually eliminates intersection carnage.

5.2 The "Human Error" Baseline

To understand the magnitude of these improvements, we must look at the baseline. The National Highway Traffic Safety Administration (NHTSA) attributes approximately 94% of serious crashes to human error.

• Drunk Driving: Humans choose to ingest neurotoxins and operate heavy machinery. AVs are immune to intoxication.

• Drowsy Driving: Humans require sleep. AVs do not. * Speeding: Speeding is a choice, often driven by impatience or thrill-seeking. AVs are hard-coded to obey speed limits and adapt to flow.

5.3 The "Unavoidable" Crash

Critics argue that AVs cannot avoid every accident. This is true. If a human driver crosses the double yellow line and hits an AV head-on at 60 mph, the AV cannot rewrite the laws of physics. However, the data shows that AVs are better at mitigating these crashes. In the "responder" scenarios mentioned earlier, the AV detects the threat earlier than a human and scrubs off more speed before impact, turning a fatal crash into a survivable one.

Part VI: The Future Landscape – Cities Built for People, Not Cars

The adoption of self-driving vehicles will catalyze a transformation of the urban landscape. Currently, cities are designed around the inefficiencies of human drivers. We need wide lanes because humans weave. We need massive parking lots because private cars sit idle 95% of the time. We need traffic lights because humans can't negotiate right-of-way.

6.1 The Death of the Parking Lot

In a world of shared autonomous fleets (Transportation-as-a-Service), the concept of "parking" changes. A vehicle drops a passenger off and immediately moves to the next passenger or a remote holding area.

• Urban Reclamation: Studies suggest that AVs could reduce the need for parking space by over 90%. This frees up prime real estate for parks, housing, and pedestrian zones.

• The "Valet" City: Dropping off at the door becomes the norm. The nightmare of circling the block for 20 minutes looking for a spot—a major source of congestion and emissions—vanishes.

6.2 Narrower Lanes and Green Spaces

Because AVs can drive with centimeter-level precision, traffic lanes can be narrowed. A human needs a 12-foot lane to feel safe; an AV can operate safely in a 9-foot lane. This seemingly small difference allows city planners to widen sidewalks, add protected bike lanes, and plant trees without widening the road surface.

### 6.3 The Economic Dividend

The economic toll of human bad driving is astronomical—over $75 billion annually in medical expenses and productivity losses in the US alone. By eliminating the "crash economy" (body shops, trauma centers, litigation), AVs represent a massive efficiency dividend for society. Furthermore, the time humans currently spend driving—stressed, angry, and unproductive—becomes reclaimed time. The "commute" transforms from a source of stress into an extension of the living room or office.

Conclusion: The Inevitable Surrender of the Wheel

The evidence is overwhelming. The human driver is an obsolete component in the transportation network. We are emotionally volatile, easily distracted, sensorially limited, and prone to catastrophic lapses in judgment. We eat burgers when we should be steering; we get angry at strangers for trivial slights; and we justify our recklessness with cognitive biases that blind us to our own incompetence.

The autonomous vehicle, by contrast, is a stoic guardian. It possesses 360-degree vision that penetrates darkness and fog. It communicates telepathically with other vehicles to prevent accidents before they happen. It does not get drunk, it does not get tired, and it does not check its text messages.

The data from Waymo and other pioneers proves that the "future" is not theoretical; it is already here, and it is statistically safer than the human alternative. The transition will be difficult, largely because humans are reluctant to surrender the illusion of control. We cling to the steering wheel because we trust our own flawed judgment more than the cold logic of an algorithm. But as the road toll continues to mount, and as the "phantom jams" continue to waste our lives, the conclusion becomes inescapable.

For the sake of safety, efficiency, and the sanity of anyone who has ever been cut off by a man playing a trumpet on the freeway, it is time to let the robots drive. They won't choose to do the wrong thing. They will simply drive.

Final Summary: The Case for Automation

Feature	Human Driver	Autonomous Vehicle (AV)	Implications
Sensors	2 Eyes (Forward-facing, limited night vision).	Lidar/Radar/Camera (360°, see in dark/fog).	Superhuman Perception
Attention	Finite (Phone, food, fatigue).	Infinite (Never tires, never bored).	Zero Distraction
Reaction	Slow (~1.5s), affected by age/state.	Instant (ms), limited only by physics.	Crash Avoidance
Emotion	High (Road rage, panic, ego).	None (Stoic, utilitarian).	Rational Decision Making
Coordination	None (Independent agent).	High (V2V/V2I, Platooning).	Traffic Efficiency
Outcome	40k deaths/year (US).	84% reduction in severe crashes.	Lives Saved

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