Could Self-Driving Cars Make Traffic Worse?

Many people in favor of self-driving cars believe they will dramatically improve safety, reduce traffic backups, and forever change transportation. However, some of those expected benefits are up for debate, especially since the vehicles are not yet widely used worldwide and could have unintended downsides. Ongoing research shows these high-tech cars could worsen traffic. Why is that, and how can developers proactively address the problem?

They Stop When Encountering Problems

One reason self-driving cars could exacerbate traffic issues concerns how they deal with unexpected things in their paths. If a driver sees a broken-down vehicle, accident, or something else blocking their way, they will usually notice it in time to steer around it. That may slow traffic but usually does not stop it.

In contrast, some self-driving cars have stopped in the middle of the road when detecting something unusual. These instances even delay emergency services vehicles responding to accidents.

Many self-driving cars have humans inside, supervising the journeys. However, when an autonomous vehicle operates independently and experiences a problem such as an overheated engine or a flat tire, would it know to pull over to the side of the road, or would it stop in place? The latter option would also cause traffic backups.

Activists have even capitalized on how the cars stop when encountering obstacles. They’ve specifically placed traffic cones in the vehicles’ way, knowing that will create enough of an impediment to halt them.

It’s easy to see how stopping in the presence of a barrier is a safety feature that could prevent collisions. However, it could also stop traffic because these vehicles lack the foresight, problem-solving capabilities, and experience humans naturally use when faced with them.

Unfortunately, some people with advanced features on their cars have already begun depending on them too much. One study found that 58% of drivers with pedestrian-detecting cars have stopped looking for walkers themselves.

They Do Not Understand Social Signs

Humans in and around cars naturally give and receive signals to others around them. A pedestrian may make eye contact with a driver and watch for a nod from them before deciding to cross the street. Drivers regularly wave to each other, indicating they will let other cars out at busy intersections. Most people probably cannot pinpoint when or how they learned these things, but they understand how it makes driving and being near cars safer for everyone.

Researchers analyzed YouTube videos of self-driving cars and found they have difficulty determining whether to yield or keep moving. Their programming also falls short of allowing them to detect body language. One example reviewed by the team involved a family that wanted to cross the street. Although they waved their hands to tell a self-driving car to pass them first, the vehicle did not recognize that cue.

What happened next was particularly surprising because the vehicle stopped next to the family for 11 seconds. They took that as a sign to begin crossing. As soon as they did, the car started moving, making them run for the sidewalk.

The nods, waves, and other brief acknowledgments exchanged between drivers, pedestrians, and others go a long way in keeping traffic flowing. People understand that although safe driving requires making personal decisions, it is also a collective effort. That partially explains why high-risk drivers are the most significant accident threats within fleets.

They Need More Connectivity

The programming and connectivity of self-driving cars affect how they respond to traffic signals. Researchers also determined that those able to receive signals from nearby infrastructure are more likely to move smoothly rather than get caught in backups.

The team evaluated cars driven by humans, in addition to automated, connected, and connected automated vehicles. Those in the connected categories can receive information about the future state of nearby traffic lights and adjust their speeds. Therefore, they are more likely to encounter green lights rather than red or yellow ones.

In contrast, automated vehicles without advanced connectivity are programmed to operate more conservatively and cautiously, which can reduce the number of cars that can flow through intersections.

A computational model showed that automated cars without connectivity to traffic control systems slow intersection travel time, partly because their programming prioritizes collision reduction. Although accident prevention is an undeniably important aim, the researchers believe having more vehicles that connect and respond to traffic infrastructure would minimize the number sitting at red lights, allowing them to move with fewer interruptions.

Exploring Potential Solutions

These challenges highlight how self-driving car developers must consider multiple aspects and take thorough problem-solving approaches. A broad but practical step is to launch educational and awareness campaigns to help drivers learn more about the high-tech vehicles that increasingly appear on the roads.

Some countries require people learning to drive to attach stickers to their cars, which helps others be more patient and understanding.

Some self-driving cars have external branding that tells people what they are, but a better option may be to have a consistently applied designator. Signs could let people know that autonomous vehicles immediately stop in front of obstacles. That way, they’d be less likely to get frustrated and blow their horns when they don’t move.

In one case, researchers determined that putting green lights on self-driving cars’ roofs effectively told pedestrians when it was safe to cross the road. However, the timing of the light’s activation was also important. People showed riskier behaviors if the automobiles slowed down or turned on the light too far away from intersections. It would be better if the light-activated as the vehicles arrived at the crossing and just before they stopped.

Making self-driving cars reverse and go around obstacles directly in front of them or steer around them in time is also important from safety and traffic flow standpoints. Humans do this naturally, making those movements when it is safe. Similarly, autonomous vehicles should be programmed to steer to road shoulders when mechanical faults or other issues make it unsafe to continue moving.

Addressing New Findings

Those in the self-driving car industry should stay aware of new developments. Although these vehicles could ease traffic challenges, people should not assume that will happen. They must look deeper to find and address other possibilities to make the roads safer for all.