Chauffeurs without Caps… Moving Toward Automated Vehicles


As accident rates continue to decrease, the NHTSA and automobile industry continues to look for new ways to make driving safer. A variety of advanced driver assistance systems (ADAS) are offered on many new vehicles and market penetration is expected to increase as the installation cost decreases and safety benefits are realized. Furthermore, as vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) technologies are developed, vehicles will be increasingly connected to each other and their surrounding environment. The hope is that these technologies will become ubiquitous safety features much like the airbag and electronic stability control, which are now standard equipment with proven benefits. As these technologies mature, there will be challenges that include not only technical ones, but questions of implementation, customer acceptance, regulation, and policy.

Advanced Driver Assistance Systems

During its century-long life, the auto industry has seen the introduction of numerous driver assistance systems. Speedometers are an example of an early system introduced to provide contextual information to the driver, electric starters and automatic transmissions to simplify vehicle operation, and anti-lock braking systems (ABS) and electronic stability programs (ESP) to improve a vehicle’s stability while driving. However, due to dramatic improvements in computational capability and the development of sophisticated sensing technology, there has been a rapid increase in advanced driver assistance systems coming to market in recent model year vehicles. For example, forward collision warning and blind spot detection/warning systems promise to reduce the likelihood of a collision, improve safety, and/or augment the driving experience in general.

Not surprisingly, the technology at the core of ADAS is fundamental in the implementation of automated vehicles. For instance, during highway driving, a high level of automation can be reached with a combination of forward collision auto brake, lane keep assist, and adaptive cruise control. Interestingly though, non-traditional players such as Google and Uber are jumping directly to a fully automated solution, while traditional automakers are taking a staged approach with the next big leap being the connected vehicle.

The Connected Vehicle

The “connected vehicle” is a broad term which encompasses communications between a vehicle and its surrounding environment, and is commonly referred to as “V2X”. Currently the most explored technologies are vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications; however, progress is continually being made into expanding the sources of information including, but not limited to, vehicle-to-pedestrian (V2P) communication. Connected vehicles may soon become a reality, given the Advanced Notice of Proposed Rulemaking released by the National Highway Traffic Safety Administration (NHTSA) in August 2014 and its recent announcement in May 2015 that it would accelerate the rulemaking process. Generally speaking, V2V technology is widely seen as complementary to ADAS, mainly because it helps overcome technology limitations such as line-of-sight and range issues associated with existing ADAS sensors. More importantly, V2V is reported to potentially mitigate up to 81% of unimpaired light-vehicle crashes.

The basic elements of a V2V system include a dedicated short range communication (DSRC) device, a global positioning system (GPS) transceiver, and a dedicated V2V processing and storage unit. The DSRC device transmits and/or receives data at 5.9 GHz with other vehicles within an approximate 300 meter range. The GPS receiver provides time, vehicle velocity, and position using a commercial grade system yielding positional accuracy of approximately 5 meters. Finally, the V2V processing and storage unit executes the safety applications based on information aggregated by the DSRC and GPS units. In addition, it verifies the authenticity of the DSRC information received from other vehicles, decomposes and stores aggregate data, and interfaces with the existing vehicle’s communication network.

Although there are many safety applications that can be implemented with V2V technology, the three identified by the NHTSA exclusively being implemented in V2V are Intersection Movement Assist (IMA), Left Turn Assist (LTA), and Emergency Electronic Brake Light (EEBL). Intersection Movement Assist will warn drivers of a high likelihood of collision with another vehicle when approaching an intersection. Left Turn Assist will warn drivers of an impending collision with another vehicle travelling in the opposing direction when making a left turn. Emergency Electronic Brake Light will warn drivers of a rapidly decelerating vehicle ahead, e.g. in inclement weather (rain, fog, snow), so that they may apply the brakes. V2V can also be leveraged to improve other safety applications previously discussed, such as forward-collision warning and blind spot detection (in the context of making a lane change).

Generally speaking, ADAS and V2V technologies complement each other. The shortcomings of ADAS such as limited field of view, range of effectiveness, reliability in adverse weather conditions, and susceptibility to sensor misalignment on the vehicle’s exterior are all mitigated by V2V technology. At the same time, shortcomings in V2V technology such as positional accuracy, reliability of GPS measurements in difficult scenarios (e.g., tunnels, variation in urban area building topology, etc.), and concerns with security and privacy are less of a concern in ADAS technology. Natural progression therefore suggests that these two technologies will be combined to inform the driver and manage potential safety threats, ultimately resulting in fewer accidents.

Challenges and Future Trends

The use of ADAS and V2X technologies is unlikely to take us to an accident-free world. Unfortunately, given the complexity of traffic patterns and the elevated number of variables at play, even the most sophisticated system cannot deterministically avoid accidents 100% of the time. These technologies face challenges that include false positive detections, customer acceptance, and performance evaluation.

From the technical point of view, today’s ADAS are still maturing and one challenge they face is reducing false positive threats. Systems that can be tuned to a wider field of view and lower detection thresholds can possibly detect more threats, but at the cost of increased false positives. On the other hand, a system with reduced field of view can reduce the number of false positives, but may miss some of the real threats (false negative). Manufacturers are taking a conservative approach, releasing systems that operate within tight constraints, considering design trade-offs typical of a product life cycle.

Ideally, each sensor should possess an optimal receiver operating characteristic (i.e., high true positive/negative and low false positive/negative). Data fusion from both ADAS and V2X technologies can help to achieve this objective by combining information from multiple sensors, thus improving fault tolerance at the same time. However, as with all technologies that need to deal with situational awareness, operating in an unstructured (or minimally structured) environment can hinder performance. Unforeseen driving situations that have not been considered in the system design process can bewilder the sensors, thus reducing their effectiveness. A police officer overriding traffic light operations or a temporary detour imposed by a construction zone are just two examples from the list of non-canonical driving scenarios, which is theoretically endless. This is especially challenging in the development of automated vehicles.

Because technology development has outpaced the development of standards, another challenge associated with ADAS and V2X technologies is testing. These systems perform as black-boxes to the external observer, creating a non-transparent layer between inputs and outputs. Moreover, the interaction of additional technologies with potentially competing objectives may lead to non-deterministic behavior.


ADAS and V2X technologies are ferrying the automotive, transportation, and their peripheral industries into a new era. With the promise of increased safety and an enhanced driving experience, these technologies will have to overcome serious technical and regulatory challenges, needing continuous evolution over the next decade. In moving toward fully automated driving systems, there will be challenges in addressing unforeseen driving situations that have not been considered in the systems design process. However, introducing additional sensing redundancy at low cost, and optimizing data fusion will help us move closer to more effective driver assistance systems.

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