Smart vehicles

Significant progress has been made to apply cellular and dedicated short range communication technologies to support a two way link between vehicles and roadside infrastructure. The various communication links involved are described using the following abbreviations:

• V2X: a two-way communication link between vehicles and several other elements such as other vehicles, roadside transceivers, or wide-area cellular networks
• V2V: a two-way communication link between vehicles, from one vehicle to another
• V2N: vehicle to network, another way to describe a two-way communication link from vehicles to a communication network such as cellular

While early work focused on short range communications, latest implementations have incorporated the use of cellular V2X approaches. It is likely in the future that the three different approaches will be used in combination to create additional capability.

In parallel with the development of wireless communication techniques, there has been significant progress in the use of data inside the vehicle. Engine management systems and carry area networks provide the possibility for a rich stream of data to be received from the vehicle. Now this data is only available to mechanics and technicians and other systems on board the vehicle. By combining this advance, with connected vehicle technology, the possibility now exists to externalize in vehicle data and use it as the basis for better insight and understanding for traffic and transportation management. At a basic level, the ability to receive data from the vehicle regarding vehicle identification, instantaneous vehicle speed, original origin for the trip and ultimate destination for the trip will be an important part of the smart mobility revolution. 

The availability of this data will cause sudden and dramatic change in our approaches and our ability to manage traffic and transportation. This new data can be the basis for more sophisticated transportation planning and more effective traffic engineering. Vehicle speed data reduces our dependence on collecting such data from roadside infrastructure sensors, while also offering a much finer level of detail and a better understanding of the variation of vehicle speed throughout the network. An understanding of the original origin and ultimate destination of the vehicle also enables us to place existing investments in traffic signal control and advanced traffic management within the wider context. Such techniques, now, focus on vehicle trip patterns and behavior within the control network and have little information on how the vehicle entered and exited the network. Possessing this additional information will allow us to take a wider, multimodal approach to citywide transportation management. Beyond a basic set of data, the following data can also be obtained from connected vehicles:

• Road conditions: sensors on board the vehicle detect road geometry changes and condition of the road surface. Sensors also detect average vehicle speed which can indicate traffic conditions being experienced

• Environmental conditions: sensors on board the vehicle measure ambient temperature, detection of windshield wiper use can detect rain

• Operating status of the vehicle: a wide range of data that describes the operating status of the engine, transmission, wheels, and other onboard equipment

• vehicle usage: additional sensors monitor vehicle speed, location, and average load weight

• Driver behavior: the use of cell phones and Internet-based services can be monitored

Estimates vary widely, but it is expected that the full set of data that can be obtained from or connected vehicle could be as large as 300 TB per day.

We need to get ready to manage large volumes of data from vehicles and efficiently turn into information. We need to revise our current analytics to include the availability of the new data and develop new analytics for new insight and understanding. We need to make sure that we have data sharing agreements in place to enable us to access the data from the vehicle. This will include a clear definition of data ownership. It is a multitude of new services that can be supported from the new data and you approach to existing services. For example, the insurance industry can be revolutionized by using the data to customize insurance rates the vehicle and driver behavior. 

 These are vehicles that can drive themselves. A considerable amount of research and financial research is focused on the development of vehicle automation technology that can replace the driver. While this is a difficult task, significant progress has been made of the past few years. A vehicle automation system will feature sensors that can detect the operating environment of the vehicle including infrastructure and other vehicles. 

It also incorporates processing capability to enable the sense data to be turned into decision support. This in turn is fed into the vehicle control system which uses automated breaking, acceleration, and steering, to guide the vehicle according to the sensed data. Sensors will also detect the presence of pedestrians and other obstacles. In a similar manner to the connected vehicles described above, automated vehicles will generate significant data. This is likely to be larger than connected vehicle data due to the presence of more sophisticated sensors on automated vehicles including lidar and cameras. It is likely that automated vehicles will also require two-way interaction with infrastructure to enable a complete picture for vehicle operation and automation decision-making. Automated vehicles will initially supplement the role of the driver and will ultimately replace the driver. 

This will have significant impact on transportation as it sets the scene for on-demand automated vehicles, and more equitable access to transportation for the young, the old and those not able to use existing transportation services. Vehicle automation could have a considerable cost reduction impact on freight and transit, where the driver is present purely for vehicle operating purposes and not to get to a particular destination. It is estimated that driver compensation contributes about $0.48 per mile to the cost of operating a truck. Automated vehicles will also have a significant impact on short distance logistics within urban areas such as fast food delivery and package delivery. 

Electrically propelled vehicles are not new, but advances in technology over the past few years have made them much more commercially viable. In the past the use of electric propulsion systems and vehicles was restricted to fleets, where the specialist support required to keep the vehicles operational could be supported and justified. Advances in battery technology and in the manufacturing of electric vehicles have led us to the point where electric vehicles are becoming much more prevalent in the market and are likely to dominate the automobile market in the next 5 to 10 years. Electric vehicles have the important characteristics of been cheaper to operate with zero omissions. 

Although it could be argued that emissions are not completely avoided but merely shifted from the vehicle to the point at which electricity is generated i.e., the power station or power plant. This is still desirable, as it is much simpler and cheaper to manage emissions at a central location such as a power station, rather than distributed emission sources represented by millions of vehicles. It is a significant economic aspect of electric vehicles on a geopolitical level. A move towards the use of electric vehicles, will reduce our dependence on oil. 

Electric vehicles must be treated as a single system. While there is still considerable potential for improving the internal combustion engine, it is likely that electric vehicles will play a much more significant role in the future. This means that we must replicate the ubiquity of gasoline filling stations, with appropriate electric vehicle charging infrastructure. In addition to geographic coverage of electric vehicle charging points, each charging point must have the appropriate characteristics for the location. For example, a home charging point can use a lower power rating as it is likely to have at least eight hours to charge the vehicle. 

Charging points in route, will have a need for higher power and faster charging, while charging points at popular destinations such as offices, shopping malls and schools will require characteristics somewhere in the middle. The expected demand for vehicle charging should also be considered to ensure that unacceptable wait times are not experienced which within themselves cost congestion. Recent experience with electric taxis in Amsterdam suggests that the distortion in the energy consumption patterns in urban areas are much greater with electric vehicles than expected. This leads to consideration of efficiencies and electricity generation and distribution, turning to solar power and microgrid technologies which are often part of the wider smart city picture.