Projected impact: High
Timeframe: Already here

Consumer preferences and technological breakthroughs add up to a fundamental shift in the future mobility behaviour in the transport and logistics.

Good and services are increasingly delivered to consumers. As consequence, the traditional business model of transport and logistics will be completed by a range of diverse IT solutions. The connection of vehicles to the Internet offers new possibilities and applications which bring new functionalities to the logistics companies that will make the transport easier and safer. New mobile ecosystem based on trust, security and convenience to mobile/contactless services and transportation applications are created and the developments such as Internet of Vehicles are connected with Internet of Energy for providing services in an increasingly electrified mobility industry.

In the same time representing human behaviour in the design, development and operation of cyber-physical systems in autonomous vehicles is a challenge. Incorporating human-in-the-loop considerations is critical to safety, dependability and predictability. There is currently limited understanding of how driver behaviour will be affected by adaptive traffic control cyber-physical systems.

Self-driving vehicles today are evolving and the vehicles are equipped with technology that can be used to help understand the environment around them by detecting pedestrians, traffic lights, collisions, drowsy drivers and road lane markings. Those tasks initially are more the sort of thing that would help a driver in unusual circumstances rather than take over full time.

Technical elements of such systems are smart vehicle on-board units which acquire information on board systems (e.g. vehicle status, position, energy, usage profile, driving profile). They interact with external systems (e.g. traffic control systems, parking management, vehicle sharing management, electric vehicle charging infrastructure).

The parallel emergence of the megatrends in the last 2 years mobility, such as automated driving and digital experience and electrification will trigger many changes in the logistics and transport domain in the next 10 to 15 years, the logistics and transport domain will be effectively reshaped.

In reality the reshaped logistics and transport domain will trigger the replacing of the sensory functions of the drivers with technology such as:

from to
manual driving autonomous driving
decision making capabilities machine learning algorithms
memory maps/environmental models
eyes sensors
ears vehicle to X communication (vehicle, infrastructure, machine)
reflexes/coordination of movement actuator control

 

In the field of connected autonomous vehicles for logistics IoT and sensing technology replace human senses and advances are needed in many areas such as:

  • vehicle’s location and environment: as there would no longer be active human input for vehicle functions, highly precise and real-time information of a vehicle’s location and its surrounding environment will be required (e.g. road signs, pedestrian traffic, curbs, obstacles, traffic rules).
  • prediction and decision algorithms: advanced concepts based on Artificial neural Networks (unsupervised/deep learning, machine learning) will be needed to create systems to detect, predict and react to the behaviour of other road users, including other vehicles, pedestrians and animals.
  • high accuracy, real time maps: detailed and complete maps must be available to provide additional and redundant information for the environmental models that vehicles will use for path and trajectory planning.
  • vehicle driver interface: a self-adapting interface with smooth transition of control to/from the driver, mechanisms to keep the driver alert and a flawless ride experience will be instrumental in winning consumer confidence.

Successful deployment of safe and autonomous vehicles (SAE international level 5, full automation) in different use case scenarios using local and distributed information and intelligence is based on real-time reliable platforms managing mixed mission and safety critical vehicle services, advanced sensors/actuators, navigation and cognitive decision-making technology, interconnectivity between vehicles (V2V) and vehicle to infrastructure (V2I) communication. Level 5: Full Automation means the automated system can perform all driving tasks under all conditions that a human driver could perform them compared to the Level 4: High Automation, where an automated system can conduct the driving task and monitor the driving environment, and the human need not take back control, but the automated system can operate only in certain environments and under certain conditions.

In particular, with regards to the high density truck platooning for logistics and transport domain, there is a need for ultra-reliable, low latency V2V safety-relevant communication between the platoon leader and the following trucks in the platoon. There is certainly a need for critical adaptations on side of the trucks, as well as a need for the establishment of close cooperation between the mobile network operators and the truck industry in order to guarantee the requested minimum service level agreements (SLA) for the truck platooning to take place.

Such a communication environment is depicted in the next figure.

In order to be implemented such autonomous vehicle in logistics and transport domain, to evaluate and demonstrate dependability, robustness and resilience of the technology over longer period of time and under a larger variety of conditions, there is a huge need to demonstrate in real-life environments (e.g. highways, congested urban environment and/or dedicated lanes), mixing autonomous connected vehicles and legacy vehicles the functionalities.

The evolutions in the global automotive industry are influencing the logistics and transport industry through different factors that are driving the change in the automotive ecosystem, the move to new business models such as mobility-as-a-service, logistics-as-a-service and the best conditions and the technologies that are supporting the digital transformation.

Nevertheless, there is a need to clarify the business use cases in truck automation on both the private and public sector sides. Standards are needed to support interoperability of trucks that are coupled into platoons and standard methods need to be developed and adopted for measuring the energy savings that can be gained from truck platooning.

Author: Eusebiu Catana

Examples from industry
References

Eusebiu Catana, Johanna Tzanidaki, Connected Corridor for Driving Automation and High Density Truck Platooning in the CONCORDA project, paper EU-TP1533, 25thITS World Congress 2018, Copenhagen, Denmark

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