A vehicle treatment system includes a signalling device with at least one sensor and a signal generator. The sensor can continuously detect the position of the vehicle in a predetermined approach region in front of or in the vehicle treatment system. The signal generator can output a signal which changes continuously or discretely and corresponds to a continuously changing position of the vehicle. In this case, the signalling device has at least two lights arranged above one another. A corresponding method can be used for determining and displaying entry information.

A vehicle treatment system includes a signalling device with at least one sensor and a signal generator. The sensor can continuously detect the position of the vehicle in a predetermined approach region in front of or in the vehicle treatment system. The signal generator can output a signal which changes continuously or discretely and corresponds to a continuously changing position of the vehicle. In this case, the signalling device has at least two lights arranged above one another. A corresponding method can be used for determining and displaying entry information.

A network system provides interventions to providers to reduce the likelihood that its users will experience safety incidents. The providers provide service to the users such as transportation. Providers who are safe and have positive interpersonal behavior may be perceived by users as high quality providers. However, other providers may be more prone to cause safety incidents. A machine learning model is trained using features derived from service received by users of the network system. Randomized experiments and trained models predict the effectiveness of various interventions on a provider based on characteristics of the provider and the feedback received for the provider. As interventions are sent to providers, the change in feedback can indicate whether the intervention was effective. By providing messages proactively, the network system may prevent future safety incidents from occurring.

A method, apparatus and computer program product are provided to define a strand upstream of a direction based traffic (DBT) link. In a method, a strand is defined upstream of a DBT link. The method includes extending the strand so as to include one or more links upstream of the DBT link. The strand is extended by determining whether a link is to be added to the strand based upon evaluation of a termination criteria. The termination criteria is at least partially based upon a relationship of a function class of the link to the function class of one or more other links. In an instance in which the termination criteria is satisfied, the method ceases further extension of the strand.

A method, apparatus and computer program product are provided to define a strand upstream of a direction based traffic (DBT) link. In a method, a strand is defined upstream of a DBT link. The method includes extending the strand so as to include one or more links upstream of the DBT link. The strand is extended by determining whether a link is to be added to the strand based upon evaluation of a termination criteria. The termination criteria is at least partially based upon a relationship of a function class of the link to the function class of one or more other links. In an instance in which the termination criteria is satisfied, the method ceases further extension of the strand.

The present invention discloses a method for expressing traffic flow characteristics based on a quantum harmonic oscillator model, including: (1) constructing an energy eigenequation of a quantum harmonic oscillator (QHO) for vehicle movement, and converting the energy eigenequation to an Hermite polynomial; (2) solving traffic flow characteristic parameters using K-order Hermite polynomial approximation; and (3) expressing the traffic flow characteristic parameters on a sphere. On the premise of the autonomous decision of a driving strategy by a driver and centering on the objective limitation that the individual accurate state information in the long-distance expressway traffic flow is not observable, the dynamic evolution of the speed and the state of the vehicle is described using a quantum state, the driving state of the vehicle is expressed as the superposition state of three driving states, and the probability of the three states is represented using QHO model parameters.

The present invention discloses a method for expressing traffic flow characteristics based on a quantum harmonic oscillator model, including: (1) constructing an energy eigenequation of a quantum harmonic oscillator (QHO) for vehicle movement, and converting the energy eigenequation to an Hermite polynomial; (2) solving traffic flow characteristic parameters using K-order Hermite polynomial approximation; and (3) expressing the traffic flow characteristic parameters on a sphere. On the premise of the autonomous decision of a driving strategy by a driver and centering on the objective limitation that the individual accurate state information in the long-distance expressway traffic flow is not observable, the dynamic evolution of the speed and the state of the vehicle is described using a quantum state, the driving state of the vehicle is expressed as the superposition state of three driving states, and the probability of the three states is represented using QHO model parameters.

A traffic monitoring apparatus includes: at least one memory storing instructions; and at least one processor. The processor is configured to execute the instructions to; acquire waterfall data from a distributed acoustic sensor (DAS), wherein the waterfall data includes a generation position of a vibration on a roadway adjacent to the DAS, a generation time of the vibration and an amplitude of the vibration; preprocess the waterfall data; estimate at least one enhancement of the processed waterfall data, wherein an enhancement corresponds to a traffic flow property; and estimate at least one traffic flow property of the roadway from the enhancements of the processed waterfall data.

The invention provides systems and methods for an Intelligent Road Infrastructure System (IRIS), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. IRIS systems and methods provide vehicles with individually customized information and real-time control instructions for vehicle to fulfill the driving tasks such as car following, lane changing, and route guidance. IRIS systems and methods also manage transportation operations and management services for both freeways and urban arterials. In some embodiments, the IRIS comprises or consists of one of more of the following physical subsystems: (1) Roadside unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) vehicle onboard unit (OBU), (4) traffic operations centers (TOCs), and (5) cloud information and computing services. The IRIS manages one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. IRIS is supported by real-time wired and/or wireless communication, power supply networks, and cyber safety and security services.

Electronic devices and methods for recognizing driving behavior are provided. The electronic devices may perform the methods to obtain first electronic signals encoding movement data associated with the electronic device from the at least one sensor at a target time point; operate logic circuits to determine whether the first electronic signals encoding movement data meets a precondition; and upon the first electronic signals encoding movement data meeting the precondition, send second electronic signals encoding movement data within a predetermined time period associated with the target time point to a remote server.