A method of performing green wave coordination control, an apparatus of performing green wave coordination control, an electronic device, and a storage medium, which relate to a field of intelligent transportation, and in particular, to a field of traffic control. The method includes: obtaining (S210) an intersection parameter and a green wave parameter of n intersections on a preset road; calculating (S220) a duration of green wave travel for each road segment according to a green wave speed for the preset road; determining (S230) a constraint of green wave coordination according to the intersection parameter, the green wave parameter and the duration of green wave travel; determining (S240) an objective function of green wave coordination according to the forward green wave bandwidth and the reverse green wave bandwidth of each road segment; and performing green wave coordination control (S250) according to the constraint and the objective function.

Methods, vehicles and systems for managing vehicle velocity along routes having traffic lights. The behavior of an individual vehicle is adjusted to account for surrounding vehicles to avoid inefficient outcomes across a group of vehicles. A vehicle is configured to determine the presence of other vehicles in a defined following distance, and uses the presence of such other vehicles to adjust its own travel strategy, with or without communication or coordination with, or control over, the other vehicles.

A system and method are provided for quantifying greenhouse gas (GHG) emissions associated with vehicle traffic. The method includes receiving data from a plurality of devices located at a plurality of traffic intersections in a traffic network, each device comprising at least one sensor configured to obtain data from the corresponding traffic intersection; using the received data and a traffic model to determine vehicle trajectory data; using the vehicle trajectory data and an emissions model to obtain corresponding GHG emissions data; and evaluating the corresponding GHG emissions data to a baseline of GHG emissions using a GHG quantification methodology to determine a GHG reduction that can achieve a carbon offset credit.

A system and method are provided for quantifying greenhouse gas (GHG) emissions associated with vehicle traffic. The method includes receiving data from a plurality of devices located at a plurality of traffic intersections in a traffic network, each device comprising at least one sensor configured to obtain data from the corresponding traffic intersection; using the received data and a traffic model to determine vehicle trajectory data; using the vehicle trajectory data and an emissions model to obtain corresponding GHG emissions data; and evaluating the corresponding GHG emissions data to a baseline of GHG emissions using a GHG quantification methodology to determine a GHG reduction that can achieve a carbon offset credit.

Provided are implementation method and system for road traffic reservation passage, and electronic device. The method includes: determining path reservation speed curve according to path planning information of vehicle, which includes driving data of the vehicle passing through intersection in planned path; the vehicle sending the path reservation speed curve to traffic scheduling center; the traffic scheduling center classifying the received path reservation speed curve according to intersection information to obtain the classification result, and sending it to signal control calculation unit of the corresponding intersection; the signal control calculation unit determining intersection signal lamp timing scheme and vehicle speed guide data according to the classification result and sending same to the vehicle; the vehicle determining driving speed control curve according to the received intersection signal lamp timing scheme and the vehicle speed guide data, and guiding the passing of the vehicle according to the driving speed control curve.

Provided are implementation method and system for road traffic reservation passage, and electronic device. The method includes: determining path reservation speed curve according to path planning information of vehicle, which includes driving data of the vehicle passing through intersection in planned path; the vehicle sending the path reservation speed curve to traffic scheduling center; the traffic scheduling center classifying the received path reservation speed curve according to intersection information to obtain the classification result, and sending it to signal control calculation unit of the corresponding intersection; the signal control calculation unit determining intersection signal lamp timing scheme and vehicle speed guide data according to the classification result and sending same to the vehicle; the vehicle determining driving speed control curve according to the received intersection signal lamp timing scheme and the vehicle speed guide data, and guiding the passing of the vehicle according to the driving speed control curve.

An adaptive traffic management system includes a plurality of traffic lights positioned at a plurality of roadway intersections. Associated with each intersection is one or more sensors to detect traffic flow. A control system is connected to the traffic lights and the sensors and based upon data received and predetermined weights for various situations generates a signal timing plan that operates the traffic lights. The control system also may be connected to multiple sources, wearables, and/or in-vehicle sensors that are also used to generate the signal timing plan and operate the traffic lights.

An adaptive traffic management system includes a plurality of traffic lights positioned at a plurality of roadway intersections. Associated with each intersection is one or more sensors to detect traffic flow. A control system is connected to the traffic lights and the sensors and based upon data received and predetermined weights for various situations generates a signal timing plan that operates the traffic lights. The control system also may be connected to multiple sources, wearables, and/or in-vehicle sensors that are also used to generate the signal timing plan and operate the traffic lights.

The present disclosure provides a method for traffic scheduling at an intersection in a smart city and an Internet of Things system. The method includes: for the intersection in a preset area, determining whether traffic congestion is likely to occur at the intersection during a next time period based on a comparison result between the number of the first vehicles and the number of second vehicles; in response to determining that the traffic congestion is likely to occur at the intersection during the next time period, determining whether a traffic scheduling strategy is needed to be switched based on traffic data information of the intersection during the next time period; and in response to determining that the traffic scheduling strategy is needed to be switched, switching a first traffic scheduling strategy to a second traffic scheduling strategy.

A method, apparatus and computer program product are provided for generating structured trajectories based on probe data for simulating traffic flow. Methods include: receiving a plurality of sequences of probe data points; identifying splitting points in each of the plurality of sequences representing points where a respective sequence is split and decomposed into a plurality of legs; identifying the plurality of legs between pairs of splitting points; grouping legs according to a hierarchical optimizer into bunches of legs; determining, from the bunches of legs, a map representation of a road network; composing bunches of legs into a directed graph based on leg continuations, where the directed graph is formed by bunches of legs connected to continuation bunches of legs, and graph nodes of the directed graph represent intersection decision points; and simulating a condition including traffic flow within the road network based on decisions made at the intersection decision points.