Abstract: An adaptive cruise control system and an adaptive cruise control method supporting traffic light recognition are provided. The adaptive cruise control system in the present disclosure includes: a wireless receiver adaptive with a wireless transmitter of each traffic light on a current lane and configured to receive first traffic light state information about the traffic light on the current lane sent by the wireless transmitter; and a main controller being in communication with the wireless receiver and configured to obtain the first traffic light state information received from the wireless receiver, and perform a stop control or adaptive cruise control based on the first traffic light state information. By implementing the adaptive cruise control method, an adaptive cruise control for avoiding a driver from violation of traffic light is further realized based on the state information of the traffic lights, so that a safety of driving can be improved.

Abstract: A cruise control method and system, and a vehicle, the method being applied to a first vehicle. When the first vehicle is driving in a first lane, before the first vehicle enters from the first lane into a preset recognition region to thereby complete vehicle identity recognition in the preset recognition region, the cut-in probability of a second vehicle cutting into the first lane can be predicted according to a movement parameter of the second vehicle that is in an adjacent second lane, and it is determined, according to the cut-in probability and the stopping time of the first vehicle, whether to brake to stop the first vehicle; therefore, during the process of controlling the first vehicle to pass through the preset recognition region, the driver is not required to temporarily take over control of the first vehicle.

Abstract: A target tracking method and device, relating to the field of vehicles. The method comprises: reading a target fusion list at the current moment, wherein the target fusion list comprises a target attribute set corresponding to each environment target in one or more environment targets, and the target attribute set comprises parameter attribute sets, measured by one or more sensors, of the environment targets; determining whether the target fusion list at the current moment is an initial target fusion list or not; and if the target fusion list at the current moment is not the initial target fusion list, determining a target tracking list at the current moment according to the target fusion list at the current moment and a stored target tracking list at the previous moment, wherein the target tracking list comprises a parameter attribute set corresponding to each screened environment target and a fusion tracking ID.

Abstract: Disclosed are a road feature point extraction method and system. The road feature point extraction method comprises: acquiring map information for the current position of a vehicle, wherein the map information comprises the attributes of the current road and the attributes of the next road section; comparing the attributes of the current road with the attributes of the next road section to determine the road type of the next road section; and extracting, in conjunction with the road type of the next road section and the map information corresponding to the next road section, a road feature point representing a road scene on the next road section, and outputting the name of the extracted road feature point and information of the relative distance between the road feature point and the vehicle.

Abstract: A traffic lane line fitting method includes: obtaining map information for a current position of a vehicle, the map information comprising a number of traffic lanes, a road width and line point information of traffic lane lines on both sides of the vehicle; determining, from among the traffic lane lines on both sides of the vehicle, a traffic lane line on one side, consistent with the direction indicated by at least one of the following, to be a traffic lane line offset reference used for traffic lane line fitting; offsetting and generating a plurality of traffic lane lines of the vehicle on the basis of the traffic lane line offset reference; performing curve fitting on a set of line points on the generated plurality of traffic lane lines so as to obtain a corresponding traffic lane line equation.

Abstract: A method and apparatus used for extracting a feature point of an environmental target, which relate to the field of vehicles. The method comprises: acquiring the position of each corner point of an environmental target; and determining a feature point of the environmental target according to the position of each corner point of the environmental target. Thus, the problem wherein target identification is not precise may be solved, which is particularly suitable for the identification of a large target.

Abstract: A method and apparatus used for extracting a feature point of an environmental target, which relate to the field of vehicles. The method comprises: acquiring the position of each corner point of an environmental target; and determining a feature point of the environmental target according to the position of each corner point of the environmental target. Thus, the problem wherein target identification is not precise may be solved, which is particularly suitable for the identification of a large target.

Abstract: A cruise control method and system, and a vehicle, the method being applied to a first vehicle. When the first vehicle is driving in a first lane, before the first vehicle enters from the first lane into a preset recognition region to thereby complete vehicle identity recognition in the preset recognition region, the cut-in probability of a second vehicle cutting into the first lane can be predicted according to a movement parameter of the second vehicle that is in an adjacent second lane, and it is determined, according to the cut-in probability and the stopping time of the first vehicle, whether to brake to stop the first vehicle; therefore, during the process of controlling the first vehicle to pass through the preset recognition region, the driver is not required to temporarily take over control of the first vehicle.

Abstract: An adaptive cruise control system and an adaptive cruise control method supporting traffic light recognition are provided. The adaptive cruise control system in the present disclosure includes: a wireless receiver adaptive with a wireless transmitter of each traffic light on a current lane and configured to receive first traffic light state information about the traffic light on the current lane sent by the wireless transmitter; and a main controller being in communication with the wireless receiver and configured to obtain the first traffic light state information received from the wireless receiver, and perform a stop control or adaptive cruise control based on the first traffic light state information. By implementing the adaptive cruise control method, an adaptive cruise control for avoiding a driver from violation of traffic light is further realized based on the state information of the traffic lights, so that a safety of driving can be improved.

Abstract: Disclosed are a road feature point extraction method and system. The road feature point extraction method comprises: acquiring map information for the current position of a vehicle, wherein the map information comprises the attributes of the current road and the attributes of the next road section; comparing the attributes of the current road with the attributes of the next road section to determine the road type of the next road section; and extracting, in conjunction with the road type of the next road section and the map information corresponding to the next road section, a road feature point representing a road scene on the next road section, and outputting the name of the extracted road feature point and information of the relative distance between the road feature point and the vehicle.

Abstract: A target tracking method and device, relating to the field of vehicles. The method comprises: reading a target fusion list at the current moment, wherein the target fusion list comprises a target attribute set corresponding to each environment target in one or more environment targets, and the target attribute set comprises parameter attribute sets, measured by one or more sensors, of the environment targets; determining whether the target fusion list at the current moment is an initial target fusion list or not; and if the target fusion list at the current moment is not the initial target fusion list, determining a target tracking list at the current moment according to the target fusion list at the current moment and a stored target tracking list at the previous moment, wherein the target tracking list comprises a parameter attribute set corresponding to each screened environment target and a fusion tracking ID.

Abstract: Disclosed are a road feature point extraction method and system. The road feature point extraction method comprises: acquiring map information for the current position of a vehicle, wherein the map information comprises the attributes of the current road and the attributes of the next road section; comparing the attributes of the current road with the attributes of the next road section to determine the road type of the next road section; and extracting, in conjunction with the road type of the next road section and the map information corresponding to the next road section, a road feature point representing a road scene on the next road section, and outputting the name of the extracted road feature point and information of the relative distance between the road feature point and the vehicle.

Abstract: A method and apparatus used for extracting a feature point of an environmental target, which relate to the field of vehicles. The method comprises: acquiring the position of each corner point of an environmental target; and determining a feature point of the environmental target according to the position of each corner point of the environmental target. Thus, the problem wherein target identification is not precise may be solved, which is particularly suitable for the identification of a large target.