1. A vehicle-road cooperative driving assistance system, comprising: the intelligent network comprises a pedestrian end, a vehicle end, a road side end and a cloud end, wherein the pedestrian end receives a public traffic running state and emergency vehicle avoidance information, the vehicle end monitors the state in a cabin, collects road information and communicates with other vehicles, the road side end issues a road sign and signal lamp color timing, and the cloud end establishes intelligent network connection, calculation, storage and data transmission for the pedestrian end, the vehicle end and the road side end.

2. The vehicle-road cooperative driving assistance system according to claim 1, wherein the road-side end issues signal light color timing, including: the road side sends signal lamp color timing to the cloud side, the vehicle side subscribes the signal lamp color timing, the cloud side forwards the signal lamp color timing to the vehicle side, and the vehicle side prejudges the passing route according to the signal lamp color timing.

3. The vehicle-road cooperative driving assistance system according to claim 2, further comprising: the vehicle end publishes a traffic route to the cloud end, the road side end subscribes the traffic density, the cloud end calculates the traffic density according to the traffic route and forwards the traffic density to the road side end, and the road side end adjusts the color timing of a signal lamp according to the traffic density.

4. The vehicle-road cooperative driving assistance system according to claim 1, further comprising: the special vehicles or pedestrians and vehicles meeting special conditions apply temporary permission to the traffic police, obtain red marks, display the red marks at the nearby vehicle ends, send out voice prompts and request to make way.

5. The vehicle-road cooperative driving assistance system according to claim 1, further comprising: the cloud acquires ponding information issued by the meteorological bureau, calculates the ponding depth, forwards the ponding information to the roadside end, displays the ponding depth by the roadside end, and the vehicle end acquires ponding depth data by a sensor and issues the ponding depth data to the cloud.

6. The vehicle-road cooperative driving assistance system according to claim 1, further comprising: the vehicle terminal collects information of facial expressions, head postures and eyeball focusing of the driver at variable time, prompts rest if judging that the driver is tired in driving, and transmits videos in the vehicle to a public security department if judging that the driver has life risks.

Background

The number of private cars is increased, so that the efficiency and safety of traveling are challenged. A large number of traffic accidents occur in the country on average every day, and the number of people who die due to the traffic accidents is few. The most effective way to reduce road congestion is to build overhead and widen roads, but infrastructure construction is not done all at once. The foundation of original road facilities is kept, traffic pressure is relieved from the technical level, and personal safety of road trip personnel is guaranteed.

Compared with a straight road, various uncertain factors at the intersection cause the intersection to become a frequent accident road section. Signal lamps, zebra crossings, crossing lane change signs and the like are used as original infrastructure, normal operation of the crossings is guaranteed, and the current situations of congestion and frequent accidents cannot be changed. When the signal lamp is shielded by a large vehicle in front, no signal lamp is arranged at the intersection, and the signal lamp fails to display normally, a driver can drive with the vehicle or pass through the vehicle quickly, so that traffic accidents and traffic jam are easily caused.

When a special vehicle is blocked on a road, even if the special vehicle is subjected to whistle reminding, on one hand, the front vehicle is not informed due to road noise, and on the other hand, the current situation of traffic jam cannot be improved due to the fact that only one vehicle gives way, so that precious rescue time is delayed on the special vehicle on the road.

Pedestrians are the most uncertain factor on roads, and are extremely free and most vulnerable to injury. Whether pedestrians in front can be found or not depends on active observation of a driver, sometimes the driver is influenced by sight shielding, and the pedestrians cannot be found to suddenly emerge in time and have no time to step on a brake.

Obstacles caused by manual operation excavation and natural disaster invasion to road smoothness exist potential safety hazards if the obstacles cannot be predicted by a driver in time. For boring driving, drowsiness is easy to occur in a closed car cabin, and fatigue driving is also a big cause of traffic accidents.

Disclosure of Invention

In order to solve the problems in the prior art, the invention provides a vehicle-road cooperative auxiliary driving system with four elements of people, vehicles, roads and clouds.

The system comprises a pedestrian end, a vehicle end, a road side end and a cloud end, wherein the pedestrian end receives a public traffic running state and emergency vehicle avoidance information, the vehicle end monitors the state in a cabin, collects road information and communicates with other vehicles, the road side end issues road indicating signs and signal lamp color timing, and the cloud end establishes intelligent network connection, and calculates, stores and transmits data for the pedestrian end, the vehicle end and the road side end.

The road side sends out the signal lamp color timing including sending, subscribing and forwarding, the road side sends out the signal lamp color timing to the cloud, the vehicle side subscribes the signal lamp color timing, the cloud forwards the signal lamp color timing to the vehicle side, and the vehicle side judges the passing route in advance according to the signal lamp color timing.

The vehicle end issues a traffic route to the cloud end, the road side end subscribes the traffic density, the cloud end calculates the traffic density according to the traffic route and forwards the traffic density to the road side end, and the road side end adjusts the color timing of the signal lamp according to the traffic density to realize the self-adaptive adjustment of the color timing of the signal lamp along with the traffic flow, so that traffic jam is relieved.

The special vehicles or pedestrians and vehicles meeting special conditions apply temporary permission to the traffic police, obtain red marks, display the red marks at the nearby vehicle ends, send out voice prompts and request to make way.

The cloud acquires ponding information issued by the meteorological bureau, calculates the ponding depth and forwards the ponding depth to the roadside end, the roadside end displays the ponding depth, and the vehicle end adopts the sensor to acquire the ponding depth data and issues the ponding depth data to the cloud.

The vehicle terminal collects information of facial expressions, head postures and eyeball focusing of the driver at variable time, prompts rest if judging that the driver is tired in driving, and transmits videos in the vehicle to a public security department if judging that the driver has life risks.

According to the vehicle synchronous running and queuing condition, the signal lamp is adjusted, the congestion phenomenon is improved, the road section information is transmitted, the vehicle is prompted to avoid a congestion area, a passage is opened for people and vehicles with emergency traffic demands, the vehicle is used for detecting the depth of accumulated water, the accumulated water prompt is issued to the road section, the wading dangerous condition is avoided, the driving state is monitored in real time, and the fatigue driving is avoided.

Drawings

Fig. 1 is a schematic diagram of a system configuration, fig. 2 is a flowchart of a special vehicle processing, fig. 3 is a flowchart of a water accumulation section handling, fig. 4 is a flowchart of a fatigue driving handling, fig. 5 is a graph of a queued vehicle function, fig. 6 is a graph of a number of stops and a length of queue, and fig. 7 is a graph of a delay time.

Detailed Description

The technical scheme of the invention is specifically explained in the following by combining the attached drawings.

The system structure principle is shown in fig. 1, the main functions of the pedestrian end are that a mobile phone receives a public traffic running state and prompts of emergency avoidance of vehicles, the main functions of the vehicle end are cabin interior monitoring, road information acquisition and vehicle-to-vehicle communication, the main functions of the road side end are that an intelligent network connection direction mark issues information in real time, the color of a signal lamp is transmitted, and timing is conducted, and the main functions of the cloud end are data calculation and transmission.

In order to reduce the delay time of the special vehicle for rescue, the processing flow is as shown in fig. 2, red marks are carried out on the special vehicle, pedestrians and the like, other vehicles are weak color marks, other vehicles can apply for temporary red marks after traffic police permit when meeting special conditions, the red marks are displayed on display screens of surrounding vehicle ends, and corresponding voice prompt is carried out to inform surrounding vehicles of giving way.

The coping process is shown in figure 3 when the vehicle end has accumulated water in rain or construction, the vehicle end acquires information of a serious accumulated water road section published by the road side end, and simultaneously autonomously detects the depth of the accumulated water, wherein the former depends on a weather bureau to display the information of the accumulated water road section through an intelligent network connection road sign, and the latter depends on a corresponding sensor of the vehicle end.

The in-cabin fatigue monitoring and coping process is shown in fig. 4, the attitude information of a driver is collected at an irregular vehicle end and comprises facial expressions, head postures and eyeball focusing power, when the system judges that the driver has a risk of fatigue driving, the driver is prompted to have a rest at a high speed nearby through voice, and when the driver is found to have a life danger, the system automatically transmits video in the vehicle to a public security department.

To verify that signal light adjustment improves in the mitigation of queuing congestion, the function curve of the queuing vehicles is shown in FIG. 5, with the vehicles at t₁，t₂…, the cumulative number of arrivals may be expressed as a function A (t) where the vehicle arrives₁’，t₂', … are respectively separated at time, and the cumulative number of separated can be expressed as function D (t)

At time t_iThe cumulative arrival number is A (t)_i) The cumulative number of departures is D (t)_i) Queue length Q (t)_i) Is composed of

Q(t_i)＝A(t_i)-D(t_i)

According to the first-in first-out principle, at the time ti, the arriving vehicle is j, and the leaving time is t_j’＝D^-1(j) The waiting time is W_j＝D^-1(j)-A^-1(j)

the slope of the arrival function a (t) at time t is λ (t) ═ da (t)/d (t)), and is the instantaneous arrival rate at time t, and the slope of the departure function d (t) at time t is μ (t)₁) (dD (t)/dt) represents the instantaneous departure rate at time t

The traffic capacity can not exceed the service rate mu (t), if lambda (t) < mu (t), no queuing exists, D (t) is coincident with A (t), and the vehicle enters and leaves; if λ (t) > μ (t), queuing occurs; if lambda (t) is equal to service rate mu (t), the queue length is maximum

The waiting time in line of the vehicle isAverage waiting time of n vehicles isThe total number of vehicles in the time period T isAverage queue length of

The areas enclosed by the two curves are equal nW_a＝TQ_aOr Q_a＝nW_aAnd n/T is the average number of arriving vehicles in unit time, namely the average queuing length is the average waiting time multiplied by the average arrival rate.

And obtaining a digital simulation result based on VISSIM (visual system identity Module) road simulation software and C # programming software, carrying out graphical processing by using MATLAB (matrix laboratory), verifying the improvement of the optimized adaptive signal lamp on the road traffic capacity, and providing theoretical basis and technical guidance for the arrangement of the actual signal lamp.

Setting simulation conditions, setting the maximum traffic capacity of a single road to be 900 vehicles per hour, wherein as shown in fig. 6, the traffic flow in four directions reaches the maximum value within 1200-1800 seconds, monitoring the traffic flow once per 240 seconds, and changing the road section of the signal lamp, as shown in fig. 7, the maximum queue length, the number of times of parking in the queue and the total delay index of the intersection of the signal lamp in the time period are all superior to the road section without the signal lamp.

The above-described embodiments are not intended to limit the present invention, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present invention are included in the scope of the present invention.