Research and sharing of vehicle model analysis technology based on single chip microcomputer and vehicle detector

1 Introduction

With the rapid development of science and technology, single-chip microcomputers are also changing with each passing day and developing rapidly. At present, it is not only widely used in industry, but also has been widely infiltrated into various sectors of the national economy, especially playing an important role in transportation construction. In the current and future transportation system, vehicle detectors have attracted great attention from traffic engineering experts for their "eyes and ears" of traffic control. Vehicle detectors can provide vehicle sensing signals for traffic monitoring and control systems, and provide information and data on traffic environment conditions. There are many types of vehicle detectors, and the detection methods are also different. The main vehicle detectors currently used are electromagnetic vehicle detectors, geomagnetic vehicle detectors, ultrasonic vehicle detectors, toroidal coil (active and passive) vehicle detectors, etc. The main working principles of these detectors are different, but they are all based on the passage or existence of vehicles, which changes the energy in the detector and generates vehicle sensing signals.

2 Current status of vehicle model classification technology application at home and abroad

The so-called vehicle type refers to the type of vehicle people classify according to the degree of damage and occupation of the road caused by the vehicle when driving. The purpose of vehicle classification is to collect tolls at different rates. Large vehicles cause more damage and occupation of the road, so the toll is high; small vehicles cause less damage and occupation of the road, so the toll is low. Therefore, there are two main bases for classification, namely the size of the vehicle and the load capacity.

At present, there are two different technical schools of thought in the research of vehicle classification technology: Automatic Vehicle Classification (AVC) and Automatic Vehicle Identification (AVI). The former is to actively classify vehicles by detecting the inherent parameters of the vehicle itself and using appropriate classification and identification algorithms under certain vehicle classification standards; the latter is to realize the classification and confirmation of vehicle models by self-introduction through wireless communication between the on-board unit and the toll collection facilities.

As for the automatic vehicle classification technology AVC, most of the current methods adopted at home and abroad are to charge by vehicle type by detecting the inherent parameters of the vehicle itself and indirectly classifying it according to the vehicle's designed load capacity. This is because the inherent parameters of the vehicle itself, such as: vehicle length, vehicle width, vehicle height, wheel diameter, wheelbase, number of wheels, number of axles, wheelbase, chassis height and external dimensions, are closely related to the vehicle's load capacity and are relatively easy to collect.

3 Principle of electromagnetic vehicle detector

Electromagnetic detectors can detect the passage and presence of vehicles. The detector probe is made of a high-permeability material to form a magnetic core, with a coil wound on its outer frame, placed in a protective tube, and buried under the road surface. The probe is connected to the detection circuit through a lead wire. The probe coil is connected in parallel with the capacitor on the detection circuit to form a resonant circuit. Its equivalent circuit is shown in Figure 1, and its resonant frequency is:

The principle of electromagnetic vehicle detector is to use electromagnetic induction detection technology, that is, according to the different changes in the inductance of the circular induction coil buried under the road, different vehicles are detected to detect the arrival and departure of the vehicle and classify the vehicle type. The key part of the system is the coil detector, which consists of an induction coil and a control part. When no vehicle passes, the frequency of the oscillator is f0. When a vehicle approaches and passes through it at a certain speed, the inductance parameter of the coil changes, which in turn causes a slight change in the oscillation frequency of the oscillator, which is assumed to be f1. During the driving process of the vehicle, since the shape of the vehicle chassis is different, f1 will also change accordingly. When the vehicle leaves the circular coil, the frequency of the oscillator will return to f0, so the value that changes with the time of the car passing is obtained, that is, the frequency difference △f=f1-f0. Different types of vehicles have different shapes, sizes, and heights of the chassis, which leads to different effects on the coil, that is, the change △f of the oscillator frequency is also different, and the frequency difference curves of different types of vehicles passing through the coil are different. In this way, the passage and existence of vehicles can be judged in reverse through the difference of △ factory. Figure 2 is the frequency difference curve obtained when different vehicles pass through the induction coil.

Electromagnetic detectors are both through-type and presence-type, and can detect flow and vehicle speed, with a detection range of 4-meter lanes. This type of detector has low cost and good stability.

4 Hardware Block Diagram

Its hardware circuit is based on the 89CXX series single-chip microcomputer produced by Atmel Company as the core device, and uses a new interface chip with multiple functions to expand the interface circuit. The interface circuit includes vehicle detection circuit, checkpoint alarm circuit, data information storage circuit, vehicle counting and display circuit, clock circuit, keyboard circuit, communication circuit, etc. Its hardware structure block diagram is shown in Figure 3.

5 Software program flow chart

According to the principle of electromagnetic detectors, three electromagnetic detectors are buried in series under the road surface, and the output signals of the three electromagnetic detectors are sent to the single-chip microcomputer for processing. When the three electromagnetic detectors have signal outputs at the same time, it is a large vehicle, when two electromagnetic detectors (adjacent) have signal outputs at the same time, it is a medium vehicle, and when only one electromagnetic detector has a signal output, it is a small vehicle; and no matter whether it is a large vehicle, a medium vehicle or a small vehicle, as long as there is a vehicle passing or existing, it will be counted and displayed.

Assume that the three electromagnetic vehicle detectors are a, b, and c, and their installation positions are shown in FIG4 .

The software program flow chart is shown in Figure 5.

6 Conclusion

For my country, the current unified vehicle classification standard is to classify toll vehicles according to the abstract characteristics of the vehicle (passenger vehicles are classified according to the rated number of seats, and trucks are classified according to the rated load). The current research status shows that various vehicle automatic classification technologies have failed to meet the real practical requirements (identification accuracy of 99.999 9%). At the same time, the vehicle automatic identification technology based on electronic tags has been successfully applied in countries around the world, which provides a good reference for my country's automatic toll collection. The survey of the Intelligent Transportation Research Center (ITSC) of the Ministry of Transport of China shows that the use of high-security prepaid cards to carry out electronic payment business for highway tolls is an inevitable development trend, and dual-interface IC cards and dual-chip ETC electronic tags are used as prepaid card media for networked toll collection systems.

Taking all factors into consideration, the automatic vehicle identification (AVI) technology itself has strong inherent adaptability, high recognition accuracy, can be used around the clock, and has the advantage of being easily integrated with computer network, database and other technologies, making it relatively convenient to implement networking and automatic toll collection services. With the advancement of technology and economic development, after solving the problem of its initial investment being too expensive, it is believed that it should be the most promising and most likely automatic vehicle classification technology in China.