智能汽车的控制

智能汽车的控制
智能汽车的控制

智能汽车的控制

ABSTRACT

From the beginning of the artificial intelligence there was a desire of having a fully automated intelligent car. Numbers of experiments have been done and some of them were very much fruitful. As a result now we have intelligent smart cars. These cars are intelligent and can take some of the decision of their own. But they actually assist the driver for a limited amount of time. None of them are fully automated. We think a fully automated transportation can only be possible by having a combination of intelligent car and traffic system as well the environment like road on which the car actually moves. In this paper we have tried to discuss a new idea for an autonomous transportation system- a complete solution.

General Terms

Artificial Intelligence, Intelligent Car

Keywords

Intelligent Transportation, GPS (Global Positioning System), ACC (Adaptive Cruise Control),AHS (Automated Highway Systems), Smart Cars, DLCC (Dynamic Laser Cruise Control).

1. INTRODUCTION

Autonomous or Adaptive Cruise Control (ACC) is mostly used intelligent system for smart car controlling. Normally a radar or laser setup is used that allows the vehicle to slow when the front vehicle is slowing down and speed up to the preset speed that the traffic allows when no vehicle is in front. But these systems can only take control or take decision in straight roads where there is no possibility of taking decision about changing the route. But in this paper we tried to offer a system when it is fully autonomous. Here we have not only considered the intelligence in the car but also in the traffic system, so that an intelligent network can be established which is able to take decision for end to end transportation without any human interaction.

2. THE CHALLENGE

There are basically two challenges related with this intelligent transportation system. Those are –

1. Technical Challenge

2. Social Challenge

As technical challenge we face problems in designing the sensors and the control systems and also problem in source to destination decisions. On the other hand as a Social Challenge we found the problems like- getting people to trust into automated car, getting legislators permission for being car onto

the public roads, and untangling the legal issues of liability for any mishaps with no in charge. Now the solutions to get a automated car can be broken into four sub-systems like-

1. Sensing: knowing where an obstacle is and what is around it which means sensing the surrounding.

2. Navigation: getting to the target location from the present location.

3. Motion planning: Moving on the road, avoiding obstacles, avoiding harm to the people, and obey to the rules of the road which means actually taking decision of breaking, accelerating, turning etc.

4. Control of the vehicle itself: actuating the system's decisions.

3. AVAILABLE SYSTEMS

Typically for ACC most popular systems are-

1. Laser Based ACC

2. Radar Based ACC

Presently the laser based ACC which is low cost but available. It is available in near luxury cars within 400-600 USD/euro. But the problem with this is it fails to detect and track well in adverse weather conditions. These cars are also unable to track dirty non reflective vehicles. Laser-based sensors have to be exposed and typically found in the lower grill offset. On the other hand Radar based ACC gives better performance then laser based ACC sacrificing more cost. They are available in luxury cars within 1000-3000 USD/euro. Available systems basically focus on automatic speed adaptation technique and intelligent breaking. They don’t bother about route choosing and track changing. Normally they the front car and maintain safe distance from that car in order to take speed adaptation decisions. Here is a figure that shows how it is been done. Jaguar Cars and Mercedes-Benz first offered radar-based systems in 1999. Mercedes-Benz offered the ‘Distronic Plus’ system that can halt the car if necessary on their S-Class luxury sedans in 2006. Audi Q7 also offers this feature. Toyota's

Figure 1: Adaptive Cruise Control (ACC)

Lexus first brought laser-based systems to the US market with the 2001 Lexus LS430 "DLCC" (Dynamic Laser Cruise Control). It also offered radar-based systems on its IS, ES, GS and LS models and the laser based on its RX model. Acura RL features Collision Mitigation Braking System. It can alert drivers of objects if the distance is less. It brakes slightly and tugs at the seatbelts too. Even if the driver doesn’t react then the RL retracts, locks the seatbelts and brakes hard. Lexus LS430/460 also offers the system.

4.PAST RESEARCHES

Different Research groups did researches on different issues related to the system. Among them some were very fruitful that showed new pathways. Automated highway systems (AHS) are an effort to construct special lanes on existing highways that would be equipped with magnets or other infrastructure to allow vehicles to stay in the center of the lane,

while communicating with other vehicles (and with a central system) to avoid collision and manage traffic. AHS allows specially equipped cars to join the system using special 'acceleration lanes' and to leave through 'deceleration lanes'. When leaving the system each car verifies that its driver is ready to take control of the vehicle, and if that is not the case, the system parks the car safely in an area. The implementation of the AHS demo is done in 1997 near San Diego, sponsored by the US government, in coordination with the State of California and Carnegie Mellon University. The test site is a 12-kilometer, high-occupancy-vehicle (HOV) segment of Interstate 15, 16 kilometers north of downtown San Diego. The event generated much press coverage which was a great achievement. The technology is become the subject of a book. This united effort by the US government seems to have been pretty much abandoned because of social and political forces, above all else the desire to create a less futuristic and more marketable solution. As in 2007, a three-year project is underway to allow robot controlled vehicles, including buses and trucks, to use a special lane along 20 Interstate 805. The intention is to allow the vehicles to travel at shorter following distances and thereby allow more vehicles to use the lanes. The vehicles will still have drivers since they need to enter and exit the special lanes. Before entering those lanes car should have take help from the driver who starts up the car, speed up into a certain limit, enter into a safe state as well as a safe lane and then take over the control of the car into itself. Here car is half automated where car needs some assistant from the human as before being automated. The system is being designed by Swoop Technology, based in San Diego country. Over here we have analyzed the past research which was reached up to a level of assisting driver for taking decision while driving but still it needs most of the involvement of the drivers. Those researches show the pathway of the automated car.

5. OUR CONTRIBUTION

5.1. Identifying the basic things that need to be autonomous

In order to drive a car, a system would need to:

1. Understand its environment (Sensors)

2. Identify where it is and where it wants to go (Navigation)

3. Identify its way in the traffic (Motion planning)

4. Operate the staring of the vehicle (Actuation)

It is concluded that almost 2?of these problems are already solved which varies in terms of environment and place. Navigation and Actuation problem solved completely, and Sensors partially, but improving fast. The main unsolved part is the motion planning which is our main concern.

5.1.1 Sensors

Sensors employed in driverless cars vary from the minimalist ARGO project's monochrome stereoscopy to Mobileye's inter-modal (video, infra-red, laser, radar) approach. The minimalist approach imitates the human situation most closely, while the multi-modal approach is "greedy" in the sense that it seeks to obtain as much information as is possible by current technology, even at the occasional cost of one car's detection system interfering with another's thus create another problem.

5.1.2 Navigation

The ability to plot a route from where the vehicle is to where the user wants to be has been available for several years. These systems, based on the US military's Global Positioning System are now available as standard car fittings, and use satellite transmissions to ascertain the current location, and an on-board street database to derive a route to the target. The more sophisticated systems also receive radio updates on road blockages, and adapt accordingly. There are also sensors that greatly affect the whole nature of it.

5.1.3 Control of vehicle

As automotive technology matures, more and more functions of the underlying engine, gearbox etc. are no longer directly controlled by the driver by mechanical means, but rather via a computer, which receives instructions from the driver as inputs and delivers the desired effect by means of electronic throttle control, and other drive-by-wire elements. Therefore, the technology for a computer to control all aspects of a vehicle is well understood.

5.2 Some things which assists a human as well a automated car

These systems warn or inform the driver about events that may have passed unnoticed, such as

Lane Departure Warning System (LDWS)

Visibility aids for the driver, to cover blind spots and enhanced vision systems such as radar Wireless vehicle safety communications and night vision.

Infrastructure-based, driver warning/information-giving systems.

6. LATEST ACHIEVEMENT

Google modified Toyota prius [6] uses an array of sensors to navigate a public road without human involvement. It includes different types of sensors like –

?GPS: The Global Positioning System (GPS) [1] is a space-based global navigation satellite system that provides reliable location and time information in all weather and at all times and anywhere on or near the Earth when and where there is an unobstructed line of sight to four or more GPS satellites.

?Motion Sensor: This one is used for monitoring the speed of the car.

?LIDAR: A rotating sensor on the roof which scans around

Figure 2: Autonomous Speed Adaptation with Intelligent Highway

200 feet in all the direction of the car to generate a precise three dimensional map on the car’s surrounding.

?Position estimator: A sensor mounted on the left rear wheel which measures the small movement made by the car and to accurately locate its position on the map.

?Video Camera: A camera near the rear view mirror deflects traffic lights and helps the car`s onboard computer recognize moving obstacle like pedestrian and bicyclists. ?Radar: Four standard automotive radar sensors, three in front and one in the rear, help to determine the position of the distant objects. By using these kind of sensors this car overcome the problem of Navigating and actuating itself, hence using various types of

sensor it also achieved good sensing capability but still motion planning is a challenging issue for that car on which factor basically we emphasizes. 7. OUR PROPOSAL Here in this paper we are actually trying to offer a complete end to end solution we have divided our proposal into five specific parts:

1.Route Analysis

2.Autonomous Speed Adaptation

https://www.360docs.net/doc/8516128286.html,ne Detection & Change

4.Intelligent Breaking System

5.Artificial vision image processing

6.Avoid Collusion

7.Security Issues

7.1. Route Analysis

When we are starting with our car we need to fix our route towards our destination. Now with an intelligent system we only need to specify our destination. From the GPS [1] the car knows its present position and from the digital map it knows all the routes towards the destination. It then finds out all alternatives of the routes and gives the best low cost and low distance solution. It also gives an option that from the possible solution which one the owner would like to have. If he gives a choice it follows the gives route. Else it would follow the low cost route or the optimum solution. This is the first step of the journey where the route is already been fixed. Now the car has to move towards the destination on the route it has selected.

7.2. Autonomous Speed Adaptation

This is actually a well recognized system that is already in use. But we are offering a few modifications on the present system Causes for these modifications are described here. In the present system the speed adaptation [2] is basically done depending on the front vehicle. If the vehicle slows down the car slows its speed and if the car accelerate then the car accelerates. Here the driver has to set the speed limit that up to which speed it can accelerate and also have to be concerned about the signals. That means though we are actually saying that it is automatic but much of the decisions are given by the driver. Again when there is no vehicle in front then it can not take any decision depending on the signal that the red light is on and it needs to be slow down. We offer that the previous adaptation system would be in use but in addition to it the highway should be made intelligent also. In the signal positions the signal posts should communicate with all the vehicles that already a red signal has been shown so slow down or green light is on you can move. When ever the car is entering any speed zone the speed limit posts should inform the cars that this is a speed limit area so the maximum speed limit should be that. So the car can itself take the maximum speed decision. In this way two of the human dependency can be reduced.

Fig. 3: Lane Detection

7.3. Lane Detection and Change

Lane detection is a major concern in order to move automatically on the road. From the GPS [1] we know that where there is a curve on the road but how much bend is there it is not clear from the GPS or the digital map [1]. Again from the Radar or Laser sensor it is

possible to get a view that there is curve if obstacle is there though it is tough to have a correct estimation about the bend and even sometimes hard to notify the curve. But if we can estimate that in which lane we are now and always keep our car on the track then with the bend of the lane the car will also take a turn itself. So no problem arises with taking a decision in a curve road. That makes the automation possible in any kind of road not only in straight ones. Now this lane detection can be achieved by having roadside wireless signals. These signals will always transmit that where is it residing and how many lanes are there in the road. From these readings the car knows that in which lane he is now. And by measuring the distance it ensures that it resides always in the same lane. Again lane changing is also a difficult decision to take. In present smart cars we have to change the lane manually. So for the time human interaction is needed. This makes actually the whole automation useless as the driver has to be concern always about the change of the lane. But this can be made automated using two more radar or sensor device in the car. The figure shows that how this can be done. Two laser or radar devices residing on the sides will always search that is there any vehicle moving either of the sides. Another laser or radar device on the back checks that is there any vehicle trying to overtake. If it finds on the possibilities negative it takes the decision for having a lane change. This way the lane 图

Figure 4: Lane Changing Decision

changing can be made automated. But using three more devices is a costly choice. So we can perform the task using one device. This will have time scheduled checking on three of the sides and gives the same output that we want to have.

7.4. Intelligent Breaking System

As speed adaptation is needed thus is the speed control. So we need to be concerned about the breaking system. Now the breaking system mostly depends on finding any obstacles. If it finds any obstacle it would slow down. It would also measure

its speed and size. Now that requires a video camera to take effect. Now this analysis result helps the car to take decision that when and how to break. It first slows itself down gradually and when it finds a break situation it breaks with some more additional tasks. It should tight the seatbelt to ensure the safety of the passengers, give horn to alert others and in an extreme situation it should give a signal to the driver to notify him about the situation.

7.5 Artificial vision image processing

This one is the feather which could be achieved by image processing. Actual automated system could be achieved only when we incorporate our car with a sensor which can sense like human & take decision like human. In GPS we get data which is not precisely instant. Other sensor that we use can sense the things or obstacles in front of our car but for getting instant feedback we need image processing software which gets image from the Video Camera. After processing that our onboard computer takes necessary steps for motion control of the automated car. This image processing basically helps us for avoid the accident in case of sudden obstacles come in front of the automated car which is basically acts like human intelligence.

7.6. Avoid Collusion

The cars will avoid collisions with obstacles located in the environment using laser (long range) and ultrasonic (short-range) sensors. Laser will be used for identifying the obstacles which is in front of that car. On the other hand short range sensor like ultra sonic sensor will be used for avoiding the collusion of the adjacent lane cars or been struck the road divider. Road divider will also have some short range sensor which will be sensed by the car when it crosses the certain threshold limit of the distance between the car and the divider.

7.7. Assistance in Turning

All of the intelligent that have already developed is well suited for the straight road. Some of the statistics shows that around 90% time car is autonomous that means in that time car was independent of driver though he was present; rest of the 10% time those intelligent cars needs the assistant of the drivers. It is true that that 10% time was the situation when the car needs to take left or right turn as because then more intelligent decision should have to take by the car which is not achieved by the intelligent car yet. Over this situation our proposal is to use ultra sonic senor on the divider of the road which will be sensed by the car. By using the intensity of that sensor output our car will know how closer he is to the divider. When this distance is tends to be shorter then it takes necessary steps for making that distance constant, like take left turn when divider is on right or vice versa. Thus we can achieve the problem of left and right turning. On the meantime cars ultra sonic sensor is used for detecting the adjacent lanes cars position to avoid the collusion with those car.

7.8. Security

Different security issues should be maintained with intelligence. This can be done by applying different systems. Our proposed systems are-

a. The starting should be done as a button press and that button should have a finger print analysis system. The owner and the user of the car all have their finger prints prerecorded. This ensures that no other person is able to start the car by any illegal mean.

b. Airbags [5] should be controlled centrally and the car should have the decision taking capability that within what time they should be exposed depending on the speed of the cars and the force of the collision.

c. The car should always have communication with the central traffic system so that at any mishap it can inform the central system. The central system should always track the vehicle. This ensures help on the spot at any case of emergency.

8. ADVANTAGES & DISADVANTAGES

The benefits we are expecting to have are as follows:

1.It would be fully autonomous system from end to end without any human interaction. So it gives a full relax in driving that means the driverless transportation would be possible.

2. The intelligent car is fully aware of its own condition. So there is no need to be concerned about the condition of the vehicle. It is checked automatically and problem can be detected and fixed from the central system.

3. The security issues makes the automated car a much safer driving experience. It is also aware of the conditions of the passengers and at any disturbance with their health condition and at any emergency situation it can inform the central system and take necessary actions.

4. We expect to have a much lower rate of accidents as automation will add more accuracy in driving. Moreover the automated driving will not depend on the mental condition of the driver. So no hamper would be there.

5. Customization would become an easy task as with a single soft copy of a module we can define the full customization of the vehicle. The car recognizes the user and it itself makes the customizations.

The basic drawback of this proposal would face is the cost. The devices we are about to use here will make the cost increase. But it should be acceptable as a new technology always comes a bit costly. Moreover the car is offering no driver and diagnosis needed that saves money. So in spite of its cost hopefully it would be a fruitful proposal to be implemented in near future.

9. CONCLUSION

This proposal gives a view to a complete automation of the transportation system. But further works should be done to find out its faults and to solve them. But as far as we understood we think that it can give a complete guideline for the system and should be very much helpful for further researches. We think that with a full automated transportation the dream of having the automated society will come to true. Automated transportation will be one major step in that dream come true. By using multiple sensors effectively we can achieve the automated car, which will relief the people of taking burden of driving a car that saves thousand of working hour of human. We believe if our proposal in incorporated with the recent advancement then with 5 year we will find the fully self dependent automated car. Over here is a factor of cost as for getting one automated car people have to spend more but that will be in return when they can save thousands of working hours as well as get safe, easy, comfortable, optimum and reliable journey. REFERENCES

[1] Basnayake C; Mezentsev O; Lachapelle G; Cannon M (2004): "A Portable Vehicular Navigation System Using High

Sensitivity GPS Augmented with Inertial Sensors and Map-Matching", SAE Paper 2004-01-0748.

[2] Carsten O ; Tate F (2005): "Intelligent Speed Adaptation: Accident Savings and Cost-Benefit Analysis",

Accident Analysis and Prevention 37, pp.407-416.

[3] ETSC (2006): "Intelligent Speed Assistance Myths and Reality: ETSC Position on ISA", European Transport Safety

Council, May 2006

[4] Regan M; Triggs T; Young K; Tomasevic N; Mitsopoulos E; Stephan K ; Tingvall C (2006) :"On-road Evaluation of ISA,

Following Distance Warning and Seat Belt Reminder Systems: Final Results of the TAC Safecar Project", Monash University

Accident Research Centre, September 2006.

[5] Carsten O (2001) : "ISA: the Best Collision Avoidance System?", Proceedings of 17th Conference on

the Enhanced Safety of Vehicles, Netherlands.

AUTHORS

Md. Nazmul Hasan has completed his graduation from Islamic University of Technology (IUT) in November 2008. After his graduation he has joined in Stamford University Bangladesh as a lecturer of Computer Science department and till now he is serving here. He is also been working as a part time faculty member of Islamic University of Technology (IUT). His research interest includes Distributed Systems, Parallel Processing, Sensor Network, Cellular Network, Artificial Intelligence etc.

S. M. Didar-Al-Alam has completed his graduation form Islamic University of Technology (IUT) in November 2008. Just after his graduation he joined Islamic University of Technology (IUT) as a Lecturer in Department of Computer Science and Information Technology (CIT) and till now he is serving IUT. His major research interests are related to the field of Artificial Intelligence, Wireless Communication & Networking, Ubiquitous Computing.

Sikder Rezwanul Huq has completed his graduation from Islamic University of Technology (IUT) in November 2009. After his graduation he has joined at Stamford University Bangladesh as lecturer of Computer Science department and working to date. His research interest includes Grid Computing, Distributed Systems, Parallel Processing, Sensor Network, Artificial Intelligence etc.

智能汽车技术发展及研究现状

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车辆智能控制技术的研究与应用

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发了Shakey移动机器人,作为人工智能研究工作的试验平台。1973一1981年间由Hans.Moravec在Stanford研究所领导的stanford。art工程则第一次实现了自主驾驶。 进入二十世纪八十年代以后,军方和一些大型汽车公司对自主驾驶技术表现出了浓厚的兴趣。美国军方先后组织了多项车辆自主驾驶的研究项目,其中包括DARPA的ALV项目,DARPA的DEMo一H计划、DEMo一111计划等。这一系列的研究都试图将自主驾驶技术使用到军事上去,以提高部队战斗力。其它包括英国、法国、德国等在内的一些国家 也都在进行自主驾驶技术在军事使用领域的相关研究。大型汽车公司则更加注重汽车自主 驾驶研究,以期提高汽车性能。 然而直到二十世纪九十年代前期,有关研究主要由大学联合有关公司进行。其中比较成功的有: (l)德国慕尼黑国防军大学所进行的vaMoRs和vaMP自主驾驶汽车研究。 (2)美国卡耐基一梅隆大学的Navlab系列自主驾驶汽车研究。 (3)美国加州理工大学的PAI,H研究群体。 (4)意大利帕尔玛大学的ARGO自主车样车。 其它包括法国、日本等都在开展自主驾驶汽车的研究工作。 国内关于自主驾驶汽车的研究,是二十世纪八十年代末期开始的,已取得了令人鼓舞的研究成果。 国防科学技术大学1991年研制的汽车自主驾驶系统实现了低速自主驾驶。2000年,以BJ2020为平台的自主驾驶汽车实现了75.6km/h的高速公路车道跟踪实验。2003年,由国防科学技术大学和中国第一汽车集团公司联合开发的红旗车自主驾驶系统实现了17Okm/h的高速公路车道跟踪驾驶,并具有了超车功能。该成果标志着中国汽车自主驾驶技术已经达到了国际先进水平。

智能汽车技术与应用

智能汽车技术及应用

智能车辆 绪论 智能车辆是在电子信息技术和其他高新技术基础上发展起来的,它通过智能系统起 到辅助驾驶的作用,使驾驶更为方便,利用多种传感器和智能公路技术实现最终达到无 人驾驶。 智能汽车的产生与发展:对智能车辆的研究始上世纪世纪五十年代初美国一家公司 开发出的世界上第一台自动引导车辆系统。在1974年,瑞典一家轿车装配工厂与 Schiinder-Digitron公司合作,研制出一种可装载轿车车体的AGVS,并由多台该种AGVS 组成了汽车装配线,从而取消了传统应用的拖车及叉车等运输工具。.由于Kalmar工厂采用AGVS获得了明显的经济效益,许多西欧国家纷纷效仿Volvo公司,并逐步使AGVS 在装配作业中成为一种流行的运输手段。20世纪80年代,伴随着与机器人技术密切相关的计算机。 电子、通信技术的飞速发展,国外掀起了智能机器人研究热潮,其中各种具有广阔应用前景和军事价 值的移动式机器人受到西方各国的普遍关注。 智能车辆的研究方向:A:驾驶员行为分析:研究驾驶员的行为方式、精神状态与车辆行驶之间 的内在联系,建立各种辅助驾驶模型,为智能车辆安全辅助驾驶或自动驾驶提供必要的数据,如对 驾驶员面部表情的归类分析能够判定驾驶员是否处于疲劳状态,是否困倦瞌睡等;B.环境感知:主 要是运用传感器融合等技术,来获得车辆行驶环境 的有用信息,如车流信息、车道状况信息、周边车辆的速度信息、行车标志信息等;C.极端情况下的自 主驾驶:主要研究在某些极端情况下,如驾驶员的反应极限、车辆失控 等情况下的车辆自主驾驶;D.规范环境下的自主导航:主要研究在某些规范条件下,如有人为设置 的路标或道路环境条件较好,智能车辆根据环境感知所获得的环境数据,结 合车辆的控制模型,在无人干预下,自主地完成车辆的驾驶行为。E.车辆运动控制系统:研究车辆控制的 运动学、动力学建模、车体控制等问题;F.主动安全系统:主要是以防为主,如研究各种情况下的避障、防撞安全保障系统等;G.交通监控、车辆导航及协作:主要研究交通流诱导等问题;H.车辆交互通信: 研究车辆之间有效的信息交流,主要是各种车辆间的无线通信问题;I.军事应用:研究智能车辆系统在 军事上的应用;J.系统结构:研究智能车辆系统的结构组织问题;K.先进的安全车辆:研究更安全、具 有更高智

中国智能汽车发展研究

内燃机与配件 0引言 美国、 欧洲和日本的智能汽车发展较早,有很多地方值得我国借鉴学习,尤其是日本,早在上个世纪九十年代,日本就建立了一套智能汽车发展策略,即突破智能技术、开放交通信息、建设道路。 有关资料显示,截至2017年底全球的新能源汽车总量已经接近130万辆,这其中有60%左右为中国保有。改革开放以来,中国的汽车工业飞速崛起,而且我国的网络发展迅猛,这为我国的智能汽车发展提供了非常有利的平台。中国的智能汽车发展有优势,也同样存在着诸多制约因素,发展智能汽车将是一场翻天覆地的变革,中国汽车工业发展面临着巨大的挑战。 1中国智能汽车发展制约因素1.1缺少核心技术 中国汽车工业起步较晚, 基础薄弱,很多汽车零部件需要进口,尤其是一些重要的核心总成件也是进口的,这制约着中国汽车工业的发展,同时也制约着中国智能汽车的发展。另外,国外许多车企都拥有二十年以上的辅助驾驶技术研究经验,这也是中国无法与之相比的。 1.2缺少统一标准 中国的汽车工业很多标准都是从国外学习而来的,具有一定的指导作用,但是缺少针对本土环境的进一步的改进。中国的汽车缺少由国家统一制定的标准,使得很多智能汽车制造商只能“闭门造车”。另外,从法律层面上,中国的智能汽车在路面上行驶时也缺乏相应完善的法律约束,没有约束的自由也是相对不安全的,从而使得智能汽车发展缓慢。 1.3安全问题 实现无人驾驶是目前几乎所有智能汽车希望实现的技术,但是随之而来的汽车行驶安全问题和信息安全问题也亟待解决,解决了安全问题,才能大踏步的去发展智能汽车。 1.4道路问题 随着网络的发展,开始涌现出了大批量的网约车,这促进了智能汽车的发展,但是交通管治问题依然存在,汽 车保有量大幅度增加,道路基础设施的建设和管理无法满 足交通需求,交通堵塞问题没有得到很好的解决,从而智能汽车的发展也就受到制约。 1.5缺乏合作精神 中国的智能汽车生产企业,目前已经具备较大的科研团队,拥有先进的研发设备,但是其智能汽车研发模式仅限于自主研发,缺乏与一些网络服务商的密切深度合作,从而制约智能汽车发展。 2解决措施 针对以上制约因素, 我们可以在国家的指导下,完善智能汽车发展的各个环节。 首先,政府应该制定总体战略目标,在加强对交通基础设施投入的同时,鼓励民营资本融入到智能汽车工业中来,发挥政府职能,完善相应管理规范,加快跨行业的创新合作,加快汽车产业成果转化,推动产业发展,建立有利于智能汽车发展的社会环境,力争在新的产业革命中占据有利地位。 其次,应该集合车企、网络通讯企业、国家重点实验室等多方技术,加快智能汽车研发,抓重点,突破技术难题,推动资本运作和产业的结合,翻开智能汽车业新的里程碑。国家也应将智能汽车计划纳入重点发展项目,推动智能汽车业发展。 再次,在汲取国外经验的同时,应该从国家层面制定出针对智能汽车的技术标准,使得智能汽车在研发过程中,有标准可循,还可进一步参与到国际标准的制定中去,引领智能汽车产业发展。另外,要完善智能汽车在路面上行驶的法律规范,使得驾驶智能汽车具有法律约束,从而提高出行保障。 最后,进行道路设施设备规划,提高道路网络覆盖率,加强对汽车网络的监管,保护好个人信息不泄露;提高人、车、路、环境和网络之间的相互联系,加快信息传输速度,实现海量数据传输,使得车辆信息、路况信息能够实时传递,从而这些信息被正确处理并给出相应判断,实现安全驾驶。 3中国智能汽车发展前景 智能汽车领域是一个综合的高新技术领域, 他顺应了时代的发展, 随着汽车业和网络智能的发展,在未来,智能汽车将向着健康、 有序、个性化的方向大踏步迈进。许多车企和零部件供应商,已经将市场转向智能汽车——————— ————————————————作者简介:沈广辉(1993-),男,本科在读,研究方向为交通运输; 郝艺源(1996-),男,本科在读,研究方向为交通运输;冯莉(通讯作者)(1982-),女,讲师,研究方向为交通运输、车辆工程。 中国智能汽车发展研究 沈广辉;郝艺源;冯莉 (沈阳工学院机械与运载学院,抚顺113122) 摘要:汽车工业的飞速发展,大家对汽车的安全性、舒适性提出了更高的要求,伴随着网络技术的进步,智能汽车应运而生,中国 作为汽车大国,其汽车产业发展将迎来新的机遇和挑战。 关键词:智能汽车;中国汽车;发展研究 ·198·DOI:10.19475/https://www.360docs.net/doc/8516128286.html,ki.issn1674-957x.2019.04.094

现代汽车智能控制技术

现代汽车智能控制技术研究 张亮 摘要:针对当前汽车底盘及安全技术发展特点,分析了汽车智能化技术的主要特点和研究现状,探讨了如何应用智能化技术解决汽车工业发展中的关键技术,并提出了未来汽车的发展方向。 Abstract:This report makes a conclusion of the functions of automobile intelligence and discusses how to use intelligence to solve the safety and congestion problem in automobile industry. During the process to driving without person, we put forward to an imagination that we can achieve driving with no person in addition to computer memory system and sense system under designated environment. 引言 汽车发展到至今,已不再是一个单纯的庞大机械系统,而是集电子控制、液压、环境感知、规划决策、高技术通讯等功能于一体的智能化综合系统,汽车技术的发展,综合体现了当今计算机科技、现代化传感技术、信息融合通信、自动控制及人工智能等技术的研究情况,是典型的高新技术综合体。 美国,日本,欧洲部分发达国家多年来一直致力于汽车智能化技术的发展,伴随着上世纪70年代以后微电子技术的飞速发展,汽车智能化的推进也加速至一个新的阶段,现如今,对汽车智能化的研究已成为汽车行业的一大热点。

(完整版)智能小车的研究背景及意义

1.1本课题的研究的背景以及现实意义 目前,在企业生产技术不断提高、对自动化技术要求不断加深的环境下,智能车辆以及在智能车辆基础上开发出来的产品已成为自动化物流运输、柔性生产组织等系统的关键设备。世界上许多国家都在积极进行智能车辆的研究和开发设计。移动机器人是机器人学中的一个重要分支,出现于20世纪06年代。当时斯坦福研究院(SRI)的Nils Nilssen和charles Rosen 等人,在1966年至1972年中研制出了取名shakey的自主式移动机器人,目的是将人工智能技术应用在复杂环境下,完成机器人系统的自主推理、规划和控制。从此,移动机器人从无到有,数量不断增多,智能车辆作为移动机器人的一个重要分支也得到越来越多的关注。智能小车,是一个集环境感知、规划决策,自动行驶等功能于一体的综合系统,它集中地运用了计算机、传感、信息、通信、导航及白动控制等技术,是典型的高新技术综合体。 智能车辆也叫无人车辆,是一个集环境感知、规划决策和多等级辅助驾驶等功能于一体的综合系统。它具有道路障碍自动识别、自动报警、自动制动、自动保持安全距离、车速和巡航控制等功能。智能车辆的主要特点是在复杂的道路情况下,能自动地操纵和驾驶车辆绕开障碍物并沿着预定的道路(轨迹)行进。智能车辆在原有车辆系统的基础上增加了一些智能化技术设备: (1)计算机处理系统,主要完成对来自摄像机所获取的图像的预处理、增强、分析、识别等工作; (2)摄像机,用来获得道路图像信息; (3)传感器设备,车速传感器用来获得当前车速,障碍物传感器用来获得前方、侧方、后方障碍物等信息。 智能车辆技术按功能可分为三层,即智能感知/预警系统、车辆驾驶系统和全自动操作系统团。上一层技术是下一层技术的基础。三个层次具体如下: (1)智能感知系统,利用各种传感器来获得车辆自身、车辆行驶的周围环境及驾驶员本身的状态信息,必要时发出预警信息。主要包括碰撞预警系统和驾驶员状态监控系统。碰撞预警系统可以给出前方碰撞警告、盲点警告、车道偏离警告、换道/并道警告、十字路口警告、行人检测与警告、后方碰撞警告等.驾驶员状态监控系统 2 包括驾驶员打吨警告系统、驾驶员位置占有状态监测系统等。 (2)辅助驾驶系统,利用智能感知系统的信息进行决策规划,给驾驶员提出驾驶建议或部分地代替驾驶员进行车辆控制操作。主要包括:巡航控制、车辆跟踪系统、准确泊车系统及精确机动系统。 (3)车辆自动驾驶系统,这是智能车辆技术的最高层次,它由车载计算机全部自动地实现车辆操作功能。目前,主要发展用于拥挤交通时低速自动驾驶系统、近距离车辆排队驾驶系统等。 这种智能小车的主要应用领域包括以下几个方面: (1)军事侦察与环境探测 现代战争对军事侦察提出了更高的要求,世界各国普遍重视对军事侦察的建设,采取各种有效措施预防敌方的突然袭击,并广泛应用先进科学技术,不断研制多用途的侦察器材和探测

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