INTRODUCTION
Road fatalities are a major concern in the developed world. Recent studies show that a third of the number of fatal or serious accidents are associated with excessive or inappropriate speed, as well as changes in the roadway (like the presence of road-work or unexpected obstacles). Reduction of the number of accidents and mitigation of their consequences are a big concern for traffic authorities, the automotive industry and transport research groups. One important line of action consists in the use of advanced driver assistance systems (ADAS), which are acoustic, haptic or visual signals produced by the vehicle itself to communicate to the driver the possibility of a collision. These systems are somewhat available in commercial vehicles today, and future trends indicate that higher safety will be achieved by automatic driving controls and a growing number of sensors both on the road infrastructure and the vehicle itself.
A prime example of driver assistance systems is cruise control (CC), which has the capability of maintaining a constant user-preset speed, and its evolution, the adaptive cruise control (ACC), which adds to CC the capability of keeping a safe distance from the preceding vehicle.
A drawback of these systems is that they are not independently capable of distinguishing between straight and curved parts of the road, where the speed has to be lowered to avoid accidents. However, curve warning systems (CWS) have been recently developed that use a combination of global positioning systems (GPS) and digital maps obtained from a Geographical Information System (GIS), to assess threat levels for a driver approaching a curve too quickly; likewise, intelligent speed assistance (ISA) systems warn the driver when the vehicle’s velocity is inappropriate, using GPS in combination with a digital road map containing information about the speed limits.
However useful, these systems are inoperative in case of unexpected road circumstances (like roadwork, road diversions, accidents, etc.), which would need the use of dynamically-generated digital maps. The key idea offered by this paper is to use Radio Frequency Identification (RFID) technology to tag the warning signals placed in the dangerous portions of the road. While artificial vision-based recognition of traffic signals might fail if visibility is poor (insufficient light, difficult weather conditions or blocking of the line of sight by preceding vehicles), RF signals might still be transmitted reliably.
In the last years, RFID technology has been gradually incorporated to commercial transportation systems. A well-known example is the RFID-based highway toll collection systems which are now routinely employed in many countries, like the Telepass system in Italy or the Autopass system in Norway. Other uses include monitoring systems to avoid vehicle theft, access control to car parking or private areas, and embedding of RFID tags in license plates with specially coded IDs for automatic vehicle detection and identification. Placement of RFID tags on the road lanes has been proposed in order to provide accurate vehicle localization in tunnels or downtown areas where GPS positioning might be unreliable. In the work by Seoet al., RFID tagging of cars is offered as an alternative to traffic data collection by inductive loops placed under the road surface. The information about the traffic collected by a network of RF readers is then used to regulate traffic at intersection or critical points in the city. The work by Sato et al.describes an ADAS, where passive RFID tags are arranged in the road close to the position of real traffic signals. An antenna placed in the rear part of the car and close to the floor (since the maximum transmitting range of the Sensors tags is about 40 cm) permits reading of the information stored in the tag memory and conveys a visual or auditive message to the driver. Initial tests at low driving speeds (20 km/h) show good results.
The work described in this paper is a collaboration between AUTOPIA (Autonomous Vehicles Group) and LOPSI (Localization and Exploration for Intelligent Systems), both belonging to the Center for Automation and Robotics (CAR, UPM-CISC).
This information is collected in real time by RFID sensors placed onboard of the vehicle (an electric Citroën Berlingo), which we have modified to automatically change its speed to adapt to the circumstances of the road. In particular, we have implemented a fuzzy logic control algorithm acting on the longitudinal speed of the vehicle, with actuators which control the vehicle’s throttle and brake to reach and maintain a given target speed.
Rates of accidents and other road hazards are continually on the increase even with the interventions of road safety laws and regulations. This therefore served the need for an automated vehicle speed control system. To get an efficient speed control system many factors are to be considered ranging from
All to ensure the presence of active traffic signals and Radio Frequency Identification (RFID)sensor system.
1.2 PURPOSE OF STUDY
The main purpose of this research work is to design and simulate a vehicle speed control system.
The aim and objective of the system to be designed is superior in the sense that all the tasks related to driving are automated and secure. The driver just has to sit back and enjoy the ride.
This system has a large number of advantages:
1) Smooth traffic flow due to lane driving.
2) Speed is maintained at a constant 30 km/h. The speed is fast enough for travelling and slow enough for the driver to escape unhurt in a highly unlikely accident.
3) Driving for the physically challenged.
4) Transport of goods and personnel in sensitive areas like nuclear stations, military installations, industrial hazard-areas or even in large companies
5) Tireless driving devoid of the stress involved in long distance driving
6) Accident prevention due to automatic collision control
7) Only a few components are added to get all these extra advantages
8) Extremely cost effective
9) Easily implementable as the parts required are available in any garage
These above objectives shall be accomplished through a sensor system built for infrastructure to vehicle (I2V) communication, which can transmit the information provided by active signals placed on the road to adapt the vehicle’s speed and prevent collisions. By active signals we mean ordinary traffic signals that incorporate long-range active RFID tags with information stored into them.
The scopeof this research work is purely based on design and simulation of a vehicle speed control system. This shall be done using various concepts that would make the project simulation implementable.
This project will be limited to the data available at hand, data outside the researcher will not be made use of.
The limitations militating against this research are financial constraints, time factor and other circumstances.
We use intelligent instruments in every part of our lives. It won’t take muchtime that we realize that most of our tasks are being done by electronics. Very soon, aswe shall see, they will perform one of the most complicated tasks that a person does in aday, that of driving a vehicle.
This is for the better. As the days of manned driving are getting extremelynumbered, so are those of traffic jams, bad, dangerous and rough drivers and moreimportantly, accidents. According to Mr. Willie D. Jones in the IEEE SPECTRUMmagazine (September 2001), a person dies in a car crash every second. Automation ofthe driving control of two-wheelers is one of the most vital need of the hour.
Advanced driver assistance systems – ADAS
Cruise control – CC
Adaptive cruise control – ACC
Curve warning systems – CWS
Geographical Information System – GIS
Intelligent speed assistance – ISA
Radio Frequency Identification –RFID
GSM, GPS, GSM, GNSS, Windows phone OS, GPRS