Design of an Automatic Vehicle Speed Limit Notification and Warning System 1
Thandiwe E Mashayahanya, 1Powell Mlambo, 1Eugenia R Chiweshe, 2Rumbidzai Muvunzi ,1Michael Matingo 1
Department of Mechatronic Engineering School of Engineering Sciences and Technology Chinhoyi University of Technology 2
Department of Production Engineering School of Engineering Sciences and Technology Chinhoyi University of Technology
[email protected] Abstract. Over the past decades researches has been undergoing with intentions of improving people’s travelling experiences. From a larger perspective, the community is looking for Intelligent Transportation Systems (ITS) to enhance safety and efficiency of physically limited road systems. Road system units such as speed limit signs are erected with intentions of notifying drivers the maximum speed within a particular zone. However, drivers are frequently violating traffic rules by speeding as a result of ignorance, and bad driving behavior. This paper presents the design of an automatic vehicle speed limit notification and warning system with intentions of improving traffic safety. Outlined are the design steps followed in coming up with the proposed system. Three main modules were designed for the system: the Road Side System (RSS), Wireless Communication Link (WCL) and an In-Vehicle Embedded Device (IED). The designed RSS consists of a digital display using LED technology and a vehicle detection unit. The transmission channel was also modeled, channel propagation effects investigated and it was observed that reliable signal transmission could be achieved 100m from the RSS. We conclude that an inside the vehicle display system coupled with a voice signal can greatly improve road safety by addressing limitations associated with looking at road sign speed limits and therefore improving the safety of all road users. Further work is required to operationalize this system. Keywords: wireless vehicular communication, embedded systems, intelligent transportation system, automatic vehicle speed limit
1 Introduction Road accidents are claiming many lives with statistics indicating that around 1.3 million people are dying yearly with 90% of these deaths occurring in low and middle income countries (Midzi 2014). Investigations within Zimbabwe (a developing country) also shows that the major causes of accidents within the country include: bad state of roads, speeding, drunken driving, fatigue, bad driver attitude, use of cell phones whilst driving and going through red robots. According to a publication by the U.S. Department of Transportation, National Highway Traffic Safety Administration, speeding is reported as a driver-level attribute that combines “driving too fast for conditions" or "in excess of posted speed limit” (Liu & Chen 2009). In fatal crashes, about 55 percent of all speeding-related crashes were due to exceeding the posted speed as compared to the 45 percent that were due to driving too fast (Liu & Chen 2009). It has found that, in urban areas, the risk of a casualty crash is doubled for each 5km/h over the limit. (Michae, David & Ian 2009).
Therefore, a number of researches on ITS and vehicle communications for the purpose of safe driving have attracted much attention from car manufacturers, road operators, and standardization bodies. (Zeinab et al. 2013) (Pavle et al. 2009). To aid drivers, state of art vehicles such as the BMW 7 series have been developed with Advanced Driver Assistance systems such as the one designed by Mobileye, a vision-based driver assistance system which has capabilities of relaying speed limit information to the driver (Geissler 2008). Such systems consist of highly dynamic range of cameras and high performance chips which can cater for the computational requirements of intensive visual interpretations. Other intelligent systems make use of a combination of global positioning systems and digital maps to provide to the driver with information on speed limits in particular regions. Such systems can be cost prohibitive with artificial visionbased recognition also being prone to failure in cases of poor visibility (insufficient light, difficult weather conditions or blocking of the line of sight by preceding vehicles) and digital maps need to be fully dynamic so that unexpected road changes would not result in incorrect information being relayed (Ankita et al. 2012). Such problems which are related to a single, isolated automotive vehicle and its subsystems, leads the research community into exploring the “big picture” of intelligent road transportation systems—a system, or system of systems, consisting of many vehicles and their drivers interacting on roads. (Samad & Annaswamy 2011). The idea is for vehicles, roadside infrastructure (roads and highways), and back-end (telecommunications and Internet backbones) to work together. This could be through Vehicle-to-Vehicle (V2V), Infrastructure-to-Vehicle (I2V), Vehicle-to-Infrastructure (V2I) and Vehicle-to-Device (V2X) (any wireless device). In I2V, generally the infrastructures plays a management role of gathering global or local information on traffic and road conditions and then suggests or impose certain behaviors on a group of vehicles (Samad & Annaswamy 2011). However, challenges are being faced when it comes to ensuring timely and reliable communication amongst vehicles and infrastructure elements in the development and deployment of I2V systems (Michae, David & Ian 2009). 2. System Development The proposed design is divided into the following parts.
The Road Side System Wireless communication link In vehicle embedded device
2.1 The Road Side System (RSS) The RSS is designed in such a way that a vehicle is detected, its speed calculated at a distance that accommodates both slow moving vehicles and fast moving vehicles with the speed being display on an LED display. The 18F4550 microcontroller is used in this design because of it large flash memory of 32KB and low cost. The microcontroller is programmed using MikroC which is a number of libraries hence simplifying the programming process. In Figure 1, the block diagram of the RSS is shown.
Figure 1 Road Side System 2.1.1 LED Display Unit LED displays comprises of LEDs organized in matrices to make effective use of resources. In a matrix the LEDs are organized in rows and columns. To localize the LED matrix, a method called multiplexing is used for displaying images, such that a single row and column of the LED array may be activated at any time. This was achieved through the use of an LED –driver, the MAX7219. Communication between the microcontroller and MAX7219 was achieved via Serial Peripheral Interface (SPI). 2.1.1.1 The Display Process To demonstrate the functionality of the LED matrices a program for displaying the American Standard Code for Information Interchange (ASCII) characters (0-9, A-Z, a-z, etc.) was written. The information for all printable ASCII was stored in a 2-dimensional character array. The Figure 2 shows the active LEDs in each column to display the character ‘A’ in an 8x8 dot-matrix format. This is the basic building block for the display unit.
Figure 2 Schematic of character ‘A’ displayed on an LED matrix To increase the size of the display unit the LED matrices are cascaded together. The character values were generated from an Excel sheet. This procedure was carried out for displaying a character on a single matrix up to displaying on four 8X8 matrices with the drivers having been cascaded. Figure 3 shows how the character ‘A’ code is generated for display on four matrices (16x16 display unit).
Figure 3 Letter ‘A’ being generated in excel 2.1.2 Vehicle Speed Detection For vehicle speed detection, the choice of the sensor is such that it can be mounted by the road side and can detect a speeding vehicle (for example 200km/hr ) at a distance that enables the system to display an appropriate message enabling the driver to read it on the display. It must be noted however that in developing the prototype for demonstration purposes, vehicle detection was achieved through the use of an ultrasonic sensor which trigger a timer to start when a vehicle is at distance X meters from the RSS and stopping the timer when it is at distance Y meters away. Dividing the distance (X-Y) meters by the time taken gives the speed the vehicle is travelling. The observed speed and related message is then displayed and transmitted to the IED. 2.2 Infrastructure-to-Vehicle Communication In order to communicate to driver the relevant message about their speed, the road side sensor sends a signal wirelessly to the vehicle. The message is sent in data form and will be decoded by the vehicle’s converter so that it can be converted to voice. This is done because the human brain responds better to audio stimuli than to visual. The message has to be sent to only one vehicle thus a communication link is established between the transmitter and receiver first and will be maintained until it has been confirmed that the message has been transmitted. To this end, the signal is sent over the 5.9 GHz band using the Dedicated Short Range Communication (DSRC) technology. The DSRC was developed by the Institute of Electrical and Electronics Engineers (IEEE) for communication on the roads. It is an amendment to the standard IEEE 802.11a, also known as Wifi, which was adapted for vehicular communication and known as Vifi. The DSRC standard, IEEE802.11p, was designed for Wireless Access for Vehicular Environments (WAVE). It consists of seven, 10 MHz channels in the 5.9GHz band. Because of the environment where the transmission is occurring, several channel propagation effects were taken into consideration when selecting the transmitter and receiver. Firstly, the channel in the vehicular environment is prone to fast fading. Because of the LOS component between the vehicle and RSU, a Ricean fading channel model is used. This model with variance σ has probability density function (Gozalvez, Sepulcre & Bauza 2011).
𝒙
𝒇(𝒙, 𝝈) = 𝝈𝟐 𝒆−𝒙
𝟐 ⁄𝟐𝝈𝟐
Equation 1
if the transmitter and receiver have a dominant line of sight between them. It was also noted that communication is between a moving object and a stationary road side unit. Thus Doppler Effect was also considered in designing the communication channel. The shift is given by; ∆𝒇 =
−𝑽𝒔,𝒓 𝒇𝟎 𝑪
Equation 2
Where 𝑉𝑠,𝑟 is the transmitter (source) velocity minus the receiver velocity , 𝑓0 is the frequency of the signal and C is the speed of the waves. There is also attenuation of the signal due to distance between the transmitter and receiver, known as path loss. Several models are suggested in literature to model path loss. In this paper we shall consider the two models that we found to be most appropriate to the given situation. The Two- Ray ground model is employed for LOS conditions and is widely used for vehicular environment simulations such as in (Alshaer & Horlait 2005). It is given by: 𝝀𝟐
𝟏𝟎𝑳𝒐𝒈𝟏𝟎 (𝒅𝟐(𝟒𝝅)𝟐) 𝒊𝒇𝒅 < 𝒅𝒄 𝑷𝑳 = { Equation 3 𝒉𝟐 𝒉𝟐 𝟏𝟎𝑳𝒐𝒈𝟏𝟎 ( 𝒅𝑨 𝟒 𝒃 ) 𝒊𝒇𝒅 ≥ 𝒅𝒄 and 𝒅𝒄 =
𝟒𝝅𝒉𝑨 𝒉𝑩 𝝀
Equation 4
Where d is the distance between the transmitter and the receiver ℎ𝐴 and ℎ𝐵 are the transmitter and receiver antenna heights respectively. However, this model is too simple and differs very little from the general path loss model. (Gozalvez, Sepulcre & Bauza 2011), suggest that the use of the WINNER model (Dopart 2014). This model distinguishes the difference between LOS and non-line of sight (NLOS) conditions. It also assumes antenna heights of 5m and 1 m, a situation that is consistent with our design. Thus, this paper considers the winner pathloss model, which is given by:
PLOS
22.7 log10 (d a [m]) 41 20log10 ( f [GHz ] / 5) if d a Rbp 40log10 (d a [m]) 41 17.3log10 ( Rbp ) 20log10 ( f [GHz ] / 5) if d a Rbp
Equation 5
Where: Rbp 4
(ha 1)(hb 1)
Equation 6
ha and hb are the antenna heights for vehicle a (Transmitter) and vehicle b (Receiver) in meters. d a is the distance from the transmitter to the receiver in meters Rbp is the break point distance in meters λ is the wavelength in meters. The shadowing is modeled following a lognormal distribution with standard deviation 𝜎 assumed to be equal to 5dB and zero mean. With all this information, simulations were done to determine the reliability of the message sent. Figure 4 below shows the graph obtained when the channel propagation effects were incorporated and Signal to Interference and Noise Ratio (SINR) was measured for different distances. From the graph it can be seen that over a distance of 100m, the SINR dropped by only about 0.08 dB. Thus, the channel selected causes minimum drop of SINR as distance is increased. Therefore the signal in such a situation can be transmitted reliably.
SINR (dB)
5 4.98 4.96 4.94 4.92 70
75
80
85 Distance (m)
90
95
100
Figure 4: SINR obtained at different distances (DBPSK modulation, transmit power= 1 W) 2.2.1 Latency of Transmission It is important that the time taken for the transmission of the signal be minimal. In this paper, we came up with an algorithm to ensure that the driver receives the signal in time to brake. For example, assuming a driver reaction of R seconds, if the driver is travelling at V1 m/s, and is D m from the sign, while the recommended deceleration of De m/s is recommended and the final velocity should be V2 m/s, then the driver will take time t=R+V1-V2/De to decelerate to velocity V2.
2.3 In-Vehicle Embedded Device
LCD Display
Unit
RF Reciver
Microcontroller
The IED constitutes of a RF receiver, voice recording and playback device (for example APR 9600), microcontroller and an LCD display.
Playback device
Figure 5 In vehicle embedded device
Figure 6 Schematic of IED
As the vehicle passes the RSS and appropriate message is receive with the driver being alerted on his speed through a voice, beeping sound and flashing LEDs. 4. Conclusion In this paper the process of designing the hardware and testing the prototype were discussed. Here by from the theory presented it can also be noted that the project implementation is feasible on the current system and is low cost and durable, enhancing safety to passengers and the public. It should be noted that this proposed design can be incorporated with Global System for Mobile communication (GSM) modules for remote notification of law enforcement agencies of drivers’ behavior thereby enhancing the system functionality. Future work will also have to focus on automatically adjusting the vehicle speed to suit the required zone limit. 5. Acknowledgements The authors would like to acknowledge the members of the Department of Mechatronics in providing helpful suggestions and feedback in the writing of this paper. A special also thanks goes to Moseline Nhengo for her support during the writing of this paper. References Alshaer, H & Horlait, E 2005, 'An optimized adaptive broadcast scheme for inter-vehicle communication', In Proceedings of IEEE vehicular technology conference VTC spring , pp. 2840– 2844. Ankita, M, Jyoti, S, Harshala, BP, Saxena & Pranav, P 2012, 'Design of RF based speed control system for vehicles', International Journal of Advanced Research in Computer and Communication Engineering, vol 1, no. 8, pp. 583-586. Dopart, K 2014, 'Vehicle-to-Infrastructure (V2I) Communications for Safety', http://www.its.dot.gov/factsheets/v2isafety_factsheet.htm. Geissler, N 2008, 'Combined Technologies from Continental and MobileyeSupport the New Speed Limit, Information of the New BMW 7 Series', External Communications, Continental, Frankfurt am Main, Germany. Gozalvez, J, Sepulcre, M & Bauza, R 2011, 'Impact of the radio channel modelling on the performance of VANET communication protocols', Telecommunication Systems, Springer. Liu, C & Chen, C-L 2009, 'An Analysis of Speeding-Related Crashes:Definitions and the Effects of Road Environments', National Technical Information Service, Springfield, Virginia 22161, Washington DC. Michae, LP, David, P & Ian, F 2009, 'SPEED LIMITING TRIALS IN AUSTRALIA'. Midzi, E 2014, 'First Report Of The Portfolio Committee On Transport And Infrastructural Development On The Causes Of Road Carnage', Parliament Of Zimbabwe, Harare. Pavle, B, Danilo, V, Alexander, P, Thomas, Z, Fabio, R & Christoph, M 2009, 'On Wireless Links for Vehicle-to-Infrastructure Communications', IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY.
Samad, T & Annaswamy, AM 2011, 'The Impact of Control Technology', The Impact of Control TechnologyThe Impact of Control Technology. 'WINNER consortium' 2007, WINNER II channel models. WINNER European Research project Public Deliverable. Zeinab, T, Hamide, K, Masoud, B, Mehri, M & Javad, AS 2013, 'Received Signal Strength Estimation in Vehicle-to-Vehicle Communications Using Neural Networks', International Journal of Digital Information and Wireless Communications, pp. 42-47.
