Smart Cruise Control System with Stop&Go and Predictive Road Mapping

Adil EL Rharbali, Hamza Bousfiha, Manal Hasri, Yassine Salih-Alj School Of Science and Engineering

Al Akhawayn University Ifrane, Morocco

{a.elrharbali, ha.bousfiha, m.hasri, y.salihalj}@aui.ma

Abstract—There is an increase need for advanced tools to support the next generation of automotive application. Hence, the development of the transportation field calls new technologies all gathered under ITS: Intelligent Transportation Systems. This paper gives an approach to ITS by introducing the Smart Cruise Control System (SCCS). This system combines the Stop&Go feature to the predictive one, all while maintaining the basic functions of an adaptive cruise control. SCCS suggests predictive speed adjustment and map reading from GPS data, in addition to the regulation of the security distance to the road conditions. The results obtained from this research show significant reduction of fuel consumption and an increase of traffic safety.

Keywords-ACC, Intelligent transportation system, Stop&Go, Predictive Cruise Control, Longitudinal Controllers, Fuel consumption.

I. INTRODUCTION During the last few decades, modern societies have been

suffering from problems due to the increase of on road traffic that created a congested network and has a negative impact on traffic safety, energy consumption, and air pollution [1].

The emergence of Intelligent Transportation Systems (ITS) tries to overcome these lasts by applying telematics and robotic technologies and techniques to reach safe driving since this could lead to innovative systems that could contribute to the problems encountered. Intelligent transportation systems support the driver in his tasks while increasing the driver’s safety and comfort, in addition they can have a positive impact on traffic flow and reduce gas emissions and fuel consumption. An advanced driver assistance system that is widely used in automotive industry is the Adaptive Cruise Control (ACC) [2].

Unlike the conventional cruise control that adjusts the speed of the car to a predetermined speed fixed by the driver, ACC can automatically adjust the selected speed and change it to match that of a preceding vehicle and to maintain a proper headway distance or gap between vehicles in the same lane [3]. This is achieved through a radar headway sensor, digital signal processor and a speed controller. The system sends a signal to the engine or the braking system to decelerate when approaching a vehicle with a lower speed or if another object is detected. Then, it re-accelerates to the level of previously set speed when the vehicle upfront accelerates or changes the lane. Previous research demonstrated that ACC significantly improves traffic conditions [4].

Cruise Controls systems were first introduced in 1995; Toyota, Jaguar, Mercedes, Lexus, and BMW have introduced them as an optional device for luxury vehicles [7]. During heavy traffic conventional cruise control has some limitations, it is operational starting a threshold speed (30 to 40 km/h) and it fails at lower speeds and when the preceding vehicle stops. Stop&Go systems control the throttle in this tedious situation during traffic jam where rear-end collisions are common because of slow response in low speed driving. Stop&Go systems are being introduced to automate the maneuver of repeated acceleration and deceleration. In addition, the introduction of Predictive Cruise Control (PCC) based on topographic road data reduces fuel consumption and enhances speed management of the vehicle. The combination of ACC with Stop&Go and PCC increases driving comfort, and smoothes traffic speed [5], [6].

The objective of this paper is to enhance ACC by adding Stop&Go and the Predictive features using a one central control unit to synchronize data from these last two technologies and the sensor fusion technology. This paper is organized as follow: in section II we introduce the System Definition and Architecture; in section III and IV we discuss the main features included in our SCCS; then in section V, we explain the technologies used. Finally, a schematic is provided for our suggested system, with an evaluation of the fuel consumption.

II. SYSTEM DEFINITION AND ARCHITECTURE

The main function of any cruise control system is to automatically control the vehicle’s speed, throttle and brake. The way this is actually done is through range sensors that relatively measure the velocity of two successive vehicles. Depending on the behavior of the preceding vehicle, the system detects its speed and decides whether to maintain the speed set by the driver by controlling the throttle, brake in case the vehicle is too close, or maintain the headway time.

The safety distance that should be kept between the two

vehicles is calculated using equation (1):

. (1)

where v is the velocity of the vehicle, T is the response time of the ACC to detect the retardation of the preceding vehicle, and d is the headway from the preceding vehicle.

Adaptive cruise control systems are composed of distributed systems using common Electronic Control Units (ECU) [8], each of which is a module that controls a specific component of the

978-1-4673-2617-9/12/$31.00 ©2012 IEEE

 

vehicle (engine, brake), plus one that is composed of the range sensor and the controller.

The architecture of an adaptive cruise control system can be

divided into four parts: 1. Signal collecting (SC): The switch control activates the

ACC system if the switch is ON and the driver has set up the speed and time. Then, the range sensors identify the preceding vehicles. If the switch button is pressed to the OFF position or either the brake pedal or the acceleration pedal is pressed by driver, the switch control module turns off the ACC system. Sensors are the fundamental components for signal collecting.

2. Signal processing (SP): In case the preceding vehicle is far, the speed control module is active and the vehicle runs in the velocity control state [8]. However, if they are close then the preceding vehicle module is selected and activates the distance control module. This is done through digital signal processors.

3. Signal actuating (SA): once the speed control module is activated, it controls the engine control module. On the other hand, the distance control module controls the brake and throttle control modules (transmission control module is an option in both cases).

4. Signal displaying (SD): When the system is operating, the control indicator displays the operating state (velocity control state or distance control state). The buzzer calls for the driver’s intervention in case the deceleration is insufficient, whereas the brake lamp turns on when the driver is braking or the brake control activated.

III. STOP&GO FEATURE

ACC as presented before highly increases the comfort and safety of drivers in steady flow traffic. However the system is not of much usage when driving in the packed metropolitan roads where speed is reduced and traffic is usually bumper to bumper with frequent stops and starts. As suggested in the introductory section, our SCCS will incorporate a Stop&Go function that will improve the driving conditions in metropolitan areas. The system will guarantee, as a normal ACC would do, that the car will remain at a preset distance from the next car, yet when the traffic gets slower and the car ahead stops, it will reduce the speed of the car and if necessary stop it. Then if traffic starts flowing again and the vehicle ahead moves, the system will increase the speed gradually and up to the predefined speed.

For the development of such feature, the study of the physics

applied on the car and the engine behavior in metropolitan areas is indispensable. First of all, the engine will turn at low rotational speed (up to 25,000 rotation/min). Second, the drag forces applied on the car are different and must be considered all together whether they are aerodynamic forces or rolling frictions. In addition, it is very difficult to keep a fixed distance with the next car, since it frequently starts, accelerates, decelerates or stops which produces a disturbance for the radar transponder.

Finally, the cruise control system should be able to deal with stationary targets. Therefore, the same models used in developing both conventional cruise control and adaptive cruise control are no more applicable. The creation of models capable of discerning the additional complexity that the stop and go (SG) feature added has interested many researchers. In summary, the literature about SG cruise control tackles this issue by developing algorithms that control longitudinal distance by dividing it into upper and lower levels of controllers [9].

To be able to model the SG feature of the SCCS we need to be

able to track the relative distance and speed within a desired value. Therefore, the implementation of the stop and go feature will pass through a precise depiction of the attributes related to sensors, actuators and controllers.

A. Stop and Go Sensors:

Information derived from appropriate detection of vehicle environment is very important to develop a good SG feature. The levels of sensing regarding dynamics of the vehicle and surrounding ones are higher than in regular ACC. For SG, the system will need to integrate multiple sensors that will be connected to each other and able to detect with precision all type of vehicles in the forward and adjacent lanes. Sensors will have to be efficient especially in short ranges up to 30 meters and lateral detection in order to track vehicles even in light curves and adjacent lanes.

In order to meet these prerequisites, the SG system will combine different sensors using different sensing technologies with overlapping detection ranges. This combination of sensors as described by Fig.1 will have multiple advantages.

Figure 1. Multiple-target tracking and sensor fusion concept

First, it will enable fast object detection through the combination of redundant information coming from all types of sensors. Second, it minimizes the occurrence of un-synchronized data and tracking errors due to bad weather conditions and other disturbance sources. It also procures a framework for detecting signal drops or sensors malfunctioning. Finally, the sensing system will include a filter that will assure the continuity of signal coming from all sensors.

B. Stop and Go controllers

Sensory arrangements as discussed above will provide the system with accurate information about location and velocity of a relative vehicle. This information will need to be translated by

 

a controller in order to assess threats and produce the adequate car behavior. This control is exerted through the activation/deactivation of acceleration and braking systems in order to meet the driver’s preset settings for velocity, headway and braking. In this system we develop a safe, consistent and predictable control model based on speed control and distance control.

The distance control is able to maintain a specified or safe distance from preceding vehicle by determining the command variables. These command variables express the behavior of the vehicle in terms of acceleration, speed and headway as a function of time. Of course this controller is subjected to some constraints. The first one is that it has to be done within a small time span because vehicle users will not accept that the SG takes too much time to respond. The second consists of stopping the vehicle at a human acceptable boundary even though the system sensors are capable of cm-accuracy.

As in [11], we opt for a controller which meets many of the requirements mentioned above and subject to the constraints we mentioned before:

∆ ∆

where is the desired vehicle acceleration in m/s2, ∆ is the difference between of velocities the preceding and the equipped vehicle in m/s, ∆ represents the headway error in m

∆ (3)

where is the desired headway. The parameter represents dumping and is the stiffness. is the disturbance acceleration that is due to road slopes, wind friction and uncertainties of parameters.

There is a linear relationship between the desired headway and the vehicles speed that can be expressed as:

(4)

with being the headway time is seconds and the minimum vehicle distance at zero speed in meter either predefined by driver or =1.5m by default. We can then express the vehicle’s acceleration as

(5)

By combining (2) and (5) we can derive the modeling function for our distance controller; the distance error ∆ can be then derived as follows:

∆ ∆ ∆ (6)

We realize that our model is dependent on the acceleration of the preceding vehicle since is still present in (6). This model is appropriate for several traffic situations and can be adjusted by assigning the parameters and in a correct manner.

C. Stop and Go actuators:

For the development of the SG feature in our SCCS, no additions are required for the actuators used in ACC. The basic throttle and brake controlling systems influence the dynamics of the vehicle. The acceleration and deceleration of the vehicle are to be altered so that they fit and respond to the Stop and Go circumstances. E.g. deceleration levels will need to be up to 5m/s2 while it was only 2.5m/s2 for ACC.

IV. PREDICTIVE CRUISE CONTROL

One interesting and innovative feature that can be considered in the development of ACC systems and that would optimize their utility in terms of safety, assistance and fuel economy is the consideration of topography. Exploring the possibilities of combining GPS data with vehicle control systems will provide information about future road curves and gradients ahead of time, and thus allow predicting future longitudinal load. This information will help optimizing control signals and reducing fuel consumption.

The idea behind developing a predictive cruise control is to allow velocity adjustments according the route topography. As any cruise control system, the driver should be able to set up the velocity to a certain reference level; however, changes in the slope of the road may lead to deviations in these references. A predictive cruise control could be used to recalculate the target speed within a maximum and minimum speed range.

To illustrate this feature, let’s consider a vehicle that is set to a constant velocity. When a downhill slope is detected (slope < -threshold), the velocity could be lowered, which would save fuel and reduce braking, instead of accelerating to a velocity exceeding the preset speed. If, on the other hand, an uphill slope is sensed (slope > threshold), the control system will accelerate before reaching it, and without braking, the vehicle is decelerated gradually at a crest, if a downhill follows, or simply to reach a demanded speed level. These features can be implemented using an algorithm that takes as an input the comparison between the slope ahead and the threshold slope and affect the fuel consumption by reducing time spent on lower gears.

The operation of a predictive cruise control starts by receiving input signals from the GPS about the actual position of the vehicle. A predictive distance is set up and used in order to trace the reference trajectory that the car will follow. Using this trajectory and the predictive distance, the next reference position can be determined. The GPS provides the control system with the current speed of the vehicle that is used to calculate the next position. The controller uses the difference between the actual and next position to determine the height at the next reference position and thus calculates the gradient.

 

In order to get accurate results as for the calculations of the distance on earth, a function known as the Great Circle Distance Formula is used:

arccos sin 1 sin 2 cos 1cos 2 cos 2 1 (7)

where is the radius of the earth (r = 6378.7km). The variables lat1, long1 and lat2, long2 are the actual and predicted positions, respectively.

The value of the gradient calculated provides information about the road ahead, and based on this information the signal actuators send the appropriate control signal.

V. ELECTRONICS AND TECHNOLOGY

Mobile communications and broadband distribution systems are stronger now thanks to GaAs (gallium arsenic) components compared to the silicon semiconductors. This technology applied to ACC radars as higher frequency applications is of great interest. The radar sensor designed by Thomson-CSF Radars for ACC system, is the first radar sensor to use monolithic microwave integrated circuit technology (MMIC). The automotive radar has been developed at a number of frequencies where 75 to 77 GHz is the widely available frequency for the application. Holger Meinel researcher at Daimler Benz Aerospace AG said that the high production of low cost collision-avoidance sensors has to rely on the availability of millimeter-wave GaAs MMICs [12]. ACC based on 24 GHz or 77 GHz radar sensors senses the distance and relative speed of the nearest vehicle in front up to 100m. A new generation of 77 GHz radar detects exceptional speed resolution and a range of detection higher than 250 meters with maximum control at long distance.

The advantage of the new radar based sensor is that its relative velocity can be measured directly. Also, the weather condition does not affect its performance in order to have a large angular reach with a good resolution. Mechanically-scanned systems will offer a better angular resolution but are most likely more expensive than fixed-beam radars. First available ACC were based on laser sensors. This technology has cheaper and offers a larger angular reach with an excellent angular resolution. However, this laser based systems are more susceptible to bad weather conditions reducing the detection range and creating

false obstacles. While Ultrasonic based sensors are becoming out of date. The computer vision systems face same issues as the laser one, in addition to their high cost and complexity of extraction of the related data.

The data from sensors is processed by digital signal processors (DSP) to generate inputs for the controller. With recent digital signal processing techniques, it is possible to locate target reflectors at greater distances than other sensor with a high degree of accuracy. The distance and the relative velocity between two vehicles is the frequency shift between the sent signal and the received one from the sensors. Receiving and processing this data in real time requires the use of several digital signal processors to perform such high speed tasks. Most of the DSPs offer built-in hardware multipliers designed for high speed, low complexity calculations and have regular structure in order to be easily integrated within the vehicle.

Real time situation are converted into proper actions by braking or accelerating through the controllers. This conversion of raw information from sensors to actions is done by analyzing traffic conditions and deciding on a particular situation. The headway controller is a programmable digital computer used for multiple inputs and output arrangements. The throttle controller can be programmed to generate the control signals according to the sensor data and mostly consists of the following features: SRAM, Flash memory, EEPROM (Electrically-erasable programmable ROM), UART interfaces (Universal asynchronous receiver/transmitter), Real time clock and CAN interface (Controller Area Network). The throttle valve is actuated and the air intake is controlled so the fuel and the air injected in the engine increase to change the speed.

VI. SUGGESTED SCCS ARCHITECTURE & FUEL CONSUMPTION

EVALUATION

A. Our suggested schematic for the SCCS:

     As a combination of all discussed systems above, the SCCS incorporates the best technologies and features in one smart system. The schema in Fig.2 represents signal and data flows over the different components of Mechatronics system. Here, the use of a single control unit would synchronize the data collected from the sensors with the preset speed, and suggest an optimal velocity after slope estimation.

 

Figure 2. Schematic representation of the setup of the SCCS

The SCCS control unit will prevent conflicting decision making such as privileging the optimal velocity in a speed limitation zone or neglecting obstacle to maintain the preset speed.

B. Fuel consumption evaluation

The objective of this simulation tests is to examine the response and the performance of the models presented as additional features on our PCC. This study will inspect the fuel consumption of conventional ACC compared to the optimized consumption model proposed by the predictive function of the PCC and estimates the realized profit.

The simulation scenario is as follow: A truck traverses a road for which the slope and attitude were measured using GPS data. The truck model includes the engine (MAN D2066) and endurance brake dynamics (ZF Intarder), a fuel consumption model, a robotized gear box (ZF Astronic). The simulation was done for a 40t tractor-trailer with 2000 Nm reference torque at 1000 rpm and 324kW at 1900 rpm. The gears are shifted automatically by the robotized gear box and are not subject to optimization.

The simulation is carried out on the same model within the same environment using both a Conventional Cruise Controller and our SCCS over a distance of 18.5 km.

Equation (10) calculates the profit generated and allows the comparison between the two controllers for the savings made.

∑ ∆ ∆ ,

∆

vx: Income MAD/km – cost MAD/km

vt: Cost per time unit (MAD/s)

vΓ: Cost per gram fuel (MAD/g)

(t): Current speed

, : Fuel consumption map output (g/s)

∆ : Sample time

We calculated the amount of fuel consumed, the time spent, and the profit madeby the truck for the two controllers. Table 1 reports the results.

Table 1: Performance of SCCS relative to a CCC

Controller Fuel (g)

% Time (s)

% Profit (MAD)

%

CCC 9560 0 842 0 1.32 0 PCC 9222 -3.5 861 2.2 1.49 11.2

The results of this simulation prove that using PCC allows saving on the fuel consumption of the truck. The truck equipped with a PCC made a saving of 3.5% of the fuel consumed compared to the ones that rely on a CCC, even though they spent more time to travel the same distance. These savings allowed making a profit that is 11.4% higher.

 

Figure 3: fuel consumption and duration

VII. CONCLUSION

The Smart Cruise Control System presented in this paper, is a combination of both a conventional and an adaptive cruise control systems. This system is proposed to satisfy multi-objectives which are comfort, safety, and fuel economy. This system makes use of data obtained from sensors and GPS to adjust the speed of the vehicle without any intervention from the driver. The system includes the Stop and Go feature that controls the behavior of vehicles in congested metropolitan traffic, as well as the ability to calculate the road curvature and adjust the behavior of the vehicle ahead of time. PCC and stop and go in addition to the conventional cruise control are all embedded in the SCCS and are controlled through the same control unit which guarantees the synchronization and accuracy of information to be transmitted to the system and vehicle actuators.

VIII. FUTURE WORK

Multiple enhancements can be added to the PCC. First, when the SCCS is off and the car is moving, it can still assist the driver through displaying the gradient and road curvatures ahead in the dash board. Second, it could incorporate 3D-map reader to overcome GPS signal failure and improve the speed of data retrieval. Also, the SCCS could mislead the driver by suggesting an optimum velocity in a speed limited zone, in order to prevent this system deficiency we can add vision sensors to recognize stopping points. E.g. recognize traffic light status, road signs and road lines (stop lines, pedestrians etc…). In the future, systems like SCCS are developed not only to increase safety and comfort of drivers but to achieve an automatically dirigible vehicle that would serve both in urban and extra-urban areas.

REFERENCES

[1]Ministry of Transport, Public Works and Water Management, Nota Mobiliteit; Naar een betrouwbare en voorspelbare bereikbaarheid, 2004, The Hague. (Dutch)

[2] European Commission, Final Report of the eSafety Working Group on Road Safety, Nov. 2002, Brussels, Belgium: EC DG IST.

[3] Scenarios and Evaluation Framework for City Case Studies, 2002. European Comission Fifth Framework Programme Energy, Environment and Sustainable Development Programme Key Action 4: City of Tomorrow and Cultural Heritage.

[4]  P. A. Ioannou and C. C. Chien, “Autonomous intelligent cruise control,” IEEE Trans. Veh. Technol., vol. 42, pp. 657–672, Nov. 1993.

[5] M. Persson, F. Botling, E. Hesslow, and R. Johansson, “Stop&go controller for adaptive cruise control,” in Proc. IEEE Control Applications Conf., vol. 2, 1999, pp. 1692–1697.

[6] S. Kato, S. Tsugawa, K. Tokuda, T. Matsui, and H. Fujiri, “Vehicle control algorithms for cooperative driving with automated vehicles and intervehicle communications,” IEEE Trans. Intell. Transport. Syst., vol. 3,no. 3, pp. 155–161, Sept. 2002.

[7] R. Holve, P. Protzel, J. Bernasch, and K. Naab, “Adaptive fuzzy control for driver assistance in car-following,” in Proc. 3rd Eur. Congr. Intelligent Techniques and Soft Computing—EUFIT’95, Aachen, Germany, Aug. 1995, pp. 1149–1153.

[8] L.Xiao and F.Gao A comprehensive review of the development of adaptive cruise control systems Vehicle System Dynamics Vol. 48, No. 10, October 2010, 1167–1192. [9] S.  Moon, and Y. Kyongsu. Human driving data-

based design ofa vehicle adaptive cruise control algorithm Vehicle System Dynamics, Aug2008, Vol. 46 Issue 8.

[10] K. Yi, Hki. Moon, and D.K. Young, A vehicle-to-vehicle distance control algorithm for stop-and-go cruise control. Intelligent Transportation Systems, 2001, in Proceedings of 2001 IEEE, Oakland, CA, USA, 2001. [11] Naab, K.: Abstandsregelung (ACC). Haus der Technik E.V., Essen, 8-9 December, 1999. [12] M. HOLGER. “Automotive Millimeterwave Radar History and present Status.” Microwave Conference, 1998. 28th European, pp. 619 - 629.

9000910092009300940095009600

CCC PCC

Fuel Consumption

830835840845850855860865

CCC PCC

Time