International Journal of Vehicle Autonomous Systems (8 papers in press)
Queueing theory based accelerated traffic discharging model in front of emergency vehicle on intersection
by Sony Sumaryo, Abdul Halim, Kalamullah Ramli, Endra Joelianto
Abstract: Intelligent Transportation System (ITS) is the integration between communication networks, real-time control, and information technology. The system is expected to perform more complex traffic arrangements, in particular traffic management of emergency vehicles. Implementation with traffic signal pre-emption alone is not enough to give space for the emergency vehicle to cross an intersection safely, especially if the lane street has only one lane. The paper proposes a new model of traffic discharge acceleration based on queueing theory approach. In the proposed model, two performance indicators are introduced, which are speed of normal traffic in front of the emergency vehicle and travelling time of the emergency vehicle. The model is aimed that the emergency vehicle could reach a destination within a certain time and a constant speed. Moreover, the delay should be managed to a minimum. A linear and an exponential acceleration formulas of the traffic in front of the emergency vehicle are derived and then validated. Performances of the models are tested against the model in the literature. Simulation results show the proposed model leads to better assurance that emergency vehicle is not delayed significantly. Based on the validation test, a formula has also been developed according to the proposed model.
Keywords: emergency vehicle; queueing theory; traffic management; signal pre-emption; simulation; acceleration discharge.
Path planning and re-planning of lane change manoeuvres in dynamic traffic environments
by Armin Norouzi, Reza Kazemi, Omid Reza Abbasi
Abstract: Automatic lane change is of utmost importance in designing autonomous vehicles and driver assistance systems. In this study, a novel path for lane change manoeuvres, based on mathematical functions, is introduced. To obtain a suitable path for lane change manoeuvres, four functions, namely quintic, septic, sinusoidal, and tangent functions, were examined. The analysis revealed that, according to the ISO Standards and peak acceleration criterion, a quintic function has the advantage of passenger comfort over other path functions. After choosing the appropriate path, an algorithm for re-planning the lane change path, based on dynamic traffic conditions, is proposed. The simulation results show that the proposed algorithm is capable of designing the path in various traffic conditions. Moreover, the algorithm can navigate the vehicle to the initial lane, if the manoeuvre is not possible. Our analytical results showed that the designed paths are suitable, comfortable, and safe.
Keywords: automatic lane change; autonomous vehicle; path planning; lane change re-planning.
Drivable path detection based on image fusion for unmanned ground vehicles
by D. Abraham Chandy, Biji Yohannan, A. Hepzibah Christinal, Riju Ghosh
Abstract: Autonomous vehicles are used for a range of tasks, such as automated highway driving, transporting work, etc. These vehicles are used in both structured and unstructured environments. This work presents an effective method for path detection using statistical texture features extracted from fused LIDAR sensor and visual camera images. An edge-based feature detection approach is adopted for image registration. The gray level co-occurrence matrix (GLCM) based texture features are extracted from the fused image. Classification performances of K-NN and Support Vector Machine (SVM) classifiers are analysed in this work. For experimentation, the data available in Ford Campus Vision dataset are used. The results of this new approach are very promising for path detection problem of unmanned ground vehicles.
Keywords: unmanned ground vehicle; autonomous navigation; image fusion; support vector machines; Ford Campus Vision.
Special Issue on: Dynamics, Control and Energy Efficiency of Electrified Vehicles
A modified extreme seeking based adaptive fuzzy sliding mode control scheme for vehicle anti-lock braking
by Wenfei Li, Haiping Du, Weihua Li
Abstract: Vehicle anti-lock braking systems (ABS) are designed to optimise vehicle braking performance, but there are some challenges for their control. One of the challenges is that the optimal slip ratio is difficult to obtain in real time and it can differ under different road conditions. Another challenge is that ABS are nonlinear and many parameters of them are difficult to identify in advance. To solve these problems, a new extremum seeking based adaptive fuzzy sliding mode control strategy is proposed to seek and track the optimal slip ratio for improving the performance of a blended anti-lock braking system. The proposed modified sliding mode based extreme seeking algorithm (MSMES) is able to avoid the large oscillation and automatically search for the optimal slip ratio even when road conditions change. An adaptive fuzzy sliding mode controller (AFSMC) is designed to overcome the problem of possible disturbances, uncertainties, and the nonlinear characteristics of ABS and it is able to mimic an ideal controller and to estimate the error boundary between the ideal controller and the designed controller. In order to validate the effectiveness of the proposed approach, numerical simulations on a quarter-vehicle braking model have been tested. The results show that the proposed control method not only is able to track the optimal slip ratio under different road conditions accurately but also is very robust.
Keywords: anti-lock braking system; extremum seeking; adaptive fuzzy sliding mode control; adaptive nonlinear observer.
Dynamic performance analysis of electrified propulsion system in electric vehicles
by Jency Joseph, T. Aruldoss Albert Victorie, Josh F.T, Joseph M.C
Abstract: High speed can be achieved by choosing a compact size of the propulsion system in an electric vehicle. The cost of the propulsion system is one of the major design considerations governed by the type of motor and controller. The choice of pancake shape Axial Flux Permanent Magnet Brushless DC Motor (AFPM BLDC) reduces the size of the propulsion system and improves the onboard space of the EV. The intermittent periodic duty class has been considered to choose the power rating of AFPM motor. The new type of zeta converter is proposed here to regulate the input side DC voltage. The dynamic performance of the EV has been compared with and without zeta converter, which will be useful for researchers in future.
Keywords: axial flux permanent magnet brushless DC motor; static model; zeta converter; total harmonic distortion; electric vehicle acceleration; distance travelled.
Research on synchronous control strategy of steer-by-wire system with dual steering actuator motors
by Min Hua, Guoying Chen, Changfu Zong, Lei He
Abstract: Steer-by-wire (SBW) system with dual steering actuator motors is a novel and potential type of steering system by means of hardware fault-tolerant redundancy to enhance driving safety. The basic control strategy "road feel feedback and steering angle control" has been carried out. Aiming at the non-synchronous appearance of dual steering actuator motors, dual-motor synchronous control employing differential negative feedback method has been proposed to reduce the adverse influence of servo fight non-synchronous issue. In addition, considering the existence of unavoidable backlash impact, dual-motor anti-backlash control adopting variable bias compensation current method has been developed to abate the negative effect caused by backlash factors for SBW system, so that the precision of steering implementation for SBW system can be enhanced. The results of simulations and hardware-in-loop experiments are analysed and then the conclusion is drawn that the proposed control strategy is effective and feasible.
Keywords: steer-by-wire system; dual steering actuator motors; synchronous control; anti-backlash control.
An investigation on coordination of lane departure warning based on driver behaviour characteristics
by Hongyu Zheng, Mingxin Zhao
Abstract: As an important part of advanced driver assistance systems (ADAS), lane departure warning system (LDWS) plays a significant role in lane departure prevention and reducing traffic accidents caused by lane departure. In order to improve the warning effect of the system as well as driver acceptance, this paper describes an LDWS algorithm for personalised driving assistance. The proposed combination algorithm consists of a multi-mode time to lane crossing (TLC) and a future offset distance (FOD) based on driver behaviour characteristics. To detect drivers lane change intention, the steering behaviour has been developed incorporating vehicle states and road curvature. Driving simulator tests are conducted to validate the lane departure warning algorithm with multi-mode based on TLC and FOD under various driving situations. The obtained test results are consistent with the expected performance.
Keywords: lane departure warning system; time lane crossing; future offset distance; driver characteristics; simulator experiments.
Special Issue on: Advancements, Applications and Challenges in Internet of Vehicles for Smart Transportation
Socio-realistic optimal path planning for indoor realtime autonomous mobile robot navigation
by Rahul Pol, B. Sheela Rani, Mahalingam Murugan
Abstract: An autonomous mobile robotic navigation system consists of many modules that work co-ordinately and concurrently. The most important module is the realistic and optimal path planning algorithm (ROPPA) through which the overall system performance increases. Many algorithms developed and deployed for data structures and computer games are partially modified to use in realtime robotic environments. The major drawback of such modified algorithms is they are designed for unconstrained artificial environments where a robot's collision with static obstacles or moving objects is partially allowed. Many researchers successfully developed the path planning algorithm through improving the basic A* algorithm, such as D* lite, theta*, any angle path planning, and jump point search. In real environments one should explore the optimal path along with maintaining uniform safer distance with the objects or in-path obstacles. This paper describes the implementation and evaluation of a new realistic optimal path planning algorithm, which follows the safer distance rule through exploring minimum workspace area along with less memory overhead; the algorithm also explores the shortest final path with fewer subpaths if it exists. The experimentation with different map size and obstacle density clearly defines improvement in ROPPA over the other path planning methods.
Keywords: grid-based segmentation; modified A*; theta*; any angle path planning; optimal path planning; safer path planning; realistic optimal path planning.