International Journal of Vehicle Autonomous Systems (7 papers in press)
Shift control of vehicle automatic transmission based on traffic congestion identification
by Guang Xia, You Zheng, Xiwen Tang, Baoqun Sun, Shaojie Wang
Abstract: This work builds a TS fuzzy neural network that identifies traffic congestion conditions by using average vehicle speed, average throttle opening and frequency of brake pedal actuation as evaluation factors. A strategy that controls the shift of vehicle automatic transmission based on the identified congestion conditions is also devised. This strategy divides the vehicle automatic transmission system into the upper identification and decision-making layer and the lower shift execution layer. Simulation and real vehicle tests are performed to verify the effectiveness of the proposed strategy. The results show that congestion conditions can be accurately identified by using the TS fuzzy neural network and that the proposed layered correction shift control strategy can prevent the frequent changing of gears under congestion conditions, thereby reducing the wear of the shift execution parts and the braking system.
Keywords: traffic congestion identification; T-S fuzzy neural network; shift correction; layered control; real-vehicle test.
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.
Towards an immersive and safer driving experience using computer vision integrated with encoded vibro-tactile feedback
by Rajshekhar Mukherjee, Dharmendra Kumar Mahato, Sangeeta Yadav, Amit Pundir, Geetika Jain Saxena
Abstract: This paper describes the setting up of an immersive, responsive vehicle driving system and mechanism for a driving assist technology for expanding the sensory horizon of humans while driving and is motivated by absence of any such system in the real world. The system can control and direct an assembly of electronic devices in real time, using an image acquisition subsystem, an object-recognition and tracking algorithm and a haptic modelling subsystem working in tandem with the user. The object tracking subsystem operates in real time to determine the current position of a vehicle in front by using a camera and continuously updates it in a live video feed, while also identifying and tracking moving or stationary vehicles. The haptic system, which is integrated with the tracking system, has been programmed to warn the driver of the potential threats that moving or stationary vehicles may generate. All the subsystems are updated and synchronised with each other in real time to produce a seamless and smooth transition between frames, facilitating a precise and immersive driving experience for anyone. The high accuracy and robustness of the proposed system makes it a versatile component, which can be integrated into a variety of applications for enhancing a persons reality perception.
Keywords: object tracking; image detection; SURF; vibro-tactile; vision-to-touch; human-centred computing; immersive reality.