Learning semantically-annotated routes for context-aware recommendations on map navigation systems

Modern technology has brought many changes to our everyday lives. Our need to be in constant touch with others has been met with the cellphone, which has become our companion and the convergence point of many technological advances. The combination of capabilities such as browsing the Internet and GPS reception has multiplied the services and applications based on the current location of the user. However, providing the user with these services has certain drawbacks. Although map navigation systems are the most meaningful way of displaying this information, the user still has to manually set up the filter in order to obtain a non-bloated visualization of the map and the available services. To tackle this problem, we present here a semantic multicriteria ant colony algorithm capable of learning the user's routes, including associated context information, and then predicting the most likely route a user is following, given his current location and context data. This knowledge could then be used as the basis for offering services related to his current (or most likely future) context data close to the path he is following. Our experimental results show that our algorithm is capable of obtaining consistent solutions sets even when multiple objective ontological terms are included in the process.     

Modelling deformations in car crash animation

In this paper, we present a prototype of a deformation engine to efficiently model and render the damaged structure of vehicles in crash scenarios. We introduce a novel system architecture to accelerate the computation, which is traditionally an extremely expensive task. We alter a rigid body simulator to predict trajectories of cars during a collision and formulate a correction procedure to estimate the deformations of the collapsed car structures within the contact area. Non-linear deformations are solved based on the principle of energy conservation. Large plastic deformations resulting from collisions are modelled as a weighted combination of deformation examples of beams which can be produced using classical mechanics.     

汽车导航系统的分岔路口向导设计

汽车导航系统是近十年来兴起的一种汽车驾驶辅助设备。在所有导航系统的模块中,提供声音提示、表示图等功能的向导是实现导航功能最基本最重要的模块。为了提高导航系统在分岔路口处的导航能力,本文在原系统的向导模块中添加了一个新的分岔路口向导功能模块。基于以上目的,首先介绍了本文使用的汽车导航系统的模块结构与其功能,特别是向导模块。然后,系统地分析、设计并实现了分岔路口向导功能。这一功能的实现,更进一步地完善了汽车导航系统。     

多功能导航智能小车设计

设计一款基于STC89C52单片机的可实现自主导航和手动控制的多功能导航智能小车。该系统中,红外避障传感器通过调节与障碍物的距离实现躲避,红外巡线传感器按照给定黑线实现自主导航,超声波传感器在避障的同时实现距离的测量。该系统设计为智能交通无人驾驶汽车提供支持,自动导航代替人为驾驶,减少了因人操作不当或其他因素而导致交通事故的可能。     

Understanding driver adoption of car navigation systems using the extended technology acceptance model

This study proposes an integrated research model for investigating driver adoption of car navigation systems. We consider the potential causal connections between core cognitive and psychological factors and driver intention to use these systems. We extracted possible factors that may significantly affect the perceived usability of car navigation systems from in-depth interviews with two groups of individuals: an expert group and a driver group. Data collected from N?=?1045 drivers via an online survey were analysed by structural equation modelling. The results showed that the service & display quality components of the systems were the most significant determinants of driver attitude and intention to use car navigation systems. Two other factors, namely attitude and perceived usefulness, also had impacts on driver intention. Moreover, both satisfaction and service & display quality were affected by perceived system reliability, while usefulness was affected by both perceived locational accuracy and satisfaction. Satisfaction also significantly affected perceived ease of use. In addition, we introduced new external variables to the technology acceptance model (TAM) and validated the causal connections proposed by the original TAM. The present study provides valuable insights into the core factors that significantly affect driver perspectives of and intention to use car navigation systems.     

The effects of gender differences on operational performance and satisfaction with car navigation systems

This study investigates whether gender differences have an impact on the definition of good interface design and whether manufacturers should develop interfaces that fit small-display portable car navigation systems (CNSs) based on gender. This work adopted an experimental design for collecting data from three tasks – locating points, planning routes, and searching polygons – each emphasizing a different aspect of way-finding. Study results show that gender, the CNS interface the participant used, and a combination of the two predict a person’s operational performance and satisfaction with a CNS. This study’s results provide a better understanding of whether manufacturers should develop interfaces that fit a CNS’s small display based on gender.     

Enhanced fog detection and free-space segmentation for car navigation

Free-space detection is a primary task for car navigation. Unfortunately, classical approaches have difficulties in adverse weather conditions, in particular in daytime fog. In this paper, a solution is proposed thanks to a contrast restoration approach on images grabbed by an in-vehicle camera. The proposed method improves the state-of-the-art in several ways. First, the segmentation of the fog region of interest is better segmented thanks to the computation of the shortest routes maps. Second, the fog density as well as the position of the horizon line is jointly computed. Then, the method restores the contrast of the road by only assuming that the road is flat and, at the same time, detects the vertical objects. Finally, a segmentation of the connected component in front of the vehicle gives the free-space area. An experimental validation was carried out to foresee the effectiveness of the method. Different results are shown on sample images extracted from video sequences acquired from an in-vehicle camera. The proposed method is complementary to existing free-space area detection methods relying on color segmentation and stereovision.     

Autonomous car driving by a humanoid robot

Enabling a humanoid robot to drive a car requires the development of a set of basic primitive actions. These include walking to the vehicle, manually controlling its commands (e.g., ignition, gas pedal, and steering) and moving with the whole body to ingress/egress the car. We present a sensor‐based reactive framework for realizing the central part of the complete task, consisting of driving the car along unknown roads. The proposed framework provides three driving strategies by which a human supervisor can teleoperate the car or give the robot full or partial control of the car. A visual servoing scheme uses features of the road image to provide the reference angle for the steering wheel to drive the car at the center of the road. Simultaneously, a Kalman filter merges optical flow and accelerometer measurements to estimate the car linear velocity and correspondingly compute the gas pedal command for driving at a desired speed. The steering wheel and gas pedal reference are sent to the robot control to achieve the driving task with the humanoid. We present results from a driving experience with a real car and the humanoid robot HRP‐2Kai. Part of the framework has been used to perform the driving task at the DARPA Robotics Challenge.     

Methods for choosing loaded train and car routes along a railroad network

We consider the problems of designing the routes for freight cars from departure stations to destination stations and problems and planning model for the works and for finding the necessary number of trains to deliver a given number of freight cars from departure stations to destination stations.     

Evaluation of driver discomfort during long-duration car driving

The evolution of indices of fatigue, discomfort, and performance of subjects seated for long duration (150 min) in car seats were studied (n=11). Four experimental configurations were used: with and without vibration for two seats (U, uncomfortable; C, comfortable). Surface electromyography (SEMG) data were recorded bilaterally from cervical erector spinae and external oblique muscles. Discomfort increased significantly during the trial, regardless of the experimental condition (p<0.05). Performance was significantly worse for seat U with vibration (p<0.05). The median frequency of SEMG signals did not change between experimental conditions or across time. It would appear that, either the level of discomfort experienced was insufficient to change either performance or SEMG measures, or that the large parameter estimation variance of the SEMG signals might have masked any underlying spectral change. Further refinement of the SEMG signal processing methodology may be necessary to be able to detect fatigue of postural muscles.     

Algorithmic support for integrated navigation systems

A method of synthesis of integrated navigation systems with different structure of the measuring complex is considered. Examples of synthesis of stochastic models for the state vector of the multistructural navigation system are given. A new control method for the choice of the estimation structures for navigation variables based on the use of nonlinear probabilistic criteria is proposed.     

汽车驾驶模拟器控制系统的设计与实现

为使汽车驾驶模拟器实现实车运动状态及结构特征仿真,设计了基于单片机的数据采集系统和仪表控制系统。首先,数据采集系统采用ATmega2560单片机对模数信号进行采集与处理。其次,仪表控制系统采用Arduino UNO R3开发板、步进电机扩展板和28BYJ-48步进电机实现车速表和转速表的实时显示。然后,以数据帧的形式完成串口通信,基于VS2010使主控计算机同时完成读写功能。最后,在汽车驾驶模拟器上进行实验并对方向盘信号的处理过程进行优化。实验结果表明：系统能够完成行业标准(JT/T 378-2014)对汽车培训驾驶模拟器的功能要求,且可以实时传送操作状态,动作延迟低,数据传输稳定,且成本较低,具有一定的实用性。     

Redirecting walking and driving for natural navigation in immersive virtual environments

Walking is the most natural form of locomotion for humans, and real walking interfaces have demonstrated their benefits for several navigation tasks. With recently proposed redirection techniques it becomes possible to overcome space limitations as imposed by tracking sensors or laboratory setups, and, theoretically, it is now possible to walk through arbitrarily large virtual environments. However, walking as sole locomotion technique has drawbacks, in particular, for long distances, such that even in the real world we tend to support walking with passive or active transportation for longer-distance travel. In this article we show that concepts from the field of redirected walking can be applied to movements with transportation devices. We conducted psychophysical experiments to determine perceptual detection thresholds for redirected driving, and set these in relation to results from redirected walking. We show that redirected walking-and-driving approaches can easily be realized in immersive virtual reality laboratories, e. g., with electric wheelchairs, and show that such systems can combine advantages of real walking in confined spaces with benefits of using vehicle-based self-motion for longer-distance travel.     

A fuzzy-rule-based driving architecture for non-player characters in a car racing game

Videogame-based competitions have been the target of considerable interest among researchers over the past few years since they provide an ideal framework in which to apply soft computing techniques. One of the most popular competitions is the Simulated Car Racing Competition which, thanks to the realism implemented by recent car simulators, provides an excellent test bed for the application of autonomous driving techniques. The present work describes the design and implementation of a car controller able to deal with competitive racing situations. The complete driving architecture consists of six simple modules, each one responsible for a basic aspect of car driving. Three modules use simple functions to control gear shifting, steering movements, and pedal positions. A fourth manages speed control by means of a simple fuzzy system. The other two modules are in charge of (i) adapting the driving behaviour to the presence of other cars, and (ii) implementing a basic ‘inter-lap’ learning mechanism in order to remember key track segments and adapt the speed accordingly in future laps. The controller was evaluated in two ways. First, in runs without adversaries over several track designs, our controller allowed some of the longest distances to be covered in a set time in comparison with data from other previous controllers, and second, as a participant in the 2009 Simulated Car Racing Competition which it ended up winning.     

Crowdsourcing good landmarks for in-vehicle navigation systems

Augmenting navigation systems with landmarks has been posited as a method of improving the effectiveness of the technology and enhancing drivers’ engagement with the environment. However, good navigational landmarks are both laborious to collect and difficult to define. This research aimed to devise a game concept which could be played by passengers in cars, and would collect useful landmark data as a by-product. The paper describes how a virtual graffiti tagging game concept was created and tested during on-road trials with 38 participants. The data collected in the road trials were then validated using a survey, in which 100 respondents assessed the quality of the landmarks collected and their potential for reuse in navigation applications. Players of the game displayed a consensus in choosing where to place their graffiti tags, with over 30% of players selecting the same object to tag in 10 of the 12 locations. Furthermore, significant correlation was found between how highly landmarks were rated in the survey and how frequently they were tagged during the game. The research provides evidence that using crowdsourcing games to collect landmarks does not require large numbers of people, or extensive coverage of an area, to produce suitable candidate landmarks for navigation.     

An embedded testbed architecture to evaluate autonomous car driving

The progress in autonomous car driving or also called Advanced Driving Assistance Systems (ADAS) has recently received an increasing attention in car industries. Thus, many autonomous car models are recently developed and some are even commercialized. However, they are still not ready to enter our daily life since they lack efficiency and reliability. In this sense, to obtain efficient and reliable systems, the evaluation process plays an important role. Nowadays, the evaluation is strongly related to the number of kilometers of drive. However, in order to make a comprehensive evaluation of such systems, in addition to the number of kilometers, each component should also be tested. In this study, we focused on developing a system that is able to evaluate each component of ADAS. We defined a versatile architecture that simplifies the evaluation of different types of ADAS. Several evaluation scenarios are shown and discussed.