Tire–road friction coefficient and tire cornering stiffness estimation based on longitudinal tire force difference generation

A sequential tire cornering stiffness coefficient and tire–road friction coefficient (TRFC) estimation method is proposed for some advanced vehicle architectures, such as the four-wheel independently-actuated (FWIA) electric vehicles, where longitudinal tire force difference between the left and right sides of the vehicle can be easily generated. Such a tire force difference can affect the vehicle yaw motion, and can be utilized to estimate the tire cornering stiffness coefficient and TRFC. The proposed tire cornering stiffness coefficient and TRFC identification method has the potential of estimating these parameters without affecting the vehicle desired motion control and trajectory tracking objectives. Simulation and experimental results with a FWIA electric vehicle show the effectiveness of the proposed estimation method.     

Stochastic modeling and analysis of road–tramway intersections

In the last decades, the socio-demographic evolution of the population has substantially changed mobility demand, posing new challenges in minimizing urban congestion and reducing environmental impact. In this scenario, understanding how different modes of transport can efficiently share (partially or totally) a common infrastructure is crucial for urban development. To this aim, we present a stochastic model-based analysis of critical intersections shared by tram traffic and private traffic, combining a microscopic model of the former with a macroscopic model of the latter. Advanced simulation tools are typically used for such kind of analyses, by playing various traffic scenarios. However, simulation is not an exhaustive approach, and some critical, possibly rare, event may be ignored. For this reason, our aim is instead to adopt suitable analytical solution techniques and tools that can support instead a complete, exhaustive analysis, so being able to take into account rare events as well. Transient analysis of the overall traffic model using the method of stochastic state classes is adopted to support the evaluation of relevant performance measures, namely the probability of traffic congestion over time and the average number of private vehicles in the queue over time. A sensitivity analysis is performed with respect to multiple parameters, notably including the arrival rate of private vehicles, the frequency of tram rides, and the time needed to recover from traffic congestion.

     

RoadLab — A constraint based laboratory for road design

Constraints provide a powerful computational model to support designing, different from global optimization or rule-based decision-making. This paper reviews the theory of constraints and techniques of constraint management with respect to geometric road layout. We describe RoadLab, a constraint-based graphic programming environment, and discuss the application of the constraint model to designing.     

Development of generic multibody road vehicle models for crashworthiness

The crashworthiness analysis of road vehicles requires detailed data of the vehicles that the automotive manufacturers are, generally, unable to release due to commercial or legal restrictions. In the development of passive safety subsystems or substructures, the overall crash response of a vehicle model used to support it, must mimic that of the real vehicle; if this exists, regardless of any particular constructive detail of its structure provided that it is not located in the vicinity of such subsystem. This work proposes a methodology for the development of multibody models of road vehicles, for passive safety analysis, which include all general structural and mechanical features of real vehicles and start by exhibiting impact dynamic responses similar to the top of line vehicles. These vehicle models, designated as generic, do not require the knowledge of most of the particular details of the design of the real vehicle, which the manufacturers are unable to release, but can be adjusted to have crash responses similar to those of the real vehicle. Based on an existing finite element model of a car, which has all constructive features of vehicles of the chosen class, a multibody model is built applying the plastic hinge approach. By using a selected number of crash scenarios, defined in international standards such as the EuroNCAP, selected parameters of the vehicle multibody model are adjusted to ensure a good correlation between its impact responses and those of the finite element model. The crash responses are measured in terms of structural deformations, velocities and accelerations, occupant injury measures and structural energy absorption capabilities. Assuming that the plastic hinge constitutive equations of the multibody model are not exactly known, their parameters are used here as the multibody vehicle model that are adjusted. The methodology proposed is demonstrated by its application to the identification of the vehicle multibody model of a large family car for which the reference vehicle is available as a detailed finite element model.     

Non-linear velocity observer for vehicles with tyre–road friction estimation

A non-linear observer is proposed for the estimation of the longitudinal and lateral velocities of automotive vehicles due to highly non-linear friction. To take the unknown time-varying road conditions into account, a real-time tyre–road friction estimation algorithm is provided for adaptation to changes of different road adhesion characteristics. Besides, the coupling effects of the longitudinal and lateral forces are fully exploited to design the non-linear observer based on the longitudinal and lateral acceleration measurements. The observer is computationally efficient and is based on a standard sensor configuration commonly available in modern cars. The uniform global asymptotical stability of the adaptive observer is guaranteed under a certain persistency-of-excitation condition. Moreover, a stronger local stability result can also be obtained, i.e. uniform local exponential stability. The performance of the observer is compared with that of existing approaches under different manoeuvres and road conditions.     

Rescue robotics — a crucial milestone on the road to autonomous systems

Rescue robotics is an important steppingstone in the scientific challenge to create autonomous systems. There is a significant market for rescue robots, which have unique features that allow a fruitful combination of application-oriented developments and basic research. Unlike other markets for advanced robotics systems like service robots, the rescue robotics domain benefits from the fact that there is a human in the loop, which allows a stepwise transition from dumb teleoperated devices to truly autonomous systems. Current teleoperated devices are already very useful in this domain and they benefit from any bit of autonomy added. Human rescue workers are a scarce resource at disaster scenarios. A single operator should, hence, ideally supervise a multitude of robots. We present results from the rescue robots at the International University Bremen in a core area supporting autonomy, i.e., mapping.     

“Super-intelligent” machine: technological exuberance or the road to subjection

Looking back on the development of computer technology, particularly in the context of manufacturing, we can distinguish three big waves of technological exuberance with a wave length of roughly 30 years: In the first wave, during the 1950s, mainframe computers at that time were conceptualized as “electronic brains” and envisaged as central control unit of an “automatic factory” (Wiener). Thirty years later, during the 1980s, knowledge-based systems in computer-integrated manufacturing (CIM) were adored as the computational core of the “unmanned factory”. Both waves dismally stranded on the contumacies of reality. Nevertheless, again thirty years later, we now experience the departure of the “smart factory” based on networks of “artificially intelligent” multi-agent or “cyber-physical systems” (often also addressed as “internet of things”). From the very beginning, these technological exuberances rooted in mistaken metaphors describing the artifacts (e.g. “electronic brain”, “knowledge-based” or “intelligent systems”) and, hence, in delusions about the true nature of computer systems. The behaviour of computers is, as computing science teaches us, strictly restrained to executing computable functions by means of algorithms, it thus neither resembles the performance of a brain as part of a complex sensitive living body nor is it in any meaningful sense “knowledgeable” or “intelligent” (this predicate remaining reserved for the programmer designing the algorithms). When the delusion of being able to implement “smart factories”, despite the countless accomplishment failures before, gains momentum anew, it appears absolutely essential to reflect on underlying misconceptions.     

On the road – listening to data subjects’ personal mobility data privacy concerns

Efficient utilisation of new mobility data-based services and promotion of acceptance of data collection from vehicles and people demand an understanding of mobility data privacy concerns, associated with increasing use of tracking technologies, diverse data usages and complex data collection environments. Understanding privacy concerns enables improved service and system development and identification of appropriate data management solutions that contribute to data subjects’ privacy protection, as well as efficient utilisation of the collected data. This study aimed to explore earlier research findings on privacy concerns evaluation and investigate their validity in mobility data collection. Explorative multimethod research was conducted in a mobility service pilot through data controller interviews, user interviews and a user survey. The study's results indicated the need to revise and complement existing privacy concerns evaluation in mobility data collection contexts. The primary findings were as follows: (1) Privacy concerns specific to the mobility data collection context exist. (2) Privacy concerns may change during the service use. (3) Users are not necessarily personally worried about their privacy although they ponder on privacy issues. (4) In contrast to traditional ‘privacy calculus’ thinking, users’ expected benefits from data disclosure may also be driven by altruistic motives.     

Information technology and road transport industry: how does IT affect the lorry driver?

A quasi-experimental design was used to study the effect of on board computer-systems (OBC-systems) on the Dutch lorry drivers' psychosocial work environment (i.e., control and demands) and coinciding mental health (i.e., need for recovery after work) and job attitudes (i.e., organisational commitment). The intervention group (n = 26) started working with an OBC-system between 1998 and 2000 and was compared with two matched reference groups (n = 26 in both groups). All participants were from a cohort of 650 drivers who participated in a prospective study on occupational stress and health. All outcome variables were quantified by standardised and validated questionnaires. Results showed that the application of OBC-systems negatively affected the drivers' job control and organisational commitment. However, OBC-systems did not influence the drivers' psychological job demands and need for recovery after work. Accordingly, it is concluded that the application of OBC-systems negatively affects the lorry driver's psychosocial work environment and job attitudes.     

The recognition of road network from high‐resolution satellite remotely sensed data using image morphological characteristics

With the development of remote sensors and satellite technologies, high‐resolution satellite data such as IKONOS images have been available recently. By these new high‐resolution satellite data, remote sensing technologies can be successfully applied to more application areas such as extracting road network from high‐resolution satellite images. This paper proposes a newly developed approach to extract a road network from high‐resolution satellite images. The approach is based on the binary and greyscale mathematical morphology and a line segment match method. First, the outline of road network is detected based on the grey morphological characteristics. Then, the basic road network is detected by the line segment match method. Next, the detected basic road network is processed based on the knowledge about the roads and binary mathematical morphological methods. Finally, visual analysis and three indicators are used to evaluate the accuracy of the extracted road networks. The results of the accuracy evaluation demonstrate that the developed road network extraction approach can provide both good visual effect and high positional accuracy.     

Stochastic model predictive braking control for heavy-duty commercial vehicles during uncertain brake pressure and road profile conditions

When heavy-duty commercial vehicles (HDCVs) must engage in emergency braking, uncertain conditions such as the brake pressure and road profile variations will inevitably affect braking control. To minimize these uncertainties, we propose a combined longitudinal and lateral controller method based on stochastic model predictive control (SMPC) that is achieved via Chebyshev–Cantelli inequality. In our method, SMPC calculates braking control inputs based on a finite time prediction that is achieved by solving stochastic programming elements, including chance constraints. To accomplish this, SMPC explicitly describes the probabilistic uncertainties to be used when designing a robust control strategy. The main contribution of this paper is the proposal of a braking control formulation that is robust against probabilistic friction circle uncertainty effects. More specifically, the use of Chebyshev–Cantelli inequality suppresses road profile influences, which have characteristics that are different from the Gaussian distribution, thereby improving both braking robustness and control performance against statistical disturbances.Additionally, since theKalman filtering (KF) algorithm is used to obtain the expectation and covariance used for calculating deterministic transformed chance constraints, the SMPC is reformulated as a KF embedded deterministic MPC. Herein, the effectiveness of our proposed method is verified via a MATLAB/Simulink and TruckSim co-simulation.     

What happens next? Predicting other road users' behaviour as a function of driving experience and processing time

Hazard perception is one of the most important facets of driving and if the appropriate diagnostic tool is used it can discriminate between novice and experienced drivers. In this study video clips of actual driving scenarios were shown to novice and experienced drivers. The clips were stopped just prior to hazard onset and either the screen went black or the final still image stayed on the screen. Participants were then asked five questions about what happened next. This variant of the hazard perception test allowed the influence of processing time to be included and the level of situation awareness to be measured. Experienced drivers significantly anticipated more correct hazardous outcomes than novice drivers when the screen went black. Novice drivers benefited from the extra processing time afforded by the image remaining on the screen and significantly anticipated more hazards when the image remained on the screen than when it went black. The findings indicate that when processing time is manipulated, hazard perception accuracy reveals experiential differences. These differences are discussed with reference to hazard perception and situation awareness. This research informs the current controversy over whether hazard perception is a good diagnostic tool for driving performance. It identifies potential confounds in previous work and demonstrates that experiential differences can be found if the appropriate tests are used. Further, it suggests improvements for new hazard perception tests.     

A comparison of algorithms for origin–destination matrix generation on real road networks and an approximation approach

This paper considers the generation of the origin–destination (OD) matrix, basic data in any vehicle routing or traveling salesman problem. An OD matrix must be generated by calculating the shortest paths between some nodes. Candidate methods for this are repetitive use of one-to-all shortest path algorithms such as Dijkstra’s algorithm, use of all-to-all shortest path algorithms such as the Floyd–Warshall algorithm, and use of specifically designed some-to-some shortest path algorithms. This paper compares the performance of several shortest path algorithms in computing OD matrices on real road networks. Dijkstra’s algorithm with approximate bucket data structure performed the best for most of the networks tested. This paper also proposes a grouping-based algorithm for OD matrix generation. Although it is an approximation approach, it has several good characteristics: it can find the exact shortest distances for most OD pairs; it guarantees that all the calculated shortest path distance values have corresponding paths; the deviation of any distance from the corresponding true shortest distance is small; and its computation time is short.     

Is three the magic number? The role of ergonomic principles in cross country comprehension of road traffic signs

Abstract

Road sign comprehension plays an important part in road safety management, particularly for those drivers who are travelling in an unfamiliar country. Previous research has established that comprehension can be improved if signs are designed to adhere to ergonomic principles. However, it may be difficult for sign designers to incorporate all the principles into a single sign and may thus have to make a judgement as to the most effective ones. This study surveyed drivers in three countries to ascertain their understanding of a range of road signs, each of which conformed in varying degrees and combinations to the ergonomic principles. We found that using three of the principles was the most effective and that the most important one was that relating to standardisation; the colours and shapes used were key to comprehension. Other concepts which related to physical and spatial characteristics were less important, whilst conceptual compatibility did not aid comprehension at all.

Practitioner Summary: This study explores how road sign comprehension can be improved using ergonomic principles, with particular reference to cross-border drivers. It was found that comprehension can be improved significantly if standardisation is adhered to and if at least three principles are used.