In and out vision-based driver-interactive assistance system

The overall driving environment consists of the Traffic environment, vehicle and driver states (TVD). advanced driver assistance Systems (ADAS) must consider not only information on each of the TVD states but also their context. Recent research has focused on making more efficient and effective assistance systems by fusing all the information from the TVD states. Based on this research trend, this paper focuses on decision-level fusion to estimate the level of danger of a warning by using visual information of the traffic environment and the driver state. The driver state consists of the gazing region and the facial feature points that are obtained using the active appearance model (AAM). The traffic environment state consists of time to collision (TTC), time to lane Crossing (TLC), and lane color information, which are obtained from the environment in front of the vehicle, i.e., position of lanes and other vehicles. Warnings against lane-off, collision, and driver inattention are generated by fusing this vision-based information from inside and outside the vehicle. The experimental results prove that our vision-based interactive driver assistance system reduces most useless warnings.     

Multivariate modeling of pedestrian fatality risk through on the spot accident investigation

Pedestrians are the most vulnerable users of public roads and represent one of the largest groups of road casualties; their death rate around the world due to vehicle-pedestrian collisions is high and tending to rise. In Spain, as in other countries of the European Union, steps have been taken to reduce the number and consequences of such accidents, with encouraging results in recent years. A key to countering this concern is the accident research activity that has obtained remarkable achievements in different fields, especially when multidisciplinary approaches are taken. This paper describes the development of a multivariate model that is able to detect the most influential parameters on the consequences of vehicle-pedestrian collision and to quantify their impact on pedestrian fatality risk. First, an accident database containing detailed information and parameters of vehicle-pedestrian collisions in Madrid has been developed. The accidents were investigated on the spot by INSIA accident investigation teams and analyzed using advanced reconstruction techniques. The model was then developed with two components: (1) a classification tree that characterizes and selects the explanatory variables, identifying their interactions, and (2) a binary logistic regression to quantify the influence of each variable and interaction resulting from the classification tree. The whole model represents an important tool for identifying, quantifying and predicting the potential impact of measures aimed at reducing injuries in vehicle-pedestrian collisions.     

Electro-hydraulic braking system for autonomous vehicles

Reducing the number of traffic accidents is a declared target of most governments. Since dependence on driver reaction is the main cause of road accidents, it would be advisable to replace the human factor in some driving-related tasks with automated solutions. To automate a vehicle, it is necessary to control the actuators of a car, i.e., the steering wheel, accelerator, and brake. This paper presents the design and implementation of an electro-hydraulic braking system consisting of a pump and various valves, allowing the control computer to stop the car. It is assembled in conjunction with the original circuit for the sake of robustness and to permit the two systems to halt the car independently. This system was developed for installation in a commercial Citroën C3 Pluriel of the AUTOPIA program. Various tests were carried out to verify its correct operation, and an experiment showing the integration of the system into the longitudinal control of the car is described.     

Optimization of bus rollover strength by consideration of the energy absorption ability

Buses are an integral part of the national transportation system of each country. A rollover event is one of the most important hazards that concerns the safety of the passengers and the crew in a bus. In the past, it was observed after the accident that the deforming superstructure seriously threatens the lives of the passengers. Thus, the stiffness of the bus frame is the first thing that needs to be considered. The unfortunate side of strengthening the bus superstructure is that it usually causes the bus weight to increase. This paper presents an efficient and robust analysis method with which to design the bus superstructure for a reduction in occupant injuries from rollover accidents while the weight of the strengthened bus is maintained at the same level. First, the absorbed energy of the bus frame and its components during a rollover were investigated by using a LS-DYNA numerical study. The highest energy absorption region, which is the side section of the bus frame, was found and focused on for the investigation of a means to re-distribute the energy-absorption ability of the side frame component. Then the thickness parameters that were obtained from the re-distribution of the energy-absorption ability were used in the analysis to optimize the design. Finally, a prototype of the bus with a reasonable thickness for the window pillars and the side wall bars, which was based on the optimized parameters, was verified to ensure it satisfied ECE R66. In this paper, an effective usage of materials and an efficient and robust analysis method were presented to design the bus superstructure. Although the optimization process for increasing the stiffness is simple, this study improves the upper displacement by 39.9% and the lower displacement by 49.3% (versus the bus survivor space) while maintaining the bus weight at the existing level.     

Optimum SUV bumper system design considering pedestrian performance

Until recently, passenger cars have primarily interested in pedestrian protection performance. Nowadays, however, it is important for a sport-utility vehicle (SUV) to meet the bumper system standards for pedestrian safety. For a SUV bumper system, there are some difficulties in attaining a high level of pedestrian performance for the lower legform. An SUV has a high bumper position from the ground level, and the bumper approach angle must also be secured, which has an effect on car insurance fees. Due to these reasons, it is difficult to meet the pedestrian performance of the lower legform for an SUV. In this paper, a comparative study was performed on various SUV bumper systems, and a concept model for a SUV bumper system was developed, which is expected to meet the pedestrian performance by using the Pugh method. The design control factors were defined to affect the bumper pedestrian performance through the experiences of tests and analyses. For the noise factor to affect the pedestrian performance, the deviation of the impactor position was selected at the moment of impact. The design control factors were optimized by using the Taguchi optimization technique. For the Taguchi method, an L18 orthogonal array table of design control factors was used in the optimization process. Particularly, for the optimization of the bumper corner region, an optimization analysis was performed three times to meet pedestrian performance. Based on the results of the Taguchi optimization method, the sensitivity of the bumper design parameters was studied, and a new SUV bumper system is proposed that satisfies the pedestrian performance of the lower legform. The optimized bumper system should obtain a full Euro-NCAP score of 6 points for the bumper test. The pedestrian performance of the optimized bumper system is validated by using a CAE (Computer Aided Engineering) analysis, which has been proven to be in accurate. A comparison between the test and analysis results is shown for the validation of accuracy. By using the optimized bumper system, the tests and development costs of a bumper can be reduced.     

Global optimization method for mixed transportation network design problem: A mixed-integer linear programming approach

This paper proposes a global optimization algorithm for solving a mixed (continuous/discrete) transportation network design problem (MNDP), which is generally expressed as a mathematical programming with equilibrium constraint (MPEC). The upper level of the MNDP aims to optimize the network performance via both expansion of existing links and addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE) problem. In this paper, we first formulate the UE condition as a variational inequality (VI) problem, which is defined from a finite number of extreme points of a link-flow feasible region. The MNDP is approximated as a piecewise-linear programming (P-LP) problem, which is then transformed into a mixed-integer linear programming (MILP) problem. A global optimization algorithm based on a cutting constraint method is developed for solving the MILP problem. Numerical examples are given to demonstrate the efficiency of the proposed method and to compare the results with alternative algorithms reported in the literature.     

Réflexions sur le transfert méthodologique de l’analyse qualitative d’accidents de la circulation routière issue de l’étude détaillée des accidents (EDA) fran?aise aux procédures d’accidents colombiennes

Nearly 90% of the traffic accidents that occur worldwide happen in developing countries. Yet road safety remains a little-studied subject in these countries, and notably accidentology studies, which provide a wealth of information. One of the major problems in studying road accidents in developing countries lies in the lack of reliable accident data. Indeed, while the comprehensive accident analysis methodologies used in developed countries provide an understanding of the origin of accidents and accident processes, as well as making it possible to define suitable, effective actions, they require reliable and relatively detailed accident data. These methodologies are notably based on detailed accident studies (DASs) and their adaptation to the analysis of accident reports. Colombia has an infrastructure for gathering and storing traffic accident data that can be used to perform comprehensive accident analyses. This article defines the feasibility of a technology transfer (clinical accident analysis) to the Colombian equivalent of accident reports. These observations are part of a doctoral thesis prepared jointly by the IFSTTAR Accident Mechanisms Research Unit and the University of the Andes in Bogotá.     

Profile of the accident prone older driver

Accident histories and other related records of elderly drivers were used to develop a profile of the accident prone older driver in Michigan. Elderly drivers were defined as drivers with age greater than or equal to 65 years. The variables used in the study were developed by stratifying drivers age, sex, and residency; type of accident and violation; and number of traffic infraction points received. Comparisons were made between these strata, and the statistical significance of observed patterns in cross tabulated data was tested by performing the chi-square test. The results of the study indicate that, by and large, the elderly drivers from urban areas as compared to those from rural areas, and male drivers as compared to females are more likely to be cited for traffic violations. The statistical analysis showed some recognizable traits of the “young” elderly drivers that suggest prioritized safety countermeasures oriented toward them.     

Application of Learning Automata to Controller Design in Slow-Active Automobile Suspensions

This study considers a new design methodology in the context of active vehicle suspension control. The approach combines concepts from Stochastic Optimal Control with those of Learning Automata. A learning automaton effectively learns optimal control on-line in the vehicle, in an appropriate stochastic “test-track” environment. For practical application, the overwhelming advantage of this approach is that no explicit modelling is required, and considerable time savings may be expected in system development. This simulation study considers the on-line learning of optimal control in a low-bandwidth active suspension system, where control feedback is confined to a body-mounted accelerometer at each corner of the vehicle. It is shown that learning can successfully take place under a range of conditions, including the case when there is substantial transducer noise. The performance of the resulting control system is shown to depend heavily on the nature of the learning environment.     

Optimization of tunnel tolls in land use and transport planning

The task of transport planning is to determine cost-effective methods of providing and improving mobility, which can include minimizing traffic congestion. A cost-effective solution to transport problems should consist of a land use pattern, a transport system an a set of road pricing policies that together bring demand and supply into balance in an efficient and equitable way. The conventional approach aimed to produce comprehensive, long-term plans for land use and transport in considerable detail, but tended to ignore the role of road pricing policy, thus ending up with solutions that might not be efficient or economical. This feature of sub-optimal road pricing policy is accentuated by the overall growth in car use, which has generated problems with the efficient use of road space. This paper presents a computer analysis system (or model) which will enable the analysis of coordinated tunnel toll pricing policies by optimising an “objective function” while satisfying the associated and other constraints. The possibility of integrating the optimal road pricing policies in the land use and transport planning are discussed. A case study based on Hong Kong data demonstrates the efficiency of optimizing tolls on two of the three harbour crossing tunnels in Hong Kong.