Vehicle trajectory challenge in predictive active steering rollover prevention

High center of mass vehicles are likely to rollover in extreme maneuvers. Available works present control strategies to prevent rollover. In these works, however, other important parameters such as path trajectory tracking are not a main concern. In this paper conflicts between rollover prevention and trajectory tracking is investigated. Model predictive control (MPC) is adopted to predict and avoid rollover while tracking desired trajectory. For this regard a model based future error estimation is introduced. The control framework predicts both rollover and trajectory error simultaneously. It avoids rollover while tries to track the trajectory. Simulation results for two controllers with and without trajectory tracking are presented. The results indicate that the controllers effectively limit rollover as a hard constraint while the trajectory tracking controller also minimizes and recovers the path error.     

Design and validation of an electro-hydraulic brake system using hardware-in-the-loop real-time simulation

This paper presents a novel electric booster (E-booster) that exibits superior performance advantages over traditional vacuum boosters. The proposed E-booster, consisting of an electric motor and a ball screw assembly, is designed for electro-hydraulic brake (EHB) systems to meet relevant requirements for electric vehicles and active safety technologies. A mathematical model for an EHB system is generated to determine the desired values of the parameters for the E-booster prototype using numerical simulation in MATLAB. Simulation results of the EHB system with the virtual E-booster demonstrate the feasibility and effectiveness of the innovative technique. Built upon the results derived from the numerical simualtions, an integrated algorithm based on the Kalman filter and a sliding mode control technique is designed to control the E-booster motor and to implement the brake booster function. A hardware-in-the-loop (HIL) real-time simulation system equipped with the E-booster prototype is developed. HIL real-time simulations are conducted to evaluate the proposed algorithm. The HIL real-time simulation results demonstrate that the proposed algorithm generates booster brake forces fast, and forces the ball nut to track the push rod well to ensure comfortable brake pedal feel.     

Shape optimization of a torsion beam axle for improving vehicle handling performance

In this study, shape optimization was conducted for a vehicle’s rear suspension torsion beam to improve its dynamic handling performance. To determine the design variables affecting the vehicle roll characteristics, a sensitivity analysis was conducted using the result of a Taguchi experiment with 6 factors in 8 runs. The upper and lower-flange lengths and web thickness of the torsion beam section, as well as the vertical height difference between the inner and outer of torsion beams, were determined as design variables through sensitivity analysis of the opposite wheel travel test for optimization of the torsion beam axle. The Box–Behnken experimental design with 4 factors and 27 runs was performed using the selected design variables and by performing opposite wheel travel analysis according to the experimental design, and the response surface functions of the roll stiffness, roll steer coefficient, roll center height, and mass of the torsion beam were generated. Using these response functions, shape optimization was conducted for the torsion beam of the rear suspension system. Dynamic performance analysis was performed by applying the optimized H-shaped torsion beam to the rear suspension of the vehicle dynamics model, and it was validated that the dynamic response performance of the optimized vehicle was improved.     

Cyclist target and test setup for evaluation of cyclist-autonomous emergency braking

From 2018, Autonomous Emergency Braking (AEB) systems dedicated to avoid or mitigate passenger car-tocyclist collisions will be considered in the safety assessment by Euro NCAP. To test such systems, appropriate equipment has been developed in a project called CATS “Cyclist-AEB Testing System”, that has run between April 2014 and August 2016. Moreover, a proposal for the most relevant test scenarios was set up. The objective of the project was to provide proof to Euro NCAP of the relevance of the proposed test scenarios and of the feasibility of practical implementation of the scenarios and test setup. The process regarding the selection, verification and validation of test scenarios is described. The cooperation between 17 industrial partners (car manufacturers and automotive suppliers) in the CATS project has stimulated the harmonization and acceptance of the protocol, target and test setup. The process and intermediate results including the used methodology, have been reviewed by the German Federal Highway Research Institute (BASt) and have been shared on a regular basis during the project with stakeholders in Europe, Japan and the USA. Euro NCAP already indicated to consider the results of the CATS project as the main input to draft the test protocol, including scenarios and target for Cyclist-AEB systems in 2018 and 2020.     

MPC-BASED steering control for backward-driving vehicle using stereo vision

We propose a steering control algorithm for autonomous backward driving in a narrow corridor. Passable spaces are detected using a stereo camera, and the steering angle is controlled by a model predictive controller (MPC). For passable space detection, an UV-disparity map is calculated from the original disparity map. Information regarding passable spaces collected by the stereo camera is used in steering control. Backward driving requires the driver’s preemptive actions, which can be learned by experience because of the non-intuitive responses (the initial motion of the vehicle is opposite to the driver’s steering angle input). This occurs because a backward-driving vehicle is a non-minimum phase system. One of the most popular steering control algorithms is Stanley method, which is based on the feedback of lateral displacement error and heading angle error. The method is very intuitive and works well for forward driving, but it exhibits significant undershoot for backward driving cases. Furthermore, the method does not explicitly consider any constraints on control inputs and states. We designed a steering controller based on the MPC technique that requires future information but can handle constraints explicitly. Because we have near-future information from the stereo camera under limited passable spaces, MPC can be effectively implemented. We performed several simulations and experiments to show the performance and superiority of the suggested method over a simple feedback-based control algorithm.     

Direct tire force generation algorithm based on non-iterative nonlinear inverse tire model

The function of vehicle dynamics control system is adjusting the yaw moment, the longitudinal force and lateral force of a vehicle body through several chassis systems, such as brakes, steering and suspension. Individual systems such as ESC, AFS and 4WD can be used to achieve desired performance by controlling actuator variables. However, integrated chassis control systems that have multiple objectives may not simply achieve the desired performance by controlling the actuators directly. Usually those systems determine the required tire forces in an upper level controller and a lower level controller regulates the tire forces through the actuators. The tire force is controlled in a recursive way based on vehicle state measurement, which may not be sufficient for fast response. For immediate force tracking, we introduce a direct tire force generation method that uses a nonlinear inverse tire model, a pseudo-inverse model of vehicle dynamics and the relationship between longitudinal force and brake pressure.     

Integrating land use and transport knowledge in strategy-making

There is broad and growing consensus regarding the central place of integrated Land Use and Transport (LUT) strategy development in establishing more efficient and sustainable urban environments. However, empirical evidence shows that such integration is hard to achieve in daily planning practice, due to many institutional barriers and substantive differences. More specifically, the tools developed to support LUT strategy development have very low implementation rates in daily planning practice. This paper introduces the concept of ‘knowledge generation’ as a potentially useful mechanism for closing the gap between support tools and planning practice. Through two specific Dutch planning cases, we analyze the applicability of this concept in supporting integrated LUT strategy development. The paper focuses on the developed strategies, how these differ from current practice, and how knowledge generation supported their development. We argue that socialization produces shared strategies and that effective socialization needs to be supported by efficient mutual exchange between tacit and explicit knowledge. We conclude by discussing the implications of this argument for the wider practice of LUT planning integration.     

Generation of synthetic datasets for discrete choice analysis

Despite the widespread use of synthetic data in discrete choice analysis, little is known about how the methodology used to generate synthetic datasets influences the properties of parameter estimates and the validity of results based on these estimates. That is, there are two potential sources of biases when using synthetic discrete choice data: (1) bias due to the method used to generate the dataset; and, (2) bias due to parameter estimation. The primary objective of this study is to examine bias due to the underlying data generation method. This study compares three methods for generating synthetic datasets and uses design of experiments and analysis of variance methods to investigate the ability to recover estimates for “true” logsum parameters for nested logit models. The method that uses nested logit probabilities to generate the chosen alternative results in unbiased parameter estimates. The method that is based on Gumbel error component approximations reveals that while the error components themselves are unbiased, subtle empirical identification problems can arise when these error components are combined with synthetically generated utility functions. The method that is based on normal error component approximations reveals that all logsum coefficients are biased upwards; the bias dramatically increases for those nests that have a low choice frequency and is most pronounced for those nests with high correlations among alternatives. Based on the results of the analysis, several recommendations for the generation of synthetic datasets for discrete choice analyses are provided.     

Explaining public transport information use when a car is available: attitude theory empirically investigated

Despite recent investments in and growing availability of various public transport information services, levels of apparent non-use (of particular information services) across the population remain high. Policymakers and information service providers could benefit from a better understanding of factors affecting information use. The goal of this paper is to provide more insight into the (non-)use of public transport information by applying attitude theory. A postal survey was sent to a random sample of 10,000 households in Bristol and Manchester, UK. The response rate was 13%. Respondents were questioned about an uncertain journey they were going to make. Structural equation modelling has been used to investigate interdependencies among the factors studied. The results show that the desire to consult public transport information for an uncertain journey is affected by attitudes, subjective norms, and past behaviour. These social-psychological factors are in turn affected by constraints such as travel behaviour and trip context. Crucially in terms of addressing issues of non-use of information it is found that consulting information is influenced by propensity to consider using public transport rather than vice versa as has hitherto been implicitly assumed by many involved in the provision of transport and information services.     

A joint flexible econometric model system of household residential location and vehicle fleet composition/usage choices

Modeling the interaction between the built environment and travel behavior is of much interest to transportation planning professionals due to the desire to curb vehicular travel demand through modifications to built environment attributes. However, such models need to take into account self-selection effects in residential location choice, wherein households choose to reside in neighborhoods and built environments that are conducive to their lifestyle preferences and attitudes. This phenomenon, well-recognized in the literature, calls for the specification and estimation of joint models of multi-dimensional land use and travel choice processes. However, the estimation of such model systems that explicitly account for the presence of unobserved factors that jointly impact multiple choice dimensions is extremely complex and computationally intensive. This paper presents a joint GEV-based logit regression model of residential location choice, vehicle count by type choice, and vehicle usage (vehicle miles of travel) using a copula-based framework that facilitates the estimation of joint equations systems with error dependence structures within a simple and flexible closed-form analytic framework. The model system is estimated on a sample derived from the 2000 San Francisco Bay Area Household Travel Survey. Estimation results show that there is significant dependency among the choice dimensions and that self-selection effects cannot be ignored when modeling land use-travel behavior interactions.