Estimation of lateral offset and drift angle for application in secondary collision avoidance system

Recent reports show that the secondary collision on the road gives much higher fatality rate than the other traffic accidents. Many studies have been carried out to prevent the secondary accidents and as a result automotive companies began to introduce brake-based secondary collision avoidance systems. To prevent the secondary accidents it is important to monitor and control the lateral deviation of the vehicle after the primary collision. An estimator for the vehicle’s lateral offset and drift angle based on the in-vehicle sensors and the camera was developed in this paper. By employing sensor fusion scheme and applying extended Kalman filter, the estimator has been designed so that it works even when the camera loses the image of the lanes due to sudden change of the vehicle’s heading angle. For validation of the estimator, simulation has been carried out on various collision scenarios. The simulation results indicated that the estimator of this paper could calculate the vehicle’s lateral deviation with robustness that may be required for application in the secondary collision avoidance systems.     

Experimental and 3D,embedded modeling for diesel engine SCR deposit

Nowadays, the selective catalytic reduction (SCR) is a promising solution to fulfill stringent nitrogen oxide (NO_X) emission standards enforced by worldwide regulation bodies for lean burning engines. However, in the practical operation, urea deposits occur under unfavorable conditions, which bring about a failure of urea dosing strategy, affect the SCR system de-NOx performance and lowering the fuel economy by increasing the engine back pressure. This paper will present 3D deposit model, which can be used to predict the deposit position. Furthermore, a model-based controls strategy and calibration are designed. The comparison test results of both engine emission tests and vehicle field tests shows there is significant deposits improvement with the embedded model.     

Drowsy behavior detection based on driving information

Drowsy behavior is more likely to occur in sleep-deprived drivers. Individuals’ drowsy behavior detection technology should be developed to prevent drowsiness related crashes. Driving information such as acceleration, steering angle and velocity, and physiological signals of drivers such as electroencephalogram (EEG), and eye tracking are adopted in present drowsy behavior detection technologies. However, it is difficult to measure physiological signal, and eye tracking requires complex experiment equipment. As a result, driving information is adopted for drowsy driving detection. In order to achieve this purpose, driving experiment is performed for obtaining driving information through driving simulator. Moreover, this paper investigates effects of using different input parameter combinations, which is consisted of lateral acceleration, longitudinal acceleration, and steering angles with different time window sizes (i.e. 4 s, 10 s, 20 s, 30 s, 60 s), on drowsy driving detection using random forest algorithm. 20 s-size datasets using parameter combination of accelerations in lateral and longitudinal directions, compared to the other combination cases of driving information such as steering angles combined with lateral and longitudinal acceleration, steering angles only, longitudinal acceleration only, and lateral acceleration only, is considered the most effective information for drivers’ drowsy behavior detection. Moreover, comparing to ANN algorithm, RF algorithm performs better on processing complex input data for drowsy behavior detection. The results, which reveal high accuracy 84.8 % on drowsy driving behavior detection, can be applied on condition of operating real vehicles.     

Experimental investigations on continuous regenerative anti-lock braking system of full electric vehicle

Functions of anti-lock braking for full electric vehicles (EV) with individually controlled wheel drive can be realized through conventional brake system actuating friction brakes and regenerative brake system actuating electric motors. To analyze advantages and limitations of both variants of anti-lock braking systems (ABS), the presented study introduces results of experimental investigations obtained from proving ground tests of all-wheel drive EV. The brake performance is assessed for three different configurations: hydraulic ABS; regenerative ABS only on the front axle; blended hydraulic and regenerative ABS on the front axle and hydraulic ABS on the rear axle. The hydraulic ABS is based on a rule-based controller, and the continuous regenerative ABS uses the gain-scheduled proportional-integral direct slip control with feedforward and feedback control parts. The results of tests on low-friction road surface demonstrated that all the ABS configurations guarantee considerable reduction of the brake distance compared to the vehicle without ABS. In addition, braking manoeuvres with the regenerative ABS are characterized by accurate tracking of the reference wheel slip that results in less oscillatory time profile of the vehicle deceleration and, as consequence, in better driving comfort. The results of the presented experimental investigations can be used in the process of selection of ABS architecture for upcoming generations of full electric vehicles with individual wheel drive.     

Electrochemical battery model and its parameter estimator for use in a battery management system of plug-in hybrid electric vehicles

This paper reports the development of a battery model and its parameter estimator that are readily applicable to automotive battery management systems (BMSs). Due to the parameter estimator, the battery model can maintain reliability over the wider and longer use of the battery. To this end, the electrochemical model is used, which can reflect the aging-induced physicochemical changes in the battery to the aging-relevant parameters within the model. To update the effective kinetic and transport parameters using a computationally light BMS, the parameter estimator is built based on a covariance matrix adaptation evolution strategy (CMA-ES) that can function without the need for complex Jacobian matrix calculations. The existing CMA-ES implementation is modified primarily by region-based memory management such that it satisfies the memory constraints of the BMS. Among the several aging-relevant parameters, only the liquid-phase diffusivity of Li-ion is chosen to be estimated. This also facilitates integrating the parameter estimator into the BMS because a smaller number of parameter estimates yields the fewer number of iterations, thus, the greater computational efficiency of the parameter estimator. Consequently, the BMS-integrated parameter estimator enables the voltage to be predicted and the capacity retention to be estimated within 1 % error throughout the battery life-time.     

Required traffic micro‐simulation runs for reliable multivariate performance estimates

Previous methods to calculate the minimum number of traffic micro‐simulation runs do not consider multiple measures of performance simultaneously at an overall confidence level, which can lead to unreliable simulation outputs. This paper describes new methodologies for calculating the minimum number of traffic micro‐simulation runs for multivariate estimates at an overall confidence level. Simultaneous confidence intervals obtained from multiple comparisons in statistical theory such as the Bonferroni inequality and simultaneous confidence interval method are used to estimate multiple measures of performance with allowable errors at an overall confidence level. Measures of performance can be means and standard deviations. Results of numerical analysis based on an example corridor suggest that the proposed methods provide improved means of assessing statistical accuracy of multiple measures of performance. Results also indicate that the minimum number of runs is influenced by not only the sample size issue but also the complexity of the traffic system. Copyright © 2015 John Wiley & Sons, Ltd.     

Ridership estimation procedure for a transit corridor with new bus rapid transit service

Ridership estimation is a critical step in the planning of a new transit route or change in service. Very often, when a new transit route is introduced, the existing routes will be modified, vehicle capacities changed, or service headways adjusted. This has made ridership forecasts for the new, existing, and modified routes challenging. This paper proposes and demonstrates a procedure that forecasts the ridership of all transit routes along a corridor when a new bus rapid transit (BRT) service is introduced and existing regular bus services are adjusted. The procedure uses demographic data along the corridor, a recent origin–destination survey data, and new and existing transit service features as inputs. It consists of two stages of transit assignment. In the first stage, a transit assignment is performed with the existing transit demand on the proposed BRT and existing bus routes, so that adjustments to the existing bus services can be identified. This transit assignment is performed iteratively until there is no adjustment in transit services. In the second stage, the transit assignment is carried out with the new BRT and adjusted regular bus services, but incorporates a potential growth in ridership because of the new BRT service. The final outputs of the procedure are ridership for all routes and route segments, boarding and alighting volumes at all stops, and a stop‐by‐stop trip matrix. The proposed ridership estimation procedure is applicable to a new BRT route with and without competing regular bus routes and with BRT vehicles traveling in dedicated lanes or in mixed traffic. The application of the proposed procedure is demonstrated via a case study along the Alameda Corridor in El Paso, Texas. Copyright © 2015 John Wiley & Sons, Ltd.     

Identifying a behaviourally relevant choice set from stated choice data

Stated choice experiments are designed optimally in a statistical sense but not necessarily in a behavioural choice making sense. Statistical designs, and consequently model estimation, assume that the set of alternatives offered in the experiment are processed by respondents with a specific processing strategy. Much has been studied about attribute processing using discrete choice methods in travel choice studies, but this paper focuses more broadly on processing of alternatives in the choice set offered in the experiment. This paper is motivated by the primary idea that the distribution of predicted choice probabilities associated with a set of alternatives defining a given choice set might provide strong evidence on the strategies that agents appear to use when choosing a preferred alternative. In an empirical setting of a choice set of size three, four model specifications are considered including a model for the selection of the best alternative in the full choice set and three variants of a best–worst regime. Using state choice data on road pricing reform, the empirical analysis examines which model specification delivers the most accurate prediction of the chosen alternative. The results suggest which alternatives really matter in choice making and hence the alternatives that might be included in a choice set for model specification.     

Stability analysis of the classical car-following model

This paper investigates the stability of the classical car-following model (for example, Chandler et al., Operations Research, 6, 165–184, 1958; Herman et al., Operations Research, 7, 86–106, 1959; Wilhelm and Schmidt, Transportation Engineering Journal (ASCE) 99, 923–933, 1973). Conditions for local and asymptotic stability as defined in the references cited are established for the linear model. These differ from those in the literature in two ways. First, it will be shown that, in the autonomous model when the product of the coefficient of proportionality α and the reaction time τ is less than or equal to 1/e, there exist oscillatory solutions with higher frequencies than 2π, although there are none with lower frequencies. Secondly, asymptotic stability is considered along with local stability. The derived condition for asymptotic stability is both necessary and sufficient. In addition, the condition depends on the frequency of the forcing term, with the sufficient condition for the asymptotic stability found in the literature being included as a special case. The nonlinear model is considered by linearization and numerical integrations. Some practical values of parameters are tested for the stability of the model. The analyses in this paper are extended to consider different values of α and τ for different drivers in the line.