Modelling driver distraction effects due to mobile phone use on reaction time

Phone use during driving causes decrease in situation awareness and delays response to the events happening in driving environment which may lead to accidents. Reaction time is one of the most suitable parameters to measure the effect of distraction on event detection performance. Therefore, this paper reports the results of a simulator study which analysed and modelled the effects of mobile phone distraction upon reaction time of the Indian drivers belonging to three different age groups. Two different types of hazardous events: (1) pedestrian crossing event and (2) road crossing event by parked vehicles were included for measuring drivers’ reaction times. Four types of mobile phone distraction tasks: simple conversation, complex conversation, simple texting and complex texting were included in the experiment. Two Weibull AFT (Accelerated Failure Time) models were developed for the reaction times against both the events separately, by taking all the phone use conditions and various other factors (such as age, gender, and phone use habits during driving) as explanatory variables. The developed models showed that in case of pedestrian crossing event, the phone use tasks: simple conversation, complex conversation, simple texting and complex texting caused 40%, 95%, 137% and 204% increment in the reaction times and in case of road crossing event by parked vehicles, the tasks caused 48%, 65%, 121% and 171% increment in reaction times respectively. Thus all the phone use conditions proved to be the most significant factors in degrading the driving performance.     

Personalised feedback and eco-driving: An explorative study

Conventional road transport has negative impact on the environment. Stimulating eco-driving through feedback to the driver about his/her energy conservation performance has the potential to reduce CO₂ emissions and promote fuel cost savings. Not all drivers respond well to the same type of feedback. Research has shown that different drivers are attracted to different types of information and feedback. The goal of this paper is to explore which different driver segments with specific psychographic characteristics can be distinguished, how these characteristics can be used in the development of an ecodriving support system and whether tailoring eco-driving feedback technology to these different driver segments will lead to increased acceptance and thus effectiveness of the eco feedback technology. The driver segments are based on the value orientation theory and learning orientation theory. Different possibilities for feedback were tested in an exploratory study in a driving simulator. An explorative study was selected since the choice of the display (how and when the information is presented) may have a strong impact on the results. This makes testing of the selected driver segments very difficult. The results of the study nevertheless suggest that adapting the display to a driver segment showed an increase in acceptance in certain cases. The results showed small differences for ratings on acceptation, ease of use, favouritism and a lower general rating between matched (e.g., learning display with learning oriented drivers) and mismatched displays (e.g., learning display with performance oriented drivers). Using a display that gives historical feedback and incorporates learning elements suggested a non-verifiable increase in acceptance for learning oriented drivers. However historical feedback and learning elements may be less effective for performance oriented drivers, who may need comparative feedback and game elements to improve energy conserving driving behaviour.     

驾驶员可靠性评价中评估因子的遴选

驾驶员可靠性评估因子的选择是进行驾驶员可靠性评价的关键。本文首先进行驾驶员可靠性分析,找到驾驶员可靠性研究的特点,然后根据道路交通事故的发生原因得出驾驶员失误模式,最后使用专家判断隶属度的方法筛选出有效的驾驶员可靠性评估因子。     

Handling qualities evaluation method based on actual driver characteristics

The present study proposes an objective handling qualities evaluation method using driver-in-the-loop analysis. The driving simulator experiments were performed for various driving conditions, drivers and vehicle dynamics. The response characteristics of the driver model and the closed-loop system were analyzed. The analysis revealed the driving strategies clearly, indicating the importance of closed-loop analysis. Using the identified driver model and its strategies, a cost function of the handling qualities was constructed. The cost function can be used to estimate the handling qualities analytically from the vehicle dynamics. The proposed method was validated by comparison with the handling qualities evaluation rated by the driver's comments.     

电机控制系统主电路及驱动电路的设计

本文中选用的无刷直流电动机的电机本体采用星形连接的三相对称绕组,同时功率器件组成的逆变器为桥式电路。文章主要叙述了控制系统的硬件电路设计过程。以EasyARM2100开发板为核心的控制单元,主电路及驱动单元行了阐述,并对硬件设计也作出了相应的解释。     

基于驾驶员行为模拟的ACC控制算法

基于驾驶员最优预瞄加速度模型建立了一种适用于多种典型行驶工况的ACC控制算法。该算法采用基于多目标模糊决策方法的驾驶安全性、工效性、轻便性与合法性评价指标以及基于预瞄跟随理论的微分校正函数，描述了ACC控制系统对自由工况、跟随工况和切入工况等不同行驶条件及汽车动力学系统强非线性特性的考虑。     

驾驶员运动感觉及其评价

本文提出三类感觉模拟的评价方法：主观评价，生理心理效应评价及计算机仿真评价，利用前庭系统模型，拟定了驾驶员运动感觉模拟逼真度的仿真评价方程式，并对汽车动态仿真器运动驱动算法进行了仿真评价。仿真结果表明，本文采用的前庭系统模型在所用频率范围内具有可信的精度，用它评价运动感觉模拟逼真度是行之有效的。     

A methodology to increase driver trust in rear-obstacle warning systems with imperfect sensing results — Proposal for a warning system using sensor reliability information

Driver's workload tends to be increased during driving under complicated traffic environments like lane-changing operation. In such cases, rear collision warning is effective for reduction of cognitive workload. On the other hand, it is pointed out that false alarm or missing alarm caused by sensor errors leads to decrease of driver trust in the warning system and it can result in low efficiency of the system. Suppose that sensor reliability information is provided in real-time. In this paper, we propose a novel warning method to increase driver trust in the system even with low sensor reliability by utilizing sensor reliability information. We investigate the effectiveness of the warning methods in high and low workload situations by driving simulator experiments.     

汽车驾驶员车速控制模式的模拟研究

系统地对汽车驾驶员在一定行车环境中的安全性认知与车速控制的决策、推理过程进行了定量研究,通过进行一系列勘测、测试和心理评价试验,应用模糊集合、模糊统计试验、模糊控制和模糊逻辑推理等分析方法,建立了描述汽车驾驶员在既定道路条件下行车时基于安全性考量的逻辑推理规则和车速控制模型,最后进行了相应的实测验证。模拟预测结果与实测结果吻合较好,证明了研究所采用方法和建立模型的正确性。     

Exploring the impact of connected and autonomous vehicles on freeway capacity using a revised Intelligent Driver Model

ABSTRACT

Connected and autonomous vehicle (CAV) technologies are expected to change driving/vehicle behavior on freeways. This study investigates the impact of CAVs on freeway capacity using a microsimulation tool. A four-lane basic freeway segment is selected as the case study through the Caltrans Performance Measurement System (PeMS). To obtain valid results, various driving behavior parameters are calibrated to the real traffic conditions for human-driven vehicles. In particular, the calibration is conducted using genetic algorithm. A revised Intelligent Driver Model (IDM) is developed and used as the car-following model for CAVs. The simulation is conducted on the basic freeway segment under different penetration rates of CAVs and different freeway speed limits. The results show that with an increase in the market penetration rate, freeway capacity increases, and will increase significantly as the speed limit increases.