Abstract

Hybrid Electric Vehicles (HEVs) enable fuel savings by re-using kinetic and potential energy that was recovered and stored in a battery during braking or driving down hill. Besides, the vehicle itself can be seen as a storage device, where kinetic energy can be stored and retrieved by changing the forward velocity. It is beneficial for fuel consumption to optimize the velocity trajectory in two ways; i) to assist the driver in tracking an optimal velocity trajectory (e.g. input to an Adaptive Cruise Controller); ii) to estimate the future power request trajectory which can be used to optimize the hybrid components use. Taking advantage of satellite navigation, together with the vehicles current mass and road load parameters, an optimization problem is formulated, and solved for a driver defined time constraint. Despite tight velocity constraints, this can result in 5% fuel saving compared to a Cruise Controller with constant velocity setpoint. The benefit of velocity trajectory optimization is indicated with experimental results. © 2010 AACC.

Abstract

In this paper, the design and results of two cooperative driving applications are presented that both increase traffic flow on highways by reducing shockwave traffic jams and decrease the risk of head-on collisions. The first application is an advisory system based on vehicle-vehicle communication that showed positive results with a penetration level of 100% of equipped vehicles. The second application is both an advisory and automated system based on infrastructure-vehicle communication that showed positive results with a penetration level of 10%-30%.

Abstract

Road throughput can be increased by driving at small inter-vehicle time gaps. The amplification of velocity disturbances in upstream direction, however, poses limitations to the minimum feasible time gap. This effect is covered by the notion of string stability. String-stable behavior is thus considered an essential requirement for the design of automatic distance control systems, which are needed to allow for safe driving at time gaps well below 1 s. Using wireless inter-vehicle communications to provide real-time information of the preceding vehicle, in addition to the information obtained by common Adaptive Cruise Control (ACC) sensors, appears to significantly decrease the feasible time gap, which is shown by practical experiments with a test fleet consisting of six passenger vehicles. The large-scale deployment of this system, known as Cooperative ACC (CACC), however, poses challenges with respect to the reliability of the wireless communication system. A solution for this scalability problem can be found in decreasing the transmission power and/or beaconing rate, or adapting the communications protocol. Although the main CACC objective is to increase road throughput, the first commercial application of CACC is foreseen to be in truck platooning, since short distance following is expected to yield significant fuel savings in this case.

Abstract

This paper presents a new method for the design and validation of advanced driver assistance systems (ADASs). With vehicle hardware-in-the-loop (VeHIL) simulations the development process, and more specifically the validation phase, of intelligent vehicles is carried out safer, cheaper, and more manageable. In the VeHIL laboratory a full-scale ADAS-equipped vehicle is set up in a hardware-in-the-loop simulation environment, where a chassis dynamometer is used to emulate the road interaction and where robot vehicles are used to represent other traffic. In this controlled environment the performance and dependability of an ADAS is tested to great accuracy and reliability. The working principle and the added value of VeHIL are demonstrated with test results of a driver information and warning system. Based on the 'V' diagram, the position of VeHIL in the development process of ADASs is illustrated. © 2009 Elsevier Ltd. All rights reserved.

Abstract

Peak Hour Avoidance is a relatively new Dutch mobility management measure. To reduce congestion frequent car drivers are given a financial reward for reducing the proportion of trips that they make during peak hours on a specific motorway section. Although previous studies show that employers are not eager to support mobility management measures, employers are nevertheless an important stakeholder. They can provide their employees with alternatives such as other travel times, work locations or travel modes and encourage their use. This paper investigates the attitudes of Dutch employers towards Peak Hour Avoidance. Exploring the factors that influence these attitudes may help to fully utilise employer support. The data from 103 employers were collected through a web questionnaire. A structural equation model on the employer support for Peak Hour Avoidance was estimated. The results demonstrate that the size of the organisation and sector only have an indirect effect on the support for Peak Hour Avoidance. Results reveal that most support for Peak Hour Avoidance can be expected from organisations who feel responsible for influencing the commuting behaviour of employees, that have human resource managers with a positive attitude towards Peak Hour Avoidance, with flexible working times and that have already implemented mobility management measures. The largest contribution to PHA that can be expected from employers is providing employees with flexible working times and encouraging employees to fully utilise this option as an alternative for driving in peak hours. This would not only be beneficial for PHA but for a wide range of mobility management initiatives as well.

Abstract

utomated driving technology is emerging. Yet, little is known in the literature about when automated vehicles will reach the market, how penetration rates will evolve and to what extent this new transport technology will affect transport demand and planning. This study uses scenario analysis to identify plausible future development paths of automated vehicles in the Netherlands and to estimate potential implications for traffic, travel behaviour and transport planning on a time horizon up to 2030 and 2050. The scenario analysis was performed through a series of three workshops engaging a group of diverse experts. Sixteen key factors and five driving forces behind them were identified as critical in determining future development of automated vehicles in the Netherlands. Four scenarios were constructed assuming combinations of high or low technological development and restrictive or supportive policies for automated vehicles (AV ...in standby, AV ...in bloom, AV ...in demand, AV ...in doubt). According to the scenarios, fully automated vehicles are expected to be commercially available between 2025 and 2045, and to penetrate the market rapidly after their introduction. Penetration rates are expected to vary among different scenarios between 1% and 11% (mainly conditionally automated vehicles) in 2030 and between 7% and 61% (mainly fully automated vehicles) in 2050. Complexity of the urban environment and unexpected incidents may influence development path of automated vehicles. Certain implications on mobility are expected in all scenarios, although there is great variation in the impacts among the scenarios. Measures to curb growth of travel and subsequent externalities are expected in three out of the four scenario

Abstract

Weather conditions are widely acknowledged to contribute to the occurrence of congestion on motorway traffic by influencing both traffic supply and traffic demand. To the best of our knowledge, this is the first paper that explicitly integrates supply and demand effects in predicting the influence of adverse weather conditions on the probability of occurrence of congestion. Traffic demand is examined by conducting a stated adaptation experiment, in which changes in travel choices are observed under adverse weather scenarios. Based on these choices, a Panel Mixed Logit model is estimated. Supply effects are taken into account by examining the influence of precipitation on motorway capacity. Based on the Product Limit Method, capacity distribution functions are estimated for dry weather, light rain and heavy rain. With the developed model to integrate the supply and demand effects breakdown probabilities can be calculated for any given traffic demand and capacity. The results show that rainfall leads to a significant increase in the probability of traffic breakdown at bottleneck locations. Interestingly the probability of a breakdown at these bottleneck locations is predicted to be slightly higher in light rain (98.7%) than in heavy rain (95.7%) conditions, which is the result of the higher traffic demand in light rain conditions. Based on the results presented in this paper, it can be recommended to always incorporate both supply and demand effects in the predictions of motorway breakdown probabilities due to adverse weather conditions to improve the validity of the predictions. © 2015 Editorial Board EJTIR. All rights reserved.

Abstract

The effects of Cooperative Adaptive Cruise Control (CACC) on traffic flow is an important issue as traffic flow stability, capacity and safety are concerned. In contrast to most research we focus on traffic flow stability. We use the Intelligent Driver Model and CACC algorithms to assess the effects. A recently field-tested and CACC-based advisory system is also evaluated as an intermediate solution. It is found that CACC can quickly damp shockwaves at lower penetration rates (50%) and that shockwaves move faster. ©2010 IEEE.

Abstract

dvanced driver assistance systems are increasingly available on road vehicles. These systems require a thorough development procedure, an important part of which consists of hardware-in-the-loop experiments in a controlled environment. To this end, a facility called Vehicle Hardware-In-the-Loop (VeHIL) is operated, aiming at testing the entire road vehicle in an artificial environment. In VeHIL, the test vehicle is placed on a roller bench, whereas other traffic participants, i.e., vehicles in the direct neighborhood of the test vehicle, are simulated using wheeled mobile robots (WMRs). To achieve a high degree of experiment reproducibility, focus is put on the design of an accurate position control system for the robots. Due to the required types of maneuvers, these robots have independently driven and steered wheels. Consequently, the robot is overactuated. Furthermore, since the robot is capable of high-dynamic maneuvers, slip effects caused by the tires can play an important role. A position controller based on feedback linearization is presented, using the so-called multicycle approach, which regards the robot as a set of identical unicycles. As a result, the WMR is position controlled, whereas each unicycle is controlled, taking weight transfer and longitudinal and lateral tire slip into account. © 2006 IEEE.