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This paper describes the development of an Advanced Driver Assistance System (ADAS) which will allow drivers to avoid collisions with an oncoming vehicle from an occluded area when turning right at intersections in left-hand traffic. Connected vehicles, in coordination with infrastructure, represent one of the commercialized ADAS technologies for collision avoidance. However, the coverage of the ADAS will be limited to designated intersections only, as communication equipment needs to be installed in both the vehicle and infrastructure to enable the assistance. This paper proposes an ADAS using on-board sensors, independent of infrastructure facilities, to control the vehicle velocity to avoid collisions. Most current intersection assistance, by using an Autonomous Emergency Braking System (AEBS), allows the driver to avoid a collision with oncoming vehicles when there is clear vision without occlusion. However, many accidents occur when the vehicle detects the oncoming vehicle too late because of occlusion in the intersection, such as a vehicle in the opposite lane. This system calculates the hazardous speed criteria of the ego vehicle, which might result in a high risk of collision when darting out occurs, and provides speed control assistance to allow the driver to escape from the hazardous speed region. The simulation results reveal that the proposed system effectively reduces the possibility of collisions compared to conventional AEBS. [ABSTRACT FROM AUTHOR]

This paper proposes an innovative framework of modeling the statistical properties of the near-accident event and pedestrian behavior at non-signalized intersections based on Poisson process and logistic regression. The first contribution of this study is that the predictive intensity model of the near-accident event is established by regarding the near-accident event as a Poisson process on space of the vehicle velocity, distance to the intersection and lateral distance to the pedestrian at the time when pedestrian appears. Besides, logistic regression is used to build the model which can predict the probability of pedestrian behavior. The two proposed models are validated in a generative simulation. The simulated pedestrian behavior data is generated by the proposed models and compared with the real data. The real data set is from the drive recorder data base of Smart Mobility Research Center (SMRC) at Tokyo University of Agriculture and Technology. Accident and near-accident data has been collected in the city streets with an image-captured drive recorder mounted on a taxi since 2006. The findings in this study are expected to be useful for constructions of traffic simulators or safety control design which considers the pedestrian-vehicle interaction. [ABSTRACT FROM AUTHOR]

The demand for autonomous electric public transport is increasing globally. New vehicle models and variants are increasing the development complexity and hence the overall development time. Therefore, there is a requirement for a vehicle-packaging tool that can translate user inputs into an optimised vehicle package and can be visualised instantly. The aim of this paper is to develop a parametric tool for designing different concepts for electric autonomous buses. The scope of application is intended in the early phase of the vehicle development process to enable a fast and efficient creation of a flexible bus concept. Through a graphical user interface (GUI), the user is able to size and select all the required components for the autonomous vehicle concepts. The vehicle specification is initiated by selection of one of the three classes of vehicle, the desired number of passengers and then the bus interior's seat arrangement design. An appropriate powertrain and chassis will then automatically be configured in the next steps. The HVAC simulation allows for the design of different components of the refrigeration circuit to ensure proper cabin temperature. For evaluating the concept, the energy consumption is analysed through simulations, and an estimated initial cost of vehicle concepts and individual systems completes the concept. A spider chart summarises all characteristics and offers an overview of the vehicle concept, providing the possibility to compare with other concepts simultaneously. The tool can create 9600 different bus concepts and provides interfaces for expansion. [ABSTRACT FROM AUTHOR]