Dataset Information

User Evaluation of Passenger Assistance System Concepts on Public Highways.

ABSTRACT: There is ample research on assistance systems for drivers in conventional and automated vehicles. In the past, those systems were developed to increase safety but also to increase driver comfort. Since many common risks have by now been mitigated through such systems, the research and development focus expanded to also include comfort-related assistance. However, the passenger has rarely been taken into account explicitly, although it has been shown that passenger discomfort is a relevant problem. Therefore, this work investigated the potential of passenger assistance systems to reduce such discomfort. Three different passenger assistant system prototypes were tested in a driving study on public highway with N = 19 participants. The systems provided information about parameters related to the performance of the driver and one additionally provided a communicative means of influence. For two passenger assistant systems, it could be shown that they significantly reduced passenger discomfort in at least a subset of the evaluated situations. The majority of participants rated one or multiple of the assistant systems as more comfortable than a ride without assistance. The system providing information about the attentiveness of the driver was most effective in reducing discomfort and was rated as the most helpful system. The results show that explicitly considering the situation of passengers in the design of assistance systems can positively impact their comfort. This can be achieved using information from common systems targeting driver assistance available to the passenger.

SUBMITTER: Ittner S

PROVIDER: S-EPMC8696277 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The front seat passenger is often neglected when developing support systems for cars. There exist few examples of systems that provide information or interaction possibilities specifically to those passengers. Previous research indicated that the passive role of the passenger can frequently lead to a feeling of discomfort, potentially caused by missing information and missing control with respect to the driving situation. This paper investigates if and how different aspects of cognitive processes as defined in a previously published model can be approached with a technical system to reduce discomfort in passengers. Five prototypical passenger assistance systems are created which provide missing information (for example about the attentiveness of the driver) or the possibility to have more influence as a passenger. In a static simulator study with N = 40 participants, these systems were investigated with respect to their influence on measures of discomfort. Participants experienced in a counterbalanced order car following and braking scenarios on the highway with different time headways (within-subjects), with and without one of the passenger assistance systems (between-subjects). Based on the subjective measures for each experienced situation, three systems were identified as particularly useful in reducing discomfort. These displayed the attentiveness of the driver, the safety distance to a vehicle in front or provided the possibility to signal the driver that the recent safety distance is too small. These best proposals significantly reduced passenger discomfort in the tested Following and Braking scenarios for different time headways. In the post inquiry, more than 64% of the passengers confirmed the helpfulness of the rated system in reducing their discomfort in each case and about 75% of the passengers reported an interest in using it in their vehicle. This demonstrates opportunities to improve the everyday driving experience beyond classical assistance systems by explicitly considering the needs of passengers.

Project description:Even-headway timetables with easy to memorize departure times are commonly in use in public transport (PT) service. In addition, some PT services are using timetables where their departure times are based on even-passenger-load at the max-load stop along the route. In practice, these two types of timetables are implemented in daily operation plans, allowing for their merits, with the former maintaining the initial, even-interval departure rules and conventions, especially when a new PT line is planned without available demand information, while the latter is demand-oriented, exhibiting fluctuation in time and space. The principles of creating the aforementioned timetables have been presented in the literature, but very few evaluations feasibly attest to performance by means of mathematical analysis. Concentrating on building a modelling framework for PT timetabling problems during the planning stage, this work is taking into account 1) passengers’ service-frequency satisfaction, in terms of waiting times, 2) passengers’ perception of riding comfort, in terms of seat availability, and 3) planned passengers’ load ratio (concerning vehicle’s capacity) linked with operation efficiency. Yielding to the models developed in a theoretical manner, the comparative evaluation is conducted through multiple timetable schemes that include four different dimensions: (A) even-headway departures with same headway throughout the time horizon, (B) even-load departures with same load throughout the time horizon, (C) even-headway departures for each demand-dependent period, and (D) even-load departures for each demand-dependent period. Finally, a case study in Nantong, China examines the comparison performances produced and the best plans for operational timetables. The results indicate that travelers attributed great importance to higher satisfaction preferences on frequency or headway-related experience linked with their waiting time. Electronic Supplementary Material Supplementary material is available in the online version of this article at 10.1007/s12205-022-1231-x.

Dataset Information

User Evaluation of Passenger Assistance System Concepts on Public Highways.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets