Anticipatory information makes the difference: Behavioral effects and user assessments of a cyclist warning system to enhance cyclists' situation awareness

PROBLEM

Increasing numbers of crashes involving pedelecs, and particularly older pedelec users, induce a need to enhance cycling safety. We evaluated a prototype cyclist warning system (CWS) that aims to increase situation awareness (SA) by alerting to safety critical events (SCE) with trimodal (auditory, visual, tactile).

METHOD

To investigate the effects of CWS usage, we conducted a 2x2 mixed design bicycle simulator study with factors (1) CWS usage (within: rides WITH vs. WITHOUT CWS) and (2) age group (between: younger vs. older cyclists) on braking reaction time, gaze behavior, mental workload, and perceived safety. In sum, N = 64 participants (n = 32 younger, 18-40 years; n = 32 older, ≥ 55 years) took part in the study and experienced two balanced blocks of short rides including SCE of particular relevance for cycling safety.

RESULTS

CWS usage resulted in earlier braking reactions to all investigated SCE and partly earlier fixation on the critical interaction partners (CIP) indicating increased cyclists' SA. Consistently to behavioral measures, participants' assessments regarding perceived safety further supported the safety improvements derived from CWS independently of age group. Moreover, CWS usage did not add to mental workload ratings. Age effects were selectively found for gaze data showing that across all SCE, older adults fixated longer and more frequently on street alignment, and less frequently on other road users.

DISCUSSION

Taken together, the CWS evaluation showed promising results indicating the potential of the tested CWS to increase SA and enhance cyclists' safety both on a behavioral level and regarding subjective assessments. Further research should address the systems' safety potential under real-world conditions and for situations of higher complexity.

PRACTICAL APPLICATIONS

Understanding the potential impact of road safety measures such as CWS is important to contribute effectively to reducing SCE.

Support systems for cyclists in automated traffic: A review and future outlook

Interaction with vulnerable road users in complex urban traffic environments poses a significant challenge for automated vehicles. Solutions to facilitate safe and acceptable interactions in future automated traffic include equipping automated vehicles and vulnerable road users, such as cyclists, with awareness or notification systems, as well as connecting road users to a network of motorised vehicles and infrastructure. This paper provides a synthesis of the current literature on communication technologies, systems, and devices available to cyclists, including technologies present in the environment and on motorised interaction partners such as vehicles, and discusses the outlook for technology-driven solutions in future automated traffic. The objective is to identify, classify, and count the technologies, systems, and devices that have the potential to aid cyclists in traffic with automated vehicles. Additionally, this study aims to extrapolate the potential benefits of these systems and stimulate discourse on the implications of connected vulnerable road users. We analysed and coded 92 support systems using a taxonomy of 13 variables based on the physical, communicational, and functional attributes of the systems. The discussion frames these systems into four categories: cyclist wearables, on-bike devices, vehicle systems, and infrastructural systems, and highlights the implications of the visual, auditory, motion-based, and wireless modes of communication of the devices. The most common system was cyclist wearables (39%), closely followed by on-bike devices (38%) and vehicle systems (33%). Most systems communicated visually (77%). We suggest that interfaces on motorised vehicles accommodate cyclists with visibility all around the car and incorporate two-way communication. The type of system and the effect of communication modality on performance and safety needs further research, preferably in complex and representative test scenarios with automated vehicles. Finally, our study highlights the ethical implications of connected road users and suggests that the future outlook of transport systems may benefit from a more inclusive and less car-centred approach, shifting the burden of safety away from vulnerable road users and promoting more cyclist-friendly solutions.

Analysis of Modern vs. Conventional Development Technologies in Transportation-The Case Study of a Last-Mile Delivery Process

Transportation plays a significant role in the global economy and society and takes part in a lot of different processes such as mass transportation and the supply chain. Therefore, it is crucial to introduce modern technologies in this area of the economy in the context of Industry 4.0. The main scope of this study is to develop a model that supports analyzing last-mile logistics modern solutions using the latest technologies such as road autonomous delivery robots (RADRs), civil drones, or smart bikes, and compare them to conventional solutions (delivery vehicles). Multi-criteria decision analysis (MCDA) was applied to build a formal comparison model that scores the solutions and weights different criteria according to decision-makers and placeholders, to rank the solutions from the most crucial option to the weakest in a predetermined scenario with set parameters and conditions (three varied scenarios were included in the present investigation). The results of the model were in favor of using civil drones or smart bicycles to perform light deliveries in small urban areas (these key findings support the assumptions that are often manifested in speech in the context of the use of new technologies). The modern solutions scored almost 40-80% higher in total in the conglomeration of assessment criteria (such as safety, economy, laws and regulations, operation time for the delivery, environment, and payload) than the conventional solution, which indicates the importance of studying the implementation of such technologies. An interesting result of the study is the operational cost reduction by ca. 60-74% in favor of autonomous delivery robots, 89-93% in favor of civil delivery drones, and 87-90% in favor of smart bikes vs. conventional delivery trucks/vans. Yet, it should be underlined that the results may vary with different assumptions within the MCDA method.