Abstract
Various mobility services have been proposed based on the integration of automated vehicle (AV) and road infrastructure. Service providers need to identify a set of road sections for ensuring the driving safety of an AV-based mobility service. The main objective of this research is to analyze the safety performance of AVs on the road geometrical features present during this type of mobility service. To achieve the research goal, a mobility service is classified by a combination of six road types, including expressway, bus rapid transit (BRT) lane, principal arterial road, minor arterial road, collector road, and local road. With any given road type, a field test dataset is collected and analyzed to assess the safety performance of the AV-based mobility service with respect to road geometry. Furthermore, the safety performances of each road section are explored by using a historical dataset for human-driven vehicle-involved accident cases. The result reveals that most of the dangerous occurrences in both AV and human-driven vehicles show similar patterns. However, contrasting results are also observed in crest vertical curve sections, where the AV shows a lower risk of dangerous events than that of a human-driven vehicle. The findings can be used as primary data for optimizing the physical and digital infrastructure needed to implement efficient and safe AV-based mobility services in the future.
Highlights
IntroductionOne of the best alternatives to reduce labor costs and operational inefficiency for a mobility service is to incorporate an automated vehicle (AV) system into public transport [5]
Accepted: 14 February 2022Many strategies have been investigated (1) to address the limitations of current public bus transport, such as low service quality and profitability, and (2) to satisfy requirements for new mobility services, such as mobility-as-a-service and ride-hailing [1,2,3,4]
We explored the relationship between automated driving safety safety and given road type based on field test dataset
Summary
One of the best alternatives to reduce labor costs and operational inefficiency for a mobility service is to incorporate an automated vehicle (AV) system into public transport [5]. Navya operates an automated driving shuttle service in Sion, Switzerland, servicing 25 locations. In Bad Birnbach, Germany, EasyMile runs an automated shuttle service linking train stations and downtown areas. AV-based public transport services increase customer convenience by linking them with the existing public transport system, thereby effectively reducing waiting time, traffic volume, and road congestion [6]. Most previous research has forecasted that the traffic flow capacity would be increased by employing an AV system [7,8,9,10,11].
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