Driving Adaptability Analysis And Evaluation Of Automation Systems On As-built Roadway Geometry

Although the main contents of driving function layers,i.e.,perception,decision,and control,between the automated systems and human drivers are still the same,there are obvious differences between them in the operational approaches,modes,and performance.Therefore,with the introduction of driving-automation-system-equipped vehicles(AVs)having different automation levels into the existing road-traffic system and the gradual replacement of drivers by systems,it is necessary to re-examine the coupling relationship between AVs and their essential carrier,road infrastructures.As the construction of road infrastructures has been basically completed,the driving adaptability of AVs to as-built road geometry is a critical issue that should be clarified in the process of promoting AV implementation.However,previous studies focused on the AVs’ safety only at important traffic nodes mainly from the traffic perspective,or assumed AVs’ functions significantly ideally.Those studies ignore the actual effects of various road geometric elements and different automation levels,and consider inadequately the possible conditions reflecting/affecting the actual perception,decision,and control performance.Therefore,to conduct a thorough and accurate analysis of the influence mechanism between AV operating characteristics(i.e.sight distances and kinematics/dynamics responses)and road geometry,and,consequently,to evaluate AVs’ driving adaptability from the perspective of the sight-distance requirement,driving safety,comfort,and speed consistency,this study with a concern of the potential risk of AVs on as-built roadway geometric conditions considered the functional distinctions among different automation levels and adopted the advantageous test method,i.e.,virtual test technology.Firstly,with a focus on the functional distinctions between drivers and system individuals,this paper illustrated and summarized those distinctions within and between various automation levels from the perspective of actors’(i.e.,drivers and systems)roles and driving technology architectures,and extracted the distinctions-associated geometric elements.The current computational models of those associated elements were modified by parameterizing those extracted distinctions,which consequently examined the correspondence between the current geometry specification and AVs.Secondly,using those extracted distinctions and associated elements mentioned above as the requisite testing scenario elements,the establishment methods of element models/blocks based on independent simulation platforms(including Pre Scan,Car Sim,and MATLAB/Simulink)were clarified.According to the interaction and integration structure of those models/blocks,the multi-platform integration process and co-simulation steps were clarified.The effectiveness of the established joint simulation platform was verified from the perspective of AV’s available sight distances(ASDs)and the performance of the adaptive cruise control(ACC)system.Thirdly,the representative conditions of geometry and AV functional characteristics were selected,followed by creating a series of test trials through the general scenario definition rules to detect AVs’ ASDs.With the testing results,the influence mechanism of the conditions of various roadway geometry and Light detection and ranging(Li DAR)sensor-related detecting technology on ASD characteristics was analyzed,followed by proposing ASD-oriented AV safe speeds.Finally,the typical parameters reflecting the kinematics/dynamics characteristics of traditional human-driven vehicles were extracted and transplanted as the main outputs of ACC functional feature tests.Then,numerous test trials were designed and created in accordance with the above general definition rules,and were executed.With the testing results,the influence mechanism of various geometry conditions on AVs’ typical kinematics/dynamics response parameters were analyzed,followed by extracting safety and comfort-oriented key geometry conditions.The actual operational characteristics of various AV’s automation levels were considered in this study,which establishes a virtual testing and analyzing framework for assessing the AVs’ driving adaptability to roadway geometry and provides a more thorough explanation of the coupling mechanism between AV operational characteristics and geometric elements.The results of this study can be compatible with the constantly updated automated driving technology,and can provide an effective testing framework,data basis,and important theoretical basis for the comprehensive evaluation of the driving adaptability to the overall roadway conditions for a more realistic AV.