Using advanced analytics to frame vulnerable road user scenarios with autonomous vehicles [R6]
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Connected and automated vehicle (CAV) technologies can dramatically improve safety by reducing human errors, which contribute substantially (an estimated 94 percent) to roadway crashes. CAVs can eventually operate effectively on roadways without experiencing decreased performance due to distraction or fatigue.However, technological advances will not uniformly decrease crash risks. Some environments, crash types, and user groups will continue to experience elevated risks, particularly vulnerable road users such as pedestrians.This project will address these critical safety issues by: Assessing the current and future landscape of pedestrian and vehicle conflicts.Identifying how vehicle technology, planning policies, and data analytics can provide systemic solutions to pedestrian-vehicle conflicts.Using big data analytics f' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Automated guided vehicle systems","Behavior","Countermeasures","Crashes","Intelligent vehicles","Pedestrians","Pedestrians and bicyclists","Planning and forecasting","Risk analysis","Vulnerable road users"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Connected and automated vehicle (CAV) technologies can dramatically improve safety by reducing human errors, which contribute substantially (an estimated 94 percent) to roadway crashes. CAVs can eventually operate effectively on roadways without experiencing decreased performance due to distraction or fatigue.However, technological advances will not uniformly decrease crash risks. Some environments, crash types, and user groups will continue to experience elevated risks, particularly vulnerable road users such as pedestrians.This project will address these critical safety issues by: Assessing the current and future landscape of pedestrian and vehicle conflicts.Identifying how vehicle technology, planning policies, and data analytics can provide systemic solutions to pedestrian-vehicle conflicts.Using big data analytics f' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Connected and automated vehicle (CAV) technologies can dramatically improve safety by reducing human errors, which contribute substantially (an estimated 94 percent) to roadway crashes. CAVs can eventually operate effectively on roadways without experiencing decreased performance due to distraction or fatigue.However, technological advances will not uniformly decrease crash risks. Some environments, crash types, and user groups will continue to experience elevated risks, particularly vulnerable road users such as pedestrians.This project will address these critical safety issues by: Assessing the current and future landscape of pedestrian and vehicle conflicts.Identifying how vehicle technology, planning policies, and data analytics can provide systemic solutions to pedestrian-vehicle conflicts.Using big data analytics f
Automated guided vehicle systems; Behavior; Countermeasures; Crashes; Intelligent vehicles; Pedestrians; Pedestrians and bicyclists; Planning and forecasting; Risk analysis; Vulnerable road users