Safe driving is a relatively new concept that focuses on solving the responsibility attribution problem for autonomous vehicles (AVs), claiming that once the AVs follow a series of pre-defined safe… Click to show full abstract
Safe driving is a relatively new concept that focuses on solving the responsibility attribution problem for autonomous vehicles (AVs), claiming that once the AVs follow a series of pre-defined safe driving policies, it is free from liability even when accidents happen. In this work, we propose safe driving policies for traffic configurations, including straight road, intersection, and Manhattan-like city. Base on the defined safe driving policies, we offer the concepts of safe driving capacity (SDC) and safe driving throughput (SDT) to measure the safe efficiency of the traffic configurations. The former measures the maximum AVs a traffic configuration could accommodate, and the latter measures the maximum throughputs of safe AVs of a traffic configuration. The values obtained are the fundamental limits of the traffic efficiencies for liability-free AVs under the defined conditions. The theoretical performance bounds give people insights on the potential limitations of the safe traffic efficiencies. Finally, this work provides analytical results of SDC and SDT on all the traffic configurations mentioned with explanations, implications, and trade-offs on the issues that may have effects on them.
               
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