安全视角下动态共乘匹配成功率的仿真

研究在安全视角下，动态共乘系统对于出行个体的匹配建模与仿真结果分析。构建动态共乘匹配模型框架，并分别建立乘客安全信任演化模型、政策导向影响模型、平台安全投入影响模型和安全事件影响模型，通过系统仿真的方式获得运行数据，以此评价政策宣传密集度和强度、平台安全投入强度、司机对安全投入敏感度和高危安全事件发生概率等因素对司乘匹配成功率的影响。研究结果表明，政府主导的监管模式相对于平台主导模式而言更能显著提升司乘匹配成功率，而政府和共享乘车平台的双重监管模式对司乘匹配率的提升最为有效。同时，政府政策导向宣传作用和平台安全投入作用均存在一定的衰减效应，政府与平台需要把控监管的时机和度量问题。特别地，平台可以重点关注对安全投入敏感度更高的司机，这类司机更容易在受监管的情况下规范自身行为，使得平台的安全投入更加行之有效。

Matching Modeling of Dynamic Ridesharing with Consideration of Safety

Under the influence of safety, a dynamic ridesharing system for individual travelers was built and the simulation results were analyzed. A framework for the dynamic ride-sharing model was constructed, with sub-models including passenger safety trust, policy orientation, platform safety investment and safety events respectively. The operation data were obtained through computational simulation to evaluate the influence of policy publicity and information intensity of policy as well as platform safety investment on the matching rate between drivers and passengers. The results demonstrate that the dual supervision system of government and platform leads to a remarkable enhancement on the matching rate. Besides, policy guidance has an important impact on the driver-passenger matching rate. Short-term policy publicity is conductive to the promotion of matching rate. However, as the publicity activities continues, the effectiveness of the promotion also decreases. Similarly, the intensity of platform safety investment has an analogous attenuation effect on the growth of driver-passenger matching rate. In particular, drivers who are more sensitive to platform safety investment are supposed to gain more focus so as to make the investment measures more efficient.