由于出租车的数量管制,以及出租车行业一直没有一个有效的调配系统,导致交通拥塞、时间浪费和耗油量增加。而车联网(Internet Of Vehicle,IOV)的迅速发展,给传统出租车行业带来了新的契机。在该背景下,针对国内出租车行业出现的问题,提出基于车联网中管-云-端架构的智能打车系统。该系统采用新型车载智能终端,功能强大的云平台和实用的客户端应用。从终端信息感知、数据处理到顶层的应用展示来进行模块化功能描述和分析。该系统能显著提高用户满意度、司机积极性和整体运营性能。最后,通过将该智能打车系统应用于现实场景证明了它的价值。结果表明,该系统的服务性能优于现存的多数打车系统。
In order to improve the broadcast reception rates of beacon messages in vehicle ad-hoc networks,a conclusion that the relationship between collision probability and minimum contention window size and the relationship between expiration probability and minimum window size was reached by building a Markov model. According to this conclusion, a back-off algorithm based on adjusting the size of minimum contention window called CEB is proposed, and this algorithm is on the basis of the differential size between the number of expiration beacons and preset threshold. Simulations were done to compare the performance of CEB with that of RBEB and BEB, and the results show that the performance of the new proposed algorithm is better than that of RBEB and BEB.
