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Traffic Management for Emergency Vehicle Priority Based on Visual Sensing

机译:基于视觉的应急车辆优先交通管理

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摘要

Vehicular traffic is endlessly increasing everywhere in the world and can cause terrible traffic congestion at intersections. Most of the traffic lights today feature a fixed green light sequence, therefore the green light sequence is determined without taking the presence of the emergency vehicles into account. Therefore, emergency vehicles such as ambulances, police cars, fire engines, etc. stuck in a traffic jam and delayed in reaching their destination can lead to loss of property and valuable lives. This paper presents an approach to schedule emergency vehicles in traffic. The approach combines the measurement of the distance between the emergency vehicle and an intersection using visual sensing methods, vehicle counting and time sensitive alert transmission within the sensor network. The distance between the emergency vehicle and the intersection is calculated for comparison using Euclidean distance, Manhattan distance and Canberra distance techniques. The experimental results have shown that the Euclidean distance outperforms other distance measurement techniques. Along with visual sensing techniques to collect emergency vehicle information, it is very important to have a Medium Access Control (MAC) protocol to deliver the emergency vehicle information to the Traffic Management Center (TMC) with less delay. Then only the emergency vehicle is quickly served and can reach the destination in time. In this paper, we have also investigated the MAC layer in WSNs to prioritize the emergency vehicle data and to reduce the transmission delay for emergency messages. We have modified the medium access procedure used in standard IEEE 802.11p with PE-MAC protocol, which is a new back off selection and contention window adjustment scheme to achieve low broadcast delay for emergency messages. A VANET model for the UTMS is developed and simulated in NS-2. The performance of the standard IEEE 802.11p and the proposed PE-MAC is analysed in detail. The NS-2 simulation results have shown that the PE-MAC outperforms the IEEE 802.11p in terms of average end-to-end delay, throughput and energy consumption. The performance evaluation results have proven that the proposed PE-MAC prioritizes the emergency vehicle data and delivers the emergency messages to the TMC with less delay compared to the IEEE 802.11p. The transmission delay of the proposed PE-MAC is also compared with the standard IEEE 802.15.4, and Enhanced Back-off Selection scheme for IEEE 802.15.4 protocol [EBSS, an existing protocol to ensure fast transmission of the detected events on the road towards the TMC] and the comparative results have proven the effectiveness of the PE-MAC over them. Furthermore, this research work will provide an insight into the design of an intelligent urban traffic management system for the effective management of emergency vehicles and will help to save lives and property.
机译:世界各地的车辆交通都在无休止地增加,并且可能导致十字路口的交通拥堵严重。如今,大多数交通信号灯都具有固定的绿灯序列,因此在确定绿灯序列时并未考虑紧急车辆的存在。因此,卡在交通拥堵中并延误到达目的地的紧急车辆,例如救护车,警车,消防车等,可能导致财产损失和宝贵生命。本文提出了一种调度紧急车辆通行的方法。该方法使用视觉感应方法,车辆计数和传感器网络内对时间敏感的警报传输,结合了对紧急车辆和十字路口之间距离的测量。使用欧几里得距离,曼哈顿距离和堪培拉距离技术计算出紧急车辆与十字路口之间的距离以进行比较。实验结果表明,欧氏距离优于其他距离测量技术。除了使用视觉传感技术来收集应急车辆信息外,使用媒体访问控制(MAC)协议以更少的延迟将应急车辆信息传递到交通管理中心(TMC)非常重要。这样,只有紧急车辆才能得到快速服务,并且可以及时到达目的地。在本文中,我们还研究了无线传感器网络中的MAC层,以区分紧急车辆数据的优先级并减少紧急消息的传输延迟。我们使用PE-MAC协议修改了在标准IEEE 802.11p中使用的媒体访问过程,这是一种新的退避选择和竞争窗口调整方案,可实现紧急消息的低广播延迟。在NS-2中开发并仿真了UTMS的VANET模型。详细分析了标准IEEE 802.11p和建议的PE-MAC的性能。 NS-2仿真结果表明,在平均端到端延迟,吞吐量和能耗方面,PE-MAC优于IEEE 802.11p。性能评估结果证明,与IEEE 802.11p相比,提出的PE-MAC优先考虑了紧急车辆数据,并以较小的延迟将紧急消息发送到TMC。还将拟议的PE-MAC的传输延迟与标准IEEE 802.15.4和用于IEEE 802.15.4协议[EBSS(用于确保在道路上快速传输检测到的事件的现有协议)的增强型退避选择方案”进行比较对TMC的评估],比较结果证明了PE-MAC相对于它们的有效性。此外,这项研究工作将为有效管理紧急车辆提供智能城市交通管理系统设计的见识,并有助于挽救生命和财产。

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