3. MATERIALS I MÈTODES
3.5. Estudis in vitro
The system proposed in Chapter 5 and evaluated in early sections in this chapter is improved and extended in this section. It has been improved by means of introducing a novel message propagation algorithm through VANETs, and the effectiveness of the system was validated by means of extended simulation results (These earlier works were based on macroscopic traffic modelling).
In Figure 6.12, it presents simulation results for the average delay propagation [s] that occurs with V2X, adopted in ICDMS, and the traditional multi-hop technique for disaster management. It verifies the effectiveness of our approach –in terms of a reduction of delay– as compared with a traditional opportunistic networking scheme in VANET.
DISASTER MANAGEMENT SYSTEM
The Al-Ramadi city is considered to measure the effectiveness of proposing the time message algorithm. Also, the propagation of warning messages from a vehicle near the glass factory is simulated, where the incident happens at 9:00 am. In particular, for ICDMS approach, the following events occur:
(i) just after the incident has occurred, a source vehicle travelling in the S direction from the glass factory sends a message along on the same direction;
(ii) at t = 4 sec., the message is propagated multi-hop within a cluster in the S direction; (iii) at t = 7 sec., a relay vehicle enters an RSU‟s radio coverage, and the message is
transmitted via V2I to the RSU, until it will be received by other vehicles at t = 10 sec.
A comparison is made for this scenario with traditional opportunistic networking technique in VANETs, where the following events occur:
(i) just after the incident has occurred the source vehicle travelling in the S direction from the glass factory sends a message along on the same direction;
(ii) at t = 4 sec., the message is forwarded to a vehicle in the N (opposite) direction; (iii) at t = 6 sec., the message propagates via multi-hop within a cluster in the S direction; (iv) the transmission stops at t = 10 sec.
For comparative purposes, in the simulation setup we posed parameters according to [214]. We assume the source vehicle is moving at 70 km/h, the inter-RSU and inter-vehicular distance is 500 and 100 m, respectively. Typical message size L = 300 bit, and data rate transmission B = 10 Mbit/s (e.g., for WiMAX connectivity), have been assumed. The inter- vehicle communication data rate has been assumed equal to 6 Mbit/s, while data rates via V2I and I2V are in the range [2.5, 14] Mbit/s.
DISASTER MANAGEMENT SYSTEM
Figure 6.12 Delay propagation in the transportation network of the Al-Ramadi city, comparison between V2X used in DMS and the traditional approach for disaster scenario
A strong reduction in the delay propagation has been noticed with respect to other forms of opportunistic networking: after t = 10 sec. from the incident occurrence, the maximum transmission delay in intelligent disaster management system is 6.81 sec., while 30.45 sec. for the traditional multi - hop approach. The reduction of delay in intelligent disaster management system is mainly due to the protocol switching decision of V2X, which exploits high data rates from wireless network infrastructure.
SOFTWARE MODEL
7
TRANSPORTATION EVACUATION
SIMULATION SOFTWARE MODEL
The emphasis on implementing a disaster management system does not necessarily mean avoiding exposure to disasters utterly, but it could be also designed to minimize/mitigate losses when applicable. On this basis, many emergency evacuation systems have been proposed to warn and evacuate a person, group and community during different threat situations. Meanwhile, prior disaster warning; alerting people in advance or at least immediately before the disaster occurs, would give distinctive and effective results especially in the areas that are susceptible to frequent disasters.
The study concerning disasters and strategies is the first step towards giving the best opportunities to support the concept of disaster strategies management and thus the ability to develop the decision support tools including choosing the best strategy as much as possible for the types available [221] and [101].
In this study, the simulation models approach is exploited, macro-simulation software to evaluate the proposed intelligent disaster management system and micro-simulation software; improving a micro-simulation model via developing a software model, to investigate the proposed system performance on improving the decision for evacuation strategies.
In this chapter, the city model contains the ITS controllers (the in – vehicle sensors and the roadside signs and applications) which pass messages to vehicles in order to help to change the driver‟s behaviours. Those messages come from the user, via the external SNMP controller. In other words, an external software model has been developed for the aim of this project, it‟stheITScontroller– where the SPreadSHeet is the user interface of this model. It‟s theinnovativecomponentandit‟stheonethatpassesthosemessages.
SOFTWARE MODEL
Section 7.1 is dedicated to define a wide range of important fundamentals that affect the credibility of the project. Section 7.2 reviews some simulation models that have been developed and used to improve the traffic ability. We present and compare between some simulation models which employed in such disaster management problem. This is to show the features of each model and justify the model selection. Subsequently, we introduce the S- Paramics ITS System features in Section 7.3. In Section 7.4, we describe the development process of the software model for studying urban networks and specifically for evacuation strategies implementing.