A PSO Enable Multi-Hop Clustering Algorithm for VANET

VANET (Vehicle Ad-hoc Network) is an emerging technology in today’s intelligent transport system. In VANET, there are many moving nodes which are called the vehicle running on the road. They communicate with each other to provide the information to driver regarding the road condition, traffic, weather and parking. VANET is a kind of network where moving nodes talk with each other with the help of equipment. There are various other things which also make complete to VANET like OBU (onboard unit), RSU (Road Aside Unit) and CA (Certificate authority). In this paper, a new PSO enable multi-hop technique is proposed which helps in VANET to Select the best route and find the stable cluster head and remove the malicious node from the network to avoid the false messaging. The false can be occurred when there is the malicious node in a network. Clustering is a technique for making a group of the same type node. This proposed work is based on PSO enable clustering and its importance in VANET. While using this approach in VANET, it has increased the 20% packet delivery ratio.

Towards Intelligent Road Traffic Management over Weighted Large Graphs Hybrid Meta-heuristic-Based Approach

This paper introduces a new approach of hybrid meta-heuristics based optimization technique for decreasing the computation time of the shortest paths algorithm. The problem of finding the shortest paths is a combinatorial optimization problem which has been well studied from various fields. The number of vehicles on the road has increased incredibly. Therefore, traffic management has become a major problem. We study the traffic network in large scale routing problems as a field of application. The meta-heuristic we propose introduces new hybrid genetic algorithm named IOGA. The problem consists of finding the k optimal paths that minimizes a metric such as distance, time, etc. Testing was performed using an exact algorithm and meta-heuristic algorithm on random generated network instances. Experimental analyses demonstrate the efficiency of our proposed approach in terms of runtime and quality of the result. Empirical results obtained show that the proposed algorithm outperforms some of the existing technique in term of the optimal solution in every generation.

Detection of Sybil attack in vehicular ad hoc networks by analyzing network performance

<span>Vehicular ad hoc network (VANET) is an emerging technology which can be very helpful for providing safety and security as well as for intelligent transportation services. But due to wireless communication of vehicles and high mobility it has certain security issues which cost the safety and security of people on the road. One of the major security concerns is the Sybil attack in which the attacker creates dummy identities to gain high influence in the network that causes delay in some services and fake voting in the network to misguide others. The early detection of this attack can prevent people from being misguided by the attacker and save them from getting into any kind of trap. In this research paper, Sybil attack is detected by first applying the Poisson distribution algorithm to predict the traffic on the road and in the second approach, analysis of the network performance for packet delivery ratio (PDR) is performed in malign and benign environment. The simulation result shows that PDR decreases in presence of fake vehicles in the network. Our approach is simple and effective as it does not require high computational overhead and also does not violate the privacy issues of people in the network.</span>

Towards Intelligent Road Traffic Management Over a Weighted Large Graphs Hybrid Meta-Heuristic-Based Approach

This paper introduces a new approach of hybrid meta-heuristics based optimization technique for decreasing the computation time of the shortest paths algorithm. The problem of finding the shortest paths is a combinatorial optimization problem which has been well studied from various fields. The number of vehicles on the road has increased incredibly. Therefore, traffic management has become a major problem. We study the traffic network in large scale routing problems as a field of application. The meta-heuristic we propose introduces new hybrid genetic algorithm named IOGA. The problem consists of finding the k optimal paths that minimizes a metric such as distance, time, etc. Testing was performed using an exact algorithm and meta-heuristic algorithm on random generated network instances. Experimental analyses demonstrate the efficiency of our proposed approach in terms of runtime and quality of the result. Empirical results obtained show that the proposed algorithm outperforms some of the existing technique in term of the optimal solution in every generation.

DESTROYING EFFECTS OF TRUCK TIRES ON THE DESIGN OF ROADWEAR

The article presents a mathematical model of the destructive effect of a wide-profile tire on the roadway. The mathematical model makes it possible to adequately reproduce the effect of a wide-profile tire on the road surface, taking into account the load and parameters of the tire, as well as the structure of the road surface and the temperature state.

EVALUATION OF THE DESIGN OF RETAINING WALLS ON THE ROAD SUKABUMI (BAROS) - SAGARANTEN KM BDG 115+200

<p>The Sukabumi (Baros) – Sagaranten Km Bdg 115+200 road section which is located in Sukabumi Regency is a road section for the province of West Java. Because the road is always damaged due to being eroded by water infiltration in the rice fields that seeps into the road body area at that location and the soil at that location tends to be unstable based on the results of lab tests having a shear angle value of 4.99ᵒ and having a specific gravity of 17.45, then it is carried out analysis of the existing damaged retaining wall and the design of a new gabion-type retaining wall at that location. The gabion retaining wall building will be designed with 3 designs, the first using a stone volume of 13 m3, the second using a stone volume of 8 m3 and the third using a stone volume of 6.5 m3. Based on the results of the calculation analysis using Rankine theory, it was found that the existing retaining wall was unable to withstand the shearing force which got a check value of 1.18 which should have a value of SF &gt; 1.5, while the 3 gabion plan buildings got the appropriate SF value, namely against the overturning force, shear force and soil bearing capacity.</p>

Evaluation of the elastic modulus of pavement layers using different types of neural networks models

Introduction. This paper studies the capability of different types of artificial neural networks (ANN) to predict the modulus of elasticity of pavement layers for flexible asphalt pavement under operating conditions. The falling weight deflectometer (FWD) was selected to simulate the dynamic traffic loads and measure the flexural bowls on the road surface to obtain the database of ANN models.Materials and Methods. Artificial networks types (the feedforward backpropagation, layer-recurrent, cascade back- propagation, and Elman backpropagation) are developed to define the optimal ANN model using Matlab software. To appreciate the efficiency of every model, we used the constructed ANN models for predicting the elastic modulus values for 25 new pavement sections that were not used in the process of training, validation, or testing to ensure its suitability. The efficiency measures such as mean absolute error (MAE), the coefficient of multiple determinations R2, Root Mean Square Error (RMSE), Mean Absolute Percent Error (MAPE) values were obtained for all models results.Results. Based on the performance parameters, it was concluded that among these algorithms, the feed-forward model has a better performance compared to the other three ANN types. The results of the best four models were compared to each other and to the actual data obtained to determine the best method.Discussion and Conclusions. The differences between the results of the four best models for the four types of algorithms used were very small, as they showed the closeness between them and the actual values. The research results confirm the possibility of ANN-based models to evaluate the elastic modulus of pavement layers speedily and reliably for using it in the structural assessment of (NDT) flexible pavement data at the appropriate time.

The efficacy of road safety education to prevent pedestrian fatalities in Limpopo Province (South Africa)

This paper explores road safety education to prevent pedestrian fatalities in Limpopo Province. Pedestrian safety remains one of the main challenges for road safety authorities as many road users are losing their lives on the road. The inability of both pedestrians and motorists to understand and interpret the rules of the road is a major problem in Limpopo Province. The study utilised quantitative approach. The sample consisted of 195 respondents. Comprises of 15 civil engineering companies, 23 civil society organisations, 52 community members, 51 teachers and 54 traffic police officials. The findings from the study revealed among many others, that 64.1% of respondents agreed that non-involvement of parents in road safety education contribute to pedestrian fatalities; 61% of the respondents agreed that ineffective scholar patrol contribute to pedestrian fatalities; 67.2% of the respondents agreed that lack of professional support in road safety contribute to pedestrian fatalities and 72% of the respondents agreed that limited resources in road safety contribute to pedestrian fatalities. Based on the findings, the author provided, possible recommendations such as; Department of Transport and Education should involve parents/guardians in road safety education; Department of Education should review scholar patrol to ensure that it assist positively in preventing pedestrian fatalities; Traffic authorities should partner with academics to provide road safety policies and strategies; Department of Transport should partner with private sector to provide resources for road safety education in Limpopo Province.