Low Vehicle Density Research Articles

Towards Delay Tolerant Networking for Connectivity Aware Routing Protocol for VANET-WSN Communications

Vehicular Ad Hoc Networks (VANETs) are increasingly playing a fundamental role in improving driving safety. However, VANETs in a sparse environment may add risk to driving safety. The probability of a low density of vehicles in a rural area at midnight is very high. Consequently, the packet will be lost due to the lack of other vehicles, and the arrival of the following vehicles in the accident area is unavoidable. To overcome this problem, VANET is integrated with Wireless Sensor Network (WSN). The most challenging features of VANETs are their high mobility. This high mobility causes sensor nodes to consume most of their energy during communication with other nodes, leading to frequent network disconnectivity. With the evolution of VANET and WSN, the Store/Carry-Forward (SCF) paradigm has emerged as an exciting research area in the Delay Tolerant Networks (DTNs) to solve network disconnectivity. This paper proposes the Energy-Mobility-Connectivity aware routing protocol (EMCR) for a hybrid network of VANET-WSN. A comprehensive performance analysis that considers realistic propagation models and real city scenario traffic is performed in NS3. The simulation results show that the SCF mechanism is essential in the EMCR protocol to maximize the delivery ratio and minimize energy consumption and overhead.

Analyzing the effect of fixed and moving bottlenecks on traffic flow and car accidents in a two-lane cellular automaton model

Traffic bottleneck is considered as one of the major causes of the disturbance in traffic flow. The understanding the dynamics between vehicles and bottlenecks is crucial for enhancing traffic flow and ensuring road safety. This research examines a two-lane traffic cellular automaton model to understand the effects of static (e.g., lane reductions) and dynamic (e.g., slow-moving vehicles) bottlenecks on traffic flow and road safety. We found that at low vehicle densities, slow vehicles gravitate towards the open lane, while faster vehicles switch lanes to overtake, returning to their original lane post-bottleneck. At high densities, traffic flow near static bottlenecks ceases, independent of bottleneck length. Safety analysis shows that extended static bottlenecks reduce rear-end collision risk due to fewer lane changes and increased vehicle stationarity. At maximum density, gridlock nullifies the chance of such collisions. Our findings provide actionable insights for traffic planning focused on bottleneck management to improve road safety.

Performance of a Link in a Field of Vehicular Interferers With Hardcore Headway Distance

The Poisson point process (PPP) is not always a realistic model for the locations of vehicles along a road, because it does not account for the safety distance a driver maintains from the vehicle ahead. In this article, we model the inter-vehicle distance equal to the sum of a constant hardcore distance and a random distance following the exponential distribution. Unfortunately, the probability generating functional of this point process is unknown. To approximate the Laplace transform of interference at the origin, we devise simple approximations for the variance and skewness of interference, and we select suitable probability functions to model the interference distribution. When the coefficient-of-variation and the skewness of interference distribution are high, the PPP (of equal intensity) approximation of the outage probability becomes loose in the upper tail. Relevant scenarios are associated with urban microcells and highway macrocells with a low density of vehicles. The predictions of PPP deteriorate with a multi-antenna maximum ratio combining receiver and temporal indicators related to the performance of retransmission schemes. Our approximations generate good predictions in all considered cases.

Reducing violation behaviors of pedestrians considering group interests of travelers at signalized crosswalk

Violating traffic signals behaviors of Pedestrians are common phenomenon. How to reduce or even eliminate these dangerous behaviors has attracted deep attention from researchers and governments. This paper proposes signal control algorithm considering dual-flow (SCACDF), which prioritizes the interests of travelers groups and aims to use real-time traffic data to predict future short-term traffic conditions, redistribute the green time for pedestrians and vehicles, timely meet the traffic demand of pedestrians and reduce the probability of traffic accidents. A typical signalized crosswalk is employed as a case study. Experiments, which are implemented in AnyLogic software, are conducted to investigate the impact of the proposed algorithm under different levels of traffic demand (pedestrian demand and vehicle demand) scenarios. The results show that compared with traditional timing signal control, the proposed algorithm could reduce pedestrian violation rates and improve traffic safety in multiple scenarios. Under low vehicle density, the pedestrian violation rate dropped respectively by 28.8% and 45.3% on average when the green splits ratio is 0.5 and 0.7. Especially when the green splits ratio is relatively large, the pedestrian violation rate drops from 22.6% to 14.3% under the proposed control algorithm. In most cases, the re-segmentation of the red-man phase under the proposed algorithm could have a certain negative impact on vehicle traffic per unit time. However, when the green splits ratio is 0.5, the algorithm even improves the total traffic volume per unit time including pedestrians and passengers. In addition, the factors that affect the proposed algorithm and the optimal scope of application are also briefly discussed.

FWDP: A fuzzy logic-based vehicle weighting model for data prioritization in vehicular ad hoc networks

In vehicular ad hoc networks (VANETs), data propagation is quite challenging due to the high mobility of vehicles, the instability of communication links, and the inherent topology changes. This paper presents FWDP, a fuzzy logic-based vehicle weighting model (VWM) for scheduling prioritized data in VANETs. FWDP employs roadside units (RSUs) to dominate the frequent topology changes and manage the data propagation. A Fuzzy C-Mean clustering (FCMC) is used for handling clustered vehicles that compete to utilize the shared channel. RSUs receive prioritized data from cluster heads (CHs) in the proposed model wherein CHs allocate scheduled service channels to weighted vehicles during an interval. FWDP is equipped with a fuzzy inference system (FIS) for vehicle weighting according to the velocity and inter-vehicle distance metrics. In addition, RSUs compute the signal-to-noise and the interference ratio (SINR) to solve the hidden terminal problem to prevent radio interference. The OMNET++ simulator is used to show the performance improvement of FWDP in terms of the packet delivery ratio, interference ratio, suspend data ratio, Throughput, end-to-end delay, channel utilization, and packet loss ratio metrics intended for low, intermediate, and high vehicle densities.

Effect of individual differences on the jamming transition in traffic flow.

The individual difference, particularly in drivers' distance perception, is introduced in the microscopic one-dimensional optimal velocity model to investigate its effect on the onset of the jamming instability seen in traffic systems. We show analytically and numerically that the individual difference helps to inhibit the traffic jam at high vehicle densities while it promotes jamming transition at low vehicle densities. In addition, the jamming mechanism is further investigated by tracking how the spatial disturbance travels through traffics. We find that the jamming instability is uniquely determined by the overall distribution of drivers' distance perception rather than the spatial ordering of vehicles. Finally, a generalized form of the optimal velocity function is considered to show the universality of the effect of the individual difference.

Transmission Control Method for Data Retention Taking into Account the Low Vehicle Density Environments

Transmission Control Method for Data Retention Taking into Account the Low Vehicle Density Environments

Road network layout based multi-hop broadcast protocols for Urban Vehicular Ad-hoc Networks

In recent years, the decentralized wireless Vehicular Ad hoc Networks (VANETs) have emerged as a key technology for Intelligent Transportation Systems (ITS). The need for an efficient and reliable broadcast protocol, mainly in urban VANETs, is of great importance to support different services such as road safety, traffic efficiency, entertainment and advertisement. This paper proposes two new routing broadcast protocols: the Enhanced Counter-based broadcast protocol in Urban VANET (ECUV) and the Enhanced distance-based broadcast protocol in Urban VANET (EDUV). Both of them improve the distribution of data on urban VANETs. ECUV and EDUV use a road-network-topology-based approach to select a set of relay nodes with enhanced coverage capabilities during the data delivery in urban Vehicle to Vehicle (V2V) scenarios. They also improve the performance of the receiver-based protocols by alleviating the negative effect of their stochastic behavior. We study the behavior of these protocols with an analytical model, which shows that the enhanced versions reduce the transmission probability in high vehicle density to avoid the broadcast storm problem. Moreover, the obtained results proved that these proposed protocols increase the transmission probability in low vehicle density to satisfy the reachability requirement of data broadcasting. The network simulation results show clearly that ECUV and EDUV outperform other methods in terms of coverage capacity and efficiency.

New Discrete Cuckoo Search Optimization Algorithms for Effective Route Discovery in IoT-Based Vehicular Ad-Hoc Networks

Recently, the Internet of Things (IoT) is widely considered in vehicular ad-hoc networks (VANETs) for use in intelligent transportation systems. In particular, the pervasive deployment of different sensors in modern vehicles has unlocked interesting possibilities for improving routing performance in VANETs. Nevertheless, the discovery of short single loop-free routes for effective and efficient information dissemination in VANETs remains a challenge. This challenge proves more difficult to solve since it reduces to the case of finding the shortest Hamiltonian path for effective routing in VANETs. Consequently, in this paper, we propose two discretized variants of the cuckoo search optimization (CSO) algorithm, namely, the Levy flight-based discrete CSO (LF-DCSO) and the random walk-based discrete CSO (RW-DCSO) for effective route discovery in VANETs. In addition, we investigated the inverse mutation operator gleaned from genetic algorithm (GA) in order to improve the exploration properties of our DCSO variants. We describe a new objective function that effectively models the reliability of individual links between nodes that comprise a single route. A detailed report of the routing protocol that controls the routing process is presented. Our proposed methods were compared against the roulette wheel-based GA and the improved k-means-based GA termed IGAROT. Specifically, our findings reveal that there was no significant difference in the performance of the different methods in the low vehicle density scenario, however, in the medium vehicle density scenario, the RW-DCSO algorithm achieved 2.56%, 100%, and 128.57% percentage increment in its route reliability score over the LF-DCSO, RW-GA, and IGAROT algorithms, respectively. Whereas in the high vehicle density scenario, the LF-DCSO algorithm achieved a percentage increment of 42.85%, 525%, and 733.33% in the route reliability score obtained over the RW-DCSO, IGAROT, and RW-GA algorithms, respectively. Such results suggest that our methods are able to guarantee effective routing in VANETs.

Independent Mix Zone for Location Privacy in Vehicular Networks

The sensitive information of vehicles is related to location in vehicular networks. Pseudonym change is an effective way to protect the location privacy of vehicles, which is to establish a specific area called mix zone, where at least $k$ number of vehicles change pseudonyms together to obtain $k$ anonymity. However, it depends on the number of collaborative ones in spatiotemporal context. To solve the pseudonym change problem in the low density of vehicles, an independent mix zone scheme, shorted for indMZ, is proposed in this paper. It specifies a pseudonym scheme for the vehicular networks, which consists of the procedures of certification issuance and pseudonym issuance. Each vehicle will have $L$ pseudonyms when it enrolls to a road side units. As a pseudonym is about to be expired, the vehicle can establish a mix zone through beacon messages which are inherently broadcasted in neighborhood periodically. The independent mix zone means that each of the collaborative vehicles will produce some randomized versions of a pseudonym, respectively, and contribute to the desired $k$ -anonymous mix zone. Even in the worst case of zero collaborator, the vehicle can still establish a $k$ anonymous pseudonym change region all by itself. We evaluate indMZ and other mix zone schemes with respective to the performance and strength of location privacy in the low density of vehicular networks. It shows that indMZ can ensure $k$ anonymity with $k/2$ average cost of extended beacon message and be independent on any trusted third party.

Modelling unmanned aerial vehicles base station in ground‐to‐air cooperative networks

After disasters, road side units, which can provide wireless communications to vehicles, may fail due to physical damages or power outages. Vehicle-to-vehicle communication also may not perform well owing to lack of neighbours in low vehicle density scenario or collisions in high vehicle density circumstance which may happen in disaster areas. In this study, the deployment of unmanned aerial vehicles (UAVs) as flying base stations to improve connectivity among vehicles in disaster affected areas is analysed. First, the connectivity among vehicles as a function of the altitude of the UAV is derived. Furthermore, multiple UAVs scenario is analysed to determine the minimum number of UAVs needed to guarantee a target connectivity threshold among vehicles for a given geographical area and vehicle density. Numerical and simulation results verify that there exist optimal UAV altitudes for different scenarios as shown in the authors' analyses, and the simulation results also verify that the number of UAVs must be larger than a certain value to guarantee a target connectivity threshold among vehicles.

Efficient message delivery in hybrid sensor and vehicular networks based on mathematical linear programming

In this paper, we address the timely message delivery problem in Hybrid Sensor and Vehicular Networks (HSVNs). We formulate the problem as a bi-objective binary linear program with twofold goals: (1) to ensure real-time and accurate delivery of sensed information from roadside nodes (roadside units (RSU) and sensor nodes) to the sink, and (2) to extend the network’s lifetime by inciting the roadside nodes to essentially perform sensing tasks and to act as relay nodes only when needed (e.g. network disconnections, low density of vehicles, etc.). The proposed linear programming model has been tested on several network topologies, and the experimental results have shown that small and medium size problems can be resolved in reasonable time.

The effect of motor vehicle emission towards lead (Pb) content of rice field soil with different clay content

Motor vehicle gas emission contains lead (Pb) which is a hazardous and toxic substance. Agricultural land, especially rice field, which is located nearby roads passed by many motor vehicle, are susceptible to the accumulation of Pb. If Pb is permeated by plants cultivated in the rice field, it will be very hazardous for humans as they are the final consumers. Hence, it is essential to identify Pb content of rice-field soil initiated by motor vehicle gas emission. This study was aimed to identify the effects of motor vehicle density, the distance between rice-field and road, and the clay content of soil towards Pb content of soils in Blitar and Ngawi Regencies of East Java. The method used for the study was survey method managed by using three-factor nested design with three replicates. The results of this study showed that motor vehicle density and the distance of rice field to road provide significant affected the total of Pb content of soil. However, the dissemination pattern of Pb in the soil was irregular due to the factors of climate and environment. Before Pb reached soil surface, Pb was spread out in the air due to the effect of temperature, wind velocity, vehicle velocity, size of vehicle, and road density. Consequently, the location with low motor vehicle density and positioned faraway to the road had higher total rate of Pb than the location with high motor vehicle density and positioned nearby the road. Clay content affected the total rate of Pb content as much as 37%, every 1% increase of clay content increased the total rate of Pb as much as 0.08 mg/kg.

Effect of interactions between vehicles and pedestrians on fuel consumption and emissions

This paper presents a study of variations of fuel consumption and emissions of vehicles due to random street crossings of pedestrians. The pedestrian and vehicle movement models as well as the interaction model between the two entities are presented. Extensive numerical simulations of single and multiple cars are carried out to investigate the traffic flow rate, vehicle average speed, fuel consumption, CO, HC and NOx emissions. Generally more noncompliant road-crossings of pedestrians lead to higher level of fuel consumptions and emissions of vehicles, and the traffic situation can be improved by imposing higher vehicle speed limit to some extent. Different traffic characteristics in low and high vehicle density regions are studied. The traffic flow is more influenced by crossing pedestrians in the low vehicle density region, while in the high vehicle density region, the interactions among vehicles dominate. The main contribution of this paper lies in the qualitative analysis of the impact of the interactions between pedestrians and vehicles on the traffic, its energy economy and emissions.

Using topology and neighbor information to overcome adverse vehicle density conditions

Vehicular networks supporting cooperative driving on the road have attracted much attention due to the plethora of new possibilities they offer to modern Intelligent Transportation Systems. However, research works regarding vehicular networks usually obviate assessing their proposals in scenarios including adverse vehicle densities, i.e., density values that significantly differ from the average values, despite such densities can be quite common in real urban environments (e.g. traffic jams). In this paper, we study the effect of these hostile conditions on the performance of different schemes providing warning message dissemination. The goal of these schemes is to maximize message delivery effectiveness, something difficult to achieve in adverse density scenarios. In addition, we propose the Neighbor Store and Forward (NSF) scheme, designed to be used under low density conditions, and the Nearest Junction Located (NJL) scheme, specially developed for high density conditions. Simulation results demonstrate that our proposals are able to outperform existing warning message dissemination schemes in urban environments under adverse vehicle density conditions. In particular, NSF reduces the warning notification time in low vehicle density scenarios, while increasing up to 23.3% the percentage of informed vehicles. As for high vehicle density conditions, NJL is able to inform the same percentage of vehicles than other existing approaches, while reducing the number of messages up to 46.73%.

Analysis of Factors that Affect the Frequency of Truck Parking Violations in Urban Areas

It has been estimated that the illegal parking of parcel delivery vehicles is the third leading cause of urban nonrecurring congestion, behind vehicle crashes and construction. However, little has been done to investigate the causes of illegal parking by trucks and to develop mitigation strategies. As an exploratory step toward addressing truck parking problems in urban areas, this study analyzed data on truck parking citations in Chicago, Illinois, to identify factors that affected the high density of violations. A geographic information system was used to analyze hot spots. The analysis showed that parking problems were generally worse in or near downtown and became less prevalent toward the outer perimeter of the city. However, truck parking did not seem to be a serious issue in the part of the city that had been home to industrial sites for a long time. Regression analysis revealed that truck parking problems could be exacerbated by concentrations of food businesses in newly developed neighborhoods with a low density of vehicles owned by residents. This finding underscored the importance of land use plans and urban and streetscape designs that took into account trucks in neighborhoods that might not seem to generate intense truck activities. The study also found that alleys could alleviate some truck parking problems.

A Route-Aware Delay Tolerant Routing Protocol for Sparse Vehicular Ad-Hoc Networks

In vehicular ad-hoc networks (VANETs), vehicles move highly and non-randomly along roads while exchanging information with other vehicles. Rapid movement of vehicles and frequent topology changes cause repeated link breakages, increasing the packet loss rate. Because of these characteristics, routing protocols based on greedy forwarding such as greedy perimeter stateless routing (GPSR) are known to be very suitable for VANETs. Greedy forwarding based routing protocols select the vehicle nearest to the destination as a relay vehicle within the transmission range of the sender vehicle. Therefore, it is challenging for selecting the next relay vehicle in a low density of vehicles. To this end, we propose a routeaware delay tolerant routing (RADTR) protocol by combing greedy forwarding and storecarry-forwarding for spare VANETs such as the early morning hours. RADTR uses map data to generate a scheduled route and to predict the moving position during the relay node selection process. And each vehicle is assumed to be aware of its route to its destination and a route is specified by a sequence of its scheduled roads. Simulation results using ns-2 revealed that RADTR performs much better than the existing routing protocols in sparse VANETs.

Properties of vehicle gap distribution in the mixed traffic flow

Using the cellular automaton traffic flow model, we study the vehicle gap distribution of the mixed traffic flow under the different delay probability and the different mixing rate for given vehicle density. Computer simulation results show that the delay probability has no effect on the vehicle gap distribution for the case of the high vehicle density; whereas, for the cases of the low and intermediate vehicle density, the delay probability has great effect on the vehicle gap distribution. Furthermore, one notes that the mixing rate has great effect on the vehicle gap distribution for the case of the low vehicle density.

Connectivity-aware minimum-delay geographic routing with vehicle tracking in VANETs

In this paper, we propose the connectivity-aware minimum-delay geographic routing (CMGR) protocol for vehicular ad hoc networks (VANETs), which adapts well to continuously changing network status in such networks. When the network is sparse, CMGR takes the connectivity of routes into consideration in its route selection logic to maximize the chance of packet reception. On the other hand, in situations with dense network nodes, CMGR determines the routes with adequate connectivity and selects among them the route with the minimum delay. The performance limitations of CMGR in special vehicular networking situations are studied and addressed. These situations, which include the case where the target vehicle has moved away from its expected location and the case where traffic in a road junction is so sparse that no next-hop vehicle can be found on the intended out-going road, are also problematic in most routing protocols for VANETs. Finally, the proposed protocol is compared with two plausible geographic connectivity-aware routing protocols for VANETs, A-STAR and VADD. The obtained results show that CMGR outperforms A-STAR and VADD in terms of both packet delivery ratio and ratio of dropped data packets. For example, under the specific conditions considered in the simulations, when the maximum allowable one-way transmission delay is 1 min and one gateway is deployed in the network, the packet delivery ratio of CMGR is approximately 25% better than VADD and A-STAR for high vehicle densities and goes up to 900% better for low vehicle densities.

SADV: Static-Node-Assisted Adaptive Data Dissemination in Vehicular Networks

Vehicular networks have recently attracted great interest in the research community, and multihop data dissemination has become an important issue. To improve data-delivery performance, we propose deploying static nodes at road intersections to help relay data. In this paper, we present SADV, which is a static-node assisted adaptive data-dissemination protocol for vehicular networks. With the assistance of static nodes at intersections, a packet is forwarded to the static node when there are no vehicles available to deliver the packets along the optimal path. The static node is able to store the packet and transmit it when the optimal delivery path becomes available. In addition, we let adjacent static nodes measure the delay of forwarding data between each other in real time so that the routing decision that is made at static nodes can adapt to the changing vehicle densities. Moreover, a multipath routing mechanism is also adopted in SADV, which is effective in reducing the data-delivery delay. Our simulation results show that SADV outperforms other multihop data dissemination protocols, particularly under median or low vehicle density where the network is frequently partitioned. In this paper, we also present some heuristic deployment strategies to maximize SADV performance under partial deployment of static nodes and analyze them by simulations.