Out-Door Air Pollution Levels in Vehicular-Traffic Junctions in Nsukka Metropolis, Enugu Metropolis and Awgu Semi-Urban Area in Enugu State, Nigeria

Studies were carried out to investigate the outdoor air pollution levels in vehicular traffic junctions in the major cities of Nsukka, Enugu and semi-urban area of Awgu all in Enugu State, Nigeria using standard analytical procedures. PM2.5 was collected using Envirotech air sampler, APM 550 and analyzed gravimetrically. Other determined air pollutant gases such as SO2, NO2, O3 and CO were analyzed using colorimetric techniques. The mean hourly traffic density in the vehicular traffic junctions in Nsukka metropolis, Enugu metropolis and Awgu were 2015, 2873 and 587 respectively. The mean range of values of PM2.5, NO2, SO2, O3 and CO in vehicular traffic junctions within the investigated environments were 1.67 - 12.16 μg/m3, 3.72 - 23.83 μg/m3, 2.96 - 30.09 μg/m3, 5.45 - 66.54 μg/m3 and 1.18 - 15.17 ppm respectively. The mean levels of the determined air pollutants in the air around vehicular traffic junctions in Nsukka metropolis, Enugu metropolis and Awgu semi-urban area differed significantly. The mean levels of PM2.5, and CO in the air around vehicular traffic junctions in Enugu metropolis and CO in the air around traffic junctions in Nsukka metropolis were above the recommended permissible limits. Traffic density was therefore seen as the single most important factor contributing to the varying air pollution levels observed in the investigated environments.

Modelling vehicular interactions for heterogeneous traffic flow using cellular automata with position preference

This paper proposes and validates a modified cellular automata model for determining interaction rate （i.e. number of car-following/overtaking instances） using traffic flow data measured in the field. The proposed model considers lateral position preference by each vehicle type and introduces a position preference parameter fl in the model which facilitates gradual drifting towards preferred position on road, even if the gap in front is sufficient. Additionally, the model also improves upon the conven- tional model by calculating safe front and back gap dynamically based on speed and deceleration properties of leader and follower vehicles. Sensitivity analysis was carried out to determine the effect of β on vehicular interac- tions and the model was calibrated and validated using interaction rates observed in the field. Paired tests were conducted to determine the determining interaction rates validity of the model in Results of the simulations show that there is a parabolic relationship between area occupancy and interaction rate of different vehicle types. The model performed satisfactorily as the simulated interaction rate between different vehicle types were found to be statistically similar to those observed in field. Also, as expected, the interaction rate between light motor vehicles （LMVs） and heavy motor vehicles （HMVs） were found to be higher than that between LMVs and three wheelers because LMVs and HMVs share the same lane. This could not be done using conventional CA models as lateral movement rules were dictated by only speeds and gaps. So, in conventional models, the vehicles would end up in positions which are not realistic. The position preference parameter introduced in this model motivates vehicles to stay in their preferred positions. This study demonstrates the use of interaction rate as a measure to validate micro- scopic traffic flow models.

Characteristics of lateral vehicular interactions in heterogeneous traffic with weak lane discipline

Heterogeneous traffic conditions prevail in developing countries. Vehicles maintain weak lane discipline which increases lateral interactions of vehicles significantly. It is necessary to study these interactions in the form of maintained lateral gaps for modeling this traffic scenario. This paper aims at determining lateral clearances maintained by different vehicle types while moving in a heterogeneous traffic stream during overtaking. These data were collected using an instrumented vehicle which runs as a part of the stream. Variation of obtained clearance with average speed of interacting vehicles is studied and modeled. Different instrumented vehicles of various types are developed using （1） ultrasonic sensors fixed on both sides of vehicle, which provide inter-vehicular lateral distance and relative speed; and （2） GPS device with cameras, which provides vehicle type and speed of interacting vehicles. They are driven on different roads in six cities of India, to measure lateral gaps maintained with different interacting vehicles at different speeds. Relationships between lateral gaps and speed are modeled as regression lines with positive slopes and beta-distributed residuals. Nature of these graphs （i.e., slopes, intercepts, residuals） are also evaluated and compared for different interacting vehicle-type pairs. It is observed that similar vehicle pairs maintain less lateral clearance than dissimilar vehicle pairs. If a vehicle interacts with two vehicles （one on each side） simultaneously, lateral clearance is reduced and safety of the vehicles is compromised. The obtained relationships can be used for simulating lateral clearance maintaining behavior of vehicles in heterogeneous traffic.

An analysis of vehicular exhaust derived nanoparticles and historical Belgium fortress building interfaces

Air pollution monitoring is one of the most important features in contamination risk management.This is because many of the compounds contained within air pollution present a serious risk both for the preservation of open air cultural heritage and for human health.New particle formation is a major contributor to urban pollution,but how it occurs in cities is often puzzling.As more and more people enjoy an increased quality of life through outdoor activity,managing outdoor air quality is vital.This study presents the application of a low-cost system for monitoring the current level of road traffic passengers’exposure to particulate air contamination.The global rise in tourism also leads to apprehension about its probable destructive influence on various aspects of global preservation.One of the major risks encountered by tourists,stemming from modes of transport,are nanoparticles(NPs)(<100 nm)and ultra-fine particles(UFPs)(100-1000 nm)consisting of potentially hazardous elements(PHEs).This study examines Steen Castle,a medieval fortress located in Antwerp,Belgium.Significant NPs with PHEs,were found in the air sampled in this area.The self-made passive sampler(LSPS)described in this study,consisting of retainers specially designed for advanced microscopic analysis,is used for the first time as a simple way to characterize the surrounding atmospheric contamination caused by NPs and UFPs,without the need of other commonly employed more expensive particulate focused active samplers such as cascade impactors.This study aims to assess the result of the utilization of a low-cost,LSPS,to determine outdoor NPs and UFPs in a Belgian urban(Steen Castle)and rural area(Fort van Schoten).This work is the first to detail the usefulness of LSPS for the evaluation of Belgium’s outdoor air for NPs and UFPs,which contain PHEs.

面向队列实际行为特性的混合交通流建模及分析

为探讨自主汽车队列实际行为特性对交通流的影响,针对混入前车跟驰(PF)汽车队列的混合交通流,考虑队列实际行为特性并按照其实际控制策略进行建模,基于元胞自动机方法建立了混合交通流模型。仿真分析表明:队列车头时距、队列渗透率、队列规模、控制增益等队列特征对混合交通流呈现出耦合及非线性的影响特性,不同队列特征下的混合交通流时空特征差异显著;减小队列车头时距或增加队列渗透率对提升道路的通行能力总体是有利的;队列规模及控制增益对交通流量的一致性影响规律不明显,都需要结合其他队列特征进行具体分析。

Dynamic Vehicular Clustering Enhancing Video on Demand Services Over Vehicular Ad-hoc Networks

Nowadays,video streaming applications are becoming one of the tendencies driving vehicular network users.In this work,considering the unpredictable vehicle density,the unexpected acceleration or deceleration of the different vehicles included in the vehicular traffic load,and the limited radio range of the employed communication scheme,we introduce the“Dynamic Vehicular Clustering”(DVC)algorithm as a new scheme for video streaming systems over vehicular ad-hoc networks(VANET).The proposed algorithm takes advantage of the small cells concept and the introduction of wireless backhauls,inspired by the different features and the performance of the Long Term Evolution(LTE)-Advanced network.Vehicles are clustered together to form dynamically ad-hoc sub-networks included in the vehicular network.The goal of our clustering algorithm is to take into account several characteristics,such as the vehicle’s position and acceleration to reduce latency and packet loss.Therefore,each cluster is counted as a small cell containing vehicular nodes and an access point that is elected regarding some particular specifications.Based on the exceptional features of the LTE-Advanced network(small cells and wireless backhauls)the DVC algorithm is a promising scheme for video streaming services over VANET systems.Experiments were carried out with a virtual topology of the VANET network created with four clusters to implement the DVC algorithm.The results were compared with other algorithms such as Virtual Trust-ability Data transmission(VTD),Named Data Networking(NDN),and Socially Aware Security Message Forwarding(SASMF).Our algorithm can effectively improve the transmission rate of data packets at the expense of a slight increase in end-to-end delay and control overhead.

Modulating Traffic Signal Phases to Realize Real-Time Traffic Control System

This paper proposes innovations to address challenges emanating from road traffic congestion. Improving economies create more car owners resulting in increased automobile manufacturing, increased vehicle population giving rise to higher emission of CO2 resulting in traffic congestion. Congested traffic has idling vehicles which emit higher CO2 and pollution. Besides, traffic congestion increases turnaround time, delivery time, commuting time and related logistical aspects. Commuting time negatively impacts working hours. Unless the traffic congestion is mitigated, the economy will take a beating creating a vicious ecology cycle. Building new roads, bridges or reconditioning of infrastructure is not always the best possible solutions. Efficient traffic management is a key to country’s economic growth. Various analytical models are employed to study, appreciate traffic congestion. The paper studies these models to infer that real time approach is the only solution. Several approaches are being worked on and few commercial systems too are available. These systems provide traffic information for course correction. However, it has latency and hence deviates from real time environment. Traffic congestion being highly dynamic in nature, it necessitates real time solution with real time inputs. It is proposed to integrate Real time traffic data with the traffic signal thus modulating the cycle timings at every junction. Deviation from static asymmetric cycle timing is implemented by assigning green phases based on density of vehicles. With minimalistic infrastructure and negligible incremental cost, the paper not only proposes to address traffic congestion but also paves the way for capturing traffic offenses, vehicle tracking and toll collection. The research is imminently realizable and makes a strong case for a PPP (Public Private Partnership) project.

Mathematical Modeling,Field Calibration and Numerical Simulation of Low-Speed Mixed Traffic Flow in Cities

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A Model with Traffic Routers, Dynamically Managing Signal Phases to Address Traffic Congestion in Real Time

On-road Vehicular traffic congestion has detrimental effect on three lifelines: Economy, Productivity and Pollution (EPP). With ever increasing population of vehicles on road, traffic congestion is a major challenge to the economy, productivity and pollution, notwithstanding continuous developments in alternative fuels, alternative sources of energy. The research develops accurate and precise model in real time which computes congestion detection, dynamic signaling algorithm to evenly distribute vehicle densities while ensuring avoidance of starvation and deadlock situation. The model incorporates road segment length and breadth, quality and achievable average speed to compute road capacity. Vehicles installed with GPS enabled devices provide their location, which enables computing road occupancy. Road occupancy is evaluated based on number of vehicles as well as area occupied by vehicles. Ratio of road occupancy and road capacity provides congestion index important to compute signal phases. The algorithm ensures every direction is serviced once during a signaling cycle ensuring no starvation. Secondly, the definition of minimum and maximum signal timings ensures against dead lock situation. A simulator is developed to validate the proposition and proves it can ease congestion by more than 50% which is better than any of the contemporary approaches offering 15% improvement. In case of higher congestion index, alternate routes are suggested based on evaluation of traffic density graphs for shortest route or knowledge database. The algorithm to compute shortest route is optimized drastically, reducing computation cost to 3*√2N vis-à-vis computation cost of N2 by classical algorithms. The proposal brings down the cost of implementation per traffic junction from USD 30,000 to USD 2000.

A Greedy Traffic Light and Queue Aware Routing Protocol for Urban VANETs

Vehicular Ad-hoc Networks(VANETs) require reliable data dissemination for time-sensitive public safety applications. An efficient routing protocol plays a vital role to achieve satisfactory network performance. It is well known that routing is a challenging problem in VANETs due to the fast-changing network typology caused by high mobility at both ends of transmission. Moreover, under urban environment, there are two non-negligible factors in routing protocol design, the non-uniform vehicle distribution caused by traffic lights, and the network congestion due to high traffic demand in rush hours. In this paper, we propose a greedy traffic light and queue aware routing protocol(GTLQR) which jointly considers the street connectivity, channel quality, relative distance, and queuing delay to alleviate the packet loss caused by vehicle clustering at the intersection and balance the traffic load among vehicles. Through performance evaluation, we show that our proposed protocol outperforms both TLRC and GLSR-L in terms of packet delivery ratio and end-to-end delay.

Traffic Flow Merging and Bifurcating at Junction on Two-Lane Highway

In this paper we study the traffic states and jams in vehicular traffic merging and bifurcating at a junction on a two-lane highway. The two-lane traffic model for the vehicular motion at the junction is presented where a jam occurs frequently due to merging, lane changing, and bifurcating. The traffic flow is called the weaving. At the weaving section, vehicles slow down and then move aside on the other lane for changing their direction. We derive the fundamental diagrams (flow-density diagrams) for the weaving traffic flow. The traffic states vary with the density, slowdown speed, and the fraction of vehicles changing the lane. The dynamical phase transitions occur. It is shown that the fundamental diagrams depend highly on the traffic states.

Wi-Fi Traffic Enforcement System (WiTE)

This paper proposes a single integrated traffic enforcement system that is able to recognize and report various traffic violations. It consists of a Wi-Fi infrastructure that enables communication between moving vehicles and a central node. Unlike existing solutions, which address single violations, the proposed model encompasses several issues like exceeding speed limits, entering a no entry street, car theft, congestion and tolling. OPNET simulations were run to test the Wi-Fi model and define its different characteristics and limitations. A proof-of-concept case was modeled, and the proposed architecture succeeded in meeting all design requirements.

Advanced Leader Election for Virtual Traffic Lights

We examine the network performance of algorithms for self-organized traffic management. In particular, we focus on wireless network- ing between cars. One of many technologies that make road traffic safer and more efficient is the Virtual Traffic Light （VTL） system, which is able to coordinate the traffic flow at intersections without the need for physical lights. VTL takes a leading vehicle at an inter- section and uses it to control the traffic lights. We developed algorithms for leader election and traffic light computation in realistic ve- hicular networking scenarios. Our key contribution is the extension of this algorithm to support arbitrary intersection layouts. We in- vestigated the proposal in synthetic and realistic scenarios. The results show that, overall, VTLs use network resources efficiently and positively influences driving experience. It performs better than stationary traffic lights for a low to medium network load. We also identify potential optimizations to deal with high network load and to improve fairness.

Fuzzy Rules to Improve Traffic Light Decisions in Urban Roads

Many researchers around the world are looking for developing techniques or technologies that cover traditional and recent constraints in urban traffic con-trol. Normally, such traffic devices are facing with a large scale of input data when they must to response in a reliable, suitable and fast way. Because of such statement, the paper is devoted to introduce a proposal for enhancing the traffic light decisions. The principal goal is that a semaphore can provide a correct and fluent vehicular mobility. However, the traditional semaphore operative ways are outdated. We present in a previous contribution the development of a methodology capable of improving the vehicular mobility by proposing a new green light interval based on road conditions with a CBR approach. However, this proposal should include whether it is needed to modify such light duration. To do this, the paper proposes the adaptation of a fuzzy inference system helping to decide when the semaphore should try to fix the green light interval according to specific road requirements. Some experiments are conducted in a simulated environment to evaluate the pertinence of implementing a decision-making before the CBR methodology. For example, using a fuzzy inference approach the decisions of the system improve almost 18% in a set of 10,000 experiments. Finally, some conclusions are drawn to emphasize the benefits of including this technique in a methodology to implement intelligent semaphores.

Research on an Urban Traffic Control System Based on DGPS

The basic principles of GPS (Global Positioning System) and DGPS (Differential GPS) are described. The principle and structure of vehicle navigation systems, and its application to the urban traffic flow guidance are analyzed. Then, an area coordinated adaptive control system based on DGPS and a traffic flow guidance information system based on DGPS are put forward, and their working principles and functions are researched. This is to provides a new way for the development of urban road traffic control systems.

容量约束的间歇式公交专用道控制策略

间歇式公交专用道虽然能有效提高专用道的利用率,但是过量的社会车辆借道会导致公交车辆的额外延误,因此有必要对借道车辆的总量进行控制。提出车联网环境容量约束的控制策略,首先,将相邻前后公交车辆之间的路段空间设置为基本控制单元;然后,以公交车辆行驶方向的下游信号交叉口通行能力作为可借道容量约束;最后,利用车辆间通信允许不超过基本控制单元可借道容量的社会车辆在控制单元范围借道。此外,还提出了容量约束的专用道入口控制策略作为无车联网时的替代策略。SUMO仿真验证表明:相较于一般间歇式公交专用道,容量约束控制策略在不增加公交车延误和不干扰邻道交通流运行稳定性的同时,不仅可提高道路通行能力和减少行程时间,而且更适用于饱和交通环境。

车头间距分布规律的研究

以我国混合车流作为高等级公路交通流的基本构成 ,分析了混合车流车型跟驶序列组合的概率 ;采用计算机模拟手段 ,得到了车头时距阈值与速度关系、不同跟车序列最小车头间距、车头间距与随机度关系和车头间距与流量关系 ;

感知实时车流信息的VANET路由仿真研究

车用自组织网络利用车辆间通讯来提高道路交通安全和效率,路由协议的性能至关重要。提出一种感知实时车流信息的路由协议,能够不依赖于基础设施,通过挖掘和汇聚车辆位置数据,实现城市道路上的车流密度估算,并给出车流自适应路径选择方法,动态产生及维护由多条道路连成的数据包传递路径。对车辆高密度和低密度场合下的仿真表明,在网络开销没有明显增长的情况下,协议可以获得较好的性能,数据包递送率达到83%以上,平均发送延迟限制在2秒以内。