Different Types Of Vehicles Research Articles

A business establishment fleet ownership and composition model

Commercial vehicle fleet ownership is a business decision that is fundamental to the transportation operations of a business establishment. This paper develops a model of fleet ownership and composition for the Region of Peel, Canada. A trivariate model is developed to represent a business establishment’s correlated decisions of how many passenger cars, pickups/vans, or trucks/tractors are owned by the company. The joint model is approximated into a closed-form formulation by using the composite marginal likelihood approach combined with copula functions. The models are estimated using establishment data from the Region of Peel Commercial Travel Survey, and land use and transportation infrastructure variables developed from GIS databases. Larger establishments, as measured by number of employees, are more likely to own vehicles, as are establishments with greater demand for goods and services. Differences are found between establishments in different industry classifications, with the construction industry favoring pickups/vans, and the office/service industries less inclined to own trucks or pickups/vans. Significant negative copulas between ownership of different vehicle types reveal a substitution effect. This also shows the importance of developing the joint model over the independent formulation for decisions on ownership of different types of vehicles.

A Bus Crew Scheduling Problem with Eligibility Constraints and Time Limitations

Abstract: In this study, we consider a real life crew scheduling problem (CSP) of a public bus transportation authority, where the objective is to determine the optimal number of different types of crew members with a minimum cost that cover a given set of tasks regarding working and spread time limitations. Each driver has a spread time limit from the start time to the end time of his/her shift, including the idle times. Additionally, a driver cannot exceed the maximum total working time limit. The processing times of the tasks assigned to each driver are included in his/her working time, as well as the sequence-dependent setup times. As our study is inspired from a real life CSP, the tasks can require different types of vehicles that require different crew capabilities. Therefore, there are several crew classes based on the competencies required to use certain vehicle types inducing eligibility constraints in the problem. We formulate a Tactical Fixed Job Scheduling Problem based binary programming model for the problem. In the formulation, we consider only processing times of tasks as working time. In order to avoid defining an additional sequence control variable that explodes the model size and in turn ruins solution performance, we develop an iterative valid inequality generation scheme, which eliminates task sequences exceeding the total working time when setup times are included. The performance of the developed model is investigated through a comprehensive experimentation and the numerical results are reported. The results show that our optimal seeking solution procedure is quite effective in terms of solution time for instances with up to 120 tasks.

Analysis of Car Type Preferences Among Students Based on Seemingly Unrelated Regression

Vehicle type purchase intentions are interesting from a marketing point of view, because car manufacturers are competing to attract potential buyers. Furthermore, from the point of view of transport planners as well as the government, there are environmental concerns. This study focused on students’ intention to purchase different types of vehicles. The study obtained a sample of 1,229 students from seven countries, to understand cultural differences in preferences. The dependent variables were intention to buy cars in different categories, including hybrid and electric cars. The aim was to explain intentions with three categories of explanatory variables: psychological aspects, sociodemographics, and site-specific dummy variables. To account for correlation between the dependent variables, the analysis used seemingly unrelated regression. The study found that attitudinal factors are significant, particularly for the intention to buy more environmentally friendly types of vehicles; the paper discusses policy implications. The study observed the importance of the symbolic-affective value of a car in explaining car type preferences, as well as the importance of awareness of the negative effects cars might have on the environment and society. It is suggested that these findings can be used to promote more environmentally friendly cars.

SUVと中型セダン型乗用車の前面衝突事故における乗員の傷害内容の分析

Recently, AACN (Advanced Automatic Collision Notification) that presupposed cooperation with emergency life-saving organizations is expected. Therefore, emergency life-saving organizations must recognize injury speciation of patients, as quickly as possible. So, the author tried the traffic accident analyzing method by statistical data analysis from combing analysis items analysis items for main site of injury and analysis items for injury contents (indicated in the traffic accident statistics vote by Japanese National Police Agency). And furthermore it is necessary to improve the safety of vehicles not only for same class collisions but also for collisions between vehicles of different types (e.g., between SUVs and sedans). In this study, the author applied the method of analysis as described above for frontal collision between SUVs and middle sedans, and analyzed using statistical data stored in ITARDA (Institute for Traffic Accident Research and Data Analysis). In the case of fatal or severe injuries, it is shown that the component rate of chest fracture of middle sedan drivers is higher than that of SUVs. It is supposed that the difference in these rates is caused by the vertical offset configuration between the frames of the two different types of vehicles when they crash into each other.

Key Findings of German Showcase Region for Electric Mobility: E-Mobility Works! Economic Feasibility and Legal Frameworks as Main Challenges

The Showcase Region for Electric Mobility LivingLab BWe mobil takes place in the two largest cities of Baden-Wuerttemberg in the south-west of Germany. The results of large-scale regional government-funded demonstration projects are described in this paper. Electric mobility works in various use cases and different types of vehicles, but economic feasibility is still a challenge in some use cases. For this reason continuous R&D activities are needed and appropriated legal frameworks help to overcome obstacles and offer incentives.

EVALUATION OF THE PATTERNS OF INJURIES IN ROAD TRAFFIC ACCIDENTS IN GREAT CAIRO, EGYPT

Background: Road traffic accidents (RTAs) are the leading cause of death among those aged from 15 to 44 years worldwide. In Egypt, the rapid increase in the number of vehicles, the overpopulation and the lack of proper strategy for prevention of RTAs, contribute to make Egypt one of the highest world’s RTAs rate. Aim of the study: To evaluate patterns of injuries in cases of motor vehicle accidents. Material and methods: data of 150 victims of RTAs admitted to the Emergency Department, in El Sahel Teaching Hospital, from May 2013 to November 2013 were recorded including their demographic data, injuries, their outcome and different types of vehicles involved in the accidents. Results: private cars were more involved in RTAs followed by motorcycles. Males constituted the major victims of RTAs with statistically significant percentage (76% of pedestrians and 95% of vehicle occupants). In pedestrians, the most common affected body regions were the lower limbs (66%), head (54%), and upper limbs (26%). Contusions occurred in all pedestrians. Fracture and joint dislocation occurred in 74% of the cases. Most pedestrians recovered completely (78%), 8% had complications and 14% of cases died. Most common cause of death was head injury induced complications (12%). As regards vehicle occupants, most common injured body parts were lower limbs (54%), head (45%) and upper limbs (24%). Contusions and fracture with joint dislocation occurred in 99% and 78% respectively. Most vehicle occupants had complete recovery (82%), 16% had complicated recovery and 2% of cases died due to complications of head and chest injuries. Conclusion: the results of this study demonstrated the types and distribution of injuries in victims of RTAs. These results may help health care providers to anticipate the injuries in patients with subsequent early diagnosis and treatment of RTAs victims. Moreover, results may enable concerned authorities to reconstruct the accident when needed.

An Intelligent Street Light System based on Piezoelectric Sensor Networks

Objectives: The project aims at saving energy by detecting the vehicle movement on highways and switching on the block of street light ahead of it and simultaneously switching off the trailing lights. Methods: This project requires a sensor to detect the day and night and an array of piezoelectric sensors to detect the vehicle movements and accordingly switching on the lights ahead of it. So when there are no vehicles on the highway, all the lights remains off. Sensors used on either side of the road-senses vehicle movement and sends logic commands to microcontroller to change the intensity of the lamps accordingly. Findings: In current years, the street light control is automated by changing the resistance using the light-sensitive device. The reliability of this method is less. Though it reduces the man power, it does not conserve energy spent during night time. It cannot meet the needs of the growing street lamp information and intelligent management. The aim of smart street lights is to save energy, and to save cost. In our project we make use of the piezoelectric sensors, which is cost effective. ZigBee technology is used to communicate between the lights and internet of things to calculate parameters as well as store the information about the vehicles. Statistical analysis is also done on the data obtained from the sensors. Experiments were conducted on the road and with different types of vehicles. Sufficient data were obtained and were consolidated to come to the conclusions. All these data were processed using MATLAB Software to obtain the graphical results. The shape of the graph clearly gives us some strong conclusions. Improvements: The entire setup can be connected to the IOT (Internet of Things) for processes like data extraction, warning vehicles and is particularly useful for places like a 4-way junctions etc.

Heterogeneous traffic flow modelling using second-order macroscopic continuum model

Modelling heterogeneous traffic flow lacking in lane discipline is one of the emerging research areas in the past few years. The two main challenges in modelling are: capturing the effect of varying size of vehicles, and the lack in lane discipline, both of which together lead to the ‘gap filling’ behaviour of vehicles. The same section length of the road can be occupied by different types of vehicles at the same time, and the conventional measure of traffic concentration, density (vehicles per lane per unit length), is not a good measure for heterogeneous traffic modelling. First aim of this paper is to have a parsimonious model of heterogeneous traffic that can capture the unique phenomena of gap filling. Second aim is to emphasize the suitability of higher-order models for modelling heterogeneous traffic. Third, the paper aims to suggest area occupancy as concentration measure of heterogeneous traffic lacking in lane discipline. The above mentioned two main challenges of heterogeneous traffic flow are addressed by extending an existing second-order continuum model of traffic flow, using area occupancy for traffic concentration instead of density. The extended model is calibrated and validated with field data from an arterial road in Chennai city, and the results are compared with those from few existing generalized multi-class models.

Sovereign Wealth Funds, Globalization of Capital Markets, and Internationalization Strategies

In this work, we study the strategies driving cross-border sovereign wealth fund (SWF) investments worldwide. In particular, we investigate how SWFs internationalize their activities, studying whether the use of investment vehicles as signal of passive investment approach to access foreign markets is influenced by SWF- and deal-specific characteristics and the presence of bilateral trade agreements between the SWF’s and the target country. We use a new dataset on SWF investments, whose size is comparable with the datasets used in the most popular SWF studies. Our probit and multinomial logit estimates show that fund opacity, fund politicization, strategic industry targets, and majority ownership choices lead to a more likely use of vehicles, while bilateral trade agreements negatively affect such investment strategy. When we disentangle the different types of vehicles and their geographical location, we find that fund opacity increases the likelihood to use SWF-controlled vehicles, while fund politicization, strategic industry targets, and majority ownership choices increase the likelihood to use a corporate vehicle. While, bilateral trade agreements reduce the use of corporate vehicles. As to the geographic location of the vehicle, politicized foreign SWFs are more likely to invest through vehicles located in third countries. Instead, targeting strategic industries leads to invest in vehicles located in the target country. Our results control for SWFs’ strategic goals, SWF experience (reliance on external managers or advisors, fund size), type of funding sources, crisis period, deal-specific effects, and legal and institutional differences across countries and over time.

A Prufer-based genetic algorithm for allocation of the vehicles in a discounted transportation cost system

ABSTRACTIn this document, allocation of different types of vehicles for transporting products from a manufacturing firm to its depots is considered. The problem involves a limited number of vehicles of various capacities, with the fixed and variable costs as well as a discount mechanism. The objective is defined as the minimisation of the total transportation costs. A mathematical model in the form of nonlinear integer programming is developed and converted to the linear zero-one programme. Due to the NP hard complexity of the proposed mathematical model, a Prufer-based genetic algorithm capable of solving large instances is developed. The efficiency of the proposed algorithm is compared with the solution obtained by CPLEX and the results are reported. The results reveal that the proposed algorithm is capable of providing astonishing solutions with the minimum computational effort.

Causes and consequences of the sinkhole at El Trébol of Quito, Ecuador – implications for economic damage and risk assessment

Abstract. The so-called El Trébol is a critical road interchange in Quito connecting the north and south regions of the city. In addition, it connects Quito with the highly populated Los Chillos Valley, one of the most traveled zones in the Ecuadorian capital. El Trébol was constructed in the late 1960s in order to resolve the traffic jams of the capital city and for that purpose the Machángara River was rerouted through an underground concrete box tunnel. In March 2008, the tunnel contained a high amount of discarded furniture that had been impacting the top portion of the tunnel, compromising the structural integrity. On 31 March 2008 after a heavy rainfall a sinkhole of great proportions formed in the Trébol traffic hub. In the first few minutes, the sinkhole reached an initial diameter of 30 m. The collapse continued to grow in the following days until the final dimensions of 120 m in diameter and some 40 m of depth, revealing the Machángara River at the base of the sinkhole.A state of emergency was declared. The cause of the sinkhole was a result of the lack of monitoring of the older subterranean infrastructure where trash had accumulated and damaged the concrete tunnel that channelized the Machángara River until it was worn away for a length of some 20 m, leaving behind the sinkhole and the fear of recurrence in populated areas.With the intent to understand the causes and consequences of this sinkhole event, rainfall data are shown together with hydrogeological characteristics and a view back to the recent history of sinkhole lineation or arrangement of the city of Quito. The economic impact is also emphasized, where the direct costs of the damage and the reconstruction are presented and compared to indirect costs associated with this socio-natural disaster. These analyses suggest that the costs of indirect financial damage, like time loss or delay, and subsequent higher expenses for different types of vehicles, are equivalent to many times the costs of the reconstruction of El Trébol.

Nonlocal multi-scale traffic flow models: analysis beyond vector spaces

Realistic models of traffic flow are nonlinear and involve nonlocal effects in balance laws. Flow characteristics of different types of vehicles, such as cars and trucks, need to be described differently. Two alternatives are used here, \(L^p\)-valued Lebesgue measurable density functions and signed Radon measures. The resulting solution spaces are metric spaces that do not have a linear structure, so the usual convenient methods of functional analysis are no longer applicable. Instead ideas from mutational analysis will be used, in particular the method of Euler compactness will be applied to establish the well-posedness of the nonlocal balance laws. This involves the concatenation of solutions of piecewise linear systems on successive time subintervals obtained by freezing the nonlinear nonlocal coefficients to their values at the start of each subinterval. Various compactness criteria lead to a convergent subsequence. Careful estimates of the linear systems are needed to implement this program.

An integrated design approach for evaluating the effectiveness and cost of a fleet

This work presents a new method for designing and evaluating different fleet paradigms to determine an effective and cost efficient solution. The method requires the user to define a set of functions which must be carried out by the fleet, as well as a set of candidate vehicles or systems that can carry out these functions. These function and fleet models are then evaluated to determine their performance. All the data is then fed into a stochastic dynamic fleet operation model to identify the amount of vehicles or systems needed to complete each mission defined on a fixed time horizon. The output of the fleet operation model is then used by cost models to determine the cost of completing each fleet mission. The overall approach is demonstrated on a military fleet composed of two different types of vehicle: a conventional fleet and a fleet composed of modules. The method shows the potential for savings using a modular fleet for a hypothetical fleet mission profile; more work in this area is suggested.

Size speed bias or size arrival effect—How judgments of vehicles’ approach speed and time to arrival are influenced by the vehicles’ size

Crashes at railway level crossings are a key problem for railway operations. It has been suggested that a potential explanation for such crashes might lie in a so-called size speed bias, which describes the phenomenon that observers underestimate the speed of larger objects, such as aircraft or trains. While there is some evidence that this size speed bias indeed exists, it is somewhat at odds with another well researched phenomenon, the size arrival effect. When asked to judge the time it takes an approaching object to arrive at a predefined position (time to arrival, TTA), observers tend to provide lower estimates for larger objects. In that case, road users’ crossing decisions when confronted with larger vehicles should be rather conservative, which has been confirmed in multiple studies on gap acceptance. The aim of the experiment reported in this paper was to clarify the relationship between size speed bias and size arrival effect. Employing a relative judgment task, both speed and TTA estimates were assessed for virtual depictions of a train and a truck, using a car as a reference to compare against. The results confirmed the size speed bias for the speed judgments, with both train and truck being perceived as travelling slower than the car. A comparable bias was also present in the TTA estimates for the truck. In contrast, no size arrival effect could be found for the train or the truck, neither in the speed nor the TTA judgments. This finding is inconsistent with the fact that crossing behaviour when confronted with larger vehicles appears to be consistently more conservative. This discrepancy might be interpreted as an indication that factors other than perceived speed or TTA play an important role for the differences in gap acceptance between different types of vehicles.

AN APPROACH FOR REDUCING CO2 EMISSION BY REAL TIME TRAFFIC LIGHT CONTROL USING IOT

Intelligent road traffic flow control is one of the major areas of research in transportation and city traffic management in recent times. It is found in studies that most of the pollution is attributed by vehicles waiting at the junctions than driving vehicles. Several past works have emphasized on traffic flow based on intelligent traffic light control, however such methods has failed to reduce the pollution level of the cities because they don’t take into consideration of the pollution being attributed by waiting vehicles or different types of vehicles. For example, a truck would generate higher level of pollution than a car. In order to reduce the city traffic pollution and at control the traffic flow effectively, we have proposed a novel technique of traffic light management based on pollution sensing. The proposed technique is implemented over IoT architecture; it guarantees that the traffic light timing is adjusted based on the observed pollution value by a physical sensor. This work integrates real time pollution sensing mechanism with a traffic simulation framework to provide a comprehensive analysis and proof of the concept. The result shows that the system response to changes in the pollution level with minimum latency and it retains the flow based traffic light control intelligence as a part of the system. The system not only is able to reduce the traffic congestion in city street junctions but at the same time helps in reducing the pollution level and traffic will flow in smooth way.

Three methods of PCU estimation at unsignalized intersections

Estimation of passenger car unit (PCU) is a vital component of any traffic study conducted in developing countries owing to the heterogeneity in the vehicular traffic. Past studies on PCU factors are majorly limited to intercity and urban roads. However, PCU factors for different types of vehicles on unsignalized intersections have not been investigated so well. This paper presents three methods of estimating PCU factors for different types of vehicles on unsignalized intersections under highly heterogeneous traffic conditions. The first method is based on the occupancy time of a vehicle while clearing the intersection. The second method is based on the capacity of a priority movement estimated in terms of different vehicle categories. Queue clearance rate is used as the basis for PCU estimation in the third method. Data were collected at two unsignalized intersection in semi-urban area of two cities of India and PCU for different types of vehicles is determined using the three methods. The resulting values of PCU factors were found to be logical and are representatives of the actual field conditions.

An Intelligent System for Vehicle Access Control using RFID and ALPR Technologies

This paper introduces a hybrid system for vehicle access control using RFID and automatic license plate recognition (ALPR) technologies. RFID technology is proven to provide an effective solution to different tracking and localization problems. However, the technology has its shortcomings in tracking objects/users without a tag. As such, we propose to complement this technology with ALPR to control the access of different types of vehicles to the area of Makkah (Saudi Arabia) during Pilgrimage seasons. This limited area can easily get congested with the huge number of vehicles attempting access. Before the start of the season, vehicles authorized to access the region are assigned passive RFID tags specifying their allowed schedule of entry. Violating vehicles that do not have RFID tags are detected and identified using ALPR. The developed system was tested over two pilgrimage seasons. The experiments showed that the developed RFID system was able to identify all passing vehicles with speeds up to 100 km/h, while the ALPR system achieved 94 % recognition accuracy of vehicles not equipped with RFID tags.

LATERAL MOVEMENT OF VEHICLES UNDER WEAK-LANE DISCIPLINE HETEROGENEOUS TRAFFIC

Safe driving can be achieved by prevention of risky situations which requires the knowledge of the vehicle dynamics and road geometry. The Indian traffic condition is heterogeneous in nature and has weak lane discipline. Hence, vehicles interactions takes place laterally also along with their longitudinal interaction. Vehicles lateral movements (interactions) are quite high due to absence of lane discipline. Therefore, the lateral acceleration of vehicles are an important variable which characterizes the corresponding vehicle dynamics. Several studies have been done by various authors on lateral acceleration in curves, however, lateral movement study of vehicles on straight road section is also important to analyze vehicles’ maneuver in such traffic (i.e. traffic stream with weak lane discipline). Therefore, the present study is about the observation of lateral movements of vehicles over different types of roads in three metropolitan cities of India (Kolkata, Mumbai and Pune) under moderate traffic conditions. Lateral acceleration variation of five different types of vehicles (SUV cars, Sedan cars, Hutch Back cars, motorized three wheeler and two wheeler) have been recorded to investigate its relationship with vehicles longitudinal characteristics (i.e. longitudinal speed) in Indian heterogeneous and weak lane disciplined traffic. Lateral acceleration values quickly rises with initial increase in speed afterward lateral acceleration values reduces with further increase in vehicles longitudinal speed. Impact of vehicle type and locations on the lateral maneuvering of vehicles have also been studied

The design of capacitated intermodal hub networks with different vehicle types

In this study, we allow using alternative transportation modes and different types of vehicles in the hub networks to be designed. The aim of the problem is to determine the locations and capacities of hubs, which transportation modes to serve at hubs, allocation of non-hub nodes to hubs, and the number of vehicles of each type to operate on the hub network to route the demand between origin-destination pairs with minimum total cost. Total cost includes fixed costs of establishing hubs with different capacities, purchasing and operational costs of vehicles, transportation costs, and material handling costs. A mixed-integer programming model is developed and a variable neighborhood search algorithm is proposed for the solution of this problem. The heuristic algorithm is tested on instances from the Turkish network and CAB data set. Extensive computational analyzes are conducted in order to observe the effects of changes in various problem parameters on the resulting hub networks.

A bi-objective approach for scheduling ground-handling vehicles in airports

In the present paper, we propose a new approach for scheduling ground-handling vehicles, tackling the problem with a global perspective. Preparing an aircraft for its next flight requires a set of interrelated services involving different types of vehicles. Planning decisions concerning each resource affect the scheduling of the other activities and the performance of the other resources. Considering the different operations and vehicles instead of scheduling each resource in isolation allows integrating decisions and contributing to the optimization of the overall ground-handling process. This goal is defined through two objectives: (i) minimizing the waiting time before an operation starts and the total reduction of corresponding time windows and (ii) minimizing the total completion time of the turnarounds. We combine different technologies and techniques to solve the problem efficiently. A new method to address this bi-objective optimization problem is also proposed. The approach has been tested using real data from two Spanish airports, thereby obtaining different solutions that represent a trade-off between both objectives. Experimental results permit inferring interesting criteria on how to optimize each resource, considering the effect on other operations. This outcome leads to more robust global solutions and to savings in resources utilization.