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Fulltext Sequential Insertion Heuristic with Adaptive Bee Colony Optimisation Algorithm for Vehicle Routing Problem with Time Windows

Jawarneh S, Abdullah S

PLoS One, 2015;10(7):e0130224.
PMID: 26132158 DOI: 10.1371/journal.pone.0130224

This paper presents a bee colony optimisation (BCO) algorithm to tackle the vehicle routing problem with time window (VRPTW). The VRPTW involves recovering an ideal set of routes for a fleet of vehicles serving a defined number of customers. The BCO algorithm is a population-based algorithm that mimics the social communication patterns of honeybees in solving problems. The performance of the BCO algorithm is dependent on its parameters, so the online (self-adaptive) parameter tuning strategy is used to improve its effectiveness and robustness. Compared with the basic BCO, the adaptive BCO performs better. Diversification is crucial to the performance of the population-based algorithm, but the initial population in the BCO algorithm is generated using a greedy heuristic, which has insufficient diversification. Therefore the ways in which the sequential insertion heuristic (SIH) for the initial population drives the population toward improved solutions are examined. Experimental comparisons indicate that the proposed adaptive BCO-SIH algorithm works well across all instances and is able to obtain 11 best results in comparison with the best-known results in the literature when tested on Solomon's 56 VRPTW 100 customer instances. Also, a statistical test shows that there is a significant difference between the results.

Matched MeSH terms: Motor Vehicles/statistics & numerical data*
Fulltext Where and how are roads endangering mammals in Southeast Asia's forests?

Clements GR, Lynam AJ, Gaveau D, Yap WL, Lhota S, Goosem M, et al.

PLoS One, 2014;9(12):e115376.
PMID: 25521297 DOI: 10.1371/journal.pone.0115376

Habitat destruction and overhunting are two major drivers of mammal population declines and extinctions in tropical forests. The construction of roads can be a catalyst for these two threats. In Southeast Asia, the impacts of roads on mammals have not been well-documented at a regional scale. Before evidence-based conservation strategies can be developed to minimize the threat of roads to endangered mammals within this region, we first need to locate where and how roads are contributing to the conversion of their habitats and illegal hunting in each country. We interviewed 36 experts involved in mammal research from seven Southeast Asian countries to identify roads that are contributing the most, in their opinion, to habitat conversion and illegal hunting. Our experts highlighted 16 existing and eight planned roads - these potentially threaten 21% of the 117 endangered terrestrial mammals in those countries. Apart from gathering qualitative evidence from the literature to assess their claims, we demonstrate how species-distribution models, satellite imagery and animal-sign surveys can be used to provide quantitative evidence of roads causing impacts by (1) cutting through habitats where endangered mammals are likely to occur, (2) intensifying forest conversion, and (3) contributing to illegal hunting and wildlife trade. To our knowledge, ours is the first study to identify specific roads threatening endangered mammals in Southeast Asia. Further through highlighting the impacts of roads, we propose 10 measures to limit road impacts in the region.

Matched MeSH terms: Motor Vehicles/statistics & numerical data*
New method for distance-based close following safety indicator

Sharizli AA, Rahizar R, Karim MR, Saifizul AA

Traffic Inj Prev, 2015;16(2):190-5.
PMID: 24827899 DOI: 10.1080/15389588.2014.921913

The increase in the number of fatalities caused by road accidents involving heavy vehicles every year has raised the level of concern and awareness on road safety in developing countries like Malaysia. Changes in the vehicle dynamic characteristics such as gross vehicle weight, travel speed, and vehicle classification will affect a heavy vehicle's braking performance and its ability to stop safely in emergency situations. As such, the aim of this study is to establish a more realistic new distance-based safety indicator called the minimum safe distance gap (MSDG), which incorporates vehicle classification (VC), speed, and gross vehicle weight (GVW).

Matched MeSH terms: Motor Vehicles/statistics & numerical data
Relationship between vehicle count and particulate air pollution in Amman, Jordan

Alnawaiseh NA, Hashim JH, Isa ZM

Asia Pac J Public Health, 2015 Mar;27(2):NP1742-51.
PMID: 22899706 DOI: 10.1177/1010539512455046

The main objective of this cross-sectional comparative study is to observe the relationship between traffic-related air pollutants, particularly particulate matter (PM) of total suspended particulate (TSP) and PM of size 10 µm (PM10), and vehicle traffic in Amman, Jordan. Two study areas were chosen randomly as a high-polluted area (HPA) and low-polluted area (LPA). The findings indicate that TSP and PM10 were still significantly correlated with traffic count even after controlling for confounding factors (temperature, relative humidity, and wind speed): TSP, r = 0.726, P < .001; PM10, r = 0.719, P < .001). There was a significant positive relationship between traffic count and PM level: TSP, P < .001; PM10, P < .001. Moreover, there was a significant negative relationship between temperature and PM10 level (P = .018). Traffic volume contributed greatly to high concentrations of TSP and PM10 in areas with high traffic count, in addition to the effect of temperature.

Matched MeSH terms: Motor Vehicles/statistics & numerical data*
Investigation of factors affecting the injury severity of single-vehicle rollover crashes: A random-effects generalized ordered probit model

Anarkooli AJ, Hosseinpour M, Kardar A

Accid Anal Prev, 2017 Sep;106:399-410.
PMID: 28728062 DOI: 10.1016/j.aap.2017.07.008

Rollover crashes are responsible for a notable number of serious injuries and fatalities; hence, they are of great concern to transportation officials and safety researchers. However, only few published studies have analyzed the factors associated with severity outcomes of rollover crashes. This research has two objectives. The first objective is to investigate the effects of various factors, of which some have been rarely reported in the existing studies, on the injury severities of single-vehicle (SV) rollover crashes based on six-year crash data collected on the Malaysian federal roads. A random-effects generalized ordered probit (REGOP) model is employed in this study to analyze injury severity patterns caused by rollover crashes. The second objective is to examine the performance of the proposed approach, REGOP, for modeling rollover injury severity outcomes. To this end, a mixed logit (MXL) model is also fitted in this study because of its popularity in injury severity modeling. Regarding the effects of the explanatory variables on the injury severity of rollover crashes, the results reveal that factors including dark without supplemental lighting, rainy weather condition, light truck vehicles (e.g., sport utility vehicles, vans), heavy vehicles (e.g., bus, truck), improper overtaking, vehicle age, traffic volume and composition, number of travel lanes, speed limit, undulating terrain, presence of central median, and unsafe roadside conditions are positively associated with more severe SV rollover crashes. On the other hand, unpaved shoulder width, area type, driver occupation, and number of access points are found as the significant variables decreasing the probability of being killed or severely injured (i.e., KSI) in rollover crashes. Land use and side friction are significant and positively associated only with slight injury category. These findings provide valuable insights into the causes and factors affecting the injury severity patterns of rollover crashes, and thus can help develop effective countermeasures to reduce the severity of rollover crashes. The model comparison results show that the REGOP model is found to outperform the MXL model in terms of goodness-of-fit measures, and also is significantly superior to other extensions of ordered probit models, including generalized ordered probit and random-effects ordered probit (REOP) models. As a result, this research introduces REGOP as a promising tool for future research focusing on crash injury severity.

Matched MeSH terms: Motor Vehicles/statistics & numerical data*
Fulltext Buckling up in Singapore: residency and other risk factors for seatbelt non-compliance - a cross-sectional study based on trauma registry data

Wong TH, Lim GH, Chow KY, Trauma Coordinators and Trauma Service Representatives, Zaw NN, Nguyen HV, et al.

BMC Public Health, 2016 05 14;16:402.
PMID: 27180046 DOI: 10.1186/s12889-016-3080-3

BACKGROUND: Seatbelt non-compliance is a problem in middle income countries, and little is known about seatbelt compliance in populations with a high proportion of non-residents. This study analyses the profile of seatbelt non-compliance in Singapore based on trauma registry data from five of the six public hospitals.
METHODS: This is a cross-sectional study of seatbelt compliance of patients aged over 18 years, attending the emergency departments of five public hospitals in Singapore after road collisions from 2011-2014. Seatbelt data was obtained from paramedic and patient history.
RESULTS: There were 4,576 patients studied. Most were Singapore citizens (83.4 %) or permanent residents (2.4 %), with the largest non-resident groups from Malaysia, India, and China. Overall seatbelt compliance was 82.1 %. On univariate analysis, seatbelt compliance was higher in older patients (OR 1.02, 95 % CI 1.001-1.021, p

Matched MeSH terms: Motor Vehicles/statistics & numerical data