scholarly journals Relationship between Programmed Heavy Vehicle Inspections and Traffic Safety

Author(s):  
Behrang Assemi ◽  
Mark Hickman ◽  
Alexander Paz

Heavy vehicle crashes incur significant economic and social costs. Although most crashes are considered to be related to driver error, the effects of vehicle defects are major in many crashes. Therefore, various vehicle inspections including Queensland’s Certificate of Inspection (COI) scheme have been implemented to improve the safety of heavy vehicles. This study analyzes the trends of heavy vehicle crashes and their relationships with COI results. Longitudinal data provided by Queensland’s Department of Transport and Main Roads for the period of June 2009 through December 2013 were used to perform the analyses. The data include 474,640 programmed inspections and 2,274 crashes in which heavy vehicles were involved. The results show significant relationships between the monthly average inspection failure rate as well as the monthly average failure severity level, and the total number of heavy vehicle crashes. The results also reveal significant relationships between the monthly average inspection failure rate, average vehicle age, as well as monthly average mean maximum temperature, and the number of defect-related crashes. The implications of these results are discussed with respect to heavy vehicle safety policies.

2015 ◽  
pp. 1540-1566
Author(s):  
Sara Moridpour

Heavy vehicles have substantial impact on traffic flow particularly during heavy traffic conditions. Large amount of heavy vehicle lane changing manoeuvres may increase the number of traffic accidents and therefore reduce the freeway safety. Improving road capacity and enhancing traffic safety on freeways has been the motivation to establish heavy vehicle lane restriction strategies to reduce the interaction between heavy vehicles and passenger cars. In previous studies, different heavy vehicle lane restriction strategies have been evaluated using microscopic traffic simulation packages. Microscopic traffic simulation packages generally use a common model to estimate the lane changing of heavy vehicles and passenger cars. The common lane changing models ignore the differences exist in the lane changing behaviour of heavy vehicle and passenger car drivers. An exclusive fuzzy lane changing model for heavy vehicles is developed and presented in this chapter. This fuzzy model can increase the accuracy of simulation models in estimating the macroscopic and microscopic traffic characteristics. The results of this chapter shows that using an exclusive lane changing model for heavy vehicles, results in more reliable evaluation of lane restriction strategies.


Author(s):  
Sara Moridpour

Heavy vehicles have substantial impact on traffic flow particularly during heavy traffic conditions. Large amount of heavy vehicle lane changing manoeuvres may increase the number of traffic accidents and therefore reduce the freeway safety. Improving road capacity and enhancing traffic safety on freeways has been the motivation to establish heavy vehicle lane restriction strategies to reduce the interaction between heavy vehicles and passenger cars. In previous studies, different heavy vehicle lane restriction strategies have been evaluated using microscopic traffic simulation packages. Microscopic traffic simulation packages generally use a common model to estimate the lane changing of heavy vehicles and passenger cars. The common lane changing models ignore the differences exist in the lane changing behaviour of heavy vehicle and passenger car drivers. An exclusive fuzzy lane changing model for heavy vehicles is developed and presented in this chapter. This fuzzy model can increase the accuracy of simulation models in estimating the macroscopic and microscopic traffic characteristics. The results of this chapter shows that using an exclusive lane changing model for heavy vehicles, results in more reliable evaluation of lane restriction strategies.


Climate ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 165
Author(s):  
Prem B. Parajuli ◽  
Avay Risal

This study evaluated changes in climatic variable impacts on hydrology and water quality in Big Sunflower River Watershed (BSRW), Mississippi. Site-specific future time-series precipitation, temperature, and solar radiation data were generated using a stochastic weather generator LARS-WG model. For the generation of climate scenarios, Representative Concentration Pathways (RCPs), 4.5 and 8.5 of Global Circulation Models (GCMs): Hadley Center Global Environmental Model (HadGEM) and EC-EARTH, for three (2021–2040, 2041–2060 and 2061–2080) future climate periods. Analysis of future climate data based on six ground weather stations located within BSRW showed that the minimum temperature ranged from 11.9 °C to 15.9 °C and the maximum temperature ranged from 23.2 °C to 28.3 °C. Similarly, the average daily rainfall ranged from 3.6 mm to 4.3 mm. Analysis of changes in monthly average maximum/minimum temperature showed that January had the maximum increment and July/August had a minimum increment in monthly average temperature. Similarly, maximum increase in monthly average rainfall was observed during May and maximum decrease was observed during September. The average monthly streamflow, sediment, TN, and TP loads under different climate scenarios varied significantly. The change in average TN and TP loads due to climate change were observed to be very high compared to the change in streamflow and sediment load. The monthly average nutrient load under two different RCP scenarios varied greatly from as low as 63% to as high as 184%, compared to the current monthly nutrient load. The change in hydrology and water quality was mainly attributed to changes in surface temperature, precipitation, and stream flow. This study can be useful in the development and implementation of climate change smart management of agricultural watersheds.


2009 ◽  
Vol 7 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Mike Males

Teenagers’ high rates of motor vehicle crashes, accounting for 40% of external deaths among 16-19 yearolds, have been ascribed largely to inherent “adolescent risk-taking” and developmental hazards. However, the fact that compared to adults 25 and older, teenagers are twice as likely to live in poverty and low-income areas, risk factors for many types of violent death, has not been assessed. This paper uses Fatality Analysis Reporting System data on 65,173 fatal motor vehicle crashes by drivers in California’s 35 most populous counties for 1994-2007 to analyze fatal crash involvements per 100 million miles driven by driver age, county, poverty status, and 15 other traffic safety-related variables. Fatal crash rates were substantially higher for every driver age group in poorer counties than in richer ones. Multivariate regression found socioeconomic factors, led by the low levels of licensing and high unemployment rates prevalent in low-income areas, were associated with nearly 60% of the variance in motor vehicle crash risks, compared to 3% associated with driver age. The strong association between fatal crash risk and poverty, especially for young drivers who are concentrated in high-poverty brackets and low-income areas, suggests that factors related to poorer environments constitute a major traffic safety risk requiring serious attention.


Author(s):  
Parthkumar Patel ◽  
H.R. Varia

Safe, convenient and timely transportation of goods and passengers is necessary for development of nation. After independence road traffic is increased manifold in India. Modal share of freight transport is shifted from Railway to roadways in India. Road infrastructures continuously increased from past few decades but there is still need for new roads to be build and more than three forth of the roads having mixed traffic plying on it. The impact of freight vehicles on highway traffic is enormous as they are moving with slow speeds. Nature of traffic flow is dependent on various traffic parameters such as speed, density, volume and travel time etc. As per ideal situation these traffic parameters should remain intact, but it is greatly affected by presence of heavy vehicle in mixed traffic due to Svehicles plying on two lane roads. Heavy vehicles affect the traffic flow because of their length and size and acceleration/deceleration characteristics.  This study is aimed to analyse the impact of heavy vehicles on traffic parameters.


Author(s):  
C. C. Osadebe ◽  
H. A. Quadri

The prevalence of flexible pavement deterioration in the country has been adduced largely by highway researchers to trucks or heavy vehicles carrying much in excess of permitted legal limits. This study investigated levels of deterioration of Abuja-Kaduna-Kano road (Northern region) and Port Harcourt-Enugu road (Southern region) caused by heavy vehicles through a 14 day traffic counts conducted at 5 strategic points each in the Northern and Southern regions. Traffic data generated were analyzed with AASHTO Design Guidelines (1993) to evaluate Equivalent Single Axle Loads (ESALs) and Vehicle Damage effects on the road. The Traffic Volume, Average Daily Traffic (ADT), and Heavy Vehicle per day (HV/day) were estimated to be 2,063,977; 147,427; and 12,246 respectively in the Northern region, while in the Southern region they were estimated to be 750,381; 53,670; and 20,951 respectively. Motorcycles, Passenger cars, Mini-buses/Pick-ups, and Heavy vehicles constitute 18.7%, 49.7%, 23.3% and 8.31% of the total traffic volume respectively in the Northern region while in the South they constitute 4.6%, 30.1%, 26.2% and 39.1% respectively. ESALs were estimated according to AASHTO Design Guidelines in the Northern and Southern regions as 547,730 and 836,208 respectively. An average Load Equivalency Factors (LEFs) of 3.43 and 3.02 were estimated for each heavy vehicle plying the Northern and Southern roads respectively and this could explain some failures (alligator cracks, potholes, depressions, linear or longitudinal cracks along the centre line amongst others) inherent on the road.


2014 ◽  
Vol 8 (1) ◽  
pp. 292-296
Author(s):  
Zhi-Guo Zhao ◽  
Min Chen ◽  
Nan Chen ◽  
Yong-Bing Zhao ◽  
Xin Chen

The lateral security of heavy vehicle in deteriorative weather is one of the main causes of accidents of vehicles on roads. Road safety has become a subject of great concern to institutions of higher education and scientific research institutions. There are important theoretical and practical significances to explore applicable and effective lateral safety warning methods of heavy vehicles. One of the purposes of this paper is to provide a good theoretical basis for the core technology of heavy vehicle safety features for our country's independent research and development. Aiming at the issue of lateral security of heavy vehicle for road conditions in deteriorative weather, this paper constructs the framework of the lateral security pre-warning system of heavy vehicles based on cooperative vehicle infrastructure. Moreover, it establishes vehicle lateral security statics model through analysis of the force of the car in the slope with section bending and states the parameters of vehicles for no rollover. The side slip is indexed to calculate critical speed of vehicles in a bend. This paper also analyzes the influence of road friction coefficient, the road gradient and the turning radius on the lateral security of the vehicle with critical speed on the asphalt pavement with surface conditions ranging from wet, dry, snowing or icy. The calculation results show that the bad weather road conditions, road friction coefficient and turning radius have obvious influence on the lateral security critical speed. Experimental results indicate that the critical speed error warning is within 4% and it meets the design requirements.


2019 ◽  
Vol 11 (4) ◽  
pp. 1214 ◽  
Author(s):  
Kinga Ivan ◽  
József Benedek ◽  
Silviu Ciobanu

The analysis of pedestrian–vehicle crashes makes a significant contribution to sustainable pedestrian safety. Existing research is based mainly on the statistical analysis of traffic crashes involving pedestrians and their causes, without the identification of areas vulnerable to traffic crashes that involve pedestrians. The main aim of this paper is to identify areas vulnerable to school-aged pedestrian–vehicle crashes at a local level to support the local authorities in implementing new urban traffic safety measures. The vulnerable areas were determined by computing the severity index (SI) based on the number of fatal, serious, and slight casualties throughout the 2011–2016 period in a large urban agglomeration (Bucharest). As well as the vulnerable areas, the triggering factors and the time intervals related to school-aged pedestrian–vehicle crashes were identified. The outcomes of the study showed that the vulnerable areas were concentrated only in districts 2 and 4 of Bucharest, and they were associated with high vehicle speed and pedestrians’ unsafe crossing behavior. The findings revealed that speed and age are triggering factors in generating school-aged pedestrian–vehicle crashes. The identified time peaks with a high number of traffic crashes correspond to the afternoon time intervals, when scholars go home from school. The identification of the areas vulnerable to school-aged pedestrian crashes may help local authorities in identifying and implementing measures to improve traffic safety in large urban agglomerations.


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