Light Goods Vehicles Research Articles

The risk of road traffic crashes for occupational drivers: A responsibility study with comparison to the general population.

Road accidents are the leading type of work-related fatalities, but the impact of work-related travel on overall traffic safety has been scarcely studied. The main objective of the present study was to assess drivers' relative road accident risk between work-related and personal journeys. A responsible/non-responsible case-control study was performed on a sample of 7,051 road accidents in France from the VOIESUR project. Logistic regression determined odds-ratios according to work-related versus personal travel, and identified risk factors for responsibility, specific to each of the two sub-groups. Drivers traveling on duty or commuting home were significantly less often responsible for accidents than drivers on personal journeys: OR = 0.75 [0.63; 0.89] and 0.65 [0.53; 0.80] respectively. Responsibility was significantly more frequent in commuting to versus from work: OR = 1.38 [1.06; 1.78]. Among on-duty drivers, professional passenger-transport drivers had the lowest risk of responsibility (OR = 0.25 [0.11; 0.58]), while those on temporary or work/study contracts and professional light goods vehicle drivers had the highest risk (OR = 11.64 [2.15; 62.94] and OR = 29.83 [5.19; 171.38] respectively). When driving under the influence of alcohol, risk of responsibility was higher in commuting home than in personal journeys. On-duty drivers showed lower risk of responsibility for an accident than other drivers. However, on-duty drivers on temporary or work/study contracts, who are usually not subject to specific regulations, showed higher risk, and should be the subject of particular attention regarding occupational risk prevention.

Electric Light Good Vehicles in Singapore

Research and efforts for implementing electric vehicles (EVs) are rapidly increasing. Most light goods vehicles (LGVs) in Singapore are diesel-propelled internal combustion engine (ICE) vehicles in 2023. However, the number of electric light goods vehicles (eLGVs) is exponentially increasing, indicating a shift towards economically and environmentally resilient options. This study examines the combined economic, environmental, and operational impacts of implementing eLGVs in Singapore, which distinguishes from previous research that analysed each aspect individually. Considering data and inputs from a specific company, lifecycle cost and emissions analyses were conducted comparing EVs and ICE vehicles. In addition, a survey on operations was conducted targeting respondents with eLGVs in their fleet. Findings indicate that, in Singapore’s context, eLGVs can potentially reduce costs, and savings grow with vehicle utilisation, assuming battery lasts 10-years with minimal degradation. Regarding the environmental impact, although the production of EVs results in higher greenhouse gas emissions, emissions from usage are much lower for eLGVs and further reduced with vehicle usage, resulting in overall lower emissions. Operational challenges identified relate to eLGVs charging time and infrastructure. Recommendations to motivate companies to transition to eLGVs are provided, and an ‘expected lifecycle emissions calculator’ created to compare various types of vehicles.

Trapezoidal Interval Type-2 Fuzzy PIPRECIA-MARCOS Model for Management Efficiency of Traffic Flow on Observed Road Sections

Road infrastructure management is an extremely important task of traffic engineering. For the purpose of efficient management, it is necessary to determine the efficiency of the traffic flow through PAE 85%, AADT and other exploitation parameters on the one hand, and the number of different types of traffic accidents on the other. In this paper, a novel TrIT2F (trapezoidal interval type-2 fuzzy) PIPRECIA (pivot pairwise relative criteria importance assessment)-TrIT2F MARCOS (measurement of alternatives and ranking according to compromise solution) was developed in order to, in a defined set of 14 road segments, identify the most efficient one for data related to light goods vehicles. Through this the aims and contributions of the study can be manifested. The evaluation was carried out on the basis of seven criteria with weights obtained using the TrIT2F PIPRECIA, while the final results were presented through the TrIT2F MARCOS method. To average part of the input data, the Dombi and Bonferroni operators have been applied. The final results of the applied TrIT2F PIPRECIA-TrIT2F MARCOS model show the following ranking of road segments, according to which Vrhovi–Šešlije M-I-103 with a gradient of −1.00 represents the best solution: A5 > A8 > A2 > A1 > A4 > A3 > A6 > A12 > A13 = A14 > A11 > A7 > A9 > A10. In addition, the validation of the obtained results was conducted by changing the values of the four most important criteria and changing the size of the decision matrix. Tests have shown great stability of the developed TrIT2F PIPRECIA-TrIT2F MARCOS model.

How accelerating the electrification of the van sector in Great Britain can deliver faster CO2 and NOx reductions

As a major emission contributor with significant growth potential, the light goods vehicles (vans) play an important part in achieving net-zero. In 2020 the UK government committed to phasing out sales of new internal combustion engine (ICE) vans by 2030, but the impact of the policy and how far are we to decarbonize the entire van fleet by 2050 is unclear. This paper investigates the CO2 and NOx emission trends in the van sector in Great Britain under the 2030 ICE phase-out. ECCo model11http://www.element-energy.co.uk/sectors/low-carbon-transport/project-case-studies/ is used to forecast the future van population by powertrain. The annual van mileage is estimated based on the van activity survey22https://www.gov.uk/government/statistics/van-statistics-2019-to-2020. The instantaneous emission model PHEM, NAEI emissions inventory and remote sensing measurements are used to parameterize real-world driving emission factors of CO2 and NOx. Scenarios have been set out to assess the impact of enablers and barriers affecting the pace of emission reductions. Results suggest vans are on track to reach the tailpipe net-zero target by 2050 under all scenarios, and the speed of NOx reduction is even faster. A rapid transition to battery electric vans in the early to mid-2020s will significantly lower CO2, with associated estimated monetary benefits of £1.3 billion.

Impact of change in traffic flow on vehicle non-exhaust PM2.5 and PM10 emissions: A case study of the M25 motorway, UK.

This study quantifies the change in traffic flow on the M25 motorway in the UK due to the COVID-19 outbreak. Moreover, the impact of the change in traffic flow on non-exhaust PM2.5 and PM10 emissions for different categories of vehicle was explored. During the year of the COVID-19 outbreak (March 2020 to February 2021), the total traffic flows of passenger cars (PCs), light goods vehicles (LGVs), heavy goods vehicles (HGVs), and long HGVs on the M25 motorway decreased by 38.6%, 27.6%, 15.9% and 7.2%, respectively, in comparison to the previous year. Correspondingly, the total mass of non-exhaust emissions (PM2.5 and PM10) of PCs, LGVs, HGVs, and long HGVs reduced by 38.7%, 27.3%, 16.2% and 7%, respectively. The traffic flows per year before and during the COVID-19 outbreak of long HGVs were 87.2% and 80.7% less than those of PCs. Correspondingly, the long HGVs emitted 10.2% less but 36.3% more PM2.5 emissions, as well as 10.9% and 66.7% more PM10 emissions than the latter, indicating that long HGVs contribute much more to non-exhaust particles than PCs. In addition, it was found that resuspension of road dust on the M25 motorway was the largest contributor to air pollution among non-exhaust emissions, followed by road wear, tyre wear, and brake wear particles.

Effect of diesel particulate filter regeneration on fuel consumption and emissions performance under real-driving conditions

Diesel particulate filters (DPF) are widely adopted in diesel vehicles to meet the increasingly stringent emission regulations, which require continuous passive regenerations or/and periodic active regenerations to burn off the accumulated particulate matter (PM). In spite of many laboratory studies using DPF benches and engine/chassis dynamometers, there is currently a lack of investigation on DPF regeneration under real-world conditions. Therefore, this study was conducted to investigate the impact of active DPF regenerations on the fuel consumption and gaseous and particulate emissions performance of a diesel light goods vehicle under real-driving conditions by using the state-of-the-art portable emission measurement system. In total, 60 real-driving emission (RDE) tests (∼1200 km in total) were performed on the same route during the same periods of a day, to minimise the effect of uncontrollable real-world factors on the performance evaluation. The results showed that real-world active DPF regenerations occurred every 130 km for the studied vehicle. Although they did not occur frequently, DPF regenerations increased the trip-averaged fuel consumption rate by 13% on average. CO and THC emission factors tended to increase with DPF regenerations because the post combustion used to achieve the high exhaust temperature for regeneration of the filter occurred under oxygen-lean conditions. Total NOx emissions were not affected but NO2/NOx ratio was greatly reduced by DPF regeneration due to lower NO oxidation by the diesel oxidation catalyst and higher NO2 reduction by the DPF. Finally, DPF regenerations sharply increased PM emission factors by 27 times compared with a trip without DPF regeneration, resulting in significant exceedance of the emission limit.

Forecasting Delivery Pattern through Floating Car Data: Empirical Evidence

This paper investigates the opportunities offered by floating car data (FCD) to infer delivering activities. A discrete trip-chain order model (within the random utility theory) for light goods vehicles (laden weight less than 3.5 tons) is hence proposed, which characterizes delivery tours in terms of the number of stops/deliveries performed. Thus, the main goal of the study is to calibrate a discrete choice model to estimate the number of stops/deliveries per tour by using FCD, which can be incorporated in a planning procedure for obtaining a preliminary assessment of parking demand. The data used refer to light goods vehicles operating in the Veneto region. The database contains more than 8000 tours undertaken in 60 working days. Satisfactory results have been obtained in terms of tour estimation and model transferability.

Data for Durability for Cement Concrete Pavement and Flexible Pavement in Expansive Soil Region

In India more than 70% of the population lives in villages and their main source of livelihood is agriculture. Because of stringent environmental rules industries are now shifting towards villages. Both of these activities require a better means of communication which can be provided by good conditioned roads. Earlier village roads had low volume of traffic, consisting mostly of rural transport vehicles, like agricultural tractors/trailers, light goods vehicles, buses, animal drawn vehicles, motorized two-wheelers and cycles. Some of the rural roads used to have light and medium trucks carrying sugarcane, timber, quarry materials, etc. Kumar et al. (1998) presented a case study of Jaipur district of India regarding rural travel characteristics and highlighted the importance of the contribution of the access roads in rural development. As of now flexible pavements are preferred for village connectivity because of the type of traffic and low initial cost of construction. But due to high cost of maintenance, sensitivity to water logging and lack of institutional set up for the maintenance, village roads deteriorate very fast especially in Expansive soil regions. Every year their several kilometers are washed away by floods and water logging. Moreover, the nature of traffic is also changing due to industrial growth in the nearby areas. Rigid pavement is an alternative to flexible pavement where the soil strength is poor, aggregate are costly and the drainage conditions are bad (as in portions of the roads passing through villages and water logged areas). However, they demand a high degree of professional expertise at the design stage, construction and maintenance besides high initial cost. The guidelines have been developed by Indian Road Congress (1RC) for the design and construction of cement concrete pavements for village roads in year 2014, named as IRC: SP : 62 – 2014 However cement Concrete Pavements are also not a sustainable option in expansive soil Thus, the policy makers, planners and engineers are bound to think about a more suitable alternative pavement for rural roads in expansive soil.

Development of a New Risk Assessment Methodology for Light Goods Vehicles on Two-Lane Road Sections

Increasing mobility directly affects traffic frequency and thus increases the possible risk of traffic accident occurrences. Taking this into account, it is necessary to create models for determining risk and to act preventively based on these models; this is of great importance both to society and science. In this paper, six measuring sections of a road network are considered on the basis of eight geometric-exploitation road parameters, taking into account the data for light goods vehicles. An original methodology is proposed for identifying risk levels of road sections through their evaluation. For identifying risk levels, the Dombi Logarithmic Methodology of Additive Weights (D’LMAW) was used, which was combined with the Measurement Alternatives and Ranking according to the Compromise Solution (MARCOS) method. Statistical indicators were processed using a hybrid methodology based on the application of rough numbers and Dombi–Bonferroni functions. The performance of the presented methodology was verified on a real-world example, processing the statistical parameters of six two-lane road sections, with the sixth measuring section showing the best performance, since it had the minimum risk. Research has shown that measuring sections with increasing longitudinal gradients are safer. The analysis of measuring sections from fall to rise reduces the deviation of speeds from the speed limit on the roads. The effectiveness, rationality, and robustness of the solution of the proposed methodology was confirmed through a sensitivity analysis.

Quantifying responses to changes in the jurisdiction of a congestion charge: A study of the London western extension.

This paper quantifies behavioural responses to changes in the jurisdiction of a congestion charge, with a successive focus on (i) an extension and (ii) a reduction in the size of the charging zone. We exploit the unanticipated nature of both the implementation and removal of London’s Western Expansion Zone (WEZ) as quasi-natural experiments to test whether individual responses to policies are asymmetric. We use the UK Department of Transport Annual Average Daily Flow (AADF) data, which records traffic flows for seven transport modes (including cars, buses, bicycles, heavy and light goods vehicles). Using a difference-in-differences approach, we find that the introduction of the WEZ led to a 4.9% decline in road traffic flows in the new congestion charge area. These results are robust to different model specifications. HGVs traffic did not significantly change post-WEZ, which indicates that their road demand is price inelastic. The removal of the WEZ led to no significant variations in traffic. This result indicates asymmetry in behaviour with persistent changes in post-intervention traffic demand levels.

Reducing vehicle fuel consumption and exhaust emissions from the application of a green-safety device under real driving

Vehicle emissions have a significantly negative impact on climate change, air quality and human health. Drivers of vehicles are the last major and often overlooked factor that determines vehicle performance. Eco-driving is a relatively low-cost and immediate measure to reduce fuel consumption and emissions significantly. This paper reports investigation of the effects of an on-board green-safety device on fuel consumption and emissions for both experienced and inexperienced drivers. A portable emissions measurement system (PEMS) was installed on a diesel light goods vehicle (LGV) to measure real-driving emissions (RDE), including total hydrocarbons (THC), CO CO2, NO, NO2 and particulate matter (PM). In addition, driving parameters (e.g. vehicle speed and acceleration) and environmental parameters (e.g. ambient temperature, humidity and pressure) were recorded in the experiments. The experimental results were evaluated using the Vehicle Specific Power (VSP) methodology to understand the effects of driving behavior on fuel consumption and emissions. The results indicated that driving behavior was improved for both experienced and inexperienced drivers after activation of the on-board green-safety device. In addition, the average time spent was shifted from higher to lower VSP modes by avoiding excessive speed, and aggressive accelerations and decelerations. For experienced drivers, the average fuel consumption and NO, NO2 and soot emissions were reduced by 5%, 56%, 39% and 35%, respectively, with the on-board green-safety device. For inexperienced drivers, the average reductions were 6%, 65%, 50% and 19%, respectively. Moreover, the long-term formed habits of experienced drivers are harder to be changed to accept the assistance of the green-safety device, whereas inexperienced drivers are likely to be more receptive to change and improve their driving behaviors.

A Metro-Based System as Sustainable Alternative for Urban Logistics in the Era of E-Commerce

Business to consumer e-commerce (B2C) has increased sharply in recent years driven by a growing online population and changes in consumer behavior. In metropolitan areas, the “Amazon effect” (online retailers’ vast selection, fast shipping, free returns, and low prices) has led to an increased use of light goods vehicles. This is affecting the rational functioning of the transport system, including a high degree of fragmentation, low load optimization, and, among other externalities, higher traffic congestion. This paper investigates the potential of a metro system, in a big city like Madrid, to provide delivery services by leveraging its existing carrying capacity and using the metro stations to collect parcels in lockers. It would be a new mixed distribution model for last-mile deliveries associated with e-commerce. To that end, the paper evaluates the cost and impacts of two alternative scenarios for managing the unused space in rolling stock (shared trains) or specific full train services (dedicated trains) on existing lines. The external costs of the proposed scenarios are compared with current e-commerce delivery scenario (parcel delivery by road). The results show that underground transport of parcels could significantly reduce congestion costs, accidents, noise, GHG emissions, and air pollution.

Analysing the main and interaction effects of commercial vehicle mix and roadway attributes on crash rates using a Bayesian random-parameter Tobit model

In previous research, the effects of commercial vehicle proportions (CVP) on overall crash propensity have been found to be significant, but the results have been varied in terms of the effect direction. In addition, the mediating or moderating effects of roadway attributes on the CVP-vs-safety relationships, have not been investigated. In addressing this gap in the literature, this study integrates databases on crashes, traffic, and inventory for Hong Kong road segments spanning 2014–2017. The classes of commercial vehicles considered are public buses, taxi, and light-, medium- and heavy-goods vehicles. Random-parameter Tobit models were estimated using the crash rates. The results suggest that the CVP of each class show credible effects on the crash rates, for the various crash severity levels. The results also suggest that the interaction between CVP and roadway attributes is credible enough to mediate the effect of CVP on crash rates, and the magnitude and direction of such mediation varies across the vehicle classes, crash severity levels, and roadway attribute type in four ways. First, the increasing effect of taxi proportion on slight-injury crash rate is magnified at road segments with high intersection density. Second, the increasing effect of light-goods vehicle proportion on slight-injury crash rate is magnified at road segments with on-street parking. Third, the association between the medium- and heavy-goods vehicle proportion and killed/severe injury (KSI) crash rate, is moderated by the roadway width (number of traffic lanes). Finally, a higher proportion of medium- and heavy-goods vehicles generally contributes to increased KSI crash rate at road segments with high intersection density. Overall, the findings of this research are expected not only to help guide commercial vehicle enforcement strategy, licensing policy, and lane control measures, but also to review existing urban roadway designs to enhance safety.

Air pollution and urban road transport: evidence from the world’s largest low-emission zone in London

Low-emission zones (LEZs) have been implemented widely in Europe to tackle air pollution sourced from vehicular emissions. We quantify the effectiveness of the world's largest LEZ—London's LEZ—in reducing its target pollutant, PM10. Using a difference-in-difference (DID) framework, we find that the least stringent phase I of London's LEZ induced a short-term increase in the roadside PM10 within the zone by about 14.8%, whereas the longer and more restrictive phase II significantly drove down the PM10 by 5.5%. We explore the underlying reasons behind the disparity in policy effect across stages. We show that upon the introduction of phase I, the traffic volume of targeted heavy goods vehicles (HGVs) and temporarily exempted light goods vehicles (LGVs) has substantially increased, outweighing the environmental effect of a higher proportion of greener vehicles. We provide possible behavioral explanations for this phenomenon.

Aggregate delivery tour modeling through AVM data: experimental evidence for light goods vehicles

ABSTRACT Freight vehicle origin-destination (O-D) matrices play a key role within the assessment procedures of city logistics scenarios, and simulation of delivery tours allows such O-D flows to be obtained. Therefore, the paper revisits a modeling framework for simulating delivery tours using an aggregate approach proposed by the authors and presents the preliminary results of its implementation to a real test case using global position system (GPS) traces for extracting vehicle tours/trip chains which are available on a large scale for such uses as fleet management or vehicle insurance. The modeling framework was calibrated using a dataset of light goods vehicles operating in the Veneto region (Italy) for which automated vehicle monitoring (AVM) data were available. The results show that such an approach enables satisfactory results to be obtained in terms of freight distribution O-D matrices.

Characterisation of diesel vehicle emissions and determination of remote sensing cutpoints for diesel high-emitters

Diesel vehicles are a major source of air pollutants in cities and have caused significant health risks to the public globally. This study used both on-road remote sensing and transient chassis dynamometer to characterise emissions of diesel light goods vehicles. A large sample size of 183 diesel vans were tested on a transient chassis dynamometer to evaluate the emission levels of in-service diesel vehicles and to determine a set of remote sensing cutpoints for diesel high-emitters. The results showed that 79% and 19% of the Euro 4 and Euro 5 diesel vehicles failed the transient cycle test, respectively. Most of the high-emitters failed the NO limits, while no vehicle failed the HC limits and only a few vehicles failed the CO limits. Vehicles that failed NO limits occurred in both old and new vehicles. NO/CO2 ratios of 57.30 and 22.85 ppm/% were chosen as the remote sensing cutpoints for Euro 4 and Euro 5 high-emitters, respectively. The cutpoints could capture a Euro 4 and Euro 5 high-emitter at a probability of 27% and 57% with one snapshot remote sensing measurement, while only producing 1% of false high-emitter detections. The probability of high-emitting events was generally evenly distributed over the test cycle, indicating that no particular driving condition produced a higher probability of high-emitting events. Analysis on the effect of cutpoints on real-driving diesel fleet was carried out using a three-year remote sensing program. Results showed that 36% of Euro 4 and 47% of Euro 5 remote sensing measurements would be detected as high-emitting using the proposed cutpoints.

Calculating the population at risk for transport system users

The Risk Assessment for Reservoir Safety (RARS) guidance documentation mentions and prescribes population at risk (PAR) rates for various types of transportation routes. This paper presents a major update to the values presented in RARS, following a review of the available statistical data from the Department for Transport. Statistics for various road types (unclassified, C roads, B roads, A roads and dual carriageways in urban and rural settings) and users (two-wheel vehicles, cars, light goods vehicles, buses and heavy goods vehicles) have been used to determine a set of detailed and rapid daily-averaged PAR assessment criteria.

Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London

Growth in e-commerce has led to increasing use of light goods vehicles for parcel deliveries in urban areas. This paper provides an insight into the reasons behind this growth and the resulting effort required to meet the exacting delivery services offered by e-retailers which often lead to poor vehicle utilisation in the last-mile operation, as well as the duplication of delivery services in urban centres as competitors vie for business. A case study investigating current parcel delivery operations in central London identified the scale of the challenge facing the last-mile parcel delivery driver, highlighting the importance of walking which can account for 62% of the total vehicle round time and 40% of the total round distance in the operations studied. The characteristics of these operations are in direct conflict with the urban infrastructure which is being increasingly redesigned in favour of walking, cycling and public transport, reducing the kerbside accessibility for last-mile operations. The paper highlights other pressures on last-mile operators associated with managing seasonal peaks in demand; reduced lead times between customers placing orders and deliveries being made; meeting delivery time windows; first-time delivery failure rates and the need to manage high levels of product returns. It concludes by describing a range of initiatives that retailers and parcel carriers, sometimes in conjunction with city authorities, can implement to reduce the costs associated with last-mile delivery, without negatively impacting on customer service levels.

Concepts of Load Handling Devices, Adjusted to Light Goods Vehicles of The Weight up to 3.5t

The main aim of the article is to present three concepts of load handling devices, adjusted to light goods vehicles of the weight up to 3.5 t. The design issue commissioned by Poczta Polska - the Polish Post was analysed. On the basis of the analysis the design assumptions were taken to design a device. The construction and the method of operation of the design structures suggested by the author were discussed. All the concepts were compared with one another with the use of a SWOT analysis.

Low carbon pathways for light goods vehicles in Ireland

Transport is the most significant energy consuming sector in Ireland, accounting for 40% of final energy demand in 2013, with private cars and road freight contributing 51% and 25% to transport energy demand respectively. Despite a large literature body analysing private car energy use, there has been very little published analysis on freight transport, which itself has largely been limited to one aspect of freight transport, namely heavy goods vehicles (HGVs). This paper focuses on the energy and related CO2 emissions associated with light goods vehicles (LGVs) in Ireland, which contributes to addressing the knowledge gap in freight transport energy use. Low carbon pathways for LGV transport in Ireland, which align with an 80% CO2 emissions reduction by 2050 (relative to 1990), were developed using scenario analysis and a multi-model approach, which included i) the Irish TIMES energy systems model – a least cost optimisation model of the Irish energy system - and ii) an LGV stock model for Ireland – a sectoral simulation model of LGVs in Ireland. The introduction of energy efficiency measures and indigenous gaseous biofuels were found to be key elements in a technically feasible roadmap, which can meet the required CO2 emissions reduction target.