Conception and Development of a Last Mile Vehicle for Urban Areas

AbstractIn megacities, increasing globalization effects are leading to rapidly increasing prosperity and augmented purchasing power, and thus to a growing need for punctual, cost-effective, and environmentally friendly delivery of goods. A smart, small electric vehicle concept is presented that targets on meeting the requirements for the delivery of goods in urban areas and that is designed especially for the delivery on the last mile. This last mile vehicle (LMV) for cargo transportation is attached to a truck. Whenever it is needed, for example to deliver goods into narrow streets, in pedestrian areas or in case of traffic jams, it can be unfolded and unloaded from the truck and hereby guarantees a flexible and punctual delivery of goods. This flexible on-time delivery is possible because the last mile vehicle is designed, so that the legal regulations of the non-motorized vehicle lane, that is everywhere to be found in Asia, are met. The vehicle is designed with three wheels, a range of 40-60 km and an electric drive train with a continuous power of 2 × 250 W that enables a maximum speed up to 40 km/h of the vehicle. The drive train consists of a battery pack that can be charged electrically from the truck, two inverters, and two electric wheel hub motors. The LMV has been designed and constructed as a prototype and has been tested on non-public roads to prove the vehicle concept. For Europe, it can be classified as an L2e vehicle and with slight modifications; it can be applied on European roads as well.

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Vehicle Routing with Stochastic Supply of Crowd Vehicles and Time Windows

Transportation Science ◽

10.1287/trsc.2021.1101 ◽

2021 ◽

Author(s):

Fabian Torres ◽

Michel Gendreau ◽

Walter Rei

Keyword(s):

Urban Areas ◽

Time Window ◽

Time Windows ◽

Cost Effective ◽

Branch And Price ◽

Irrational Behavior ◽

Last Mile ◽

Stochastic Solution ◽

The Cost ◽

Price Algorithm

The growth of e-commerce has increased demand for last-mile deliveries, increasing the level of congestion in the existing transportation infrastructure in urban areas. Crowdsourcing deliveries can provide the additional capacity needed to meet the growing demand in a cost-effective way. We introduce a setting where a crowd-shipping platform sells heterogeneous products of different sizes from a central depot. Items sold vary from groceries to electronics. Some items must be delivered within a time window, whereas others need a customer signature. Furthermore, customer presence is not guaranteed, and some deliveries may need to be returned to the depot. Delivery requests are fulfilled by a fleet of professional drivers and a pool of crowd drivers. We present a crowd-shipping platform that standardizes crowd drivers’ capacities and compensates them to return undelivered packages back to the depot. We formulate a two-stage stochastic model, and we propose a branch and price algorithm to solve the problem exactly and a column generation heuristic to solve larger problems quickly. We further develop an analytical method to calculate upper bounds on the supply of vehicles and an innovative cohesive pricing problem to generate columns for the pool of crowd drivers. Computational experiments are carried out on modified Solomon instances with a pool of 100 crowd vehicles. The branch and price algorithm is able to solve instances of up to 100 customers. We show that the value of the stochastic solution can be as high as 18% when compared with the solution obtained from a deterministic simplification of the model. Significant cost reductions of up to 28% are achieved by implementing crowd drivers with low compensations or higher capacities. Finally, we evaluate what happens when crowd drivers are given the autonomy to select routes based on rational and irrational behavior. There is no cost increase when crowd drivers are rational and select routes that have a higher compensation first. However, when crowd drivers are irrational and select routes randomly, the cost can increase up to 4.2% for some instances.

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Solution of Two-Echelon Facility Location Problems by Approximation Methods

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2610-01 ◽

2017 ◽

Vol 2610 (1) ◽

pp. 1-9 ◽

Cited By ~ 3

Author(s):

Mahyar Jahangiriesmaili ◽

Sina Bahrami ◽

Matthew J. Roorda

Keyword(s):

Urban Areas ◽

Transportation Cost ◽

Cost Effective ◽

Optimal Number ◽

Approximation Techniques ◽

Delivery Costs ◽

Last Mile ◽

Selection Of ◽

Center Potential

The two-echelon delivery structure is a strategy that can be implemented in urban areas to lower delivery costs by reducing the movement of heavy goods vehicles. In a two-echelon delivery structure, large trucks deliver shipments from a consolidation center to several terminals, where packages are transferred to smaller trucks for last-mile deliveries. This paper formulates a model that solves the two-echelon delivery structure by the use of approximation techniques. Several potential terminal locations and demand areas were identified, and the optimal number and locations of the terminals were examined, as the model evaluated the most cost-effective routes between the consolidation center, potential terminals, and demand areas. Downtown Toronto, Ontario, Canada, was chosen as the case study area to assess the model, and a cost analysis of the number and locations of the terminals was performed. The experiments showed that the number and the locations of the terminals were greatly influenced by the opening cost of the terminals and the transportation cost of the delivery trucks. It was also discovered that the likelihood of selection of terminals that were positioned near both the consolidation center and the center of the service area was higher than the likelihood of selection of terminals at any other location.

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A Series of Vertical Deflections, a Promising Traffic Calming Measure: Analysis and Recommendations for Spacing

Applied Sciences ◽

10.3390/app10103368 ◽

2020 ◽

Vol 10 (10) ◽

pp. 3368 ◽

Cited By ~ 2

Author(s):

Heriberto Pérez-Acebo ◽

Robert Ziółkowski ◽

Alaitz Linares-Unamunzaga ◽

Hernán Gonzalo-Orden

Keyword(s):

Urban Areas ◽

Maximum Speed ◽

Intermediate Point ◽

Speed Reduction ◽

Traffic Calming ◽

A Value ◽

Safe Area ◽

Measure Analysis ◽

Speed Up ◽

Speed Humps

Traffic calming measures (TCM) are placed in urban areas to improve road safety, and among them, vertical TCMs are widely employed. Many researches are focused on the influence of the geometry of each measure on speed reduction, but it is demonstrated that drivers forget its effect and speed up after it. Therefore, placing consecutive TCMs can help to maintain a safe area. However, scarce literature can be found about the adequate spacing between them. Hence, the aim of this paper is to analyze the adequate distance between TCMs. Various streets with variable distances and different vertical TCMs were evaluated in Poland and Spain, including raised crosswalks, raised intersections, speed humps and speed cushions. The intermediate point between two TCMs was selected as the place where the maximum speed is achieved. Results showed that there was a good correlation between the speeds at intermediate points and the distance between TCMs, with a determination coefficient around 0.80. For an 85th percentile of the speed under 50 km/h, a maximum distance of 200 m between TCMs is recommended, and for a value of 40 km/h, 75 m.

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Efficient Schedule of Energy-Constrained UAV Using Crowdsourced Buses in Last-Mile Parcel Delivery

Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies ◽

10.1145/3448079 ◽

2021 ◽

Vol 5 (1) ◽

pp. 1-23

Author(s):

Yan Pan ◽

Shining Li ◽

Qianwu Chen ◽

Nan Zhang ◽

Tao Cheng ◽

...

Keyword(s):

Traffic Congestion ◽

Large Scale ◽

Load Capacity ◽

Scheduling Algorithm ◽

Cost Effective ◽

Promising Alternative ◽

Logistics Industry ◽

Last Mile ◽

Delivery Scheduling ◽

Schedule Approach

Stimulated by the dramatical service demand in the logistics industry, logistics trucks employed in last-mile parcel delivery bring critical public concerns, such as heavy cost burden, traffic congestion and air pollution. Unmanned Aerial Vehicles (UAVs) are a promising alternative tool in last-mile delivery, which is however limited by insufficient flight range and load capacity. This paper presents an innovative energy-limited logistics UAV schedule approach using crowdsourced buses. Specifically, when one UAV delivers a parcel, it first lands on a crowdsourced social bus to parcel destination, gets recharged by the wireless recharger deployed on the bus, and then flies from the bus to the parcel destination. This novel approach not only increases the delivery range and load capacity of battery-limited UAVs, but is also much more cost-effective and environment-friendly than traditional methods. New challenges therefore emerge as the buses with spatiotemporal mobility become the bottleneck during delivery. By landing on buses, an Energy-Neutral Flight Principle and a delivery scheduling algorithm are proposed for the UAVs. Using the Energy-Neutral Flight Principle, each UAV can plan a flying path without depleting energy given buses with uncertain velocities. Besides, the delivery scheduling algorithm optimizes the delivery time and number of delivered parcels given warehouse location, logistics UAVs, parcel locations and buses. Comprehensive evaluations using a large-scale bus dataset demonstrate the superiority of the innovative logistics UAV schedule approach.

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iBikeSafe: A Multi-Parameter System for Monitoring, Evaluation and Visualization of Cycling Paths in Smart Cities Targeted at Cycling Adverse Conditions

Smart Cities ◽

10.3390/smartcities4030056 ◽

2021 ◽

Vol 4 (3) ◽

pp. 1058-1086

Author(s):

Franklin Oliveira ◽

Daniel G. Costa ◽

Luciana Lima ◽

Ivanovitch Silva

Keyword(s):

Urban Areas ◽

Smart Cities ◽

Large City ◽

Health And Safety ◽

Parameter System ◽

Urban Centers ◽

Adverse Conditions ◽

Last Mile ◽

Real Scenario

The fast transformation of the urban centers, pushed by the impacts of climatic changes and the dramatic events of the COVID-19 Pandemic, will profoundly influence our daily mobility. This resulted scenario is expected to favor adopting cleaner and flexible modal solutions centered on bicycles and scooters, especially as last-mile options. However, as the use of bicycles has rapidly increased, cyclists have been subject to adverse conditions that may affect their health and safety when cycling in urban areas. Therefore, whereas cities should implement mechanisms to monitor and evaluate adverse conditions in cycling paths, cyclists should have some effective mechanism to visualize the indirect quality of cycling paths, eventually supporting choosing more appropriate routes. Therefore, this article proposes a comprehensive multi-parameter system based on multiple independent subsystems, covering all phases of data collecting, formatting, transmission, and processing related to the monitoring, evaluating, and visualizing the quality of cycling paths in the perspective of adverse conditions that affect cyclist. The formal interactions of all modules are carefully described, as well as implementation and deployment details. Additionally, a case study is considered for a large city in Brazil, demonstrating how the proposed system can be adopted in a real scenario.

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The Efficiency of Large Hole Boring (MSP) Method in the Reduction of Blast-Induced Vibration

Applied Sciences ◽

10.3390/app11041814 ◽

2021 ◽

Vol 11 (4) ◽

pp. 1814

Author(s):

Min Seong Kim ◽

Sean Seungwon Lee

Keyword(s):

Urban Areas ◽

Cost Effective ◽

Base Case ◽

Large Hole ◽

Promising Alternative ◽

Geological Information ◽

Drill And Blast ◽

Smooth Blasting ◽

Alternative Designs ◽

Blasting Method

Drill and blast is the most cost-effective excavation method for underground construction, however, vibration and noise, induced by blasting, have been consistently reported as problems. Cut blasting has been widely employed to reduce the blast-induced problems during underground excavation. We propose that the large hole boring method using the state-of-the-art MSP (Multi-setting smart-investigation of the ground and pre-large hole boring) machine (“MSP method”) can efficiently improve vibration reduction. The MSP machine will be used to create 382 mm diameter empty holes at the tunnel cut area for this purpose. This study assessed the efficiency of the MSP method in reducing blast-induced vibration in five blasting patterns using a cylinder-cut, which is a traditional cut blasting method. The controlled blasting patterns using the MSP method demonstrated up to 72% reduction in blast-induced vibration, compared to the base case, Pattern B, where only cylinder-cut and smooth blasting method were applied. Therefore, the MSP method proves to be a promising alternative for blasting in sensitive urban areas where non-vibration excavation techniques were initially considered. Geological characteristics of 50 m beyond the excavation face can be acquired through the proposed real-time boring data monitoring system together with a borehole alignment tracking and ground exploration system. The obtained geological information will be a great help in preparing alternative designs, and scheduling of construction equipment and labour during the tunnel construction.

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Selecting Sanitation Solutions for Peri-urban Areas: A Case Study of Can Tho, Vietnam

Water Practice & Technology ◽

10.2166/wpt.2010.109 ◽

2010 ◽

Vol 5 (4) ◽

Cited By ~ 1

Author(s):

Naomi Carrard ◽

Juliet Willetts ◽

Cynthia Mitchell ◽

Mick Paddon ◽

Monique Retamal

Keyword(s):

Urban Areas ◽

Cost Effective ◽

Asset Replacement ◽

Fit For Purpose ◽

Infrastructure Investments ◽

Sanitation Systems ◽

Can Tho City ◽

Sustainable Futures ◽

Sanitation Infrastructure ◽

Selection Of

In peri-urban areas where infrastructure investments have not yet been made, there is a need to determine the most context-appropriate, fit for purpose and sustainable sanitation solutions. Decision makers must identify the optimal system scale (on the spectrum from centralized to community to cluster scale) and assess the long-term costs and socio-economic/environmental impacts associated with different options. Addressing both cost-effectiveness and sustainability are essential to ensure that institutions and communities are able to continue to bear the costs and management burden of infrastructure operation, maintenance and asset replacement. This paper describes an approach to sanitation planning currently being undertaken as a research study in Can Tho City in southern Vietnam, by the Institute for Sustainable Futures and Can Tho University in collaboration with Can Tho Water Supply and Sewerage Company. The aim of the study is to facilitate selection of the most context-appropriate, fit for purpose, cost effective and sustainable sanitation infrastructure solution. As such, the study compares a range of sanitation alternatives including centralized, decentralized (at household or cluster scale) and resource recovery options. This paper provides an overview of the study and considers aspects of the Can Tho and Vietnamese regulatory, development and institutional context that present drivers and challenges for comparison of options and selection of fit for purpose sanitation systems.

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SIMULATION OF HYBRID ELECTRIC VEHICLE BASED ON A SERIES DRIVE TRAIN LAYOUT

Jurnal Teknologi ◽

10.11113/jt.v78.2867 ◽

2016 ◽

Vol 78 (6) ◽

Author(s):

Mohd Sabirin Rahmat ◽

Fauzi Ahmad ◽

Ahmad Kamal Mat Yamin ◽

Noreffendy Tamaldin ◽

Vimal Rau Aparow ◽

...

Keyword(s):

Electric Vehicle ◽

Hybrid Electric Vehicle ◽

Combustion Engine ◽

Automatic Transmission ◽

Permanent Magnet Synchronous Motor ◽

Drive Train ◽

Maximum Speed ◽

Power Train ◽

Human In The Loop ◽

Hybrid Electric

This paper provided a validated modeling and a simulation of a 6 degree freedom vehicle longitudinal model and drive-train component in a series hybrid electric vehicle. The 6-DOF vehicle dynamics model consisted of tire subsystems, permanent magnet synchronous motor which acted as the prime mover coupled with an automatic transmission, hydraulic brake subsystem, battery subsystem, alternator subsystem and internal combustion engine to supply the rotational input to the alternator. A speed and torque tracking control systems of the electric power train were developed to make sure that the power train was able to produce the desired throttle torque in accelerating the vehicle. A human-in-the-loop-simulation was utilized as a mechanism to evaluate the effectiveness of the proposed hybrid electric vehicle. The proposed simulation was used as the preliminary result in identifying the capability of the vehicle in terms of the maximum speed produced by the vehicle and the capability of the alternator to recharge the battery. Several tests had been done during the simulation, namely sudden acceleration, acceleration and braking test and unbounded motion. The results of the simulation showed that the proposed hybrid electric vehicle can produce a speed of up to 70 km/h with a reasonable charging rate to the battery. The findings from this study can be considered in terms of design, optimization and implementation in a real vehicle.

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Estimation of Building Heights and DEM Accuracy Assessment Using ICESat-2 Data Products

Engineering Proceedings ◽

10.3390/ecsa-8-11442 ◽

2021 ◽

Vol 10 (1) ◽

pp. 37

Author(s):

Goddu Pavan Sai Goud ◽

Ashutosh Bhardwaj

Keyword(s):

Spatial Data ◽

Rural Areas ◽

Urban Areas ◽

Accuracy Assessment ◽

Urban Expansion ◽

Population Expansion ◽

Cost Effective ◽

Absolute Error ◽

Google Earth ◽

Surface Geometry

The use of remote sensing for urban monitoring is a very reliable and cost-effective method for studying urban expansion in horizontal and vertical dimensions. The advantage of multi-temporal spatial data and high data accuracy is useful in mapping urban vertical aspects like the compactness of urban areas, population expansion, and urban surface geometry. This study makes use of the ‘Ice, cloud, and land elevation satellite-2′ (ICESat-2) ATL 03 photon data for building height estimation using a sample of 30 buildings in three experimental sites. A comparison of computed heights with the heights of the respective buildings from google image and google earth pro was done to assess the accuracy and the result of 2.04 m RMSE was obtained. Another popularly used method by planners and policymakers to map the vertical dimension of urban terrain is the Digital Elevation Model (DEM). An assessment of the openly available DEM products—TanDEM-X and Cartosat-1 has been done over Urban and Rural areas. TanDEM-X is a German earth observation satellite that uses InSAR (Synthetic Aperture Radar Interferometry) technique to acquire DEM while Cartosat-1 is an optical stereo acquisition satellite launched by the Indian Space Research Organization (ISRO) that uses photogrammetric techniques for DEM acquisition. Both the DEMs have been compared with ICESat-2 (ATL-08) Elevation data as the reference and the accuracy has been evaluated using Mean error (ME), Mean absolute error (MAE) and Root mean square error (RMSE). In the case of Greater Hyderabad Municipal Corporation (GHMC), RMSE values 5.29 m and 7.48 m were noted for TanDEM-X 90 and CartoDEM V3 R1 respectively. While the second site of Bellampalli Mandal rural area observed 5.15 and 5.48 RMSE values for the same respectively. Therefore, it was concluded that TanDEM-X has better accuracy as compared to the CartoDEM V3 R1.

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Leveraging machine learning to produce a cost-effective national building height map of Ireland

10.5194/ems2021-48 ◽

2021 ◽

Author(s):

Eoghan Keany ◽

Geoffrey Bessardon ◽

Emily Gleeson

Keyword(s):

Machine Learning ◽

Remote Sensing ◽

High Resolution ◽

Land Cover ◽

Urban Areas ◽

Cost Effective ◽

Land Cover Classification ◽

National Scale ◽

Building Height ◽

Height Data

To represent surface thermal, turbulent and humidity exchanges, Numerical Weather Prediction (NWP) systems require a land-cover classification map to calculate sur-face parameters used in surface flux estimation. The latest land-cover classification map used in the HARMONIE-AROME configuration of the shared ALADIN-HIRLAMNWP system for operational weather forecasting is ECOCLIMAP-SG (ECO-SG). The first evaluation of ECO-SG over Ireland suggested that sparse urban areas are underestimated and instead appear as vegetation areas (1). While the work of (2) on land-cover classification helps to correct the horizontal extent of urban areas, the method does not provide information on the vertical characteristics of urban areas. ECO-SG urban classification implicitly includes building heights (3), and any improvement to ECO-SG urban area extent requires a complementary building height dataset.Openly accessible building height data at a national scale does not exist for the island of Ireland. This work seeks to address this gap in availability by extrapolating the preexisting localised building height data across the entire island. The study utilises information from both the temporal and spatial dimensions by creating band-wise temporal aggregation statistics from morphological operations, for both the Sentinel-1A/B and Sentinel-2A/B constellations (4). The extrapolation uses building height information from the Copernicus Urban Atlas, which contains regional coverage for Dublin at 10 m x10 m resolution (5). Various regression models were then trained on these aggregated statistics to make pixel-wise building height estimates. These model estimates were then evaluated with an adjusted RMSE metric, with the most accurate model chosen to map the entire country. This method relies solely on freely available satellite imagery and open-source software, providing a cost-effective mapping service at a national scale that can be updated more frequently, unlike expensive once-off private mapping services. Furthermore, this process could be applied by these services to reduce costs by taking a small representative sample and extrapolating the rest of the area. This method can be applied beyond national borders providing a uniform map that does not depends on the different private service practices facilitating the updates of global or continental land-cover information used in NWP.&#160;(1) G. Bessardon and E. Gleeson, &#8220;Using the best available physiography to improve weather forecasts for Ireland,&#8221; in Challenges in High-Resolution Short Range NWP at European level including forecaster-developer cooperation, European Meteorological Society, 2019.(2) E. Walsh, et al., &#8220;Using machine learning to produce a very high-resolution land-cover map for Ireland, &#8221; Advances in Science and Research,&#160; (accepted for publication).(3) CNRM, "Wiki - ECOCLIMAP-SG" https://opensource.umr-cnrm.fr/projects/ecoclimap-sg/wiki(4) D. Frantz, et al., &#8220;National-scale mapping of building height using sentinel-1 and sentinel-2 time series,&#8221; Remote Sensing of Environment, vol. 252, 2021.(5) M. Fitrzyk, et al., &#8220;Esa Copernicus sentinel-1 exploitation activities,&#8221; in IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium, IEEE, 2019.

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