Dynamic Demand Forecast and Assignment Model for Bike-and-Ride System

Bike-and-Ride (B&R) has long been considered as an effective way to deal with urbanization-related issues such as traffic congestion, emissions, equality, etc. Although there are some studies focused on the B&R demand forecast, the influencing factors from previous studies have been excluded from those forecasting methods. To fill this gap, this paper proposes a new B&R demand forecast model considering the influencing factors as dynamic rather than fixed ones to reach higher forecasting accuracy. This model is tested in a theoretical network to validate the feasibility and effectiveness and the results show that the generalised cost does have an effect on the demand for the B&R system.</p

Adaptive vehicle extraction in real-time traffic video monitoring based on the fusion of multi-objective particle swarm optimization algorithm

Abstract In view of the problems in the real-time traffic video monitoring that the adaptive vehicle extraction is greatly affected by the environmental factors such as the illumination, noise, and so on; the missed detection and error detection rate is high; and it is difficult to meet the robustness and the real-time performance at the same time, a kind of method for the adaptive vehicle extraction in real-time traffic video monitoring based on the fusion of multi-objective particle swarm optimization algorithm is put forward. In this method, based on the multi-objective particle swarm optimization algorithm, adaptive binarization processing is carried out on the image first, and the interference points are removed by filtration through the erosion and expansion method. Simple and effective method is used to carry out the merger of the shadow line and the extraction of the real-time traffic video. In the algorithm, the information entropy in the target area and the symmetry characteristics of the vehicle tail are used to screen and identify the region of interest, which has reduced the missed detection and error detection rate of the algorithm. The multi-objective particle swarm optimization algorithm is used to extract the vehicle boundaries and has achieved relatively good effect. The results show that the detection accuracy is 89% and the average operating speed is 17.6 frames/s during the processing of the real-time traffic video with the resolution of 640 × 480

Collaborative multicenter logistics delivery network optimization with resource sharing.

Collaboration among logistics facilities in a multicenter logistics delivery network can significantly improve the utilization of logistics resources through resource sharing including logistics facilities, vehicles, and customer services. This study proposes and tests different resource sharing schemes to solve the optimization problem of a collaborative multicenter logistics delivery network based on resource sharing (CMCLDN-RS). The CMCLDN-RS problem aims to establish a collaborative mechanism of allocating logistics resources in a manner that improves the operational efficiency of a logistics network. A bi-objective optimization model is proposed with consideration of various resource sharing schemes in multiple service periods to minimize the total cost and number of vehicles. An adaptive grid particle swarm optimization (AGPSO) algorithm based on customer clustering is devised to solve the CMCLDN-RS problem and find Pareto optimal solutions. An effective elite iteration and selective endowment mechanism is designed for the algorithm to combine global and local search to improve search capabilities. The solution of CMCLDN-RS guarantees that cost savings are fairly allocated to the collaborative participants through a suitable profit allocation model. Compared with the computation performance of the existing nondominated sorting genetic algorithm-II and multi-objective evolutionary algorithm, AGPSO is more computationally efficient. An empirical case study in Chengdu, China suggests that the proposed collaborative mechanism with resource sharing can effectively reduce total operational costs and number of vehicles, thereby enhancing the operational efficiency of the logistics network

Optimization of Green Vehicle Paths Considering the Impact of Carbon Emissions: A Case Study of Municipal Solid Waste Collection and Transportation

In recent years, the waste produced as a result of the production and consumption activities of urban residents has led to significant environmental degradation and resource wastage. This paper focuses on the research object of municipal solid waste (MSW) collection and transportation based on the concept of “sustainable development and green economy”. Firstly, this study examines the current state of urban domestic garbage collection and transportation. It analyzes the following challenges and deficiencies of the existing collection and transportation system: (1) the operating efficiency of garbage collection vehicles is low, resulting in a significant accumulation of waste on the roadside and within the community; (2) the vehicle collection and transportation routes are fixed, and there are empty vehicles running; (3) the amount of garbage on a route exceeds the vehicle’s loading capacity, which requires the vehicle to perform a second round of collection and transportation. To enhance the efficiency of urban garbage collection and transportation and minimize the collection and transportation costs, we are investigating the problem of optimizing the path for green vehicles. To comprehensively optimize the fixed cost, variable cost, and carbon emission cost incurred during vehicle operation, a vehicle routing model with time windows is established, taking into account vehicle load constraints. Carbon emission coefficient and carbon tax parameters are introduced into the model and the “fuel-carbon emission” conversion method is used to measure the carbon cost of enterprises. An improved ant colony optimization (ACO) method is proposed: (1) the introduction of a vehicle load factor improves the ant state transfer method; (2) the updated pheromone method is improved, and additional pheromone is added to both the feasible path and the path with the minimum objective function; (3) the max–min ACO algorithm is introduced to address the issue of premature convergence of the algorithm; (4) the embedding of a 2-opt algorithm further prevents the ACO algorithm from falling into the local optimum. Finally, the calculation results based on the example data demonstrate that the algorithm has a significant advantage over the genetic algorithm (GA) and particle swarm optimization (PSO) algorithm. The total transportation distance determined by this algorithm is shorter than that of the GA and PSO methods, and the total cost of the scheme is 1.66% and 1.89% lower than that determined by GA and PSO, respectively. Compared to the data from the actual case, the number of vehicles required in the operation of this algorithm and model is reduced by three. Additionally, the total cost, fixed cost, and carbon emission cost incurred by the vehicles during operation were reduced by 31.2%, 60%, and 25.3% respectively. The results of this study help the station to collect and distribute waste efficiently, while also achieving the goals of energy saving, consumption reduction, and emission reduction

Study on Spatio-Temporal Patterns of Commuting under Adverse Weather Events: Case Study of Typhoon In-Fa

This study focuses on the main urban area of Yangzhou City and conducts a quantitative comparative analysis of traffic accessibility during normal weather and extreme precipitation conditions (typhoon) based on GPS trajectories of buses. From both temporal and spatial dimensions, it comprehensively examines the impact of extreme precipitation on bus travel speed, travel time, and the commuting range of residents in the main urban area of Yangzhou City. (1) Through the mining and analysis of multi-source heterogeneous big data (bus GPS trajectory data, bus network data, rainfall remote sensing data, and road network data), it is found that the rainstorm weather greatly affects the average speed and travel time of buses. In addition, when the intensity of heavy rainfall increases (decreases), the average bus speed and travel time exhibit varying degrees of spatio-temporal change. During the morning and evening rush hour commuting period of rainstorm weather, there are obvious differences in the accessibility change in each typical traffic community in the main urban area of Yangzhou city. In total, 90% of the overall accessibility change value is concentrated around −5 min~5 min, and the change range is concentrated around −25~10%. (2) To extract the four primary traffic districts (Lotus Pond, Slender West Lake, Jinghua City, and Wanda Plaza), we collected Points of Interest (POI) data from Amap and Baidu heat map, and a combination analysis of the employment–residence ratio model and proximity methods was employed. The result show that the rainstorm weather superimposed on the morning peak hour has different degrees of impact on the average speed of the above-mentioned traffic zones, with the most obvious impact on the Lotus Pond and the smallest impact on Wanda Plaza. Under the rainstorm weather, the traffic commute in the main urban area of Yangzhou in the morning and evening peak hour is basically normal. The results of this paper can help to quantify the impact of typhoon-rainstorm weather events on traffic commuting in order to provide a scientific basis for the traffic management department to effectively prevent traffic jams, ensure the reliability of the road network, and allow the traffic management department to more effectively manage urban traffic

Assessing pollution and risk of polycyclic aromatic hydrocarbons in sewage sludge from wastewater treatment plants in China's top coal-producing region

Managing and disposing of sewage sludge have been a severe environmental challenge around the world. China produces hundreds of million tons of sewage sludge annually, and a better understanding of the extent and risk of the associated pollution is of critical importance for implementing environmentally safe regulations and practices. The present study examined the quantity, composition, source, and risk of polycyclic aromatic hydrocarbons (PAHs) in sewage sludge from 18 wastewater treatment plants (WWTPs) in Shaanxi, one of China's top coal-producing provinces. The total concentrations of 16 PAHs varied from 778 to 3264ng/g dry weight, which is below the upper safety limit (5000ng/g dry weight) set for the disposal of sludge from municipal wastewater treatment plants for agricultural use in China. However, the concentration of individual PAH compound exceeded the acceptable level prescribed by the Netherland Soil Standard. Three-ring PAHs were the most abundant constituent (50% of total PAHs on average), followed by four-ring PAHs averaging 25%. Relative to sludge PAHs in the same region a decade ago, the total concentrations decreased by more than 27% and the composition shifted to a more pronounced dominance by low molecular weight compounds. This compositional shift suggests higher contributions of petrogenic sources, which may reflect China's increasing consumption of petroleum products over the past decade. The flux of sludge PAHs from each WWTP was positively correlated with the corresponding city's GDP and population, and the total flux amounted to over 100kg each year for WWTPs in the Xi'an city. The mean toxicity equivalent quantity (TEQ) value was more than twice higher than the value recommended by the Netherlands Soil Standard, and seven carcinogenic PAHs were the primary contributor (i.e., 89-99%) of the TEQ. Collectively, our findings demonstrate that sewage sludge PAHs in Shaanxi constitute a significant source of environmental pollution and toxicity, which cautions against the direct discharge and reuse of sewage sludge and further highlights challenges in managing and disposing of the vast quantities of sewage sludge in China

Removal Efficiency and Risk Assessment of Polycyclic Aromatic Hydrocarbons in a Typical Municipal Wastewater Treatment Facility in Guangzhou, China

The loading and removal efficiency of 16 US EPA polycyclic aromatic hydrocarbons (PAHs) were examined in an inverted A2/O wastewater treatment plant (WWTP) located in an urban area in China. The total PAH concentrations were 554.3 to 723.2 ng/L in the influent and 189.6 to 262.7 ng/L in the effluent. The removal efficiencies of ∑PAHs in the dissolved phase ranged from 63 to 69%, with the highest observed in naphthalene (80% removal). Concentration and distribution of PAHs revealed that the higher molecular weight PAHs became more concentrated with treatment in both the dissolved phase and the dewatered sludge. The sharpest reduction was observed during the pretreatment and the biological phase. Noncarcinogenic risk, carcinogenic risk, and total health risk of PAHs found in the effluent and sewage sludge were also assessed. The effluent BaP toxic equivalent quantities (TEQBaP) were above, or far above, standards in countries. The potential toxicities of PAHs in sewage effluent were approximately 10 to 15 times higher than the acceptable risk level in China. The health risk associated with the sewage sludge also exceeded international recommended levels and was mainly contributed from seven carcinogenic PAHs. Given that WWTP effluent is a major PAH contributor to surface water bodies in China and better reduction efficiencies are achievable, the present study highlights the possibility of utilizing WWTPs for restoring water quality in riverine and coastal regions heavily impacted by PAHs contamination

Removal Efficiency and Risk Assessment of Polycyclic Aromatic Hydrocarbons in a Typical Municipal Wastewater Treatment Facility in Guangzhou, China

The loading and removal efficiency of 16 US EPA polycyclic aromatic hydrocarbons (PAHs) were examined in an inverted A2/O wastewater treatment plant (WWTP) located in an urban area in China. The total PAH concentrations were 554.3 to 723.2 ng/L in the influent and 189.6 to 262.7 ng/L in the effluent. The removal efficiencies of ∑PAHs in the dissolved phase ranged from 63 to 69%, with the highest observed in naphthalene (80% removal). Concentration and distribution of PAHs revealed that the higher molecular weight PAHs became more concentrated with treatment in both the dissolved phase and the dewatered sludge. The sharpest reduction was observed during the pretreatment and the biological phase. Noncarcinogenic risk, carcinogenic risk, and total health risk of PAHs found in the effluent and sewage sludge were also assessed. The effluent BaP toxic equivalent quantities (TEQBaP) were above, or far above, standards in countries. The potential toxicities of PAHs in sewage effluent were approximately 10 to 15 times higher than the acceptable risk level in China. The health risk associated with the sewage sludge also exceeded international recommended levels and was mainly contributed from seven carcinogenic PAHs. Given that WWTP effluent is a major PAH contributor to surface water bodies in China and better reduction efficiencies are achievable, the present study highlights the possibility of utilizing WWTPs for restoring water quality in riverine and coastal regions heavily impacted by PAHs contamination