Transportation Letters-The International Journal of Transportation Research最新文献

Vehicle miles traveled (VMT) is an essential input for many aspects of transportation engineering, and an accurate estimation of VMT is critical for practicing engineers. Linear regression models are a popular method to estimate VMT as they provide insight into the relationships between VMT and other external factors. In linear regression models the prediction of the response variable has a non-zero probability of resulting in a negative value. For this reason, the natural logarithm of VMT is often used as the response variable to force a positive outcome. However, these log-linear regression (LLR) models provide median VMT estimate instead of the mean estimate. To overcome this limitation of LLR models, this study proposes using heteroskedastic LLR and count data methods to estimate VMT. These methods are found to have better performance than LLR models in terms of data fit and prediction accuracy.

Ride-sourcing drivers, as individual service suppliers, can freely adopt their own relocation strategies, including waiting, cruising freely, or following the platform recommendations. These decisions substantially impact the balance between supply and demand, and consequently affect system performance. We conducted a stated choice experiment to study the searching behaviour of ride-sourcing drivers and examine novel policies. A unique dataset of 576 ride-sourcing drivers working in the US was collected and a choice modelling approach was used to estimate the effects of multiple existing and hypothetical attributes. The results suggest that ride-sourcing drivers’ relocation strategies vary considerably between different drivers groups. Surge pricing significantly stimulates drivers to head toward the designated areas. However, the distance between the driver’s location and surge or high-demand areas demotivates them from following the platform repositioning recommendations. We discuss the implications of our findings for various platform policies on real-time information sharing and platform repositioning guidance.

Our objective in this paper is to evaluate the benefits of bus transit. To obtain the more accurate and highly discrimination results, this study establishes an evaluation indicator system from a stakeholder perspective and proposes a novel combined method consisting of dynamic network data envelopment analysis, cross-efficiency evaluation, and Shannon entropy aggregation method. An empirical study of bus transit systems in 33 key Chinese cities from 2016 to 2019 is provided. The results show that the benefit of bus transit in most key cities was ineffective. In contrast to production efficiency, focusing on improving service effectiveness is more conducive to improving the benefits of bus transit. Small cities have higher benefits than large cities. Meanwhile, the benefits of bus transit vary geographically. This evaluation outcome provides a more appropriate basis for decision-making related to the benefits of public transit services, as well as for operational and management studies.

In this paper, we propose a method of route optimization of vacant taxicab based on the abstract grid network. Firstly, an abstract grid network is built by the quadtree technology with the vacant trajectory data embedded. Secondly, the Markov decision process framework considering the sequential dependence is used to model the problem. Finally, we solve this problem by the policy iteration and compare the method by taking the GPS trajectory data in different hours of 797 taxicabs in a typical working day in Shenzhen, comparing that with the optimal strategy without considering sequential dependence, MNP, local hotspot and random walk algorithm by simulation, respectively. The results show that: The use of quadtree can reduce the sparseness of matching probability from 80.46% to 30.18%. The average revenue per unit distance has increased by 6.10%, 8.75%, 33.24% and 60.06%. The vacant driving rate has decreased by 5.33%, 6.15%, 18.86%, and 23.18%.

Several researchers have modified the original Social Force Model (SFM) for pedestrians by including vehicles and simulating interaction behaviors in shared space layouts. The present study is conducted at a signalized intersection where the performance and functionality are defined by spontaneous order. The SFM was modified, and two-wheelers were added along with cars and pedestrians to analyze their interactions. The Hybrid Calibration Method was adopted to calibrate the interaction parameters utilizing an optimization technique and real-time data from the study site. It can be concluded from the parameter values that the strength of interaction reduced as the range between the road agents increased. The findings can aid urban planners in visualizing the interaction behavior of pedestrians, cars, and two-wheelers. Moreover, the feasibility of introducing the shared space concept in India as an alternative to the conventional traffic planning system can also be determined during the designing phase.

Crowd motion simulation requires specification of a range of parameters, each reflecting certain aspects of agent behavior. But what parameters matter the most? Are they all equally important? The question is important given that available data and resources for parameter calibration are limited, and priorities often need to be made. Here, for the first time, a full-spectrum sensitivity analysis of crowd model parameters is reported. It is shown that estimates of simulated evacuation time are, by far, most dependent on the value of locomotion/operational parameters, especially those that determine discharge rate at bottlenecks. The next most critical set of parameters are those that influence change of direction choices. If a crowd simulation model fails to reproduce bottleneck flows accurately, efforts to refine other modeling layers will be in vain. Similarly, if the model fails to represent exit choice adaptation/changing accurately, efforts to refine the exit choice model will be fruitless.

Understanding trends in public transport usage by older people over the years is important for the long-term planning and development of age-friendly public transport. Despite extensive research on travel patterns of older people, very limited studies have explored the evolution oftheir public transport usage over the years. Using six years of smartcard transaction data and anonymous cardholder membership data from Shizuoka, Japan, we develop a latent Markov model to account for unobserved heterogeneity and to analyze the evolution of public transport usage by older people. The results indicate that age, gender, and residential built environment influence trends in publictransport usage by older adults over the years. There are five latentstates for older men and women, respectively, demonstrating theexistence of unobserved heterogeneity. Propensity to use public transport affected by unobserved factors tends to retain the same, especially for older people in the latent states of very low, low, and very high propensities.

This paper introduces an agent-based micro-simulation model to acquire the responses of road freight transportation systems like the productivity of trucks, the capability of road freight transportation companies, and the economic state of actors to different regulatory reforms. The shippers, freight companies, and drivers are the key decision-makers . These agents have different choices, including transport carrier choice, shipping price, truck allocation to shipment, and empty backhauls. Performance measures were used for the calibration phase with less than 3.7% average error. Finally, three viable regulatory reforms were evaluated, and their performance measures were estimated and discussed. We found that the shipping cost will reduce by 6% if a competitive market structure replaces the mandatory freight assignment procedure. Furthermore, we observed a 20% increase in the market share of the top fifty transport companies and a 3% improvement in the overall productivity when the physical freight companies’ branch requirements are relaxed.

Ghana commits to reducing greenhouse gas emissions of 64 MtCO₂ and reducing 2,900 premature deaths but has very low electric vehicle penetration. We used a total cost of ownership model to determine the cost of ownership parity of BEV compared to internal combustion engine vehicles (ICEV). The results show that BEV will not reach cost parity with ICEV until the 11^th year. Waiving the 20% import duty on BEV only reduced the years to parity by a year. Cost parity for the BEV was achieved in the seventh year when the interest rate was reduced from 23% to 10%. By waiving import duty and reducing the interest rate of BEV to 10%, cost parity was reached right from the first year. BEV in Ghana could reduce CO2, NOx, VOC, SOx, and PM emissions by 72%, 85%, 99.2%, 41%, and 60% respectively. Based on the 7.17 MtCO₂e attributed to transportation emissions in 2016, a BEV transition could reduce CO₂ emissions by 5 MtCO₂e. We conclude that a special financing scheme with an interest rate below 10% should be made available for green financing. Additionally, we recommend the removal of the 20% import duty for BEV to reach cost parity with ICEV.

The paper presents a model-based demand-responsive traffic control system for mixed traffic conditions using sample travel time data. The model incorporates mixed traffic characteristics such as heterogeneity, limited lane discipline of varied vehicle types, and spatio-temporal traffic dynamics across the width of the road. The methodology includes optimization of intersection performance by accommodating the varying traffic demand through signal timing variables. On validation, the model yielded reliable queue estimates within a close proximity of the actual, ranging from 20 to 40 meters. Upon optimization, the proposed model reduced total intersection delay by 15.42% on an average across 14 cycles, for near-saturated traffic conditions. The optimal green splits are found to be responsive to the varying traffic demand. The proposed system is simple and can be easily implemented in the mixed traffic conditions.