To reveal the speed control behaviour and manoeuvring characteristics of direct vehicles that stop-go through signalised intersections, a large-scale field driving test was carried out in Chongqing to collect vehicle data under natural driving conditions. The characteristics of speed, longitudinal acceleration rate and their two-dimensional correlation were analysed for deceleration and acceleration behaviour at signalised intersections. Further, a sensitivity analysis of the simulation model on measured data was done with the micro-traffic simulation experiment of a signalised intersection. The following were observed: (1) Drivers’ speed-selection behaviours become more concentrated with closer distance from the stop point. The transects ±25 m from the stop point are abrupt change points in the discrete nature of driver speed-selective behaviours. (2) Drivers’ desire to decelerate during the stop-go through signalised intersections is more robust, with the magnitude of pedal manoeuvres for deceleration behaviours being more intense than that for acceleration behaviours. (3) There is a nonlinear correlation between longitudinal acceleration rate and speed. The longitudinal acceleration rate increased with increase in speed and then decreased with the inflection point at 15 km/h. (4) The micro-traffic simulation’s acceleration rate model is sensitive to measured acceleration rate parameters. This study guides the parameter setting of speed, deceleration rate and acceleration rate models for microscopic traffic simulation and for parameter calibration of the car-following model.

2024 (Vol 36), Issue 6

The proposal to create front-loading warehouses has been suggested as a tactic to enhance the effectiveness and quality of distributing fresh agricultural products in the concluding stage of delivery. Nevertheless, there has been a noted escalation in the rate of loss of these products, which can be ascribed to multiple factors, including inaccuracies in demand forecasting. This incongruity arises from consumers’ inability to consume the initially forecasted quantities and unforeseen surges in demand from specific businesses. Consequently, surplus products are left unsold and eventually wasted. This study explores the viability of implementing a reverse logistics model for fresh agricultural products in tandem with the front-loading warehouse. The study presents both traditional and reverse dual models aimed at cost minimisation and introduces novel criteria for the selection of warehouse locations to enhance the efficiency of reverse logistics operations. An advanced hybrid heuristic optimisation algorithm is employed to identify optimal solutions, primarily focusing on minimising product loss rates, reducing logistics expenses and establishing a more equitable supply-demand equilibrium in the area. In the case of Nanjing, it is found that compared with the traditional model, because the network model assumes more functions, the front-loading warehouse in the reverse model has more site selection points in high-demand areas to meet the needs of consumers and is consistent with the distribution of population density and economic activities in Nanjing. At the same time, among the factors affecting the total cost, it is necessary to focus on transportation and fixed costs, while the impact of time and freight damage costs is less.

2024 (Vol 36), Issue 6

This paper attempts to determine the role of street lighting in the spatial clustering of night-time crashes involving pedestrians in the Republic of Croatia. Five-year (2018–2022) night-time pedestrian crash data were used in conditions with and without street lighting. First, distance-based statistical methods were used to assess the spatial clustering and deviations from complete spatial randomness (CRS) of the crash patterns. Second, the global Moran’s I analysis was conducted to investigate a degree of spatial autocorrelation of the annual crash counts aggregated in 21 counties of Croatia. Finally, the local indicators of spatial association (LISA) were used to identify the locations of the crash count hotspots. The results of the ANND analysis confirm a significant clustering of crashes for both street lighting conditions. However, different global Moran’s I values for both conditions were obtained with a high and statistically significant positive value for the crash counts without street lighting. Local Moran's I analysis reveals that the High-High (H-H) county clusters are located in coastal regions of Croatia, while the Low-Low (L-L) county clusters appear in the East continental part, next to Slavonia. The results suggest that inadequate lighting conditions have an impact on the clustering of pedestrian crashes at night.

2024 (Vol 36), Issue 6

With the rapid expansion of ride-hailing services, it has gradually become a new travel choice for urban residents. Various research studies have focused on market relationships and platform strategies from the perspective of platform competition. However, little research has been studying issues related to the platform integration of ride-hailing services from the corporate perspective. Based on an analysis of integration modes and travellers’ behavioural factors, we established an evolutionary game model to study travellers’ choice behaviour under the integration of ride-hailing platforms. Furthermore, this study employed methods of model deduction and numerical study. The findings indicate the following. (1) When the travel risk associated with platform integration is high, travellers are less likely to choose ride-hailing services, and the integration strategy of ride-hailing platforms will not be pursued. (2) Ride-hailing platforms tend to interconnect with larger-scale platforms. (3) As the negative effect of perceived sacrifice decreases, ride-hailing platforms are more likely to interconnect with other platforms, and travellers are more inclined to choose ride-hailing services. (4) A higher cost of platform integration will decrease the probability of ride-hailing platforms adopting an integration strategy, but it will not significantly impact travellers’ behaviour.

2024 (Vol 36), Issue 6

The aim of this paper is to highlight the vulnerability of Maritime Autonomous Surface Ships (MASS) to cyber-attack and to illustrate, through a simulation experiment on a testbed, how to mitigate a cyber-attack on the MASS thruster controllers during low-speed motion. The first part of the paper is based on a scoping review of relevant articles in the field, including some MASS projects, related cyber threats and modelling techniques to improve cyber resilience. In the second part of the paper, a cyber-attack on the MASS thruster controllers at low speed motion is illustrated along with the impact of the attack on the trajectory motion. The Kalman filter, as an additional device to the thruster controllers, is used as a cyber-attack mitigation aid. Under the conditions of a simulated intrusion on the input and output signals of the thruster, the experiments conducted in the MATLAB Simulink environment provide an insight into the behaviour of the MASS propulsion subsystem from the perspective of the low-speed trajectory, with and without the Kalman filter.

2024 (Vol 36), Issue 6

This paper presents a novel traffic flow prediction method emphasising heterogeneous vehicle characteristics and visual density features. Traditional models often overlook the variety of vehicles, resulting in inaccuracies. The proposed method utilises visual techniques to quantify traffic features, such as mixed flow and vehicle accumulation, enhancing dynamic density estimation and flow fluidity. We introduce a spatio-temporal prediction model that integrates various data types, capturing complex dependencies and improving accuracy. This research advances traffic flow prediction by considering the diverse nature of vehicles and leveraging visual data, offering valuable insights for intelligent transportation systems. Experimental results demonstrate the superiority of this approach over conventional methods, especially in capturing traffic flow fluctuations.

2024 (Vol 36), Issue 6