Climate change modeling and the weather-related road accidents in Canada

Amin, Shohel; Zareie, Alireza; Amador-Jiménez, Luis

doi:10.1016/j.trd.2014.07.012

Cited by 31 publications

(20 citation statements)

References 29 publications

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“…About 12 unknown parameters need to be determined in (1) and (2). Since the current traffic states of the ego vehicle can be collected through the onboard sensing system, it is easy to solve the values of a 0 , a 1 , a 2 , b 0 , b 1 and b 2 , as shown in (3). The current moment is defined as t = 0…”

Section: Description Of Trajectory Planning Problemmentioning

confidence: 99%

“…According to the traffic reports, about 90% of accidents are caused by human error [1], and the unreasonable lane‐changing manoeuvre is one of the main factors. In New Zealand, 12.6% of traffic accidents result from lane‐changing [2]; in Canada, 9.8% of crashes are caused by lane‐changing [3]; and in the USA, lane‐changing manoeuvres account for a total accidents of 8% [4]. The automated lane‐changing system is a good solution to ensure the traffic safety, alleviate the congestion and improve the road capacity [5, 6].…”

Section: Introductionmentioning

confidence: 99%

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Lane‐changing trajectory planning method for automated vehicles under various road line‐types

et al. 2020

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This study proposes a lane-changing trajectory planning method for automated vehicles under various road linetypes. The method uses the polynomial regression model to describe the road line-types, and then a non-linear optimisation model is constructed to generate the lane-changing trajectory based on the road polynomial functions. The process of connecting the lane-changing manoeuvre with the car-following manoeuvre is discussed in this study, which ensures the ride comfort of the ego vehicle after the lane-changing manoeuvre. Moreover, considering that the lag vehicle on the target lane may be affected by the lane-changing manoeuvre, the situation that the lag vehicle maintains the car-following manoeuvre with the ego vehicle is taken into account in the authors' model. Another small innovation is that they have designed a simple and effective method to find the suitable initial guess for the proposed non-linear optimisation model. The simulation results show that the lane-changing trajectory generated by the proposed model is smooth and continuous, and the automated vehicle can avoid potential collisions efficiently during the lane-changing process. In emergent conditions, the proposed model can also plan the corrected trajectory to ensure safety.

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Section: Description Of Trajectory Planning Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Lane‐changing trajectory planning method for automated vehicles under various road line‐types

et al. 2020

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“…A study was presented by [24], which integrated a spatial density analysis (KDE) and the local Moran Index to detect black spot zones of traffic accidents and to formally evaluate the extensiveness of locations with high densities to provide tools and information for planners and decision makers to effectively allocate resources for accident prevention and safety improvement. A spatial-temporal analysis of road accidents in New Brunswick, Canada, to study the impacts of climate change on hazardous weather-related traffic accidents was provided by [25]. In addition, a spatial analysis (KDE and wavelet analysis) to identify black spot regions of traffic accidents and to verify patterns that contributed to accidents that occurred in the black spot zones in Paraná State, Brazil, was applied by [26].…”

Section: Traffic Accident Researchmentioning

confidence: 99%

Characterization of Black Spot Zones for Vulnerable Road Users in São Paulo (Brazil) and Rome (Italy)

Machado

Giannotti

Neto

et al. 2015

IJGI

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Non-motorized transportation modes, especially cycling and walking, offer numerous benefits, including improvements in the livability of cities, healthy physical activity, efficient urban transportation systems, less traffic congestion, less noise pollution, clean air, less impact on climate change and decreases in the incidence of diseases related to vehicular emissions. Considering the substantial number of short-distance trips, the time consumed in traffic jams, the higher costs for parking vehicles and restrictions in central business districts, many commuters have found that non-motorized modes of transportation serve as viable and economical transport alternatives. Thus, local governments should encourage and stimulate non-motorized modes of transportation. In return, governments must provide safe conditions for these forms of transportation, and motorized vehicle users must respect and coexist with pedestrians and cyclists, which are the most vulnerable users of the transportation system. Although current trends in sustainable transport aim to encourage and stimulate non-motorized modes of transportation that are socially more efficient than motorized transportation, few to no safety policies have been implemented regarding vulnerable road users (VRU), mainly in large urban centers. Due to the spatial nature of the data used in transport-related studies,859 geospatial technologies provide a powerful analytical method for studying VRU safety frameworks through the use of spatial analysis. In this article, spatial analysis is used to determine the locations of regions that are characterized by a concentration of traffic accidents (black zones) involving VRU (injuries and casualties) in São Paulo, Brazil (developing country), and Rome, Italy (developed country). The black zones are investigated to obtain spatial patterns that can cause multiple accidents. A method based on kernel density estimation (KDE) is used to compare the two cities and show economic, social, cultural, demographic and geographic differences and/or similarities and how these factors are linked to the locations of VRU traffic accidents. Multivariate regression analyses (ordinary least squares (OLS) models and spatial regression models) are performed to investigate spatial correlations, to understand the dynamics of VRU road accidents in São Paulo and Rome and to detect factors (variables) that contribute to the occurrences of these events, such as the presence of trip generator hubs (TGH), the number of generated urban trips and demographic data. The adopted methodology presents satisfactory results for identifying and delimiting black spots and establishing a link between VRU traffic accident rates and TGH (hospitals, universities and retail shopping centers) and demographic and transport-related data.

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“…The Netherlands transportation statistics showed that 12.6% of traffic accidents resulted from lane changes [3]. Analysis of traffic accidents in Canada revealed that lane changes were responsible for about 10% of crash fatalities [4]. Data analysis by the Highway Traffic Safety Administration in China indicated that 60% of traffic crashes on freeway could be attributed to the lane change [5].…”

Section: Introductionmentioning

confidence: 99%

A Cooperative Lane Change Model for Connected and Automated Vehicles

Chan³

et al. 2020

IEEE Access

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The emerging technology of vehicle-to-vehicle (V2V) communication, vehicle-toinfrastructure (V2I) communication makes it possible for vehicles to sense the environment information, which can be exploited to assist the vehicle in cooperative motion planning. In this paper, we focus on the cooperative trajectory planning of lane changes for connected and automated vehicles (CAVs). The proposed model considers the traffic scene with multiple mandatory lane change demands and completes the trajectory planning for vehicles by taking the safety and efficiency into consideration. The model solves two critical issues: the vehicle grouping and the motion planning. In the first issue, CAVs in the cooperative zone are divided into different groups. Then the problem is simplified and divided into several subproblems. In the second issue, the trajectory planning is conducted in each group. Trajectories are generated for vehicles with and without lane change demands. Besides, these two steps are iterated and updated in the fixed time interval, which makes full use of the dynamic cooperation ability of vehicles. Extensive simulation tests are conducted to validate the performance of the model. Results show that the cooperation of vehicles realizes safe and effective lane changes. INDEX TERMS Lane change, connected and automated vehicles, motion planning, cooperative driving, collision avoidance.

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Climate change modeling and the weather-related road accidents in Canada

Cited by 31 publications

References 29 publications

Lane‐changing trajectory planning method for automated vehicles under various road line‐types

Lane‐changing trajectory planning method for automated vehicles under various road line‐types

Characterization of Black Spot Zones for Vulnerable Road Users in São Paulo (Brazil) and Rome (Italy)

A Cooperative Lane Change Model for Connected and Automated Vehicles

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