With the increasing use of electric bikes, electric bike crashes occur frequently. Analysing the influencing factors of electric bikecrashes is an effective way to reduce mortality and improve road safety. In this pap...With the increasing use of electric bikes, electric bike crashes occur frequently. Analysing the influencing factors of electric bikecrashes is an effective way to reduce mortality and improve road safety. In this paper, spatial analysis is performed by geographicinformation system (GIS) to present the hot spots of electric bike crashes during daylight and darkness in Changsha, Hunan Province,China. Based on the Ordered Probit (OP) model, we studied the risk factors that led to different severities of electric bike crashes.The results show that the main influencing variables include age, illegal behaviour, collision type and road factors. During daylightand darkness, elderly electric bike riders over the age of 65 years have a higher probability of fatal crashes. Not following trafficsignals and reverse driving are significantly related to the severity of riders’ injuries. In darkness, frontal collisions are significantfactors causing rider injury. In daylight, more serious crashes will be caused in bend and slope road segments. In darkness, roadswith no physically separated bicycle lanes increases the risk of riders being injured. Electric bike crashes are mainly concentratedin the commercial, public service and residential areas in the main urban area. In suburbs at darkness, electric bike riders are morelikely to be seriously injured. Adding protectionmeasures, such as improved lighting, non-motorized lane facilities and interventionstargeting illegal behaviour in the hot spot areas can effectively reduce the number of electric bike crashes in complex traffic.展开更多
Air route crossing waypoint optimization is one of the effective ways to improve airspace utilization,capacity and resilience in dealing with air traffic congestion and delay.However,research is lacking on the optimiz...Air route crossing waypoint optimization is one of the effective ways to improve airspace utilization,capacity and resilience in dealing with air traffic congestion and delay.However,research is lacking on the optimization of multiple Crossing Waypoints(CWPs)in the fragmented airspace separated by Prohibited,Restricted and Dangerous areas(PRDs).To tackle this issue,this paper proposes an Artificial Potential Field(APF)model considering attractive forces produced by the optimal routes and repulsive forces generated by obstacles.An optimization framework based on the APF model is proposed to optimize the different airspace topologies varying the number of CWPs,air route segments and PRDs.Based on the framework,an adaptive method is developed to dynamically control the optimization process in minimizing the total air route cost.The proposed model is applied to a busy controlled airspace.And the obtained results show that after optimization the safety-related indicators:conflict number and controller workload reduced by 7.75%and 6.51%respectively.As for the cost-effectiveness indicators:total route length,total air route cost and non-linear coefficient,declined by 1.74%,3.13%and 1.70%respectively.While the predictability indicator,total flight delay,saw a notable reduction by 7.96%.The proposed framework and methodology can also provide an insight in the understanding of the optimization to other network systems.展开更多
基金the National Natural Science Foundation of China(Grant No.52172399/51875049)the Key Research and Development Program of Hunan Province(Grant No.2020SK2099)the Scientific Research Fund of Hunan Provincial Education Department(Grant No.21A0193).
文摘With the increasing use of electric bikes, electric bike crashes occur frequently. Analysing the influencing factors of electric bikecrashes is an effective way to reduce mortality and improve road safety. In this paper, spatial analysis is performed by geographicinformation system (GIS) to present the hot spots of electric bike crashes during daylight and darkness in Changsha, Hunan Province,China. Based on the Ordered Probit (OP) model, we studied the risk factors that led to different severities of electric bike crashes.The results show that the main influencing variables include age, illegal behaviour, collision type and road factors. During daylightand darkness, elderly electric bike riders over the age of 65 years have a higher probability of fatal crashes. Not following trafficsignals and reverse driving are significantly related to the severity of riders’ injuries. In darkness, frontal collisions are significantfactors causing rider injury. In daylight, more serious crashes will be caused in bend and slope road segments. In darkness, roadswith no physically separated bicycle lanes increases the risk of riders being injured. Electric bike crashes are mainly concentratedin the commercial, public service and residential areas in the main urban area. In suburbs at darkness, electric bike riders are morelikely to be seriously injured. Adding protectionmeasures, such as improved lighting, non-motorized lane facilities and interventionstargeting illegal behaviour in the hot spot areas can effectively reduce the number of electric bike crashes in complex traffic.
基金the Civil Aviation Authority of Singapore and the Nanyang Technological University,Singapore under their collaboration in the Air Traffic Management Research Institute。
文摘Air route crossing waypoint optimization is one of the effective ways to improve airspace utilization,capacity and resilience in dealing with air traffic congestion and delay.However,research is lacking on the optimization of multiple Crossing Waypoints(CWPs)in the fragmented airspace separated by Prohibited,Restricted and Dangerous areas(PRDs).To tackle this issue,this paper proposes an Artificial Potential Field(APF)model considering attractive forces produced by the optimal routes and repulsive forces generated by obstacles.An optimization framework based on the APF model is proposed to optimize the different airspace topologies varying the number of CWPs,air route segments and PRDs.Based on the framework,an adaptive method is developed to dynamically control the optimization process in minimizing the total air route cost.The proposed model is applied to a busy controlled airspace.And the obtained results show that after optimization the safety-related indicators:conflict number and controller workload reduced by 7.75%and 6.51%respectively.As for the cost-effectiveness indicators:total route length,total air route cost and non-linear coefficient,declined by 1.74%,3.13%and 1.70%respectively.While the predictability indicator,total flight delay,saw a notable reduction by 7.96%.The proposed framework and methodology can also provide an insight in the understanding of the optimization to other network systems.