Traffic congestion on major roads consequent upon existing bottlenecks at intersections is a major problem in Akure Metropolis. To change this trend, this research was carried out in order to design effective traffic ...Traffic congestion on major roads consequent upon existing bottlenecks at intersections is a major problem in Akure Metropolis. To change this trend, this research was carried out in order to design effective traffic control mechanisms at the “troubled spots” in the metropolis. Odole intersection was identified as one of the critical intersections during a reconnaissance survey and as such, selected for study. Data on geometric features were collected using Oedometer and Google Earth software. Peak and off-peak traffic volume data were collected between 7:30 and 8:30 am and between 12.00 noon and 1.00 pm respectively every other day using Cine camera. Furthermore, discharge headway and delay data were collected using stop watch. The geometric and traffic data collected were analysed using Microsoft Excel. An appraisal of Odole Intersection indicated that the major contributors to traffic are Motorcycles (70.88%) and Passenger Cars (28.72%). Other modes of transportation account for about 0.4% of vehicles traversing the intersection. The critical traffic volume at the intersection was over 4000 veh/hr and the average delay was 22 seconds. An Average delay of 22 seconds at the intersection was an indication that the operating level of service was C (i.e. fairly stable traffic condition with average delays attributable to traffic control by personnel). By juxtaposing the results of geometric and traffic data analyses with the pros and cons of various traffic control mechanisms, traffic control by signalisation was selected and designed to suit Odole intersection. In tandem with the results of this research, appropriate measures have been recommended to ameliorate traffic and commuting problems in the metropolis.展开更多
One of the main factors affecting the safety of signalised intersections is the stop/go behaviour during the yellow interval.Although previous research has exhaustively examined drivers’stop/go decision-making,the ex...One of the main factors affecting the safety of signalised intersections is the stop/go behaviour during the yellow interval.Although previous research has exhaustively examined drivers’stop/go decision-making,the expected autonomous vehicles’(AVs’)stop/go behaviour has not yet been thoroughly investigated.Through a series of simulation experiments developed for conventional and autonomous vehicles using different carfollowing,lane-changing,lateral placement and stop/go model parameter values,we examine here whether the default VISSIM stop/go parameter values can adequately replicate the observed drivers’behaviour at the considered intersection and assess the suitability of using the currently available options,albeit referring to human drivers,to simulate the expected stop/go behaviour of AVs.We also propose a policy framework for determining the desired behaviour of AVs in yellow interval,which is integrated into an AVs logic and achieved in the last simulation to explore the effect of automation on the stop/go outcome and,hence,on the safety level of signalised intersections.Several data analysis and modeling techniques were used for the formulation of certain scenarios,including binary choice models.The default stop/go parameter values were found unfit to replicate the observed stop/go behaviour and subjected to calibration.Compared to the currently available options,the proposed AVs logic proved to produce the most accurate results,in terms of the stop/go simulation outcome.Regarding the impact of automation on the stop/go outcome,the simulation experiments showed that AVs preferred a more conservative behaviour in favor of road safety,as indicated by the significant reduction(≈15%)in the number of vehicles crossing the stop line during the yellow light and zero instances of red light violation.However,compared to the conservative drivers represented by the default stop/go parameter values,AVs preferred a more rational behaviour in favor of intersection capacity without compromising road safety.展开更多
文摘Traffic congestion on major roads consequent upon existing bottlenecks at intersections is a major problem in Akure Metropolis. To change this trend, this research was carried out in order to design effective traffic control mechanisms at the “troubled spots” in the metropolis. Odole intersection was identified as one of the critical intersections during a reconnaissance survey and as such, selected for study. Data on geometric features were collected using Oedometer and Google Earth software. Peak and off-peak traffic volume data were collected between 7:30 and 8:30 am and between 12.00 noon and 1.00 pm respectively every other day using Cine camera. Furthermore, discharge headway and delay data were collected using stop watch. The geometric and traffic data collected were analysed using Microsoft Excel. An appraisal of Odole Intersection indicated that the major contributors to traffic are Motorcycles (70.88%) and Passenger Cars (28.72%). Other modes of transportation account for about 0.4% of vehicles traversing the intersection. The critical traffic volume at the intersection was over 4000 veh/hr and the average delay was 22 seconds. An Average delay of 22 seconds at the intersection was an indication that the operating level of service was C (i.e. fairly stable traffic condition with average delays attributable to traffic control by personnel). By juxtaposing the results of geometric and traffic data analyses with the pros and cons of various traffic control mechanisms, traffic control by signalisation was selected and designed to suit Odole intersection. In tandem with the results of this research, appropriate measures have been recommended to ameliorate traffic and commuting problems in the metropolis.
文摘One of the main factors affecting the safety of signalised intersections is the stop/go behaviour during the yellow interval.Although previous research has exhaustively examined drivers’stop/go decision-making,the expected autonomous vehicles’(AVs’)stop/go behaviour has not yet been thoroughly investigated.Through a series of simulation experiments developed for conventional and autonomous vehicles using different carfollowing,lane-changing,lateral placement and stop/go model parameter values,we examine here whether the default VISSIM stop/go parameter values can adequately replicate the observed drivers’behaviour at the considered intersection and assess the suitability of using the currently available options,albeit referring to human drivers,to simulate the expected stop/go behaviour of AVs.We also propose a policy framework for determining the desired behaviour of AVs in yellow interval,which is integrated into an AVs logic and achieved in the last simulation to explore the effect of automation on the stop/go outcome and,hence,on the safety level of signalised intersections.Several data analysis and modeling techniques were used for the formulation of certain scenarios,including binary choice models.The default stop/go parameter values were found unfit to replicate the observed stop/go behaviour and subjected to calibration.Compared to the currently available options,the proposed AVs logic proved to produce the most accurate results,in terms of the stop/go simulation outcome.Regarding the impact of automation on the stop/go outcome,the simulation experiments showed that AVs preferred a more conservative behaviour in favor of road safety,as indicated by the significant reduction(≈15%)in the number of vehicles crossing the stop line during the yellow light and zero instances of red light violation.However,compared to the conservative drivers represented by the default stop/go parameter values,AVs preferred a more rational behaviour in favor of intersection capacity without compromising road safety.
