Autonomous Driving Commuting

The increasing demand for public transport and car ownership make the congestion of urban road traffic network more and more serious.Especially at the bottleneck section in the morning rush hour,serious queuing often occurs.At the same time,with the rapid development of automatic driving technology and the rise of the concept of sharing economy,the deep integration of shared travel and automatic driving will bring significant adjustments to travel modes and formats.From the perspective of activities,this paper uses the activity analysis method to study the departure time selection of commuters in the mixed driving environment of autonomous vehicles and regular vehicles in the morning peak,and designs the corresponding tradable credit scheme.On this basis,it further studies the impact of shared travel on morning peak commuting behavior in the era of automatic driving.The main work of this paper is as follows:Firstly,in order to explore the travel behavior of autonomous vehicle commuters in morning peak and their impact on traffic conditions,the departure time selection of autonomous vehicle commuters and regular vehicle commuters in mixed driving environment in morning peak is studied by using activity analysis method.Considering that automatic driving will reduce commuters’ value of time and improve road capacity,this paper constructs an activity-based bottleneck model for the mixed travel of autonomous vehicle commuters and regular vehicle commuters.Through the equilibrium conditions,cumulative arrival and departure modes and the total utility of the two types of commuters are,and the effects of the marginal activity utility of family,work and invehicle,the reduction of value of time of autonomous vehicle commuters and the improvement of road capacity on the travel behavior are analyzed.Meanwhile,the changes of queue length and total travel utility of both autonomous vehicle commuters and regular vehicle commuters with the proportion of autonomous commuters are further studied.The results show that increasing the marginal utility of three types of activities,reducing the commuters’ value of time and increasing the road capacity will increase the total utility of commuters.Increasing the marginal utility of family activities,in car activities and reducing the value of time will increase the queuing time of commuters and aggravate the congestion at the bottleneck,while improving the utility of work activities and bottleneck capacity will reduce the queuing time of commuters and alleviate the congestion.At the same time,the total utility increases first and then decreases with the proportion of autonomous vehicle commuters.Secondly,in order to further manage the congestion of commuters of the mixed driving environment in the morning peak,the corresponding tradable credits scheme is designed.By establishing the departure time selection model of morning peak commuters under the tradable credits scheme,this paper quantitatively analyzes the relationship between the total amount of road credits issued and the unit price at equilibrium.It is found that under the tradable travel ticket scheme,when the departure rate of the two types of commuters is equal to the bottleneck capacity,the crowded queuing phenomenon at the bottleneck can be completely eliminated;Compared with the management before the implementation of the tradable travel ticket scheme,the total utility of commuters under the tradable travel ticket scheme increases by about 2.82%.Finally,Impact of shared travel on commuters’ travel behavior in morning peak from the activity perspective is studied in this paper.Considering the in-vehicle activities utility impact of commuters on autonomous driving,the difference of travel costs between autonomous vehicles and shared autonomous vehicles is further analyzed,and the activity-based bottleneck model of autonomous vehicle commuters and shared autonomous vehicle commuters is proposed,which is used to approach the influence of travel cost and activity utility on commuters’ departure patterns.On this basis,the effects of ridesharing costs,ridesharing occupancy and other factors on the total travel utility of commuters and the proportion of sharing autonomous vehicle commuters.It shows that under the presented scenario with fixed travel demand and constant marginal activity utility,the proportion of sharing autonomous vehicle commuters has the variable trend of rising first and downing thereafter,whilst the proportion of autonomous vehicle commuters decreases first and increases later.In order to encourage the behavior of ridesharing,the ridesharing occupancy should be specified within a certain range.