Impact of Electric Vehicles on Travel and Electricity Demand in Metropolitan Area： A Case Study in Nagoya

In this study, we examine the impacts that EVs （electric vehicles） have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individual activity-travel behavior in each time period, as well as consider an induced demand by decreasing travel cost. In order to examine the effects that charging/discharging have on the demand in electricity, we analyze scenarios based on the simulation results of the EVs＇ parking location, parking duration and the battery state of charge. From the simulation, result under the ownership rate of EVs in the Nagoya metropolitan area in 2020 is about 6%, which turns out that the total CO2 emissions have decreased by 4% although the situation of urban transport is not changed. After calculating the electricity demand in each zone using architectural area and basic units of hourly power consumption, we evaluate the effect to decrease the peak load by V2G （vehicle-to-grid）. According to the results, if EV drivers charge at home during the night and discharge at work during the day, the electricity demand in Nagoya city increases by approximately 1%, although changes in each individual zone range from -7% to ＋8%, depending on its characteristics.

Study of older male drivers’driving stress compared with that of young male drivers

In this study,older male drivers’stress while driving in straight links and while proceeding through intersections is investigated.Controller area network(CAN),self-reported stress(SRS),and physiological data was collected in 22.4 km-long experimental trips among older and young drivers.First,this study finds that older drivers reported much less stress than young drivers.However,principal components(PCs)of the physiological data demonstrate that older drivers might underrate their driving stress in entire trips,except regarding turning at intersections.Moreover,following other vehicles reduced older drivers’driving stress because preceding vehicles might help them control driving speed,detect the path,and prevent road risks.In contrast,the similar condition increased the stress level of young drivers.The results of random effects regression models confirm that age was the significant impact factor on SRS and physiological data.While examining whether the stress at intersections could affect their driving behaviors,significant difference between two age groups was found neither in turning time nor in the driving speed.This study also confirms that physical and mental changes with aging can negatively affect older adults’behaviors.Considering the relationships among stress,speed,and accidents,we suggest the provision of more driver assistance systems,training,and education and improving intersection design for older drivers.