The objective of this study is to analyze the effects of road transportation investment on economic output and induced travel demand. Data for U.S. urbanized areas are analyzed within a dynamic panel vector auto-regression model to test whether the effects of transportation-induced economic growth and travel demand can be empirically validated. The results show that investment in road capacity increases average economic growth while simultaneously inducing additional growth in traffic (vehicle miles traveled). Indeed, a general failure of investment to alleviate levels of congestion is found; this finding suggests that productivity shifts are brought about through a net increase in the scale of travel and associated interactions rather than improved network performance as measured by travel times. The evidence also shows that congestion forms part of the decision criterion used to allocate investments in road capacity. If improvements in network performance are to be achieved in a climate of travel demand growth, demand management techniques may be more effective than capacity expansion.

This paper estimates elasticities of demand for metro services with respect to fares, income, quality of service, population and network length. Data for 32 world metro systems covering the period from 1996 to 2015 are analyzed within a dynamic panel data specification. Three key contributions are made. First, we collate a database for estimation that is more extensive than that used in previous studies. Second, the quality of the data we have available allows us to more accurately represent quality of service than has been possible previously. Lastly, we estimate and compare two different measures of demand. Our analysis finds a statistically significant negative fare elasticity of 20.25 in the long run for a passenger km specified model and 20.4 in the long run for a passenger journey specified model, and a positive long run income elasticity of 0.17 and 0.18 for the passenger km and passenger journey models respectively. Regarding quality of service, we find positive long run elasticities of 0.56 and 0.47 for the passenger km and passenger journey models respectively. Income levels, population, and the size of the network are also found to be statistically significant and positive in nature. The results suggest passenger km and passenger journeys will increase more in response to changes in service (here represented by increased capacity) than to changes in fares, with the difference in elasticities of service and fares being more pronounced for passenger km.

Platform doors are increasingly installed by metros, primarily to improve safety. However, they have the potential for both positive and negative operational impacts, mostly by affecting dwell times at stations. Using data from the CoMET and Nova international metro benchmarking consortia of 33 metro systems, this paper seeks to understand and quantify these operational impacts. Overall, platform doors have a net negative impact on dwell times, leading to between 4 and 15 s of extra time per station stop. This is due to the additional time required for the larger doors to open and close, slower passenger movements due to the additional distance between platforms and trains, and, most importantly, extended departure delays after both sets of doors are closed caused by the need to ensure safety (that no one is trapped in the gap between the two sets of doors). This is a particular problem in mainland China, where metros conduct manual safety checks that require drivers to step out of trains onto platforms. However, despite longer dwell times, platform doors have a net positive impact on metro operations, largely due to the many safety benefits that also reduce delays and thereby improve service performance. There are also potential benefits regarding energy and ventilation. To mitigate the negative impacts, metros should seek to refine procedures and improve technology to reduce dwell time delays caused by platform doors. Reducing or eliminating these extra delays are essential to delivering efficient service and maximum capacity, provided that safety can be assured.The Standing Committee on Rail Transit Systems (AP065) peerreviewed this paper (18-02825).