This paper used an implementation of the land-use model SILO in Austin, Texas, over a 27-year period with an aim to understand the impacts of the full adoption of self-driving vehicles on the region’s residential land use. SILO was integrated with MATSim for the Austin region. Land-use and travel results were generated for a business-as-usual case (BAU) of 0% self-driving or “autonomous” vehicles (AVs) over the model timeframe versus a scenario in which households’ value of travel time savings (VTTS) was reduced by 50% to reflect the travel-burden reductions of no longer having to drive. A third scenario was also compared and examined against BAU to understand the impacts of rising vehicle occupancy (VO) and/or higher roadway capacities due to dynamic ride-sharing (DRS) options in shared AV (SAV) fleets. Results suggested an 8.1% increase in average work-trip times when VTTS fell by 50% and VO remained unaffected (the 100% AV scenario) and a 33.3% increase in the number of households with “extreme work-trips” (over 1 hour, each way) in the final model year (versus BAU of 0% AVs). When VO was raised to 2.0 and VTTS fell instead by 25% (the “Hi-DRS” SAV scenario), average work-trip times increased by 3.5% and the number of households with “extreme work-trips” increased by 16.4% in the final model year (versus BAU of 0% AVs). The model also predicted 5.3% fewer households and 19.1% more available, developable land in the city of Austin in the 100% AV scenario in the final model year relative to the BAU scenario’s final year, with 5.6% more households and 10.2% less developable land outside the city. In addition, the model results predicted 5.6% fewer households and 62.9% more available developable land in the city of Austin in the Hi-DRS SAV scenario in the final model year relative to the BAU scenario’s final year, with 6.2% more households and 9.9% less developable land outside the city.

中文翻译：

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预测自动驾驶汽车在德克萨斯州奥斯丁地区的土地使用影响

本文采用了德克萨斯州奥斯汀市土地利用模型SILO的实施方案，历时27年，旨在了解完全采用自动驾驶汽车对本地区住宅土地利用的影响。SILO已与MATSim整合到奥斯汀地区。土地使用和旅行结果是在模型时间范围内相对于家庭节省旅行时间价值的情况（常规情况下，BAU）为0％的自动驾驶或“自动”车辆（AV）产生的（ VTTS）减少了50％，以反映出不再需要开车的旅行负担减少。还对BAU进行了第三种情况的比较和检查，以了解由于共享AV（SAV）车队中的动态乘车共享（DRS）选项导致的车辆占用率（VO）和/或更高的道路通行能力的影响。结果建议为8。当VTTS下降50％，VO不受影响时（AV情况为100％），平均出差时间增加1％（“超长出差”的住户数量增加33.3％）（单程超过1小时） ）作为最终模型年份（相对于BAU为0％AV）。当VO增加到2.0，而VTTS下降了25％（“ Hi-DRS” SAV情景）时，平均出差时间增加了3.5％，而有“极端出差”的家庭数量增加了16.4％。最终的模型年份（相对于AAV为0％的BAU）。该模型还预测，相对于BAU情景的最后一年，在最终模型年度中，相对于BAU情景的最后一年，在100％AV情景下，奥斯丁市的可开发土地将减少5.3％的家庭，而可开发土地将减少5.6％，而可开发土地将减少10.2％在城市外登陆。此外，模型结果预测家庭将减少5.6％，到62个。